INVESTIGATING THE IMPACTS OF GROUNDWATER
ON SOIL PROPERTIES AND PASTURE NUTRITION
IN IRRIGATED AGRICULTURE, PILBARA REGION
OF WESTERN AUSTRALIA
Simon Guo Hong Yeap
Bachelor of Science in Environmental Science and Environmental Technology
School of Veterinary and Life Sciences
Murdoch University
Murdoch, Western Australia, 6150
Australia
June 2014
Investigating the impacts of groundwater on soil properties and pasture
nutrition
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Acknowledgements
To my supervisors, Professors Richard Bell and Richard Harper, and to my family and
friends whose constant guidance and encouragement has enabled me to successfully
accomplish this research. To Rio Tinto Iron Ore for providing financial assistance and
staff – especially Dr Sunil Samaraweera for his invaluable insights and commitment to
the project, and the Hamersley Agricultural Project team, Simon Mathwin and Nicholas
Collins. Thanks are also due to Stuart Anstee (Rio Tinto), and Dr Andrew Storey and
Sarah Emery from Wetland Research and Management (WRM) for technical assistance
during the planning and reconnaissance phase. Subsequent work by Dr Sunil
Samaraweera on the Exchangeable Sodium Percentage and Sodicity of Hamersley
Agricultural Project Soils (Samaraweera, 2015) are gratefully acknowledged.
iii
DECLARATION
I declare that this thesis is my own account of my research and contains as its
main content work which has not previously been submitted for a degree at any tertiary
education institution.
Simon Guo Hong Yeap
iv
ABSTRACT
Dewatering of groundwater systems has become a common practice for iron ore
mining in the Pilbara region of Western Australia. While the discharge of surplus water
to local tributaries and re-injection into the aquifer are widely practiced, the re-use of
this water for irrigated forages is an innovative solution. However, the chemistry of the
groundwater and the impacts on soil properties from long-term application of
groundwater need to be assessed.
Surplus water from the Marandoo iron ore mine is utilised to irrigate Rhodes
grass (Chloris gayana) for hay production at the Hamersley Agricultural Project (HAP).
After amendment with nutrients, the irrigation water was slightly alkaline (pH 8.0) and
slightly brackish-sodic (total dissolved solids, TDS, of 580 mg/L) with Ca (61 mg/L), Mg
(50 mg/L) and Na (43 mg/L) as the dominant cations and bicarbonate (270 mg/L) as the
dominant anion. This study aims to identify the implications of irrigation with this water
for pasture production and soil management.
Following the commencement of irrigation in October 2012, significant changes
and trends in soil properties and leaf nutrient composition of C. gayana were examined
over a 15 month period, based on a quarterly sampling program across 10 centre-pivot
irrigation systems. Analysis initially showed that the continuation of current trends
could result in: (1) increases in soil sodicity, since ESP levels had exceeded 5% at 0-10
cm and 7% at 20-30 cm, and (2) alkalinisation, such that the soil pH is predicted to reach
~8.2. However, subsequent analysis with pre-washed soil samples to remove soluble
salts indicated that irrigation had not caused a measureable change in the ESP and hence
no change in the sodicity of HAP soils.
Nonetheless, the geochemical model WEB-PHREEQ suggests the precipitation of
carbonate, (hydr)oxide and phosphate (apatite) minerals of Ca, Mg, Fe and Mn could also
impose a risk for immobilising nutrients applied from irrigation water, given suitable
conditions for nucleation and crystal growth. Moreover, changes in the relative
abundance of soil exchangeable cations may also adversely affect plant nutritional
balance whereby exchangeable Mg2+ as a percentage of cation exchange capacity has
significantly increased while the percentages of exchangeable Ca2+ and K+ have
significantly decreased.
In the next 20 years, based on the estimated duration of the HAP, soil
alkalinisation could emerge as a problem by suppressing the availability of various
Investigating the impacts of groundwater on soil properties and pasture
nutrition
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nutrients. Future monitoring and research, in conjunction with effective irrigation and
soil management practice, will hence be imperative to ensure long-term sustainability of
pasture production at the HAP, as well as for rehabilitation of soils after
decommissioning.
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nutrition
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TABLE OF CONTENTS
DECLARATION ...................................................................................................................................... III
ABSTRACT ............................................................................................................................................ IV
TABLE OF CONTENTS ........................................................................................................................... VI
LIST OF FIGURES .................................................................................................................................. IX
LIST OF TABLES .................................................................................................................................. XIII
1. INTRODUCTION ............................................................................................................................. 1
1.1. SALINITY AND SODICITY IN IRRIGATED AGRICULTURE ........................................................... 1
1.2. SALT AFFECTED SOILS AND IMPLICATIONS FOR PLANT GROWTH ........................................... 2
1.2.1. SALINITY AND SALT STRESS 2
1.2.2. SODICITY AND ALKALI STRESS 3
1.2.3. DETERIORATION OF SOIL PHYSICAL CONDITION 5
1.3. PROJECT SCOPE .......................................................................................................................... 5
1.3.1. MINE DEWATERING IN THE PILBARA 5
1.3.2. THE HAMERSLEY AGRICULTURAL PROJECT 6
1.3.3. RESEARCH OBJECTIVES 6
2. MATERIALS AND METHODS .......................................................................................................... 8
2.1. STUDY AREA ............................................................................................................................... 8
2.1.1. IRRIGATION PIVOTS 10
2.2. SAMPLING AND MONITORING SOIL, LEAF TISSUE, AND WATER QUALITY ............................ 12
2.3. GEOCHEMICAL MODELLING FOR MINERAL PRECIPITATION ................................................. 13
2.4. ALKALINITY MASS BALANCE AND ASH ALKALINITY DETERMINATION ................................ 14
2.5. EXCHANGEABLE SODIUM PERCENTAGE ................................................................................. 15
2.6. DATA ANALYSIS ...................................................................................................................... 15
3. RESULTS...................................................................................................................................... 17
3.1. SIGNIFICANT DIFFERENCES BETWEEN MONITORING SPANS................................................. 17
3.2. BASELINE SOIL DATA .............................................................................................................. 18
3.3. SIGNIFICANT CHANGES AND TRENDS ..................................................................................... 20
3.3.1. SOIL PROPERTIES 20
3.3.2. LEAF NUTRIENT COMPOSITION 35
3.4. CORRELATION AND LINEAR REGRESSION ANALYSIS ............................................................. 41
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3.4.1. SOIL PROPERTIES 41
3.4.2. PARTICLE SIZE AND SOIL CHEMICAL PROPERTIES 47
3.4.3. LEAF NUTRIENT COMPOSITION AND SOIL PROPERTIES 48
3.5. WATER QUALITY AND GEOCHEMICAL MODELLING ............................................................... 49
3.6. ASH ALKALINITY DETERMINATION AND MASS BALANCE ...................................................... 51
4. DISCUSSION................................................................................................................................. 54
4.1. OVERVIEW ............................................................................................................................... 54
4.2. MAJOR FINDINGS ..................................................................................................................... 55
4.2.1. EXCHANGEABLE SODIUM AND SODICITY 55
4.2.2. SOIL PH AND ALKALINISATION 57
4.2.3. MINERAL PRECIPITATION 59
4.3. MINOR FINDINGS ..................................................................................................................... 63
4.3.1. EFFECT ON EXCHANGEABLE BASE CATIONS 63
4.3.2. HEAVY METALS AND METALLOIDS 64
4.3.3. VOLATILISATION OF NITROGEN FERTILISERS 67
4.4. MANAGEMENT IMPLICATIONS ................................................................................................ 67
4.4.1. OTHER IRRIGATION PROJECTS IN THE REGION 68
4.4.2. REHABILITATION AFTER DECOMMISSIONING 69
5. CONCLUSION ............................................................................................................................... 70
6. LITERATURE CITED .................................................................................................................... 72
APPENDIX A: CORRELATION ANALYSIS ............................................................................................ 90
SOIL PROPERTIES AND LEAF NUTRIENT COMPOSITION ................................................................... 90
LEAF NUTRIENT COMPOSITION ......................................................................................................... 92
APPENDIX B: WEB-PHREEQ OUTPUT DATA ................................................................................ 93
DEWATERING SURPLUS ..................................................................................................................... 93
SENSITIVITY ANALYSIS 98
FERTIGATION MIXTURE ................................................................................................................... 103
SENSITIVITY ANALYSIS 108
APPENDIX C: ASH ALKALINITY ....................................................................................................... 114
STANDARDISATION OF STRONG ACID WITH WEAK BASE .............................................................. 114
COMPARISON OF FINELY MILLED AND NON-MILLED SAMPLES ...................................................... 114
NEUTRALISING EXCESS ALKALINITY TO PREVENT SOIL ALKALINISATION ................................... 114
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APPENDIX D: CLUSTER ANALYSIS – STRATIFYING IRRIGATION PIVOTS ...................................... 117
RESULTS ........................................................................................................................................... 117
TEST 1: ELECTRICAL CONDUCTIVITY AND EXCHANGEABLE ALUMINIUM PERCENTAGE 124
TEST 2: CALCIUM CARBONATE EQUIVALENT AND CARBON/NITROGEN RATIO 125
TEST 3: CLAY CONTENT AND ARSENIC CONCENTRATION 127
APPENDIX E: SOIL CARBONATE DETERMINATION – A METHODOLOGY DEVELOPMENT EXERCISE
.......................................................................................................................................................... 130
METHODS AND MATERIALS ............................................................................................................. 130
METHOD 1 130
METHOD 2 130
PRECISION AND ACCURACY OF METHODS 1 AND 2 132
RESULTS ........................................................................................................................................... 133
DISCUSSION ...................................................................................................................................... 136
APPENDIX F: SOIL TEXTURE ........................................................................................................... 138
IRRIGATION WATER QUALITY AND RISK FOR CLAY DISPERSION .................................................. 139
CALCULATING THE SODIUM ADSORPTION RATIO 139
APPENDIX G: FUTURE SOIL AND LEAF MONITORING RECOMMENDATIONS ................................. 141
SAMPLING FREQUENCY – TEMPORAL VARIABILITY ....................................................................... 141
SAMPLE SIZE – SPATIAL VARIABILITY ............................................................................................ 143
SOIL SAMPLING DEPTH 144
APPENDIX H: CHANGES WITH TIME OF EXCHANGEABLE SODIUM PERCENTAGE (ESP) AND
SODICITY OF HAMERSLEY AGRICULTURE PROJECT SOILS ............................................................ 145
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LIST OF FIGURES
Figure 1. Hypoxia and salinity interact to decrease the growth of wheat plants (Barrett-
Lennard, 2003). Pots on the left were hypoxic (N2-bubbled for 33 days); pots on
the right were aerated: (a) Zero salt in the solutions; (b) 20 mol m-3 (or 0.02 M)
NaCl in solutions; (c) 120 mol m-3 (or 0.12 M) NaCl in the solutions. ....................... 4
Figure 2. Regional location of Marandoo and Hope Downs iron ore mine. Image adapted
from Rio Tinto Iron Ore (2008). ................................................................................................ 8
Figure 3. Cross-sectional schematic of the Southern Fortescue geology (Rio Tinto Iron
Ore, 2008). .......................................................................................................................................... 9
Figure 4. Location of 17 irrigation pivots at the Hamersley Agricultural Project (HAP).
.............................................................................................................................................................. 11
Figure 5. Schematic diagram of a 50 ha irrigation pivot and soil and leaf sampling
locations in each pivot at the Hamersley Agricultural Project (HAP)..................... 12
Figure 6. Mean (± SE) soil particle size distribution – sand (red), silt (green) and clay
(blue) content at 0-10 cm and 20-30 cm for samples collected in March 2014,
based on Pivots 1-8, 10 and 11. .............................................................................................. 20
Figure 7. Changes (left) and trends (right) in electrical conductivity (EC, dS/m) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 22
Figure 8. Changes (left) and trends (right) in pHCa at 0-10 cm and 20-30 cm between
baseline (blue) and December 2013 (red) periods. ....................................................... 23
Figure 9. Changes (left) and trends (right) in CaCO3 equivalent (CCE, %) at 0-10 cm and
20-30 cm between baseline (blue) and December 2013 (red) periods. ................ 23
Figure 10. Changes (left) and trends (right) in soil organic carbon (OC, %) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods. ....... 24
Figure 11. Changes (left) and trends (right) in nitrate-nitrogen (NO3-N, mg/kg) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 24
Figure 12. Changes (left) and trends (right) in total N content (%) at 0-10 cm and 20-30
cm between baseline (blue) and December 2013 (red) periods. ............................. 25
Figure 13. Changes (left) and trends (right) in carbon/nitrogen (C/N) ratio at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods. ....... 26
Figure 14. Changes (left) and trends (right) in Colwell P concentration (mg/kg) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 26
Figure 15. Changes (left) and trends (right) in total P concentration (mg/kg) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods. ....... 27
Figure 16. Changes (left) and trends (right) in phosphorus retention index (PRI) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 28
Figure 17. Changes (left) and trends (right) in the effective cation exchange capacity
(ECEC, cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and
December 2013 (red) periods. ................................................................................................ 28
Figure 18. Changes (left) and trends (right) in exchangeable Ca concentration
(cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and December
2013 (red) periods. ...................................................................................................................... 29
Figure 19. Changes (left) and trends (right) in exchangeable Ca percentage (%) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 29
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Figure 20. Changes (left) and trends (right) in exchangeable Mg concentration
(cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and December
2013 (red) periods. ..................................................................................................................... 30
Figure 21. Changes (left) and trends (right) in exchangeable Mg percentage (%) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 31
Figure 22. Changes (left) and trends (right) in exchangeable Na concentration
(cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and December
2013 (red) periods. ..................................................................................................................... 31
Figure 23. Changes (left) and trends (right) in exchangeable Na percentage (ESP, %) at
0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red)
periods. ............................................................................................................................................. 32
Figure 24. Changes (left) and trends (right) in exchangeable K concentration
(cmol(+)/kg) at 0-10 cm between baseline (blue) and December 2013 (red)
periods. ............................................................................................................................................. 33
Figure 25. Changes (left) and trends (right) in exchangeable K percentage (%) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods. 33
Figure 26. Changes (left) and trends (right) in exchangeable Al percentage (%) at 0-10
cm between baseline (blue) and December 2013 (red) periods. ............................. 34
Figure 27. Changes (left) and trends (right) in chromium levels (mg/kg) at 0-10 cm and
20-30 cm between baseline (blue) and December 2013 (red) periods. ............... 34
Figure 28. Significant changes (left) and trends (right) in the overall mean phosphorus
concentration (P, %) in leaf tissue between March (blue) and December 2013
(red). .................................................................................................................................................. 36
Figure 29. Significant changes (left) and trends (right) in the overall mean calcium
concentration (Ca, %) in leaf tissue between March (blue) and December 2013
(red). .................................................................................................................................................. 36
Figure 30. Significant changes (left) and trends (right) in the overall mean magnesium
concentration (Mg, %) in leaf tissue between March (blue) and December 2013
(red). .................................................................................................................................................. 37
Figure 31. Significant changes (left) and trends (right) in the overall mean sulphur
concentration (S, %) in leaf tissue between March (blue) and December 2013
(red). .................................................................................................................................................. 37
Figure 32. Significant changes (left) and trends (right) in the overall mean zinc
concentration (Zn, mg/kg) in leaf tissue between March (blue) and December
2013 (red). ...................................................................................................................................... 38
Figure 33. Significant changes (left) and trends (right) in the overall mean boron
concentration (B, mg/kg) in leaf tissue between March (blue) and December
2013 (red). ...................................................................................................................................... 38
Figure 34. Significant changes (left) and trends (right) in the overall mean nitrate-
nitrogen concentration (NO3-N, mg/kg) in leaf tissue between March (blue) and
December 2013 (red). ................................................................................................................ 39
Figure 35. Significant changes (left) and trends (right) in the overall mean cadmium
concentration (Cd, ug/kg) in leaf tissue between March (blue) and December
2013 (red). ...................................................................................................................................... 39
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Figure 36. Significant changes (left) and trends (right) in the overall mean chromium
concentration (Cr, mg/kg) in leaf tissue between March (blue) and December
2013 (red)........................................................................................................................................ 40
Figure 37. Significant changes (left) and trends (right) in the overall mean lead
concentration (Pb, ug/kg) in leaf tissue between March (blue) and December
2013 (red)........................................................................................................................................ 40
Figure 38. Significant changes (left) and trends (right) in the overall mean nickel
concentration (Ni, mg/kg) in leaf tissue between March (blue) and December
2013 (red)........................................................................................................................................ 41
Figure 39. Linear relationship between pHCa and exchangeable Mg concentration
(cmol(+)/kg) at 0-10 cm. ........................................................................................................... 42
Figure 40. Linear relationship between pHCa and exchangeable Mg percentage (%)at 0-
10 cm. ................................................................................................................................................ 42
Figure 41. Linear relationship between exchangeable Mg percentage (%) and Ca
percentage (%) at 0-10 cm (left) and 20-30 cm (right)................................................ 42
Figure 42. Linear relationship between pH (CaCl2) and exchangeable K percentage (%)
at 0-10 cm. ....................................................................................................................................... 42
Figure 43. Linear relationship between exchangeable Mg percentage (%) and K
percentage (%) at 0-10 cm. ...................................................................................................... 42
Figure 44. Linear relationship between exchangeable Na percentage (ESP, %) and Ca
percentage (%) at 0-10 cm (left) and 20-30 cm (right)................................................ 43
Figure 45. Linear relationship between electrical conductivity (EC, dS/m) and
exchangeable Na concentration (cmol(+)/kg) at 0-10 cm (left) and 20-30 cm
(right). ............................................................................................................................................... 43
Figure 46. Linear relationship between exchangeable Na concentration (cmol(+)/kg)
and Na percentage (ESP, %) at 0-10 cm (left) and 20-30 cm (right). ..................... 44
Figure 47. Linear relationship between exchangeable Al concentration (cmol(+)/kg)
and Al percentage (%) at 0-10 cm (left) and 20-30 cm (right). ................................ 44
Figure 48. Linear relationship between chromium concentrations (Cr, mg/kg) in leaf
tissue and soil at 0-10 cm (left) and 20-30 cm (right), based on Span 3 results
from March to December 2013 with December 2013 outliers included (top) and
removed (bottom). ....................................................................................................................... 48
Figure 49. Comparing a good combination (left) and a bad combination (right) of three
variables used in two-step cluster analysis .................................................................... 118
Figure 50. Test 1 clustering of 10 active irrigation pivots at the HAP, based on electrical
conductivity (EC, dS/m) and exchangeable Al percentage (%) and colour coded:
Cluster 1 (red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green). ...... 119
Figure 51. Test 2 clustering of 10 active irrigation pivots at the HAP, based on CaCO3
equivalent (CCE, %) and carbon/nitrogen (C/N) ratio and colour coded: Cluster
1 (red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green)....................... 119
Figure 52. Test 3 clustering of 10 active irrigation pivots at the HAP, based on clay
content (%) and arsenic concentration (mg As/kg) and colour coded: Cluster 1
(red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green). ......................... 120
Figure 53. Gross irrigation volumes used at each irrigation pivot at the Hamersley
Agricultural Project (HAP) for the baseline (blue) period, and periods between
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baseline and December 2013 (red), and baseline and February 2014 (green),
based on unpublished data (Rio Tinto Iron Ore, 2014). ............................................ 123
Figure 54. Level of importance of variables (EC and exchangeable Al %) used in test 1
............................................................................................................................................................ 124
Figure 55. Description of cluster size and mean values for variables (EC and
exchangeable Al %) in test 1.................................................................................................. 124
Figure 56. Comparing the distribution of individual clusters in test 1 (EC and
exchangeable Al %) with the overall distribution of the December 2013 soil
(20-30 cm layer, Span 3) data set ........................................................................................ 125
Figure 57. Level of importance of variables (CCE and C/N ratio) used in test 2 ............. 126
Figure 58. Description of cluster size and mean values for variables (CCE and C/N ratio)
in test 2 ........................................................................................................................................... 126
Figure 59. Comparing the distribution of individual clusters in test 2 (CCE and C/N
ratio) with the overall distribution of the December 2013 soil (20-30 cm layer,
Span 3) data set ........................................................................................................................... 127
Figure 60. Level of importance of variables (clay % and As concentration) used in test 3
............................................................................................................................................................ 128
Figure 61. Description of cluster size and mean values for variables (clay % and As
concentration) in test 3 ........................................................................................................... 128
Figure 62. Comparing the distribution of individual clusters in test 3 (clay % and As
concentration) with the overall distribution of the December 2013 soil (20-30
cm layer, Span 3) data set ....................................................................................................... 129
Figure 63. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights of 10,
30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.767x + 4.409 and R2 =
0.996) .............................................................................................................................................. 132
Figure 64. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights of 10,
30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.772x + 4.435 and R2 =
0.999) .............................................................................................................................................. 133
Figure 65. Calcium carbonate equivalent (CCE, %) of eight September 2013 and
December 2013 soil samples determined by Methods 1 and 2 .............................. 135
Figure 66. Correlation between pH (CaCl2) and calcium carbonate equivalent (CCE, %)
of eight September and December 2013 soil samples determined using Method
1 (left) and Method 2 (right) ................................................................................................. 135
Figure 67. Comparing expected and reported CCE (%) values from Method 1 (blue) and
Method 2 (red) from standard additions of 0, 2, 4, 6, 8 and 10 mg CaCO3/g .... 136
Figure 68. Mean monthly rainfall and temperature at Wittenoom in the Pilbara region,
Western Australia ...................................................................................................................... 142
Figure 69. Trends in mean exchangeable sodium percentage (ESP,% ± SEM) at two
depths (0-10 cm and 20-30 cm)of the soil profile of the HAP area. ...................... 145
Figure 70. Mean (± SEM) of exchangeable Na (meq/100g of soil) of a total of 28 soil
samples taken at two depths, 0-10 cm (14 samples) and 20-30 cm (14 samples).
............................................................................................................................................................ 146
Figure 71. Mean (± SEM) of exchangeable sodium percentage (ESP) of a total of 28 soil
samples taken at 0-10 cm (14 samples) and 20-30 cm (14 samples). ................. 146
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LIST OF TABLES
Table 1. One-way ANOVA between Spans 1, 2 and 3 for soil properties at 0-10 cm and
20-30 cm in December 2013. ................................................................................................... 17
Table 2. One-way ANOVA between Spans 1, 2 and 3 for leaf nutrient composition in
December 2013. ............................................................................................................................ 18
Table 3. Overall mean baseline values and standard errors of soil properties in the 0-10
cm and 20-30 cm soil layers. .................................................................................................... 19
Table 4. Overall mean values and standard errors for soil properties at the 0-10 cm and
20-30 cm soil layer between baseline (October 2012 to February 2013) and
December 2013. ............................................................................................................................ 21
Table 5. Mean values and standard errors of 20 leaf nutrient concentrations between
March and December 2013, based on 10 irrigation pivots and 3 monitoring
spans per pivot. ............................................................................................................................. 35
Table 6. Correlation (R2) between soil properties at 0-10 cm, using only Span 3 data
from baseline to December 2013 based on Pivots 1-8, 10 and 11. .......................... 45
Table 7. Correlation (R2) between soil properties at 20-30 cm, using only Span 3 data
from baseline to December 2013 based on Pivots 1-8, 10 and 11. .......................... 46
Table 8. Correlation (R2) between soil particle size and soil chemical properties at 0-10
cm and 20-30 cm, using Span 3 results based on Pivots 1-8, 10 and 11. .............. 47
Table 9. Composition of dewatering surplus and fertigation mixture sampled in
December 2013. ............................................................................................................................ 49
Table 10. Saturation indices of solid phases in source water (pH 8.2) and fertigation
mixture (pH 8.0) sampled in December 2013, calculated from WEB-PHREEQ
using input values in Table 9 – Al, Cd, Pb and Fe concentrations are half their
detection limit. ............................................................................................................................... 50
Table 11. Saturation indices of carbonates, (hydr)oxides and apatite in source water
and fertigation mixture, modelled at pH 7. ........................................................................ 50
Table 12. Ash content (%) and ash alkalinity (eq/g) of duplicate hay subsamples from
Pivots 1-5 collected in February 2014 for the growth cycle between November
2013 and January 2014 - titration of 50 ml of 0.0494 M HCl and hay ash with
0.05 M Na2CO3. ............................................................................................................................... 51
Table 13. Mean net alkalinity values determined from a mass balance of alkalinity
added from irrigation and removed by hay production for Pivots 1-5 between
November 2013 and January 2014 – based on the total alkalinity of irrigation
water measured in November 2013, using unpublished hay yield and irrigation
data (Rio Tinto Iron Ore, 2014). ............................................................................................. 53
Table 14. Total net alkalinity gained from irrigated pastures for Pivots 1-5 throughout
the study period from October 2012 to January 2014 – assuming relatively
constant total alkalinity of irrigation water, using unpublished hay yield and
irrigation data (Rio Tinto Iron Ore, 2014). ........................................................................ 53
Table 15. Comparing mean leaf nutrient concentrations of C. gayana in December 2013
with "normal"/adequate nutrient concentration ranges for C. gayana and
Phalaris aquatica. ......................................................................................................................... 64
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Table 16. Comparing December 2013 concentrations in leaf tissue of C. gayana with
maximum tolerable levels (National Research Council, 2000) and overall
toxicity limits (Underwood and Suttle, 1999) for ruminant livestock (e.g., such
as cattle and sheep). .................................................................................................................... 66
Table 17. Correlation (R2) between leaf nutrient composition and soil properties at 0-
10 cm, using only Span 3 data from March to December 2013................................. 90
Table 18. Correlation (R2) between leaf nutrient composition and soil properties at 20-
30 cm, using only Span 3 data from March to December 2013................................. 91
Table 19. Correlation (R2) between leaf composition, using only Span 3 data from
March to December 2013 ......................................................................................................... 92
Table 20. Standardisation of ~0.05 M HCl with 0.05 M Na2CO3 ............................................. 114
Table 21. Comparing ash alkalinity and net alkalinity results for finely milled and non-
milled duplicate hay subsamples for Pivots 1-5 between November 2013 and
January 2014 ................................................................................................................................ 115
Table 22. Calculated excess total alkalinity (mg CaCO3/L) in irrigation water to be
neutralised by sulphuric acid (H2SO4) to cease soil alkalinisation, based on
results in Table 17 ..................................................................................................................... 115
Table 23. Designated cluster memberships for irrigation pivots using a specified 4-
cluster solution, based on Span 3 soil properties from December 2013 and
particle size from March 2014 at the 20-30 cm layer. Colour coding is
independent for each test. ...................................................................................................... 118
Table 24. One-way ANOVA between clusters for soil properties at 20-30 cm, using Span
3 December 2013 results ........................................................................................................ 121
Table 25. Preliminary CaCO3 content (mg) and calculated CaCO3 equivalent (CCE, %) of
unknown samples using Method 2 ..................................................................................... 133
Table 26. Comparing calcium carbonate equivalent (CCE, %) assessed by Method 1 and
2 for eight September 2013 and December 2013 soil samples and their
respective soil pHCa values – pivot and span denoted as ‘P’ and ‘S’, respectively
............................................................................................................................................................ 134
Table 27. Comparing expected soil calcium carbonate equivalent (CCE, %) and reported
values from Methods 1 and 2 using standard additions of 0, 2, 4, 6, 8, 10 and
100 mg CaCO3/g .......................................................................................................................... 135
Table 28. Texture classifications from physical observations of texture and particle size
analysis using mid-infrared reflectance (MIR) spectroscopy (Rayment and
Lyons, 2011, p. 80) ..................................................................................................................... 138
Table 29. Water quality guidelines for risk of dispersion, crusting and swelling of soils
with > 30 % swelling clay (California Fertilizer Association, 1995). The location
of the HAP in this framework is indicated by the highlighted row. ...................... 139
1
1. INTRODUCTION
1.1. SALINITY AND SODICITY IN IRRIGATED AGRICULTURE
Groundwater constitutes an important water source for irrigated agriculture in
arid and semi-arid regions where rainfall is often low, unreliable, and frequently
exceeded manifold by annual evapotranspiration (Scanlon et al., 2006). However, due to
population growth and increased demand for water, pronounced water scarcity,
particularly in developing countries, has led to an increasing trend of poor irrigation
practice (e.g., overuse of saline-sodic groundwater, over-pumping of coastal aquifers,
insufficient subsoil drainage) and the continual degradation of irrigated land (Ondrasek
et al., 2011).
According to the Food and Agriculture Organization (FAO) and the United
Nations Educational, Scientific, and Cultural Organization (UNESCO), secondary
salinisation, alkalinisation (sodification) and waterlogging has affected more than 50%
of existing irrigated land worldwide (Pessarakli and Szabolcs, 1999, Martinez-Beltran
and Manzur, 2005, Sundquist, 2007). In total, about 6.5% of the global land area (or more
than 830 million hectares) is salt-affected (Shahid et al., 2011, Hasanuzzaman et al.,
2013), with many millions of hectares abandoned annually as a consequence (Szabolcs,
1988). Indeed, virtually all irrigated land in semi-arid and arid lands will, to some degree,
be susceptible to problems with salinity and sodicity (alkalinity) as salts accumulate
through time (Pessarakli and Szabolcs, 1999).
The secondary formation of salt-affected soils substantially affects the growth
and productivity of irrigated crops and pastures worldwide (Bernstein, 1975, Pessarakli
and Szabolcs, 1999, Pitman and Läuchli, 2002, Rengasamy, 2002, Wang et al., 2011, Javid
et al., 2012). In Australia, sodicity is most prevalent (Rengasamy and Olsson, 1991),
affecting over 80% of irrigated soils, with about 72% alkaline-sodic and 11% non-
alkaline sodic (Northcote and Skene, 1972). Consequently, the poor physical and
chemical conditions induced by sodicity may partly explain why the productivity of
Australian crops is generally low (Rengasamy and Olsson, 1993).
To gain a better understanding, the various implications of salinity, sodicity and
alkalinity for plant growth will be discussed in some detail. This is followed by a section
on the scope and objectives of this research.
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1.2. SALT AFFECTED SOILS AND IMPLICATIONS FOR PLANT GROWTH
Salt-affected soils comprise several groups, including saline, saline-sodic, and
sodic soils (Pessarakli and Szabolcs, 1999, Ondrasek et al., 2011):
i. saline soils develop under high concentrations of soluble salts (electrical
conductivity in saturated extract (ECe) > 4 dS/m) and low exchangeable Na
percentage (ESP < 15);
ii. saline-sodic soils develop under high electrolyte concentrations (> 4 dS/m) and
high ESP (> 15); and,
iii. sodic soils develop under low electrolyte concentrations (< 4 dS/m) and high ESP
(> 15%) which may, or may not, be alkaline (pH > 8.5) depending on the
predominant type of Na salt – e.g., Na2CO3 and NaHCO3 are capable of alkaline
hydrolysis, while Na2SO4 and NaCl are neutral.
Alkalinisation and sodification are distinct processes where alkalinisation per se
is generally defined by an increase in pH and pH buffering capacity (see Section 1.2.2).
However, due to the presence of Na2CO3 and NaHCO3, alkalinisation and sodification
often co-occur, resulting in alkaline-sodic soils. Therefore, salinisation, sodification and
alkalinisation are three serious sources of soil degradation in irrigated agriculture and
their various effects on plant growth are discussed.
1.2.1. SALINITY AND SALT STRESS
Salt-affected soils usually have low biological activity (Pessarakli and Szabolcs,
1999). Salinity suppresses the growth of all plants, but the degree to which they are
affected by salinity varies widely among species (Parida and Das, 2005) and with the
degree of waterlogging in the root zone (Barrett-Lennard and Shabala, 2013). The
injurious effect of salt on plants directly involves both osmotic and ionic stresses (Yang
et al., 2009), including: (1) increased osmotic potential of the soil solution which
decreases water availability to plants (i.e., low water potential) and thus causes
physiological drought (Pessarakli and Szabolcs, 1999); (2) nutrient imbalance and
disruption of intracellular ion homeostasis in plants by ion displacement and deficiency
(Parida and Das, 2005); and (3) toxicity from the uptake of excessive Na+ and Cl- ions
which damages plant cells and tissues (Bernstein, 1975, Warrence and Bauder, 2001,
Munns, 2002, Phocaides, 2007, Saqib et al., 2008, Yang et al., 2008a, Evelin et al., 2009,
Yang et al., 2009). Excessive levels of salinity may eventually cause death as
Investigating the impacts of groundwater on soil properties and pasture
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photosynthesis, protein synthesis, and energy and lipid metabolism become severely
impaired (Sudhir and Murthy, 2004, Parida and Das, 2005). Seed germination also
becomes constrained (Vicente et al., 2007).
When coinciding with waterlogged soils, salinity can have serious implications
for plants (Cramer and Hobbs, 2002). Waterlogging often occurs in areas of shallow
watertable or in sodic soils that are poorly drained (Barrett-Lennard and Shabala, 2013)
– this is a common feature in many irrigated agricultural landscapes of arid and semi-
arid Australia (Grieve et al., 1986, McFarlane et al., 1989, Cramer and Hobbs, 2002,
McFarlane and Williamson, 2002, Shaw et al., 2013). Waterlogging induces soil hypoxia
which causes: (1) a rapid decline in root and shoot growth, and subsequent senescence
of roots; (2) impaired solute movement and nutrient uptake; and, (3) decreased stomatal
conductance and/or leaf water potentials (Barrett-Lennard, 2003). Under both saline
and waterlogged conditions, plant growth and survival may also greatly diminish from
increased ion toxicity (i.e., Na+ and Cl-, Figure 1; Barrett-Lennard and Shabala, 2013).
1.2.2. SODICITY AND ALKALI STRESS
Sodic (alkali) stress may similarly exert both osmotic stress and ion injury, but
with the added effect of high pH (Yang et al., 2008a, Yang et al., 2009, Davis et al., 2012).
Additionally, the presence of high Na+ may severely damage soil structure and reduce
permeability (see Section 1.2.3; Warrence and Bauder, 2001, Bethune and Batey, 2002).
It is understood that sodicity and alkalinity could inflict greater damage to crop and
pasture production than salinity alone (Javid et al., 2012).
Many authors recognise that it is the high pH (> 8.5) and buffer capacity in
alkaline-sodic soils that causes injurious effects on plants (Pessarakli and Szabolcs, 1999,
Wang et al., 2008, Yang et al., 2008a, Yang et al., 2008b, Wang et al., 2011, Li et al., 2012).
Severely alkaline-sodic conditions may inhibit plant growth by disrupting
photosynthetic activities (Yang et al., 2008b) and anti-oxidative metabolism (Kukavica
et al., 2013), and also interfere with ion uptake and mineral nutrition (Peng et al., 2008).
Alkalinity may suppress the solubility and hence the bioavailability of various macro-
(e.g., Ca, N and P) and micro-nutrients (e.g., Cu, Fe, Mg, Ni, and Zn; Umali, 1993) which
becomes a principle limiting factor to plant productivity (Marlet et al., 1998). High levels
of alkalinity may also constrain seed germination (Guan et al., 2009, Li et al., 2010) and
seedling survival (Liu et al., 2010, Patil et al., 2012).
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Moreover, elevated bicarbonate concentrations could significantly depress root
growth by pH-buffering in the root apoplast and direct interference on root metabolism
(Peiter et al., 2001, Javid et al., 2012). The presence of substantial amounts of bicarbonate
may also cause Ca to precipitate and this effectively increases the ESP or SAR which may
exacerbate soil structural problems (ANZECC/ARMCANZ, 2000).
Figure 1. Hypoxia and salinity interact to decrease the growth of wheat plants (Barrett-Lennard,
2003). Pots on the left were hypoxic (N2-bubbled for 33 days); pots on the right were aerated:
(a) Zero salt in the solutions; (b) 20 mol m-3 (or 0.02 M) NaCl in solutions; (c) 120 mol m-3 (or
0.12 M) NaCl in the solutions.
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1.2.3. DETERIORATION OF SOIL PHYSICAL CONDITION
Both salinisation and sodification frequently co-occur, however the destructive
effects of sodicity only become evident after rainfall or irrigation when soluble salts are
leached (Rengasamy and Olsson, 1991). Elevated concentrations of Na+ causes soil
particles to deflocculate and colloidal particles to clog pores, resulting in reduced
permeability to air and water (Bernstein, 1975, Marlet et al., 1998). Once sodic soils dry
after wetting, surface crusting and hard-setting occurs (Condom et al., 1999), further
reducing infiltration and hydraulic conductivity, and increasing soil erodibility
(Pessarakli and Szabolcs, 1999). Such poor physical conditions impair plant
development by restricting root growth, making it difficult to obtain water and nutrients
(Stearns et al., 2005, Saqib et al., 2008). Seedling emergence and establishment also
become severely inhibited (Warrence and Bauder, 2001). As mentioned, poor drainage
may also cause temporary flooding or waterlogging which further impairs root function
and ultimately inhibits plant growth and survival (Marlet et al., 1998, Alam, 1999,
Warrence and Bauder, 2001, Barrett-Lennard, 2003).
1.3. PROJECT SCOPE
1.3.1. MINE DEWATERING IN THE PILBARA
In the Pilbara region of Western Australia, iron ore production has rapidly
developed due to growing markets in the major East Asian steel-producing countries,
China, Japan, South Korea and Taiwan (Economic Consulting Services, 2007, Department
of Water, 2010b). However, as iron ore operations continue to expand, the cumulative
impacts of mining on the environment need to be assessed.
Many iron ore mines in the region now extract ore from below the watertable
(Barber and Jackson, 2011) and, to maintain dry working conditions, an array of deep
wells surrounding the mine are pumped at high rates to locally depress the groundwater
level and this is referred to as ‘mine dewatering’ (Woldai and Taranik, 2008). Mine
dewatering consequently generates significant volumes of water that frequently exceed
mine use requirements and thus require disposal. This may involve aquifer reinjection,
transfer to other industrial locations, utilisation as irrigation water for agriculture, and
contingency discharges to nearby environments, such as rivers and streams
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(Department of Water, 2013). However, as below-watertable mining continues to
develop, dewatering will present major environmental and socio-economic challenges in
the region, particularly if in-stream discharge becomes increasingly practiced in the
future.
1.3.2. THE HAMERSLEY AGRICULTURAL PROJECT
The Hamersley Agricultural Project (HAP) is an irrigated forage scheme that
commenced operation in October 2012 as a mitigation strategy for Rio Tinto, in the
central Pilbara region of Western Australia. The HAP utilises surplus water generated
from the Marandoo Mine Phase 2 (MMP2) project as the source water for irrigating
Rhodes grass (Chloris gayana) for hay production (Hamersley Iron Pty Ltd, 2011) and
provides an exceptional opportunity for drought-proofing pastoral stations in the region
(The Chamber of Minerals and Energy of Western Australia, 2012). Accordingly,
contingency discharges from Marandoo mine to the Southern Fortescue River that began
in July 2012 have reduced from continuous to intermittent flow in favour of water use in
the HAP.
While contingency discharges may be substantially reduced, in-stream discharge
at Rio Tinto’s Hope Downs iron ore mine is required for flow supplementation in Weeli
Wolli Creek (Environmental Protection Authority, 2001). There is consequently
significant attention towards the potential cumulative impacts of in-stream discharge on
the ecosystem (e.g., Wetland Research & Management, 2010, Crisalis International Pty
Ltd, 2012), particularly for creek-bed and sediment properties and hence for stream and
riparian vegetation. Thus, as part of on-going research, the present study explores the
effects of source water from Marandoo mine on irrigated soils and pasture growth at the
HAP.
1.3.3. RESEARCH OBJECTIVES
The study explores the implications of irrigation of water derived from mine
dewatering at Marandoo for soil condition and pasture growth and nutrition at the HAP.
Soil and leaf tissue data were examined for key changes and trends between baseline
(October 2012 to February 2013) and December 2013 sampling periods. This research
also aims to identify factors that need to be considered to develop sustainable irrigation
and soil management practices for long-term pasture productivity (20 years).
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The main objectives of this study are to:
I. identify how irrigation water has altered (a) soil properties and, (b) leaf
composition of pasture species at the HAP – based on time trends for data from
baseline to December 2013 sampling periods;
II. examine the composition of irrigation water (with added nutrients) to determine
possible precipitate formation; and,
III. based on Objectives (I) and (II), identify any potential for adverse changes in
long-term pasture productivity and soil management.
Recommendations on future soil and leaf monitoring were also developed and
are provided in Appendix G.
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2. MATERIALS AND METHODS
2.1. STUDY AREA
The HAP area is located below the plains of the Karijini National Park and is
approximately 6 km west of the Marandoo mine (22o34’12.45” S, 118o00’32.99” E) in the
central Pilbara region of Western Australia (Figure 2). The study area falls within a 570
km2 upper catchment of the Southern Fortescue River Valley, bounded to the east and
west by rugged hills of outcropping Brockman Iron and Marra Mamba Iron Formations
(Figure 3). Proterozoic rocks of the Hamersley Province constitute the geology of this
catchment, with the Marra Mamba Iron Formation as the basal stratigraphic unit and ore
deposit at Marandoo. Beyond this unit are widely distributed Cainozoic rocks and soils,
including erosional remnants of the Wittenoom Formation and sequences of tertiary
sediments (Rio Tinto Iron Ore, 2008).
Figure 2. Regional location of Marandoo and Hope Downs iron ore mine. Image adapted from
Rio Tinto Iron Ore (2008).
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The climate is arid tropical, with distinct summer wet and winter dry seasons
(Gentilli, 1972, Rio Tinto Iron Ore, 2008). Summer extends from October to April, with
highest monthly mean temperatures of 36-43oC, while winter extends from May to
September, with highest monthly mean temperatures of 26-34oC (Bureau of
Meteorology, 2014a). During summer, maximum daily temperatures can exceed 47oC
(Rio Tinto Iron Ore, 2008). Rainfall mainly occurs between December and March, but is
generally low, erratic and unreliable. The average annual rainfall recorded from the
Bureau of Meteorology weather stations in the vicinity are approximately 363 mm at
Tom Price, 394 mm at Marandoo and 461 mm at Wittenoom.
Figure 3. Cross-sectional schematic of the Southern Fortescue geology (Rio Tinto Iron Ore,
2008).
However, as the Pilbara coastline is prone to cyclonic activity (averaging five
tropical cyclones annually; Department of Parks and Wildlife, 2013), cyclones passing
inland may generate localised heavy rain with over 100-200 mm falling within 24 hours
(Mattiske Consulting Pty Ltd, 2008, Rio Tinto Iron Ore, 2008). This consequently causes
major flooding and considerable erosion. In contrast, drought is common throughout the
region as evaporation rates exceed average annual rainfall by about 7.5 fold (Van
Vreeswyk et al., 2004). The average annual pan evaporation rate in the study region
ranges from approximately 2800 mm to 3200 mm, based on at least 10 years of records
from 1975 to 2005 (Bureau of Meteorology, 2014a).
In response to climatic regimes, most rivers and tributaries in the region are
ephemeral and tend to associate with shallow alluvial aquifers or sub-surface
groundwater storages (Department of Water, 2010a). Vegetation communities along the
local tributaries are consequently adapted to these conditions, comprising woodlands of
Acacia citrinoviridis interspersed with occasional patches of Eucalyptus victrix and E.
xerothermica (Mattiske Consulting Pty Ltd, 2008). In the valley, the vegetation varies
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from open woodlands of E. victrix and A. citrinoviridis to shrublands of A. pyrifolia and A.
bivenosa on alluvial flats.
2.1.1. IRRIGATION PIVOTS
The HAP comprises 17 centre-pivot irrigation systems that cover approximately
850 ha, including a 7 ha pivot for native seeds, within an area of 2800 ha (Figure 4). The
pasture chosen (C. gayana) is a subtropical (C4) perennial that is grown throughout the
year for stock feed. Water is supplied at approximately 60-80 ML/d – i.e., 80 ML/d
between October and March and 60 ML/d between April and September for an estimated
duration of approximately 20 years, based on the life of MMP2 and supply of dewatering
surplus (Hamersley Iron Pty Ltd, 2011). Low concentrations of liquid fertilisers are also
applied with irrigation water to meet daily crop requirements.
Figure 4. Location of 17 irrigation pivots at the Hamersley Agricultural Project (HAP).
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2.2. SAMPLING AND MONITORING SOIL, LEAF TISSUE, AND WATER QUALITY
The period between October 2012 and February 2013 is defined as the baseline.
During this period, each irrigation pivot was seeded and irrigation commenced, but at
different times for each pivot. Soil and leaf tissue were subsequently sampled on a
quarterly basis in March, July, September/October and December 2013 in the early
stages of the pasture growth cycle. Baseline leaf compositions of the pasture were not
available; therefore the sampling will represent different durations of continuous
irrigation for each pivot.
All sampling was planned and conducted by site personnel and hence a 2-day site
visit was undertaken by the author on the 17th to 18th December, 2013, as a
reconnaissance to understand the site, the monitoring program and sampling protocols.
Soil and leaf tissue samples were collected quarterly from the same marked location with
Figure 5 illustrating the general sampling area. Soils were sampled from depths of 0-10
cm and 20-30 cm, while leaf tissue was taken as random grab samples of whole tops (i.e.,
the whole plant above cutting height). Leaf samples were collected at the beginning
stages of seed head emergence. Soil and leaf tissue samples were bulked from five
locations within the three innermost spans along a transect route (Figure 5). These three
spans (to be referred as 'Span 1, 2, and 3') are ‘Help Lines’ which monitor the varying
rates of irrigation for crop production and soil moisture levels. The rate of irrigation at
Span 1, 2, and 3 was 2X, ½X, and X respectively, where X is the expected (or normal) rate
required for daily crop requirements. Soil and leaf tissue samples were then bulked from
each span for analysis by the CSBP Soil and Plant Analysis Laboratory, Western Australia.
Figure 5. Schematic diagram of a 50 ha irrigation pivot and soil and leaf sampling locations in
each pivot at the Hamersley Agricultural Project (HAP).
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In addition to examining soil chemical properties, mid-infrared reflectance (MIR)
for soil particle size (Rayment and Lyons, 2011, p. 80) was conducted by CSBP for March
2014 samples only. Since weathering is a relatively slow process, soil texture should
remain fairly constant (McCauley et al., 2005). No other data from March 2014 were
included in this study due to limited time.
Irrigation water samples were collected on a monthly basis, from: (1) the
Reduced Pressure Zone (RPZ), representing the quality of source water from the
Marandoo dewatering operations; and, (2) the fertigation mixture. Samples were
retained in an iced cooler for immediate delivery to SGS Australia for water quality
analysis. In this study only November and December 2013 data were used.
2.3. GEOCHEMICAL MODELLING FOR MINERAL PRECIPITATION
To determine possible mineral precipitation from irrigation water, the
saturation index (SI) of solid phases in solution were computed using the aqueous
geochemical model WEB-PHREEQ (Saini-Eidukat, 1999, Saini-Eidukat and Yahin, 1999).
This is a WWW-based version of PHREEQC by Parkhurst and Appelo (1999) for
performing a variety of low-temperature aqueous geochemical calculations. In this
study, quick speciation calculations of single solutions were performed using the quality
of source water and fertigation mixture in December 2013. The saturation index can be
defined as:
SI = logIAP
Ksp [1]
where, IAP and Ksp are the ion activity product (the activities of all the ions) and
the solubility product, respectively. Interpretations for insoluble mineral formation are
as follows:
a. IAP = Ksp, SI = 0 (or -0.2 < SI < 0.2), the solution is saturated with the
mineral (equilibrium);
b. IAP < Ksp, SI < 0, the solution is undersaturated with the mineral
(dissolution); or,
c. IAP > Ksp, SI > 0, the solution is oversaturated with the mineral
(precipitation).
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2.4. ALKALINITY MASS BALANCE AND ASH ALKALINITY DETERMINATION
The amount of alkalinity added in irrigation water and removed in hay yield was
determined to confirm the net change in soil alkalinity. As plants absorb exchangeable
base cations from solution a hydrogen ion is released to maintain electrical balance and
the resulting loss of bases and build-up of hydrogen ions causes acidity in the
rhizosphere (Plaster, 2013). Therefore, it was hypothesised that the soil pH will increase
as long as the rate of alkalinity applied from irrigation water exceeds that removed by
plants. A simple mass balance can be used to describe this relationship:
Net soil alkalinity = water(alkalinity × 𝑣) − hay(alkalinity × 𝑚) [2]
where, v and m are the volume of irrigation water and dry weight of hay yield,
respectively.
The ash alkalinity of hay was determined from duplicate subsamples of dry hay
from Pivots 1 (cut 8), 2 (cut 7), 3 (cut 6), 4 (cut 7) and 5 (cut 7). Samples were collected
in late January 2014 and represent the growth cycle from mid November 2013 to early
January 2014. Dry hay samples were finely milled and weighed to approximately 500 mg
in porcelain crucibles. Samples were then heated to approximately 550oC in a muffle
furnace for 6 hours. Crucibles were left to cool in desiccators and subsequently weighed
to determine the ash content (Poorter et al., 2011):
Ash content = dry weight of ash (g)
dry weight of plant sample (g)× 100 [3]
The ash was treated with 50 ml of 0.05 M hydrochloric acid, HCl, and boiled for a
maximum of 30 seconds to remove the carbonate (Poorter et al., 2011). Once cooled to
room temperature, this was then titrated against 0.05 M sodium carbonate, Na2CO3, with
3 drops of methyl orange as the endpoint indicator. Ash alkalinity was determined from
equation [4]:
Ash alkalinity = 𝑐[HCl]𝑣[HCl]− 𝑐[Na2CO3]𝑣[Na2CO3]
dry weight of plant sample (g) [4]
where, c and v are the concentration and volume of the reagent used,
respectively.
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The acid was prepared by adding 4.9 ml HCl (32%, 10.18 M) to 100 ml deionised
water and diluted to 1 L. The base was prepared by dissolving 5.3 g of Na2CO3
(anhydrous) in 100 ml deionised water and diluting to 1 L. Methyl orange was prepared
by dissolving 0.1 g of the solid in 100 ml deionised water. Prior to determining ash
alkalinity, HCl was standardised against 0.05 M Na2CO3 and the volume of Na2CO3 used
to reach endpoint is summarised in Appendix C.
2.5. EXCHANGEABLE SODIUM PERCENTAGE
In this study, soil ESP was determined by the CSBP Soil and Plant Analysis
Laboratory employing method 15A1 (Rayment and Lyons, 2011). This method however
does not include the removal of soluble salts prior to determination of the exchangeable
cations (Samaraweera, 2015). Therefore, a follow up study on the impact of irrigation on
soil sodicity was undertaken (Samaraweera, 2015; see Appendix H) by determining
exchangeable Na concentrations via two methods: (1) 15A1, that does not include pre-
treatment of soluble salts; and, (2) 15C1, that includes pre-treatment for soluble salts (by
washing with 60% aqueous ethanol and 20% aqueous glycerol). A total of 28 samples
collected from 7 locations at 2 depths from HAP area were analysed.
2.6. DATA ANALYSIS
To determine the effect(s) of irrigation with slightly alkaline and slightly
brackish-sodic water on soil condition, various soil properties and leaf nutrient
concentrations were examined using a series of parametric statistics from the IBM SPSS
Statistics 21 (2012) and Microsoft Excel (2007) software packages. Significant changes
over 15 months between baseline (October 2012 to February 2013) and December 2013
sampling periods were identified using t-Tests and one-way analysis of variance
(ANOVA), and available time series data evaluated for systematic pattern. Bivariate
correlation and linear regression analyses were also performed concurrently to study
possible cause-and-effect relationships amongst: (1) soil chemical properties, (2) soil
particle size and soil chemical properties, (3) soil chemical properties and leaf nutrient
concentrations, and (4) leaf nutrient concentrations (see Appendix A). The calculated
Pearson Correlation Coefficient (r) was converted to the Coefficient of Determination
(R2), with interpretations on correlation strength based on crude estimates – e.g., very
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strong (0.80-0.99), strong (0.60-0.79), moderate (0.40-0.59), weak (0.20-0.39) and very
weak to no correlation (0.00-0.19).
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3. RESULTS
3.1. SIGNIFICANT DIFFERENCES BETWEEN MONITORING SPANS
In general, soil properties and leaf nutrient composition in December 2013 were
not significantly different between Spans 1, 2 and 3 despite varying irrigation rates. Only
soil nitrate-nitrogen (NO3-N) concentrations were significantly different at both 0-10 cm
(P < 0.05) and 20-30 cm soil layers (P < 0.01; Table 1). In leaf tissue, zinc concentrations
were significantly different (P < 0.05; Table 2).
Table 1. One-way ANOVA between Spans 1, 2 and 3 for soil properties at 0-10 cm and 20-30 cm
in December 2013.
Parameters 0-10 cm 20-30 cm
F P F P
Electrical conductivity, EC 0.85 0.44 1.19 0.32
pHCa 2.06 0.15 2.85 0.08 CaCO3 equivalent, CCE 0.10 0.90 0.21 0.81
Organic C, OC 0.30 0.75 1.42 0.26
NO3-N* 5.07 0.01 6.93 0.00
NH4-N 1.24 0.30 2.21 0.13 Total N 0.72 0.49 3.16 0.06
C/N ratio 0.09 0.92 1.23 0.31
Colwell P 1.02 0.37 0.90 0.42
Total P 0.08 0.92 1.75 0.19 Phosphorus retention index, PRI 0.22 0.80 2.42 0.11
Colwell K 0.89 0.42 0.69 0.51
Total K 0.08 0.93 0.02 0.98
Ex. Ca 0.33 0.72 1.25 0.30 Ex. Mg 0.88 0.43 0.61 0.55
Ex. Na 0.10 0.90 0.78 0.47
Ex. K 0.74 0.49 0.30 0.74
Ex. Al 0.18 0.84 0.24 0.79 Effective cation exchange capacity, ECEC 0.48 0.63 1.21 0.31
Ex. Ca percentage 0.67 0.52 0.72 0.50
Ex. Mg percentage 2.49 0.10 0.58 0.56
Ex. Na percentage (ESP) 0.20 0.82 0.06 0.94 Ex. K percentage 0.05 0.95 1.06 0.36
Ex. Al percentage 0.11 0.90 0.17 0.85
As 0.02 0.98 0.04 0.96
Cd 0.25 0.78 1.04 0.37 Cr 0.36 0.70 0.37 0.69
Pb 0.07 0.94 0.03 0.97
*statistical significance (P ≤ 0.01)
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Table 2. One-way ANOVA between Spans 1, 2 and 3 for leaf nutrient composition in December
2013.
Parameter F P Total N 0.83 0.44 P 2.35 0.11 K 0.02 0.98 Ca 0.88 0.42 Mg 2.12 0.14 Na 0.33 0.72 Cl 0.12 0.89 S 1.86 0.18 Cu 2.40 0.11 Fe 1.01 0.38 Mn 0.13 0.88 Zn* 4.00 0.03 B 0.10 0.91 NO3-N 0.55 0.58 Al 0.22 0.81 As 0.04 0.96 Cd 0.69 0.51 Cr 0.16 0.85 Pb 1.91 0.17 Ni 0.01 1.00 *statistical significance (P ≤ 0.05)
3.2. BASELINE SOIL DATA
Soil samples collected from October 2012 to February 2013 constitute the
baseline data, based on 10 irrigation pivots which currently operate (i.e., Pivots 1-8, 10
and 11). Table 3 summarises the overall mean and standard errors across the site, and
determines the statistical significance due to soil depth.
Baseline results showed 10 soil properties were significantly different with soil
depth. Electrical conductivity (EC) at 0-10 cm ranged from 0.05-0.15 dS/m with an
overall mean double that at 20-30 cm (P < 0.01). Soil pHCa (1:5 soil/0.01 M CaCl2 extract)
at 0-10 cm ranged from 4.6-5.1 with an overall mean pHCa of 4.9. Though statistically
significant between depths (P < 0.05), values at 20-30 cm were similar with an overall
mean pHCa of 5.0. Soil organic carbon (OC) content at 0-10 cm was significantly higher
than at 20-30 cm (P < 0.01), with an overall mean of 0.51%, while at 20-30 cm, the overall
mean was 0.30%. The mean carbon/nitrogen (C/N) ratio was significantly higher at 0-
10 cm (P < 0.01) than at 20-30 cm (10.5 versus 6.7).
Investigating the impacts of groundwater on soil properties and pasture
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Colwell P concentrations at 0-10 cm were more than double (P < 0.01) that at 20-
30 cm (5.5 versus 2.4 mg/kg). Phosphorus retention index (PRI) was 34% lower at 0-10
cm (P < 0.01) than at 20-30 cm.
Table 3. Overall mean baseline values and standard errors of soil properties in the 0-10 cm and
20-30 cm soil layers.
Parameter Units Soil depth
P* 0-10 cm 20-30 cm
Electrical conductivity, EC dS/m 0.08 (± 0.01) 0.04 (± 0.01) < 0.01 pHCa pH units 4.9 (± 0.1) 5.0 (± 0.0) < 0.05 CaCO3 equivalent, CCE % 0.25 (± 0.02) 0.26 (± 0.01) - Organic carbon, OC % 0.51 (± 0.03) 0.30 (± 0.01) < 0.01 NO3-N mg/kg 5.93 (± 0.9) 6.70 (± 1.1) - NH4-N mg/kg 2.53 (± 1.5) 1.20 (± 0.2) - Total N % 0.05 (± 0.00) 0.05 (± 0.00) - C/N ratio 10.5 (± 0.4) 6.7 (± 0.3) < 0.01 Colwell P mg/kg 5.5 (± 0.4) 2.4 (± 0.2) < 0.01 Total P mg/kg 161 (± 10) 136 (± 8) - Phosphorus retention index, PRI
39.8 (± 3.4) 60.4 (± 4.6) < 0.01
Colwell K mg/kg 294 (± 17) 257 (± 11) - Total K mg/kg 2138 (± 147) 2370 (± 154) - Ex. Ca cmol(+)/kg 2.95 (± 0.16) 3.03 (± 0.15) - Ex. Mg cmol(+)/kg 1.15 (± 0.09) 1.07 (± 0.08) - Ex. Na cmol(+)/kg 0.16 (± 0.02) 0.05 (± 0.01) < 0.01 Ex. K cmol(+)/kg 0.71 (± 0.04) 0.63 (± 0.02) - Ex. Al cmol(+)/kg 0.10 (± 0.01) 0.09 (± 0.01) - Effective cation exchange capacity, ECEC
cmol(+)/kg 5.06 (± 0.27) 4.87 (± 0.23) -
Ex. Ca percentage % 58.0 (± 1.3) 62.1 (± 0.9) < 0.05 Ex. Mg percentage % 22.6 (± 1.0) 22.0 (± 0.9) - Ex. Na percentage (ESP) % 3.2 (± 0.4) 1.0 (± 0.1) < 0.01 Ex. K percentage % 14.1 (± 0.4) 13.0 (± 0.4) - Ex. Al percentage % 2.1 (± 0.3) 2.0 (± 0.2) - As mg/kg 15.8 (± 0.5) 15.5 (± 0.5) - Cd ug/kg 63.7 (± 5.7) 52.8 (± 5.7) - Cr mg/kg 230 (± 26) 219 (± 23) - Pb mg/kg 19.1 (± 1.1) 19.6 (± 1.2) - Sand % 63.1 (± 1.0) 62.5 (± 1.2) - Silt % 10.5 (±0.4) 7.6 (± 0.3) < 0.01 Clay % 26.4 (± 1.2) 30.0 (± 1.4) - *statistical significance (2-tail) of differences due to depth based on t-Test assuming unequal variances.
The effective cation exchange capacity (ECEC) was not significantly different
between 0-10 cm and 20-30 cm, with an overall mean of about 5 cmol(+)/kg. The
exchangeable Mg, K, and Al percentages were not significantly different between soil
depths and ranged from 15.6-26.0 %, 11.2-15.9 %, and 1.0-4.1 %, respectively.
Exchangeable Ca concentrations were not significantly different between depths,
but exchangeable Ca percentage was significantly higher at 20-30 cm (P < 0.05), ranging
from 53.8-68.9 % at 0-10 cm, while values at 20-30 cm ranged from 58.9-68.5 %.
Exchangeable Na concentration (0.16 versus 0.05 cmol(+)/kg) and ESP (3.2 versus 1.0
%) were about three times higher at 0-10 cm than at 20-30 cm (P < 0.01).
Investigating the impacts of groundwater on soil properties and pasture
nutrition
20
Trace elements such as Cr, Pb, As, and Cd were not significantly different between
0-10 cm and 20-30 cm, ranging from 45-322 mg Cr/kg, 11.7-24.8 mg Pb/kg, 12.5-17.3
mg As/kg, and 13.3-89.3 ug Cd/kg, respectively. Note that Cr concentrations were
comparatively lower in Pivot 4 (see Figure 27).
Soil particle size ranged from 57.1-68.4 % sand, 6.5-13.2 % silt and 19.2-35.7 %
clay (Figure 6). The proportion of sand and clay did not differ between depths. However,
silt content was significantly higher at 0-10 cm (P < 0.01) than at 20-30 cm (10.5 versus
7.6 %). Further details on soil texture are provided in Table 28, Appendix F.
Figure 6. Mean (± SE) soil particle size distribution – sand (red), silt (green) and clay (blue)
content at 0-10 cm and 20-30 cm for samples collected in March 2014, based on Pivots 1-8,
10 and 11.
3.3. SIGNIFICANT CHANGES AND TRENDS
3.3.1. SOIL PROPERTIES
December 2013 results were benchmarked against baseline data to determine
the overall change in soil properties. This analysis was limited to irrigation pivots
currently in operation, viz Pivots 1-8, 10 and 11. Several soil properties did not
significantly change between the baseline and December 2013 (Table 4), including CCE,
NH4-N, Colwell K, total K, exchangeable Al, As, Cd and Pb concentrations. Figures 7-27
illustrate the mean of each pivot (± SE values of 3 monitoring spans) and the overall mean
of the site for key soil properties, across the time series examined (March, July,
September and December). Trends were based on only Span 3 data to reflect the normal
irrigation rate, representative of the larger HAP irrigation area.
0
10
20
30
40
50
60
70
80
1 2 3 4 5 6 7 8 9 10 11
Par
ticl
e s
ize
dis
trib
uti
on
(%
)
Irrigation pivot
0-10 cm
0
10
20
30
40
50
60
70
80
1 2 3 4 5 6 7 8 9 10 11
Par
ticl
e s
ize
dis
trib
uti
on
(%
)
Irrigation pivot
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
21
Table 4. Overall mean values and standard errors for soil properties at the 0-10 cm and 20-30
cm soil layer between baseline (October 2012 to February 2013) and December 2013.
Parameter Units Depth (cm) Baseline Dec-13 P*
Electrical conductivity, EC
dS/m 0-10 0.08 (± 0.01) 0.15 (± 0.02) < 0.01
20-30 0.04 (± 0.01) 0.18 (± 0.01) < 0.01 pHCa pH units 0-10 4.9 (± 0.1) 6.9 (± 0.1) < 0.01 20-30 5.0 (± 0.0) 5.5 (± 0.1) < 0.01 CaCO3 equivalent, CCE % 0-10 0.25 (± 0.02) 0.28 (± 0.02) - 20-30 0.26 (± 0.01) 0.26 (± 0.02) - Organic carbon, OC % 0-10 0.51 (± 0.03) 0.66 (± 0.04) < 0.01 20-30 0.30 (± 0.01) 0.34 (± 0.01) - NO3-N mg/kg 0-10 5.93 (± 0.90) 4.57 (± 0.81) - 20-30 6.70 (± 1.10) 0.60 (± 0.10) < 0.01 NH4-N mg/kg 0-10 2.53 (± 1.5) 1.50 (± 0.13) - 20-30 1.20 (± 0.2) 1.17 (± 0.07) - Total N % 0-10 0.05 (± 0.00) 0.07 (± 0.00) < 0.01 20-30 0.05 (± 0.00) 0.06 (± 0.00) < 0.01 C/N ratio 0-10 10.5 (± 0.5) 8.9 (± 0.4) < 0.05 20-30 6.7 (± 0.3) 5.8 (± 0.2) < 0.05 Colwell P mg/kg 0-10 5.5 (± 0.4) 5.8 (± 0.4) - 20-30 2.4 (± 0.2) 1.1 (± 0.1) < 0.01 Total P mg/kg 0-10 161 (± 10) 197 (± 8) < 0.05 20-30 136 (± 8) 172 (± 6) < 0.01 Phosphorus retention index, PRI
0-10 39.8 (± 3.4) 50.4 (± 3.2) < 0.05
20-30 60.4 (± 4.6) 87.8 (±5.8) < 0.01 Colwell K mg/kg 0-10 294 (± 17) 332 (± 14) - 20-30 257 (± 11) 267 (± 13) - Total K mg/kg 0-10 2138 (± 147) 1889 (± 66) - 20-30 2370 (± 154) 2044 (± 67) - Ex. Ca cmol(+)/kg 0-10 2.95 (± 0.16) 4.18 (± 0.24) < 0.01 20-30 3.03 (± 0.15) 3.56 (± 0.18) < 0.05 Ex. Mg cmol(+)/kg 0-10 1.15 (± 0.09) 3.19 (± 0.16) < 0.01 20-30 1.07 (± 0.08) 1.66 (± 0.07) < 0.01 Ex. Na cmol(+)/kg 0-10 0.16 (± 0.02) 0.46 (± 0.04) < 0.01 20-30 0.05 (± 0.01) 0.48 (± 0.03) < 0.01 Ex. K cmol(+)/kg 0-10 0.71 (± 0.04) 0.83 (± 0.04) < 0.05 20-30 0.63 (± 0.02) 0.64 (± 0.03) - Ex. Al cmol(+)/kg 0-10 0.10 (± 0.01) 0.08 (± 0.01) - 20-30 0.09 (± 0.01) 0.10 (± 0.01) - Effective cation exchange capacity, ECEC
cmol(+)/kg 0-10 5.06 (± 0.27) 8.73 (± 0.45) < 0.01
20-30 4.87 (± 0.23) 6.44 (± 0.28) < 0.01 Ex. Ca percentage % 0-10 58.0 (± 1.3) 47.6 (± 0.6) < 0.01 20-30 62.1 (± 0.9) 55.0 (± 0.7) < 0.01 Ex. Mg percentage % 0-10 22.6 (± 1.0) 36.6 (± 0.5) < 0.01 20-30 22.0 (± 0.9) 25.9 (± 0.5) < 0.01 Ex. Na percentage (ESP) % 0-10 3.2 (± 0.4) 5.2 (± 0.3) < 0.01 20-30 1.0 (± 0.1) 7.4 (± 0.2) < 0.01 Ex. K percentage % 0-10 14.1 (± 0.4) 9.6 (± 0.1) < 0.01 20-30 13.0 (± 0.4) 10.0 (± 0.2) < 0.01 Ex. Al percentage % 0-10 2.1 (± 0.3) 0.9 (± 0.2) < 0.01 20-30 2.0 (± 0.2) 1.7 (± 0.2) - As mg/kg 0-10 15.8 (± 0.5) 16.2 (± 0.5) - 20-30 15.5 (± 0.5) 15.3 (± 0.4) - Cd ug/kg 0-10 63.7 (± 5.7) 72.8 (± 2.2) - 20-30 52.8 (± 5.7) 58.7 (± 1.2) - Cr mg/kg 0-10 230 (± 26) 351 (± 22) < 0.01 20-30 219 (± 23) 305 (± 15) < 0.01 Pb mg/kg 0-10 19.1 (± 1.1) 20.2 (± 0.8) - 20-30 19.6 (± 1.2) 19.3 (± 0.5) - *statistical significance (1-tail) based on t-Test assuming unequal variances.
Soil EC significantly increased from 0.08 to 0.15 dS/m at 0-10 cm (P < 0.01) and
from 0.04 to 0.18 dS/m at 20-30 cm (P < 0.01; Figure 7). Relative to the baseline, there
Investigating the impacts of groundwater on soil properties and pasture
nutrition
22
was a consistent increase in the overall mean EC at both 0-10 cm and 20-30 cm, except
in July 2013 at 0-10 cm which appears to have significantly dropped back to baseline
values.
Figure 7. Changes (left) and trends (right) in electrical conductivity (EC, dS/m) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods.
Soil pHCa significantly increased by 2 pH units at 0-10 cm (P < 0.01), but only by
0.5 pH units at 20-30 cm (P < 0.01; Figure 8). Mean pHCa values in December were circum-
neutral in the 0-10 cm surface layer, while remaining slightly acidic in the subsoil. Trends
were consistent although increases in pHCa at 20-30 cm were only gradual. Nonetheless,
at 0-10 cm, the overall mean pHCa significantly increased within 4 months of irrigation
between baseline and March (P < 0.01).
Soil CCE did not significantly change between baseline and December (Figure 9).
However, time trends indicated CCE to have peaked in July at both depths (P < 0.01).
Soil OC significantly increased at 0-10 cm from 0.51 to 0.66 % (P < 0.051; Figure
10), but did not significantly change at 20-30 cm. However, trends at 20-30 cm showed
an increase in the overall mean between baseline and July, but then a subsequent decline.
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
1 2 3 4 5 6 7 8 9 10 11
EC (
dS/
m)
Irrigation pivot
0-10 cm
0.00
0.05
0.10
0.15
0.20
Baseline Mar Jul Sep Dec
EC (
dS/
m)
0-10 cm
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
1 2 3 4 5 6 7 8 9 10 11
EC (
dS/
m)
Irrigation pivot
20-30 cm
0.00
0.05
0.10
0.15
0.20
0.25
Baseline Mar Jul Sep Dec
EC (
dS/
m)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
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23
Figure 8. Changes (left) and trends (right) in pHCa at 0-10 cm and 20-30 cm between baseline
(blue) and December 2013 (red) periods.
Figure 9. Changes (left) and trends (right) in CaCO3 equivalent (CCE, %) at 0-10 cm and 20-30
cm between baseline (blue) and December 2013 (red) periods.
4
5
6
7
8
1 2 3 4 5 6 7 8 9 10 11
pH
Ca
Irrigation pivot
0-10 cm
4
5
6
7
8
Baseline Mar Jul Sep Dec
pH
Ca
0-10 cm
4.0
4.5
5.0
5.5
6.0
6.5
1 2 3 4 5 6 7 8 9 10 11
pH
Ca
Irrigation pivot
20-30 cm
4.4
4.6
4.8
5.0
5.2
5.4
5.6
Baseline Mar Jul Sep Dec
pH
Ca
20-30 cm
0.1
0.2
0.3
0.4
0.5
1 2 3 4 5 6 7 8 9 10 11
CC
E (%
)
Irrigation pivot
0-10 cm
0.0
0.1
0.2
0.3
0.4
Baseline Mar Jul Sep Dec
CC
E (%
)
0-10 cm
0.1
0.2
0.3
0.4
0.5
1 2 3 4 5 6 7 8 9 10 11
CC
E (%
)
Irrigation pivot
20-30 cm
0.0
0.1
0.2
0.3
0.4
Baseline Mar Jul Sep Dec
CC
E (%
)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
24
Figure 10. Changes (left) and trends (right) in soil organic carbon (OC, %) at 0-10 cm and 20-
30 cm between baseline (blue) and December 2013 (red) periods.
Figure 11. Changes (left) and trends (right) in nitrate-nitrogen (NO3-N, mg/kg) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods.
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11
OC
(%
)
Irrigation pivot
0-10 cm
0.0
0.2
0.4
0.6
0.8
1.0
Baseline Mar Jul Sep Dec
OC
(%
)
0-10 cm
0.15
0.20
0.25
0.30
0.35
0.40
0.45
1 2 3 4 5 6 7 8 9 10 11
OC
(%
)
Irrigation pivot
20-30 cm
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Baseline Mar Jul Sep Dec
OC
(%
)
20-30 cm
0
4
8
12
16
20
1 2 3 4 5 6 7 8 9 10 11
NO
3-N
(m
g/kg
)
Irrigation pivot
0-10 cm
0
2
4
6
8
10
Baseline Mar Jul Sep Dec
NO
3-N
(m
g/kg
)
0-10 cm
0
4
8
12
16
20
24
1 2 3 4 5 6 7 8 9 10 11
NO
3-N
(m
g/kg
)
Irrigation pivot
20-30 cm
0
1
2
3
4
5
Baseline Mar Jul Sep Dec
NO
3-N
(m
g/kg
)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
25
The overall mean NO3-N concentration significantly decreased from 6.70 to 0.60
mg/kg at 20-30cm (P < 0.01; Figure 11) between baseline and December, but was not
significantly different at 0-10 cm. Mean concentrations were variable at 0-10 cm, but had
decreased consistently at 20-30 cm.
Total N significantly increased from an overall mean of 0.05 to 0.07 % at 0-10 cm
(P < 0.01) and to 0.06% at 20-30 cm (P < 0.01; Figure 12). Trends showed little
consistency over time, but patterns were similar at depth – values significantly dropped
in July 2013 before increasing to December.
Figure 12. Changes (left) and trends (right) in total N content (%) at 0-10 cm and 20-30 cm
between baseline (blue) and December 2013 (red) periods.
Soil C/N ratio significantly decreased between baseline and December at both
depths (P < 0.05; Figure 13). However, trends show mean C/N ratios peaked in July
before decreasing to December.
The overall mean Colwell P concentration at 0-10 cm was not significantly
different between baseline and December 2013, but at 20-30 cm, it significantly
decreased by more than half the mean value (P < 0.01; Figure 14). Trends showed little
consistency, but the overall mean decreased between March and September.
0.00
0.02
0.04
0.06
0.08
0.10
1 2 3 4 5 6 7 8 9 10 11
Tota
l N (
%)
Irrigation pivot
0-10 cm
0.00
0.02
0.04
0.06
0.08
Baseline Mar Jul Sep Dec
Tota
l N (
%)
0-10 cm
0.00
0.02
0.04
0.06
0.08
0.10
1 2 3 4 5 6 7 8 9 10 11
Tota
l N (
%)
Irrigation pivot
20-30 cm
0.00
0.02
0.04
0.06
0.08
Baseline Mar Jul Sep Dec
Tota
l N (
%)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
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26
Figure 13. Changes (left) and trends (right) in carbon/nitrogen (C/N) ratio at 0-10 cm and 20-
30 cm between baseline (blue) and December 2013 (red) periods.
Figure 14. Changes (left) and trends (right) in Colwell P concentration (mg/kg) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods.
2
6
10
14
18
1 2 3 4 5 6 7 8 9 10 11
C/N
rat
io
Irrigation pivot
0-10 cm
0
5
10
15
20
Baseline Mar Jul Sep Dec
C/N
rat
io
0-10 cm
4
5
6
7
8
9
1 2 3 4 5 6 7 8 9 10 11
C/N
rat
io
Irrigation pivot
20-30 cm
0
5
10
15
20
Baseline Mar Jul Sep Dec
C/N
rat
io
20-30 cm
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10 11
Co
lwe
ll P
(m
g/kg
)
Irrigation pivot
0-10 cm
0
2
4
6
8
Baseline Mar Jul Sep Dec
Co
lwe
ll P
(m
g/kg
)
0-10 cm
0
1
2
3
4
1 2 3 4 5 6 7 8 9 10 11
Co
lwe
ll P
(m
g/kg
)
Irrigation pivot
20-30 cm
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Baseline Mar Jul Sep Dec
Co
lwe
ll P
(m
g/kg
)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
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27
Total P concentration significantly increased by 22% of the overall mean at 0-10
cm (P < 0.05) and by 26% at 20-30 cm (P < 0.01; Figure 15). These increases in total P
were consistent at both depths, except from September to December at 20-30 cm.
Figure 15. Changes (left) and trends (right) in total P concentration (mg/kg) at 0-10 cm and
20-30 cm between baseline (blue) and December 2013 (red) periods.
Soil PRI significantly increased by about 27% at 0-10 cm (P < 0.05) and 45% at
20-30 cm (P < 0.01; Figure 16) between baseline and December. Trends at 0-10 cm
showed the overall mean to increase between March and July before stabilising to
December; at 20-30 cm this was somewhat variable.
The overall mean ECEC significantly increased by about 73% at 0-10 cm (P <
0.01) and by 32% at 20-30 cm (P < 0.01; Figure 17), with relatively consistent increases
over time between baseline and December.
Exchangeable Ca concentrations significantly increased by about 42% at 0-10 cm
(P < 0.01) and 17% at 20-30 cm (P < 0.05; Figure 18). Trends were consistent at 0-10 cm,
but less noticeable at 20-30 cm.
50
100
150
200
250
300
1 2 3 4 5 6 7 8 9 10 11
Tota
l P (
mg/
kg)
Irrigation pivot
0-10 cm
100
140
180
220
Baseline Mar Jul Sep Dec
Tota
l P (
mg/
kg)
0-10 cm
50
100
150
200
250
1 2 3 4 5 6 7 8 9 10 11
Tota
l P (
mg/
kg)
Irrigation pivot
20-30 cm
100
120
140
160
180
200
Baseline Mar Jul Sep Dec
Tota
l P (
mg/
kg)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
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28
Figure 16. Changes (left) and trends (right) in phosphorus retention index (PRI) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods.
Figure 17. Changes (left) and trends (right) in the effective cation exchange capacity (ECEC,
cmol(+)/kg) at 0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red)
periods.
20
30
40
50
60
70
80
90
1 2 3 4 5 6 7 8 9 10 11
PR
I
Irrigation pivot
0-10 cm
0
10
20
30
40
50
60
70
Baseline Mar Jul Sep Dec
PR
I
0-10 cm
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10 11
PR
I
Irrigation pivot
20-30 cm
0
20
40
60
80
100
Baseline Mar Jul Sep Dec
PR
I
20-30 cm
0
2
4
6
8
10
12
1 2 3 4 5 6 7 8 9 10 11
ECEC
(cm
ol(
+)/k
g)
Irrigation pivot
0-10 cm
0
2
4
6
8
10
Baseline Mar Jul Sep Dec
ECEC
(cm
ol(
+)/k
g)
0-10 cm
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10 11
ECEC
(cm
ol(
+)/k
g)
Irrigation pivot
20-30 cm
0
2
4
6
8
Baseline Mar Jul Sep Dec
ECEC
(cm
ol(
+)/k
g)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
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29
Figure 18. Changes (left) and trends (right) in exchangeable Ca concentration (cmol(+)/kg) at
0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.
Figure 19. Changes (left) and trends (right) in exchangeable Ca percentage (%) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods.
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10 11
Ex. C
a (c
mo
l(+)
/kg)
Irrigation pivot
0-10 cm
2.0
2.5
3.0
3.5
4.0
4.5
Baseline Mar Jul Sep Dec
Ex. C
a (c
mo
l(+)
/kg)
0-10 cm
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10 11
Ex. C
a (c
mo
l(+)
/kg)
Irrigation pivot
20-30 cm
2.0
2.5
3.0
3.5
4.0
Baseline Mar Jul Sep DecEx
. Ca
(cm
ol(
+)/k
g)
20-30 cm
30
40
50
60
70
80
1 2 3 4 5 6 7 8 9 10 11
Ex. C
a (%
)
Irrigation pivot
0-10 cm
30
35
40
45
50
55
60
65
Baseline Mar Jul Sep Dec
Ex. C
a (%
)
0-10 cm
45
50
55
60
65
70
75
1 2 3 4 5 6 7 8 9 10 11
Ex. C
a (%
)
Irrigation pivot
20-30 cm
50
52
54
56
58
60
62
64
Baseline Mar Jul Sep Dec
Ex. C
a (%
)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
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30
However, exchangeable Ca percentage significantly decreased from 58.0 to 47.6
% at 0-10 cm (P < 0.01) and from 62.1 to 55.0 % at 20-30 cm (P < 0.01; Figure 19). At 20-
30 cm, the decrease from baseline to March was most pronounced (P < 0.01) –
subsequent decreases were then gradual.
Exchangeable Mg concentration significantly increased by nearly 3 times the
overall mean at 0-10 cm (P < 0.01), while increasing by 55% at 20-30 cm (P < 0.01; Figure
20). Trends showed a strong consistent increase in concentrations at both depths.
Figure 20. Changes (left) and trends (right) in exchangeable Mg concentration (cmol(+)/kg)
at 0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.
Exchangeable Mg percentage also significantly increased from an overall mean
of 22.6 to 36.6 % at 0-10 cm (P < 0.01) and from 22.0 to 25.9 % at 20-30 cm (P < 0.01;
Figure 21). Trends were consistent, but there was greater variability among Pivots for
the 20-30 cm depth.
0
1
2
3
4
5
1 2 3 4 5 6 7 8 9 10 11
Ex. M
g (c
mo
l(+)
/kg)
Irrigation pivot
0-10 cm
0
1
2
3
4
Baseline Mar Jul Sep Dec
Ex. M
g (c
mo
l(+)
/kg)
0-10 cm
0.0
0.5
1.0
1.5
2.0
2.5
1 2 3 4 5 6 7 8 9 10 11
Ex. M
g (c
mo
l(+)
/kg)
Irrigation pivot
20-30 cm
0.0
0.5
1.0
1.5
2.0
Baseline Mar Jul Sep Dec
Ex. M
g (c
mo
l(+)
/kg)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
31
Figure 21. Changes (left) and trends (right) in exchangeable Mg percentage (%) at 0-10 cm
and 20-30 cm between baseline (blue) and December 2013 (red) periods.
Figure 22. Changes (left) and trends (right) in exchangeable Na concentration (cmol(+)/kg) at
0-10 cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.
10
20
30
40
50
1 2 3 4 5 6 7 8 9 10 11
Ex. M
g (%
)
Irrigation pivot
0-10 cm
20
25
30
35
40
Baseline Mar Jul Sep Dec
Ex. M
g (%
)
0-10 cm
14
18
22
26
30
1 2 3 4 5 6 7 8 9 10 11
Ex. M
g (%
)
Irrigation pivot
20-30 cm
20
22
24
26
28
30
Baseline Mar Jul Sep Dec
Ex. M
g (%
)
20-30 cm
0.0
0.2
0.4
0.6
0.8
1.0
1 2 3 4 5 6 7 8 9 10 11
Ex. N
a (c
mo
l(+)
/kg)
Irrigation pivot
0-10 cm
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Baseline Mar Jul Sep Dec
Ex. N
a (c
mo
l(+)
/kg)
0-10 cm
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
1 2 3 4 5 6 7 8 9 10 11
Ex. N
a (c
mo
l(+)
/kg)
Irrigation pivot
20-30 cm
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Baseline Mar Jul Sep Dec
Ex. N
a (c
mo
l(+)
/kg)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
32
Overall mean exchangeable Na concentrations (determined without pre-washing
of samples) significantly increased nearly 3 times at 0-10 cm (P < 0.01) and over 9 times
at 20-30 cm (P < 0.01; Figure 22). Trends at 0-10 cm were somewhat variable, but
relatively consistent at 20-30 cm. Like many other parameters, significant increases at
both depths were already observable within 4 months of irrigation (P < 0.01) from
baseline to March. By contrast, at 20-30 cm, subsequent increases were gradual before
significantly increasing to December (P < 0.01).
Overall mean ESP levels, based on samples without pre-washing for soluble salts,
significantly increased from 3.2 to 5.2 % at 0-10 cm (P < 0.01) and 1.0 to 7.4 % at 20-30
cm (P < 0.01; Figure 23). Trends were similar to that of exchangeable Na concentration.
Figure 23. Changes (left) and trends (right) in exchangeable Na percentage (ESP, %) at 0-10
cm and 20-30 cm between baseline (blue) and December 2013 (red) periods.
Exchangeable K concentration significantly increased at only 0-10 cm from an
overall mean of 0.71 to 0.83 cmol(+)/kg (P < 0.05; Figure 24), but no distinct trend was
apparent between baseline and December.
0
2
4
6
8
1 2 3 4 5 6 7 8 9 10 11
ESP
(%
)
0-10 cm
0
2
4
6
8
Baseline Mar Jul Sep Dec
ESP
(%
)
0-10 cm
0
2
4
6
8
10
1 2 3 4 5 6 7 8 9 10 11
ESP
(%
)
20-30 cm
0
2
4
6
8
10
Baseline Mar Jul Sep Dec
ESP
(%
)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
33
Figure 24. Changes (left) and trends (right) in exchangeable K concentration (cmol(+)/kg) at
0-10 cm between baseline (blue) and December 2013 (red) periods.
By contrast, the overall mean exchangeable K percentage significantly decreased
from 14.1 to 9.6 % at 0-10 cm (P < 0.01) and from 13.0 to 10.0 % at 20-30 cm (P < 0.01;
Figure 25). A consistent decrease in the mean was observed at both depths.
Figure 25. Changes (left) and trends (right) in exchangeable K percentage (%) at 0-10 cm and
20-30 cm between baseline (blue) and December 2013 (red) periods.
Exchangeable Al percentage significantly decreased at 0-10 cm (Figure 26).
Trends show mean percentages at 0-10 cm were consistently below the baseline, with
exception to values in September.
0.4
0.6
0.8
1.0
1.2
1 2 3 4 5 6 7 8 9 10 11
Ex. K
(cm
ol(
+)/k
g)
Irrigation pivot
0-10 cm
0.0
0.2
0.4
0.6
0.8
1.0
Baseline Mar Jul Sep Dec
Ex. K
(cm
ol(
+)/k
g)
0-10 cm
6
8
10
12
14
16
18
1 2 3 4 5 6 7 8 9 10 11
Ex. K
(%
)
Irrigation pivot
0-10 cm
6
8
10
12
14
16
Baseline Mar Jul Sep Dec
Ex. K
(%
)
0-10 cm
6
8
10
12
14
16
18
1 2 3 4 5 6 7 8 9 10 11
Ex. K
(%
)
Irrigation pivot
20-30 cm
6
8
10
12
14
Baseline Mar Jul Sep Dec
Ex. K
(%
)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
34
Figure 26. Changes (left) and trends (right) in exchangeable Al percentage (%) at 0-10 cm
between baseline (blue) and December 2013 (red) periods.
Chromium levels in the soil significantly increased by 53% at 0-10 cm (P < 0.01)
and by 39% at 20-30 cm (P < 0.01; Figure 27). However, trends showed no consistency
in these increases until an abrupt increase in the mean by 70% between September and
December at both depths (P < 0.01).
Figure 27. Changes (left) and trends (right) in chromium levels (mg/kg) at 0-10 cm and 20-30
cm between baseline (blue) and December 2013 (red) periods.
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10 11
Ex. A
l (%
)
Irrigation pivot
0-10 cm
0.0
0.5
1.0
1.5
2.0
2.5
3.0
3.5
Baseline Mar Jul Sep Dec
Ex. A
l (%
)
0-10 cm
0
100
200
300
400
500
600
1 2 3 4 5 6 7 8 9 10 11
Cr
(mg/
kg)
Irrigation pivot
0-10 cm
0
50
100
150
200
250
300
350
400
Baseline Mar Jul Sep Dec
Cr
(mg/
kg)
0-10 cm
0
100
200
300
400
500
1 2 3 4 5 6 7 8 9 10 11
Cr
(mg/
kg)
Irrigation pivot
20-30 cm
0
50
100
150
200
250
300
350
Baseline Mar Jul Sep Dec
Cr
(mg/
kg)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
35
3.3.2. LEAF NUTRIENT COMPOSITION
Leaf nutrient composition in December 2013 was benchmarked against those in
March, based on Pivots 1-8, 10 and 11. Statistical analyses using t-Tests show that leaf N,
K, Na, Cl, Cu, Fe, Mn, and As concentrations were not significantly different. Table 5
summarises the mean values and standard errors for leaf nutrients in March and
December 2013, with significant changes and trends illustrated in Figures 28-38.
The overall mean leaf P concentration significantly increased from 0.14 to 0.19
% (P < 0.01) between March and December (Figure 28). However, time series analysis
showed the mean P concentration failed to increase in October sampling relative to that
in July and December.
Table 5. Mean values and standard errors of 20 leaf nutrient concentrations between March and
December 2013, based on 10 irrigation pivots and 3 monitoring spans per pivot.
Parameter Units Mar-13 Dec-13 P*
Total N % 2.0 (± 0.1) 2.1 (± 0.1) -
P % 0.14 (± 0.01) 0.19 (± 0.01) < 0.01
K % 1.8 (± 0.1) 1.9 (± 0.1) -
Ca % 0.42 (± 0.02) 0.56 (± 0.01) < 0.01
Mg % 0.17 (± 0.01) 0.22 (± 0.01) < 0.01
Na % 0.38 (± 0.03) 0.47 (± 0.04) -
Cl % 1.5 (± 0.1) 1.6 (± 0.1) -
S % 0.21 (± 0.01) 0.31 (± 0.01) < 0.01
Cu mg/kg 7.0 (± 0.4) 7.3 (± 0.3) -
Fe mg/kg 100 (± 3) 113 (± 6) -
Mn mg/kg 166 (± 18) 208 (± 16) -
Zn mg/kg 22.9 (± 1.6) 32.4 (± 1.7) < 0.01
B mg/kg 4.9 (± 0.3) 8.1 (± 0.6) < 0.01 NO3-N mg/kg 137 (± 32) 47 (± 15) < 0.05 Al mg/kg 38.0 (± 2.1) 31.5 (± 2.1) < 0.05 As ug/kg 74.7 (± 5.5) 74.6 (± 5.9) - Cd ug/kg 15.6 (± 1.6) 26.4 (± 2.9) < 0.01 Cr mg/kg 0.64 (± 0.03) 4.6 (± 0.4) < 0.01 Pb ug/kg 22.6 (± 1.6) 84.0 (± 4.0) < 0.01 Ni mg/kg 4.0 (± 0.2) 2.0 (± 0.2) < 0.01 *statistical significance (2-tail) based on t-Test assuming unequal variances.
Investigating the impacts of groundwater on soil properties and pasture
nutrition
36
Figure 28. Significant changes (left) and trends (right) in the overall mean phosphorus
concentration (P, %) in leaf tissue between March (blue) and December 2013 (red).
Leaf Ca concentration significantly increased from an overall mean of 0.42 to 0.56
% (P < 0.01) between March and December (Figure 29). Mean concentrations were
consistently higher in months following March (P < 0.01).
Leaf Mg concentration significantly increased from an overall mean of 0.17 to
0.22 % (P < 0.01) between March and December (Figure 30). Trends showed Mg
concentrations in July, October and December were consistently higher than in March (P
< 0.01).
Figure 29. Significant changes (left) and trends (right) in the overall mean calcium
concentration (Ca, %) in leaf tissue between March (blue) and December 2013 (red).
0.10
0.15
0.20
0.25
0.30
1 2 3 4 5 6 7 8 9 10 11
P (
%)
Irrigation pivot0.00
0.05
0.10
0.15
0.20
0.25
Mar Jul Oct Dec
P (
%)
0.2
0.3
0.4
0.5
0.6
0.7
1 2 3 4 5 6 7 8 9 10 11
Ca
(%)
Irrigation pivot0.0
0.2
0.4
0.6
0.8
Mar Jul Oct Dec
Ca
(%)
Investigating the impacts of groundwater on soil properties and pasture
nutrition
37
Figure 30. Significant changes (left) and trends (right) in the overall mean magnesium
concentration (Mg, %) in leaf tissue between March (blue) and December 2013 (red).
Leaf S significantly increased from an overall mean of 0.21 to 0.31 % (P < 0.01)
between March and December (Figure 31). Trends were also consistent with those of
leaf Mg.
Figure 31. Significant changes (left) and trends (right) in the overall mean sulphur
concentration (S, %) in leaf tissue between March (blue) and December 2013 (red).
Zinc concentrations significantly increased by 41% (P < 0.01) between March
and December (Figure 32). However, mean concentrations were not different in July, but
were significantly higher in October and December (P < 0.01).
0.10
0.15
0.20
0.25
0.30
1 2 3 4 5 6 7 8 9 10 11
Mg
(%)
Irrigation pivot0.00
0.05
0.10
0.15
0.20
0.25
Mar Jul Oct Dec
Mg
(%)
0.10
0.15
0.20
0.25
0.30
0.35
0.40
1 2 3 4 5 6 7 8 9 10 11
S (%
)
Irrigation pivot0.00
0.05
0.10
0.15
0.20
0.25
0.30
0.35
Mar Jul Oct Dec
S (%
)
Investigating the impacts of groundwater on soil properties and pasture
nutrition
38
Figure 32. Significant changes (left) and trends (right) in the overall mean zinc concentration
(Zn, mg/kg) in leaf tissue between March (blue) and December 2013 (red).
Overall mean leaf B concentrations increased significantly by 65% (P < 0.01)
between March and December (Figure 33). Trends showed a consistent increase
although concentrations in October were significantly lower than those in July and
December (P < 0.05).
Figure 33. Significant changes (left) and trends (right) in the overall mean boron
concentration (B, mg/kg) in leaf tissue between March (blue) and December 2013 (red).
Leaf NO3-N concentrations significantly decreased by about 66% (P < 0.05)
between March and December (Figure 34). Trends showed mean concentrations in
October were significantly lower than that in March (P < 0.05), but not with July and
December – March, July and December concentrations were not significantly different.
10
15
20
25
30
35
40
45
50
1 2 3 4 5 6 7 8 9 10 11
Zn (
mg/
kg)
Irrigation pivot0
10
20
30
40
50
Mar Jul Oct Dec
Zn (
mg/
kg)
0
2
4
6
8
10
12
14
1 2 3 4 5 6 7 8 9 10 11
B (
mg/
kg)
Irrigation pivot0
2
4
6
8
10
Mar Jul Oct Dec
B (
mg/
kg)
Investigating the impacts of groundwater on soil properties and pasture
nutrition
39
Figure 34. Significant changes (left) and trends (right) in the overall mean nitrate-nitrogen
concentration (NO3-N, mg/kg) in leaf tissue between March (blue) and December 2013 (red).
Overall mean Cd concentrations in leaf tissue significantly increased by about
70% (P < 0.01) between March and December (Figure 35). However, this was not
consistent as mean concentrations in October were similar to those in March and
significantly lower relative to July and December (P < 0.05).
Figure 35. Significant changes (left) and trends (right) in the overall mean cadmium
concentration (Cd, ug/kg) in leaf tissue between March (blue) and December 2013 (red).
Leaf Cr concentrations significantly increased by over 7 times the overall mean
(P < 0.01) between March and December (Figure 36). Concentrations in March and July
were relatively similar, but significantly lower in October (P < 0.01). However, in
December, mean concentrations considerably increased (P < 0.01) by about 15 times
that in October.
0
50
100
150
200
250
300
350
400
1 2 3 4 5 6 7 8 9 10 11
NO
3-N
(m
g/kg
)
Irrigation pivot0
50
100
150
200
250
Mar Jul Oct Dec
NO
3-N
(m
g/kg
)
0
10
20
30
40
50
1 2 3 4 5 6 7 8 9 10 11
Cd
(u
g/kg
)
Irrigation pivot0
5
10
15
20
25
30
Mar Jul Oct Dec
Cd
(u
g/kg
)
Investigating the impacts of groundwater on soil properties and pasture
nutrition
40
Figure 36. Significant changes (left) and trends (right) in the overall mean chromium
concentration (Cr, mg/kg) in leaf tissue between March (blue) and December 2013 (red).
Leaf Pb concentrations significantly increased nearly 4 times the overall mean (P
< 0.01) between March and December (Figure 37). Trends showed a significant increase
in the mean from March to July (P < 0.01), but concentrations in October and December
were not significantly different.
Figure 37. Significant changes (left) and trends (right) in the overall mean lead concentration
(Pb, ug/kg) in leaf tissue between March (blue) and December 2013 (red).
Leaf Ni concentration significantly decreased by half the overall mean (P < 0.01)
between March and December (Figure 38). Mean concentrations were consistently
lower in July, October and December (P < 0.01) but were not significantly different to one
another.
0
1
2
3
4
5
6
7
1 2 3 4 5 6 7 8 9 10 11
Cr
(mg/
kg)
Irrigation pivot0
1
2
3
4
5
6
Mar Jul Oct Dec
Cr
(mg/
kg)
0
20
40
60
80
100
120
140
1 2 3 4 5 6 7 8 9 10 11
Pb
(u
g/kg
)
Irrigation pivot0
20
40
60
80
100
120
Mar Jul Oct Dec
Pb
(u
g/kg
)
Investigating the impacts of groundwater on soil properties and pasture
nutrition
41
Figure 38. Significant changes (left) and trends (right) in the overall mean nickel
concentration (Ni, mg/kg) in leaf tissue between March (blue) and December 2013 (red).
3.4. CORRELATION AND LINEAR REGRESSION ANALYSIS
Bivariate correlation and linear regression analyses were conducted using
results from baseline to December 2013 to determine possible cause-and-effect
relationships amongst: (1) soil chemical properties (Tables 6 and 7), (2) soil particle size
and soil chemical properties (Table 8), (3) soil chemical properties and leaf nutrient
concentrations (Table 17 and 18), and (4) leaf nutrient concentrations (Table 19, see
Appendix A). Only Span 3 data from Pivots 1-8, 10 and 11 were used. All moderate to
very strong correlations were significant at P < 0.01 level (2-tailed).
3.4.1. SOIL PROPERTIES
The soil pHCa at 0-10 cm was strongly-positively correlated with exchangeable
Mg concentration (R2 = 0.75; Figure 39) and Mg percentage (R2 = 0.70; Figure 40). There
was no correlation at 20-30 cm. Exchangeable Ca and Na had weak to no correlation with
pHCa.
Exchangeable Ca percentage was very strongly-negatively correlated with
exchangeable Mg percentage at both depths (R2 = 0.81 at 0-10 cm, R2 = 0.74 at 20-30 cm,
Figure 41). At 0-10 cm, exchangeable K percentage was moderately-negatively
correlated with soil pHCa (R2 = 0.45; Figure 42), but weakly-negatively correlated with
exchangeable Mg percentage (R2 = 0.37; Figure 43). Exchangeable K percentage was not
correlated with ESP.
0
1
2
3
4
5
6
1 2 3 4 5 6 7 8 9 10 11
Ni (
mg/
kg)
Irrigation pivot0
1
2
3
4
5
Mar Jul Oct Dec
Ni (
mg/
kg)
Investigating the impacts of groundwater on soil properties and pasture
nutrition
42
Figure 39. Linear relationship between pHCa
and exchangeable Mg concentration
(cmol(+)/kg) at 0-10 cm.
Figure 40. Linear relationship between pHCa
and exchangeable Mg percentage (%)at 0-10
cm.
Figure 41. Linear relationship between exchangeable Mg percentage (%) and Ca percentage
(%) at 0-10 cm (left) and 20-30 cm (right).
Figure 42. Linear relationship between pH
(CaCl2) and exchangeable K percentage (%)
at 0-10 cm.
Figure 43. Linear relationship between
exchangeable Mg percentage (%) and K
percentage (%) at 0-10 cm.
Soil ESP was moderately-negatively correlated with exchangeable Ca percentage
at both depths (R2 = 0.44 at 0-10 cm, R2 = 0.47 at 20-30 cm; Figure 44), but was not
correlated with exchangeable Mg percentage (data not shown).
R² = 0.7490
1
2
3
4
5
4 5 6 7 8
Ex. M
g (c
mo
l(+)
/kg)
pHCa
0-10 cm
R² = 0.695910
20
30
40
50
4 5 6 7 8
Ex. M
g (%
)
pHCa
0-10 cm
R² = 0.8057
30
40
50
60
70
80
10 20 30 40 50
Ex. C
a (%
)
Ex. Mg (%)
0-10 cm
R² = 0.7401
40
50
60
70
80
10 15 20 25 30 35
Ex. C
a (%
)
Ex. Mg (%)
20-30 cm
R² = 0.4537
5
8
11
14
17
20
4 5 6 7 8
Ex. K
(%
)
pHCa
0-10 cm
R² = 0.372
5
8
11
14
17
20
10 20 30 40 50
Ex. K
(%
)
Ex. Mg (%)
0-10 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
43
Figure 44. Linear relationship between exchangeable Na percentage (ESP, %) and Ca
percentage (%) at 0-10 cm (left) and 20-30 cm (right).
A decrease in exchangeable Ca may be associated with CaCO3 precipitation, but
analysis indicated no correlation between soil CCE and exchangeable Ca percentage (R2
= 0.08 at 0-10 cm, R2 = 0.02 at 20-30 cm) or ESP (R2 = 0.00 at 0-10 cm and 20-30 cm).
Soil pHCa was also not correlated with CCE (R2 = 0.06 at 0-10 cm, R2 = 0.01 at 20-30 cm).
Strong to very strong correlations were also found between exchangeable Na
concentration and soil EC (R2 = 0.76 at 0-10 cm, R2 = 0.87 at 20-30 cm; Figure 45) as well
as with ESP (R2 = 0.69 at 0-10 cm, R2 = 0.89 at 20-30 cm; Figure 46).
Figure 45. Linear relationship between electrical conductivity (EC, dS/m) and exchangeable
Na concentration (cmol(+)/kg) at 0-10 cm (left) and 20-30 cm (right).
Exchangeable Al concentrations and percentage were strongly-positively
correlated (R2 = 0.71 at 0-10 cm, R2 = 0.78 at 20-30 cm; Figure 47). However, there was
very weak to no correlation between pHCa and exchangeable Al percentage (R2 = 0.28 at
0-10 cm, R2 = 0.04 at 20-30 cm).
R² = 0.4416
30
40
50
60
70
80
0 2 4 6 8 10
Ex. C
a (%
)
ESP (%)
0-10 cm
R² = 0.4655
40
50
60
70
80
0 2 4 6 8 10
Ex. C
a (%
)
ESP (%)
20-30 cm
R² = 0.75570.00
0.10
0.20
0.30
0.40
0.0 0.2 0.4 0.6 0.8 1.0
EC (
dS/
m)
Ex. Na (cmol(+)/kg)
0-10 cm
R² = 0.86770.00
0.08
0.16
0.24
0.32
0.0 0.2 0.4 0.6 0.8
EC (
dS/
m)
Ex. Na (cmol(+)/kg)
20-30 cm
Investigating the impacts of groundwater on soil properties and pasture
nutrition
44
Figure 46. Linear relationship between exchangeable Na concentration (cmol(+)/kg) and Na
percentage (ESP, %) at 0-10 cm (left) and 20-30 cm (right).
Figure 47. Linear relationship between exchangeable Al concentration (cmol(+)/kg) and Al
percentage (%) at 0-10 cm (left) and 20-30 cm (right).
R² = 0.69130
2
4
6
8
10
0.0 0.2 0.4 0.6 0.8 1.0
ESP
(%
)
Ex. Na (cmol(+)/kg)
0-10 cm
R² = 0.88850
2
4
6
8
10
0.0 0.2 0.4 0.6 0.8
ESP
(%
)
Ex. Na (cmol(+)/kg)
20-30 cm
R² = 0.70680
2
4
6
8
0.00 0.05 0.10 0.15 0.20 0.25
Ex. A
l (%
)
Ex. Al (cmol(+)/kg)
0-10 cm
R² = 0.77920
1
2
3
4
5
6
0.0 0.1 0.2 0.3
Ex. A
l (%
)
Ex. Al (cmol(+)/kg)
20-30 cm
Table 6. Correlation (R2) between soil properties at 0-10 cm, using only Span 3 data from baseline to December 2013 based on Pivots 1-8, 10 and 11.
EC pHCa CCE OC NO3-N NH4-N Total N C/N Colwell P Total P PRI Colwell K Total K Ex. Ca Ex. Mg Ex. Na Ex. K Ex. Al ECEC Ca% Mg% ESP K% Al% As Cd Cr Pb
EC 1.00 0.06 0.00 0.18 0.04 0.05 0.12 0.01 0.00 0.35 0.23 0.06 0.12 0.13 0.28 0.76 0.12 0.03 0.27 0.23 0.17 0.68 0.09 0.11 0.10 0.02 0.00 0.03 pHCa 0.06 1.00 0.07 0.05 0.11 0.03 0.16 0.00 0.00 0.15 0.01 0.08 0.02 0.38 0.75 0.28 0.16 0.04 0.60 0.32 0.70 0.06 0.45 0.28 0.06 0.05 0.11 0.07 CCE 0.00 0.07 1.00 0.00 0.01 0.02 0.06 0.06 0.01 0.01 0.04 0.09 0.00 0.01 0.05 0.00 0.06 0.08 0.03 0.08 0.09 0.00 0.00 0.08 0.01 0.01 0.00 0.00 OC 0.18 0.05 0.00 1.00 0.05 0.04 0.11 0.33 0.00 0.22 0.03 0.15 0.16 0.28 0.12 0.14 0.23 0.04 0.23 0.00 0.01 0.02 0.04 0.19 0.00 0.01 0.00 0.01 NO3-N 0.04 0.11 0.01 0.05 1.00 0.02 0.00 0.06 0.06 0.01 0.08 0.01 0.04 0.03 0.07 0.02 0.01 0.00 0.04 0.02 0.09 0.00 0.15 0.01 0.01 0.00 0.02 0.03 NH4-N 0.05 0.03 0.02 0.04 0.02 1.00 0.05 0.19 0.08 0.03 0.00 0.06 0.02 0.00 0.02 0.02 0.08 0.00 0.01 0.07 0.04 0.01 0.01 0.02 0.00 0.01 0.02 0.00 Total N 0.12 0.16 0.06 0.11 0.00 0.05 1.00 0.29 0.01 0.19 0.02 0.11 0.08 0.45 0.30 0.21 0.19 0.09 0.41 0.00 0.04 0.01 0.13 0.21 0.01 0.07 0.19 0.00 C/N 0.01 0.00 0.06 0.33 0.06 0.19 0.29 1.00 0.01 0.00 0.00 0.01 0.01 0.00 0.01 0.00 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.01 0.01 0.01 0.10 0.01 Colwell P 0.00 0.00 0.01 0.00 0.06 0.08 0.01 0.01 1.00 0.00 0.02 0.12 0.05 0.00 0.00 0.01 0.13 0.09 0.00 0.01 0.00 0.03 0.14 0.03 0.07 0.00 0.00 0.06 Total P 0.35 0.15 0.01 0.22 0.01 0.03 0.19 0.00 0.00 1.00 0.33 0.21 0.28 0.26 0.37 0.43 0.31 0.00 0.39 0.16 0.17 0.17 0.06 0.10 0.03 0.00 0.00 0.03 PRI 0.23 0.01 0.04 0.03 0.08 0.00 0.02 0.00 0.02 0.33 1.00 0.08 0.20 0.05 0.16 0.27 0.10 0.01 0.13 0.14 0.12 0.19 0.02 0.06 0.03 0.01 0.00 0.02 Colwell K 0.06 0.08 0.09 0.15 0.01 0.06 0.11 0.01 0.12 0.21 0.08 1.00 0.36 0.34 0.19 0.06 0.94 0.21 0.33 0.01 0.02 0.01 0.07 0.35 0.03 0.00 0.01 0.04 Total K 0.12 0.02 0.00 0.16 0.04 0.02 0.08 0.01 0.05 0.28 0.20 0.36 1.00 0.09 0.03 0.07 0.40 0.04 0.09 0.00 0.00 0.01 0.09 0.07 0.17 0.05 0.00 0.00 Ex. Ca 0.13 0.38 0.01 0.28 0.03 0.00 0.45 0.00 0.00 0.26 0.05 0.34 0.09 1.00 0.61 0.32 0.46 0.17 0.87 0.00 0.10 0.00 0.28 0.49 0.02 0.03 0.06 0.03 Ex. Mg 0.28 0.75 0.05 0.12 0.07 0.02 0.30 0.01 0.00 0.37 0.16 0.19 0.03 0.61 1.00 0.63 0.32 0.08 0.90 0.35 0.67 0.19 0.44 0.36 0.00 0.01 0.10 0.03 Ex. Na 0.76 0.28 0.00 0.14 0.02 0.02 0.21 0.00 0.01 0.43 0.27 0.06 0.07 0.32 0.63 1.00 0.14 0.03 0.56 0.35 0.43 0.69 0.35 0.20 0.04 0.00 0.02 0.00 Ex. K 0.12 0.16 0.06 0.23 0.01 0.08 0.19 0.01 0.13 0.31 0.10 0.94 0.40 0.46 0.32 0.14 1.00 0.22 0.48 0.03 0.05 0.00 0.02 0.42 0.04 0.00 0.02 0.04 Ex. Al 0.03 0.04 0.08 0.04 0.00 0.00 0.09 0.00 0.09 0.00 0.01 0.21 0.04 0.17 0.08 0.03 0.22 1.00 0.13 0.01 0.00 0.00 0.00 0.71 0.02 0.01 0.06 0.01 ECEC 0.27 0.60 0.03 0.23 0.04 0.01 0.41 0.00 0.00 0.39 0.13 0.33 0.09 0.87 0.90 0.56 0.48 0.13 1.00 0.12 0.37 0.09 0.36 0.47 0.01 0.02 0.08 0.03 Ca% 0.23 0.32 0.08 0.00 0.02 0.07 0.00 0.00 0.01 0.16 0.14 0.01 0.00 0.00 0.35 0.35 0.03 0.01 0.12 1.00 0.81 0.44 0.08 0.01 0.01 0.01 0.02 0.01 Mg% 0.17 0.70 0.09 0.01 0.09 0.04 0.04 0.00 0.00 0.17 0.12 0.02 0.00 0.10 0.67 0.43 0.05 0.00 0.37 0.81 1.00 0.31 0.37 0.11 0.02 0.00 0.06 0.02 ESP 0.68 0.06 0.00 0.02 0.00 0.01 0.01 0.00 0.03 0.17 0.19 0.01 0.01 0.00 0.19 0.69 0.00 0.00 0.09 0.44 0.31 1.00 0.17 0.03 0.03 0.03 0.00 0.03 K% 0.09 0.45 0.00 0.04 0.15 0.01 0.13 0.01 0.14 0.06 0.02 0.07 0.09 0.28 0.44 0.35 0.02 0.00 0.36 0.08 0.37 0.17 1.00 0.07 0.02 0.05 0.04 0.01 Al% 0.11 0.28 0.08 0.19 0.01 0.02 0.21 0.01 0.03 0.10 0.06 0.35 0.07 0.49 0.36 0.20 0.42 0.71 0.47 0.01 0.11 0.03 0.07 1.00 0.01 0.01 0.08 0.00 As 0.10 0.06 0.01 0.00 0.01 0.00 0.01 0.01 0.07 0.03 0.03 0.03 0.17 0.02 0.00 0.04 0.04 0.02 0.01 0.01 0.02 0.03 0.02 0.01 1.00 0.59 0.19 0.41 Cd 0.02 0.05 0.01 0.01 0.00 0.01 0.07 0.01 0.00 0.00 0.01 0.00 0.05 0.03 0.01 0.00 0.00 0.01 0.02 0.01 0.00 0.03 0.05 0.01 0.59 1.00 0.43 0.27 Cr 0.00 0.11 0.00 0.00 0.02 0.02 0.19 0.10 0.00 0.00 0.00 0.01 0.00 0.06 0.10 0.02 0.02 0.06 0.08 0.02 0.06 0.00 0.04 0.08 0.19 0.43 1.00 0.04 Pb 0.03 0.07 0.00 0.01 0.03 0.00 0.00 0.01 0.06 0.03 0.02 0.04 0.00 0.03 0.03 0.00 0.04 0.01 0.03 0.01 0.02 0.03 0.01 0.00 0.41 0.27 0.04 1.00
Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).
Table 7. Correlation (R2) between soil properties at 20-30 cm, using only Span 3 data from baseline to December 2013 based on Pivots 1-8, 10 and 11.
EC pHCa CCE OC NO3-N NH4-N Total N C/N Colwell P Total P PRI Colwell K Total K Ex. Ca Ex. Mg Ex. Na Ex. K Ex. Al ECEC Ca% Mg% ESP K% Al% As Cd Cr Pb
EC 1.00 0.08 0.00 0.01 0.34 0.00 0.08 0.00 0.08 0.21 0.06 0.11 0.01 0.22 0.53 0.87 0.14 0.01 0.48 0.20 0.12 0.69 0.23 0.03 0.00 0.05 0.13 0.00 pHCa 0.08 1.00 0.03 0.16 0.11 0.05 0.03 0.05 0.15 0.01 0.00 0.00 0.03 0.20 0.27 0.12 0.01 0.00 0.25 0.00 0.05 0.07 0.32 0.04 0.02 0.02 0.01 0.05 CCE 0.00 0.03 1.00 0.00 0.00 0.09 0.24 0.11 0.09 0.00 0.02 0.03 0.02 0.01 0.00 0.00 0.00 0.00 0.01 0.02 0.01 0.00 0.01 0.00 0.01 0.00 0.07 0.00 OC 0.01 0.16 0.00 1.00 0.06 0.15 0.01 0.49 0.02 0.05 0.01 0.01 0.05 0.02 0.04 0.02 0.01 0.05 0.03 0.02 0.01 0.03 0.03 0.01 0.11 0.05 0.06 0.10 NO3-N 0.34 0.11 0.00 0.06 1.00 0.00 0.00 0.07 0.14 0.24 0.02 0.01 0.00 0.06 0.26 0.54 0.00 0.09 0.19 0.16 0.09 0.54 0.37 0.01 0.03 0.01 0.00 0.03 NH4-N 0.00 0.05 0.09 0.15 0.00 1.00 0.00 0.09 0.09 0.02 0.03 0.05 0.03 0.03 0.00 0.00 0.00 0.00 0.01 0.08 0.06 0.01 0.02 0.00 0.11 0.01 0.02 0.01 Total N 0.08 0.03 0.24 0.01 0.00 0.00 1.00 0.37 0.01 0.00 0.05 0.00 0.02 0.03 0.07 0.04 0.02 0.02 0.05 0.01 0.03 0.03 0.02 0.05 0.01 0.02 0.15 0.00 C/N 0.00 0.05 0.11 0.49 0.07 0.09 0.37 1.00 0.03 0.04 0.04 0.01 0.00 0.00 0.00 0.00 0.00 0.05 0.00 0.01 0.00 0.01 0.00 0.03 0.13 0.01 0.15 0.03 Colwell P 0.08 0.15 0.09 0.02 0.14 0.09 0.01 0.03 1.00 0.03 0.01 0.11 0.05 0.06 0.09 0.09 0.07 0.01 0.07 0.00 0.03 0.07 0.41 0.00 0.00 0.00 0.04 0.03 Total P 0.21 0.01 0.00 0.05 0.24 0.02 0.00 0.04 0.03 1.00 0.16 0.09 0.14 0.18 0.31 0.27 0.16 0.10 0.32 0.06 0.04 0.19 0.10 0.00 0.01 0.01 0.01 0.02 PRI 0.06 0.00 0.02 0.01 0.02 0.03 0.05 0.04 0.01 0.16 1.00 0.09 0.09 0.01 0.09 0.05 0.10 0.02 0.04 0.05 0.06 0.03 0.00 0.06 0.01 0.03 0.01 0.00 Colwell K 0.11 0.00 0.03 0.01 0.01 0.05 0.00 0.01 0.11 0.09 0.09 1.00 0.10 0.28 0.18 0.07 0.85 0.11 0.32 0.00 0.01 0.01 0.10 0.26 0.04 0.01 0.00 0.01 Total K 0.01 0.03 0.02 0.05 0.00 0.03 0.02 0.00 0.05 0.14 0.09 0.10 1.00 0.06 0.02 0.00 0.21 0.00 0.06 0.01 0.02 0.00 0.04 0.03 0.09 0.02 0.00 0.01 Ex. Ca 0.22 0.20 0.01 0.02 0.06 0.03 0.03 0.00 0.06 0.18 0.01 0.28 0.06 1.00 0.39 0.19 0.46 0.03 0.86 0.15 0.06 0.03 0.17 0.30 0.05 0.02 0.01 0.01 Ex. Mg 0.53 0.27 0.00 0.04 0.26 0.00 0.07 0.00 0.09 0.31 0.09 0.18 0.02 0.39 1.00 0.57 0.25 0.00 0.72 0.18 0.35 0.36 0.31 0.12 0.00 0.00 0.01 0.02 Ex. Na 0.87 0.12 0.00 0.02 0.54 0.00 0.04 0.00 0.09 0.27 0.05 0.07 0.00 0.19 0.57 1.00 0.08 0.03 0.47 0.29 0.16 0.89 0.33 0.01 0.01 0.03 0.06 0.00 Ex. K 0.14 0.01 0.00 0.01 0.00 0.00 0.02 0.00 0.07 0.16 0.10 0.85 0.21 0.46 0.25 0.08 1.00 0.11 0.48 0.02 0.02 0.00 0.06 0.34 0.05 0.00 0.01 0.00 Ex. Al 0.01 0.00 0.00 0.05 0.09 0.00 0.02 0.05 0.01 0.10 0.02 0.11 0.00 0.03 0.00 0.03 0.11 1.00 0.00 0.13 0.02 0.07 0.10 0.78 0.05 0.00 0.02 0.08 ECEC 0.48 0.25 0.01 0.03 0.19 0.01 0.05 0.00 0.07 0.32 0.04 0.32 0.06 0.86 0.72 0.47 0.48 0.00 1.00 0.00 0.01 0.19 0.25 0.22 0.02 0.01 0.02 0.02 Ca% 0.20 0.00 0.02 0.02 0.16 0.08 0.01 0.01 0.00 0.06 0.05 0.00 0.01 0.15 0.18 0.29 0.02 0.13 0.00 1.00 0.74 0.47 0.02 0.13 0.05 0.00 0.00 0.00 Mg% 0.12 0.05 0.01 0.01 0.09 0.06 0.03 0.00 0.03 0.04 0.06 0.01 0.02 0.06 0.35 0.16 0.02 0.02 0.01 0.74 1.00 0.24 0.10 0.01 0.01 0.02 0.00 0.00 ESP 0.69 0.07 0.00 0.03 0.54 0.01 0.03 0.01 0.07 0.19 0.03 0.01 0.00 0.03 0.36 0.89 0.00 0.07 0.19 0.47 0.24 1.00 0.31 0.00 0.03 0.02 0.04 0.00 K% 0.23 0.32 0.01 0.03 0.37 0.02 0.02 0.00 0.41 0.10 0.00 0.10 0.04 0.17 0.31 0.33 0.06 0.10 0.25 0.02 0.10 0.31 1.00 0.00 0.00 0.02 0.00 0.03 Al% 0.03 0.04 0.00 0.01 0.01 0.00 0.05 0.03 0.00 0.00 0.06 0.26 0.03 0.30 0.12 0.01 0.34 0.78 0.22 0.13 0.01 0.00 0.00 1.00 0.07 0.00 0.03 0.03 As 0.00 0.02 0.01 0.11 0.03 0.11 0.01 0.13 0.00 0.01 0.01 0.04 0.09 0.05 0.00 0.01 0.05 0.05 0.02 0.05 0.01 0.03 0.00 0.07 1.00 0.63 0.21 0.40 Cd 0.05 0.02 0.00 0.05 0.01 0.01 0.02 0.01 0.00 0.01 0.03 0.01 0.02 0.02 0.00 0.03 0.00 0.00 0.01 0.00 0.02 0.02 0.02 0.00 0.63 1.00 0.49 0.35 Cr 0.13 0.01 0.07 0.06 0.00 0.02 0.15 0.15 0.04 0.01 0.01 0.00 0.00 0.01 0.01 0.06 0.01 0.02 0.02 0.00 0.00 0.04 0.00 0.03 0.21 0.49 1.00 0.08 Pb 0.00 0.05 0.00 0.10 0.03 0.01 0.00 0.03 0.03 0.02 0.00 0.01 0.01 0.01 0.02 0.00 0.00 0.08 0.02 0.00 0.00 0.00 0.03 0.03 0.40 0.35 0.08 1.00
Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).
47
3.4.2. PARTICLE SIZE AND SOIL CHEMICAL PROPERTIES
Bivariate correlation and linear regression analyses between soil particle size
(March 2014) and soil chemical properties (December 2013) were assessed, using Span
3 results based on Pivots 1-8, 10 and 11 (Table 8).
Table 8. Correlation (R2) between soil particle size and soil chemical properties at 0-10 cm and
20-30 cm, using Span 3 results based on Pivots 1-8, 10 and 11.
0-10 cm 20-30 cm Sand Silt Clay Sand Silt Clay Sand 1.00 0.14 0.56 1.00 0.05 0.92 Silt - 1.00 0.12 - 1.00 0.24 Clay - - 1.00 - - 1.00 Electrical conductivity, EC 0.23 0.06 0.10 0.45 0.02 0.42 pHCa 0.49 0.11 0.22 0.01 0.01 0.01 CaCO3 equivalent, CCE 0.15 0.29 0.00 0.03 0.02 0.01 Organic C, OC 0.44 0.00 0.49 0.00 0.00 0.00 NO3-N 0.00 0.08 0.08 0.05 0.04 0.02 NH4-N 0.01 0.16 0.04 0.08 0.07 0.03 Total N 0.10 0.01 0.15 0.08 0.23 0.15 C/N ratio 0.39 0.00 0.41 0.03 0.02 0.03 Colwell P 0.17 0.33 0.00 0.17 0.12 0.22 Total P 0.35 0.00 0.42 0.61 0.15 0.66 Phosphorus retention index, PRI
0.27 0.07 0.11 0.26 0.01 0.23
Colwell K 0.07 0.04 0.16 0.43 0.07 0.44 Total K 0.31 0.02 0.45 0.60 0.00 0.47 Ex. Ca 0.02 0.02 0.06 0.47 0.00 0.38 Ex. Mg 0.02 0.04 0.09 0.53 0.00 0.40 Ex. Na 0.25 0.05 0.11 0.53 0.01 0.47 Ex. K 0.05 0.06 0.17 0.54 0.04 0.51 Ex. Al 0.00 0.03 0.00 0.11 0.44 0.24 Effective cation exchange capacity, ECEC
0.04 0.02 0.09 0.54 0.00 0.43
Ex. Ca percentage 0.01 0.00 0.01 0.17 0.00 0.14 Ex. Mg percentage 0.09 0.09 0.01 0.15 0.01 0.14 Ex. Na percentage (ESP) 0.24 0.11 0.07 0.00 0.05 0.02 Ex. K percentage 0.00 0.01 0.00 0.05 0.24 0.12 Ex. Al percentage 0.01 0.01 0.03 0.36 0.30 0.48 As 0.15 0.04 0.06 0.20 0.13 0.25 Cd 0.01 0.05 0.01 0.01 0.03 0.02 Cr 0.00 0.01 0.00 0.01 0.01 0.01 Pb 0.06 0.06 0.01 0.00 0.02 0.00 Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak).
Sand and clay fractions of the soil appear to be moderately to strongly negatively
correlated at both 0-10 cm (R2 = 0.56) and 20-30 cm (R2 = 0.92), while silt fractions were
not related. A few soil chemical properties were related to particle size at 0-10 cm but
were not greatly important. On the other hand, there was a greater degree of association
between soil chemical properties and particle size at 20-30 cm, with correlations
Investigating the impacts of groundwater on soil properties and pasture
nutrition
48
generally reflecting the moderate-strong relationships between soil nutrients with
either sand or clay percentage.
3.4.3. LEAF NUTRIENT COMPOSITION AND SOIL PROPERTIES
Most leaf nutrient concentrations were not correlated with soil properties (see
Tables 17 and 18 in Appendix A). A few moderate correlations existed, but were not
insightful. Leaf Cr concentrations were moderately and positively correlated with soil Cr
concentrations (R2 = 0.47 at 0-10 cm, R2 = 0.41 at 20-30 cm). However, Figure 48 showed
these correlations were clearly influenced by outliers – i.e., results from December 2013.
All December leaf tissue samples had unusually high Cr concentrations (see Figure 36)
and their removal resulted in no correlation between Cr concentrations in soil and leaf
tissue.
Figure 48. Linear relationship between chromium concentrations (Cr, mg/kg) in leaf tissue
and soil at 0-10 cm (left) and 20-30 cm (right), based on Span 3 results from March to
December 2013 with December 2013 outliers included (top) and removed (bottom).
R² = 0.47260
1
2
3
4
5
6
7
0 100 200 300 400 500 600
Cr
(mg/
kg)
in le
af
Cr (mg/kg) in soil
0-10 cm(Dec 2013 included)
R² = 0.40780
1
2
3
4
5
6
7
0 100 200 300 400 500
Cr
(mg/
kg)
in le
af
Cr (mg/kg) in soil
20-30 cm(Dec 2013 included)
R² = 0.08870.0
0.2
0.4
0.6
0.8
1.0
0 100 200 300 400
Cr
(mg/
kg)
in le
af
Cr (mg/kg) in soil
0-10 cm(Dec 2013 removed)
R² = 0.04120.0
0.2
0.4
0.6
0.8
1.0
0 100 200 300 400
Cr
(mg/
kg)
in le
af
Cr (mg/kg) in soil
20-30 cm(Dec 2013 removed)
49
3.5. WATER QUALITY AND GEOCHEMICAL MODELLING
The WEB-PHREEQ modelling program was used to determine possible mineral
precipitation from irrigation water with and without added nutrients, using water
quality data from December 2013 (Table 9). Saturation indices (SI) for all saturated and
oversaturated solid phases in source water and fertigation mixture are summarised in
Table 10 (see Appendix B for output data).
Table 9. Composition of dewatering surplus and fertigation mixture sampled in December 2013.
Parameter Units Source water Fertigation mixture
Temperature* oC 29.5 31.9
pH* pH units 8.2 8.0
Electrical conductivity, EC, at 25oC
dS/m 0.84 0.99
Total dissolved solids, TDS mg/L 528 580
Total alkalinity as CaCO3* mg/L 240 220
Ca* mg/L 61 61
Mg* mg/L 50 50 Na* mg/L 42 43
K* mg/L 13 31
HCO3 mg/L 290 270
Cl* mg/L 120 120
SO4* mg/L 76 92
NO3-N mg/L 0.36 14
NH4-N mg/L <0.005 15
Total N* mg/L 0.36 60
Total P* mg/L 0.01 7.2
Al* mg/L <0.02 <0.02
B* mg/L 0.3 0.3
Cd* mg/L <0.001 <0.001
Co mg/L <0.01 <0.01
Cu* mg/L 0.016 0.005
Fe* mg/L <0.02 <0.02
Pb* mg/L <0.02 <0.02
Mn mg/L 0.007 0.21
Mo mg/L <0.01 0.02
Se mg/L <0.05 <0.05
Zn* mg/L 0.08 0.26
*parameters used in WEB-PHREEQ modelling
The model shows both the source water and fertigation mixture were
oversaturated with respect to carbonate and (hydr)oxide minerals of Ca, Mg, Fe and Mn,
and with phosphate as apatite. In particular, dolomite, hausmannite, hematite and
hydroxyapatite appear to be minerals most likely to precipitate from irrigation waters
due to their relatively high saturation index.
Investigating the impacts of groundwater on soil properties and pasture
nutrition
50
Table 10. Saturation indices of solid phases in source water (pH 8.2) and fertigation mixture (pH
8.0) sampled in December 2013, calculated from WEB-PHREEQ using input values in Table 9 –
Al, Cd, Pb and Fe concentrations are half their detection limit.
Phase Source water Fertigation mixture Aragonite, CaCO3 1.21 0.57 Calcite, CaCO3 1.35 0.71 Dolomite, CaMg(CO3)2 3.03 1.76 Iron (III) hydroxide, Fe(OH)3 (a) 0.45 0.43 Goethite, FeOOH 6.50 6.57 Hausmannite, Mn3O4 2.34 2.77 Hematite, Fe2O3 15.03 15.17 Hydroxyapatite, Ca5(PO4)3OH 1.53 8.04 Manganite, MnOOH 1.04 0.70 Pyrolusite, MnO2 2.58 1.74 Rhodochrosite, MnCO3 -0.76 0.46
Relative to source water, the fertigation mixture was less oversaturated with
respect to aragonite, calcite, dolomite, manganite and pyrolusite, but more oversaturated
with respect to hausmannite, hematite, hydroxyapatite and rhodochrosite. No major
change occurred for iron (III) hydroxide and goethite after fertiliser addition to source
water. Fertiliser addition appears to have slightly lowered the potential for aragonite,
calcite and dolomite to precipitate, but not to the extent that they will not precipitate if
given suitable conditions for nucleation and crystal growth. The formation of insoluble
carbonate, (hydr)oxide and phosphate (apatite) minerals of Ca, Mg, Fe and Mn from the
fertigation mixture could therefore impose a risk for nutrient immobilisation.
Sensitivity analysis was conducted by adjusting pH values to identify the
threshold at which calcite and dolomite would remain undersaturated (Table 11; see
Appendix B for output data).
Table 11. Saturation indices of carbonates, (hydr)oxides and apatite in source water and
fertigation mixture, modelled at pH 7.
Phase Source water Fertigation mixture Aragonite, CaCO3 -0.36 -0.39 Calcite, CaCO3 -0.22 -0.25 Dolomite, CaMg(CO3)2 -0.12 -0.17 Iron (III) hydroxide, Fe(OH)3 (a) 0.41 0.29 Gibbsite, Al(OH)3 0.83 0.73 Goethite, FeOOH 6.46 6.42 Hausmannite, Mn3O4 -11.66 -6.63 Hematite, Fe2O3 14.95 14.88 Hydroxyapatite, Ca5(PO4)3OH -5.01 3.70 Manganite, MnOOH -4.58 -3.10 Pyrolusite, MnO2 -5.91 -4.06 Rhodochrosite, MnCO3 -1.77 -0.31
Investigating the impacts of groundwater on soil properties and pasture
nutrition
51
Results showed that pH 7.0 was required to achieve this for both source water
and fertigation mixture. Thus, calcite, dolomite and other Mn minerals should not
precipitate if the pH of the fertigation mixture is ≤ 7. However, this does not appear to
significantly affect the SI of iron (hydr)oxides. The fertigation mixture would still remain
oversaturated with respect hydroxyapatite (SI = 3.70). Moreover, both the source water
and fertigation mixture were predicted to be oversaturated with respect to gibbsite at
pH 7.
3.6. ASH ALKALINITY DETERMINATION AND MASS BALANCE
Ash contents ranged from 9.3-10.8 % w/w and ash alkalinity from 0.28-0.37
meq/g with a mean of 0.33 meq/g (Table 12). Net alkalinity was calculated from a mass
balance of alkalinity added from irrigation water less that removed from hay yield (Table
13).
Table 12. Ash content (%) and ash alkalinity (eq/g) of duplicate hay subsamples from Pivots 1-5
collected in February 2014 for the growth cycle between November 2013 and January 2014 -
titration of 50 ml of 0.0494 M HCl and hay ash with 0.05 M Na2CO3.
Pivot # Cut # Volume of
Na2CO3 used (ml)
Dry weight of hay sample (g)
Ash content (%) Ash alkalinity
(meq/g)
1 8 23.1 0.507 9.9 0.32 1 8 23.1 0.506 9.3 0.32 2* 7 23.2 0.499 - 0.30 2 7 22.8 0.516 9.9 0.37 3 6 22.9 0.506 10.7 0.36 3 6 22.8 0.511 10.4 0.37 4 7 22.9 0.500 10.6 0.36 4 7 23.1 0.502 10.8 0.32 5* 7 23.3 0.500 - 0.28 5 7 23.2 0.502 10.0 0.30 Mean 10.2 (± 0.2) 0.33 (± 0.01) *ash content not available due to procedural error
Calculations showed a net gain in alkalinity due to irrigation, ranging from 301-
535 kg CaCO3/ha with an overall mean of 409 kg CaCO3/ha for the growth cycle between
November 2013 and January 2014 (approximately 6-8 weeks). The amount of alkalinity
applied during this period exceeded the amount removed from pasture growth by about
five times (P < 0.01). Based on total irrigation and hay produced throughout October
2012 to January 2014, the total net gain in alkalinity ranged from 3206-4139 kg
CaCO3/ha with a mean of 3735(± 164) kg CaCO3/ha (Table 14). On average, the amount
Investigating the impacts of groundwater on soil properties and pasture
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52
of alkalinity added was more than 12 times the amount removed and could thus explain
significant increases in soil pH. Annually, this would equate to a net gain of 3168(± 67)
kg CaCO3/ha.
Table 13. Mean net alkalinity values determined from a mass balance of alkalinity added from irrigation and removed by hay production for Pivots 1-5 between
November 2013 and January 2014 – based on the total alkalinity of irrigation water measured in November 2013, using unpublished hay yield and irrigation data
(Rio Tinto Iron Ore, 2014).
Pivot # Gross irrigation
(ML/ha) Total dry hay weight (t/ha)
Alkalinity added from irrigation Alkalinity removed from hay Net alkalinity as CaCO3 (kg/ha): added
- removed Total alkalinity as CaCO3
(mg/L) Overall total alkalinity
as CaCO3 (kg/ha) Ash alkalinity (meq/g)
Overall ash alkalinity as CaCO3 (kg/ha)
1 1.774 5.950 230 408.0 0.32 (± 0.00) 94.0 (± 0.1) 314.0 (± 0.1)
2 2.900 7.911 230 667.0 0.33 (± 0.03) 132.3 (± 13.4) 534.7 (± 13.4)
3 2.806 6.527 230 645.4 0.36 (± 0.01) 118.7 (± 2.6) 526.6 (± 2.6)
4 1.990 5.376 230 457.7 0.34 (± 0.02) 91.2 (± 5.5) 366.5 (± 5.5)
5 1.568 4.121 230 360.6 0.29 (± 0.01) 59.6 (± 1.9) 300.9 (± 1.9)
Overall mean 507.7 (± 62.6) 0.33 (± 0.01) 99.2 (± 12.5) 408.6 (± 51.1)
Table 14. Total net alkalinity gained from irrigated pastures for Pivots 1-5 throughout the study period from October 2012 to January 2014 – assuming relatively
constant total alkalinity of irrigation water, using unpublished hay yield and irrigation data (Rio Tinto Iron Ore, 2014).
Pivot # Total days of
growth
Gross Irrigation (ML/ha)
Total dry weight of hay
(t/ha)
Alkalinity added from irrigation Alkalinity removed from hay Net alkalinity as CaCO3 (kg/ha):
added - removed
Net rate of alkalinity as
CaCO3 (kg/ha/year)
Total alkalinity as CaCO3 (mg/L)
Overall total alkalinity as
CaCO3 (kg/ha)
Ash alkalinity (meq/g)
Overall ash alkalinity as
CaCO3 (kg/ha)
1 456 19.3 18.9 230 4441 0.32 302 4139 3313
2 448 19.0 21.9 230 4377 0.33 361 4016 3272
3 400 15.3 18.0 230 3529 0.36 323 3206 2925
4 427 17.5 18.6 230 4016 0.34 316 3700 3163
5 417 17.0 19.7 230 3901 0.29 285 3616 3165
Overall mean 4053 (± 166) 0.33 (± 0.01) 318 (± 13) 3735 (± 164) 3168 (± 67)
54
4. DISCUSSION
4.1. OVERVIEW
Groundwater from the Marandoo iron ore mine in the central Pilbara region of
Western Australia is utilised for irrigation at the Hamersley Agricultural Project (HAP).
After amendment with nutrients, the water was slightly alkaline with pH 8.0 and total
alkalinity of 220 mg CaCO3/L, and slightly brackish-sodic with an EC of 0.99 dS/m and
TDS of 580 mg/L. The major cations include Ca, Mg and Na, and the dominant anion was
HCO3.
Over 15 months of irrigation, analysis showed: (1) significant increases in soil
sodicity, whereby ESP levels had exceeded 5% at 0-10 cm and 7% at 20-30 cm, and (2)
alkalinisation, especially within the 0-10 cm soil layer, that could result in high soil pH
(~8.2) that may adversely affect nutrient availability. However, in contrast to initial
findings on sodicity, a subsequent study indicated that the increases in ESP were
overestimated since results did not account for the increasing soluble salts in the soil.
When samples were pre-washed to remove soluble salts there was little increase in ESP
and hence no evidence of sodicity in HAP soils after 15 months (Samaraweera, 2015).
Given suitable conditions for nucleation and crystal growth, the precipitation of
carbonate, (hydr)oxide and phosphate (apatite) minerals of Ca, Mg, Fe and Mn could also
impose a risk for immobilising nutrients applied from irrigation water. Moreover, other
implications may also arise from changes in the relative abundance of soil exchangeable
cations whereby exchangeable Mg2+ as a percentage of cation exchange capacity
significantly increased while exchangeable Ca2+ and K+ percentages have significantly
decreased.
Many other soil chemical properties were also shown to significantly change over
15 months, but were not as important and/or consistent. Total As was, however, already
present in the soil at relatively high concentrations that could adversely affect sensitive
plant species. But, at this stage, leaf tissue analysis did not identify abnormalities in the
nutrient composition of C. gayana between March and December 2013, with the
exception of a spike in Cr concentration in December. In general, overall leaf
compositions have remained unaffected by changes in soil chemistry which may in part
reflect the high tolerance of C. gayana to current conditions as well as the short duration
of irrigation (≤ 15 months).
Investigating the impacts of groundwater on soil properties and pasture
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The implications of irrigation with slightly alkaline and slightly brackish-sodic
water for soil properties and pasture nutrition at the HAP site are discussed in detail,
based on the author’s initial findings. Long-term predictions will be made about the
sustainability of irrigation on the site, along with recommendations for remediation.
Suggestions for future soil and plant monitoring strategies are discussed in Appendix G.
4.2. MAJOR FINDINGS
4.2.1. EXCHANGEABLE SODIUM AND SODICITY
Significant increases in ESP by 1.5-3.7 % were already observed within the first
four months of continuous irrigation (Figure 23). After 15 months, ESP levels exceeded
5% at 0-10 cm and 7% at 20-30 cm. Soil sodicity is usually characterised by an ESP ≥ 15
(United States Soil Laboratory Staff, 1954) corresponding with a sharp deterioration in
soil physical properties (Abrol et al., 1988). However, a single value of ESP cannot be
used as a critical threshold for all conditions (Kijne et al., 1998). Soil degradation has
been observed in Australian soils when the ESP exceeds 6% (Rengasamy and Olsson,
1991), or even as low as 4% in Pakistan soils (Condom et al., 1999).
While such ESP levels indicate sodicity could emerge as an issue for future soil
management at the HAP, subsequent laboratory analysis utilising the pre-treatment
method for removal of soluble salts (Samaraweera, 2015; see Appendix H) concluded
that the addition of irrigation water had not caused a measurable change in the sodicity
of the HAP soils. Samaraweera (2015) found that almost all the sodium in the soil were
as soluble Na+ and not found in the cation exchange complex, and hence determination
of ESP in soils samples in the future should be carried out by employing methods that
include pre-treatment for soluble salts to avoid overestimation. It also means that
present conditions do not indicate significant increases in ESP or an imminent concern
about sodicity.
Increases in ESP levels over time need to be monitored given the
disproportionately high concentration of Na+ in the irrigation water and/or the
precipitation of Ca2+ and Mg2+ from irrigation water (or soil solution) which increases
the sodium adsorption ratio (SAR; Bower et al., 1968). Correlation analyses (Tables 6
and 7) strongly suggest that elevated ESP levels were directly due to high Na+
Investigating the impacts of groundwater on soil properties and pasture
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concentrations applied from irrigation water. Since no significant change occurred in soil
CCE over time, Ca and Mg carbonate precipitation is not a major issue at this stage.
Moreover, no correlation was found between CCE and exchangeable Ca2+ percentage, or
with ESP, and hence elevated ESP is likely due to irrigation with sodic water.
Sodicity, if it develops, may restrict plant growth via poor soil physical conditions
(Warrence and Bauder, 2001, Stearns et al., 2005, Saqib et al., 2008), as well as induce
osmotic stress and specific ion toxicity in sensitive species (Yang et al., 2008a, Yang et al.,
2009, Davis et al., 2012), including nutritional imbalances (e.g., impaired uptake of Ca;
Huang et al., 2012b). In cases of severe alkalinisation, the injurious effects may also be
compounded by high pH (Peng et al., 2008, Yang et al., 2008b, Kukavica et al., 2013).
Nevertheless, leaf Na concentrations did not significantly change between March and
December which may in part reflect the exceptionally high tolerance of C. gayana to
exchangeable Na+ (i.e., ESP > 60; Pearson, 1960). For that reason, it is usually the poor
physical condition caused by sodicity that results in stunting of Na-tolerant species and
not Na toxicity (Pearson, 1960).
4.2.1.1. FUTURE RISK OF SODICITY
The critical threshold for Na-induced dispersion not only depends on the ESP,
but also on the ionic strength of the soil solution (Guerrero-Alves et al., 2002), soil type
(Frenkel et al., 1992) and clay mineralogy (Alperovitch et al., 1985, Shainberg and Levy,
1992, Rengasamy, 2010). Given the current EC of irrigation water, which, while not saline
was nevertheless about 0.99 dS/m (or SAR ~1, see Appendix F), dispersion may not
occur until higher ESP values are recorded. This is because salinity has a flocculating
effect on soils by promoting clay particle aggregation (i.e., usually when irrigation water
> 0.5 dS/m; Warrence et al., 2002).
The degree of dispersion will, however, differ with soil type and clay mineralogy
(Warrence et al., 2002, Ruiz-Vera and Wu, 2006). Because clay soils, as opposed to sandy
soils, have a lower leaching fraction and greater surface area to adsorb Na+ ions (i.e.,
higher cation exchange capacity), soils with a high clay fraction are inherently more
prone to dispersion (Warrence et al., 2002) and swelling (Shainberg and Levy, 1992).
Moreover, the structure of the crystal lattice of clays will have a determining role. Clays
such as smectite become easily hydrated (i.e., adsorb water molecules) due to their 2:1
lattice structure and thus, under certain conditions, become prone to swelling and
dispersion (Boulding and Ginn, 2004). Generally, soils high in 2:1 layer silicate clays are
Investigating the impacts of groundwater on soil properties and pasture
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most dispersive, while those dominated by 1:1 layer silicates, such as kaolinite, are least
dispersive (Alperovitch et al., 1985).
Given mean ECEC values were < 10 cmol(+)/kg, kaolinite is likely the dominant
clay in HAP soils (Boulding and Ginn, 2004) and hence clay dispersion is unlikely to occur
at the present ESP level. Furthermore, due to the low active interlayer surface area of
kaolinite, swelling does not occur much and thus ESP will have a negligible effect on clay
swelling (Shainberg and Singer, 1990). In this study, changes in hydraulic conductivity
and clay dispersion were not measured, but may be closely examined if there is evidence
that soil ESP is increasing in the future.
4.2.2. SOIL PH AND ALKALINISATION
Since the commencement of sampling in October 2012, soil pHCa significantly
increased from 4.9 to 6.9 and 5.0 to 5.5 in the 0-10 cm and 20-30 cm soil layers,
respectively. Despite this, soil pHCa is still within the ideal range for C. gayana (between
5.5 and 7.5) and hence should not adversely affect plant growth (Pengelly et al., 2006).
However, an increase of 2.0 pH units at 0-10 cm, which is equivalent to a 100-fold
increase in the hydroxide (OH-) concentration, within 15 months is considerable and can
be explained by the accumulation of alkaline solutes from irrigation. In the subsoil,
however, alkalinisation is occurring at a slower rate.
There is compelling evidence that alkalinisation will continue to occur due to
irrigation. Based on mass balance calculations (Tables 13 and 14), there was an average
net gain of approximately 3.8 t CaCO3/ha (equivalent to ~0.1% CaCO3 in the 0-30 cm soil
layer) over the 15-month study period. Therefore, as irrigation continues into the future,
soil pH will rise until a new pH-buffer threshold is reached.
The magnitude of pH increase will largely depend on the abundance of salt(s)
capable of undergoing alkaline hydrolysis (Abrol et al., 1988). Here, changes in soil pH
were strongly associated with exchangeable Mg2+ concentrations rather than Na+,
suggesting that Na+ salts were not undergoing alkaline hydrolysis. WEB-PHREEQ
modelling also shows that calcite and dolomite were the major carbonate minerals in
irrigation water. Therefore, due to their relatively limited solubility, the soil will likely be
buffered at a slightly alkaline pH of ~8.0 to 8.2 (Abrol et al., 1988). The fact that the pH
of irrigation water is 8.0 also suggests that soil pH will not rise significantly higher. Once
exceeding their solubility, the rate of precipitation of Ca and Mg carbonates will increase
as will their accumulation in the soil profile (Ayers and Westcot, 1976). Excessive
Investigating the impacts of groundwater on soil properties and pasture
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mineral precipitation may present other issues for plant growth and this is discussed in
Section 4.2.3.
In alkaline-sodic soils, problems with high pH are usually due to the
accumulation of NaHCO3 and Na2CO3 (Guerrero-Alves et al., 2002). Due to their greater
solubility, there is a greater potential for hydrolysis and therefore tend to produce a
higher pH, usually > 8.5 (Guerrero-Alves et al., 2002), to as high as 10 to 10.5 when
present in appreciable amounts (Abrol et al., 1988). Nevertheless, an increase from pH 5
to 8 is very significant and can exert a marked influence on nutrient availability
(Kaupenjohann et al., 1989) by affecting their solubility and the ability of plant roots to
absorb nutrients (Atwell et al., 1999).
4.2.2.1. IMPLICATIONS FOR PASTURE NUTRITION
Nutrient deficiencies are a principal limiting factor for plant productivity (Marlet
et al., 1998) that causes the impaired function and growth of roots (López-Bucio et al.,
2003). Under alkaline soil conditions, nutrient disorders may induce leaf symptoms such
as chlorosis (Ksouri et al., 2005).
Though the study showed no significant change in leaf N, an increased pH above
7.5 (Francis et al., 2008) may dramatically reduce the availability of N in the soil through
increased NH3 volatilisation (Ryan et al., 1981, Marlet et al., 1998) particularly where
urea is used as the fertiliser. Increases in soil pH may also restrict P availability for plant
uptake due to the formation of insoluble Ca-P compounds (Hopkins and Ellsworth,
2005). However, current trends indicate P, Ca and Mg concentrations in leaf tissue to
have significantly increased even though initial leaf P concentrations were low (see Table
15 in Section 4.3.1).
Generally, as the soil pH increases above 7, the bioavailability of most trace
elements such as B (Gupta, 2007), Cu (Kopsell and Kopsell, 2007), Fe (Römheld and
Nikolic, 2007), Mn (Humphries et al., 2007), Ni (Brown, 2007) and Zn (Bolan et al., 2003)
may become substantially reduced due to their limited solubility (Valdez-Aguilar et al.,
2009). At pH 8.2, trace elements may be further immobilised due to complexation with
Ca and Mg carbonates (Storey, 2007); hence, irrigation could likely exacerbate this
problem. However, unlike these trace elements, Mo bioavailability in soils increases
under alkaline conditions (Bolan et al., 2003) such that for each unit increase in soil pH
above pH 5.0 the soluble Mo concentration increases 100-fold (Gupta and Lipsett, 1981,
Hamlin, 2007). Therefore, increasing the pH from 5.0 to 8.2 could result in sufficiently
Investigating the impacts of groundwater on soil properties and pasture
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high Mo concentrations that may affect plant growth, though, under most agricultural
conditions Mo toxicity in plants is rare (Kaiser et al., 2005). High Mo in plant tissue is
likely more of a risk to animal health from Mo toxicity and Cu deprivation (Suttle, 2010).
In particular, since bicarbonate ions are able to maintain a high pH (7.5-8.0) in
the soil (Lucena et al., 2007), elevated bicarbonate concentrations may significantly
depress root growth by pH-buffering in the root apoplast and direct interference on root
metabolism (Peiter et al., 2001, Javid et al., 2012). For instance, bicarbonate can diminish
both Fe solubility and root ferric reductase activity which prevents plants from locally
acidifying the rhizosphere to mobilise Fe from the soil (Lucena et al., 2007, Javid et al.,
2012). At this stage, there has been no significant change in leaf Fe concentration.
Nonetheless, with soil pH changing relatively slowly in the 20-30 cm soil layer, B,
Cu, Fe, Mn and Zn availability should not change significantly unless (co-)precipitation
and surface adsorption is occurring. Leaf tissue analysis confirms this by: (1) a significant
increase in B and Zn concentration and (2) no significant change in Cu, Fe and Mn
concentrations. Leaf Ni concentrations, however, consistently decreased after 9 months
of irrigation. Nickel deficiency may be a result of competing elements such as Cu, Mn, Mg,
Fe, Ca, and Zn (Brown, 2007), but analysis (Table 19, see Appendix A) indicated no
correlation between Ni and Ca, Mg or Zn concentrations in leaf tissue.
No significant changes in leaf K concentrations occurred. Given the naturally high
reserves in the soil, K+ availability is likely to remain adequate for plant uptake unless
significantly displaced by exchangeable Mg+ and/or depleted by continuous cutting of
hay (Barrow, 1968). However, in the instance of high salinity and alkalinity, the
adsorption of K+ in roots may become greatly restricted by high levels of other cations
due to alkali stress (Wang et al., 2011). High pH (> 8.5) could disrupt plant
photosynthetic activities (Yang et al., 2008b) and anti-oxidative metabolism (Kukavica
et al., 2013), as well as further interfering with ion uptake and mineral nutrition (Peng
et al., 2008).
4.2.3. MINERAL PRECIPITATION
Both source water from Marandoo and the fertigation mixture for irrigation were
oversaturated with respect to carbonate and (hydr)oxide minerals of Ca, Mg, Fe and Mn,
as well as phosphate as apatite (Table 10). Since groundwater partial pressures, such as
CO2, are typically ~10-100 times higher than atmospheric partial pressures,
groundwater abstraction (as in the case of mine dewatering) results in CO2 degassing
Investigating the impacts of groundwater on soil properties and pasture
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(Macpherson, 2009). With respect to Ca and Mg carbonates, findings were also
consistent with PHREEQC models by Crisalis International Pty Ltd (2012), showing
groundwater from production bores at Marandoo, Hope Downs 1 and Nammuldi iron
ore mines were indeed saturated (calcite) to oversaturated (dolomite) and became
strongly oversaturated on equilibrium with air. Consequently, mineral precipitation
from these waters may be expected (Wetland Research & Management, 2012).
However, oversaturation alone is not sufficient cause for the salts to crystallise
(Chew, 2006). The formation of a new crystalline entity is governed by two major
mechanisms: nucleation and crystal growth (De Yoreo and Vekilov, 2003). Precipitation
begins from the nucleation process which involves the formation of ordered molecular
aggregates or nucleus (Melia and Moffitt, 1964). However, spontaneous crystal growth
will not occur until the nucleus achieves a critical size (Cubillas and Anderson, 2010).
The probability that nucleation will occur nonetheless increases exponentially as a
function of the degree of oversaturation (Huang et al., 2012a), and even more so in the
presence of foreign particles or surfaces (heterogeneous nucleation) than in bulk
solution (homogeneous nucleation; Melia and Moffitt, 1964, Chew, 2006). The
temperature of water is also an important factor influencing solubility and hence mineral
crystallisation.
Considering their relatively high degree of oversaturation in the fertigation
mixture, dolomite, hausmannite, hematite and hydroxyapatite are the mineral forms
most likely to precipitate from the irrigation water (Table 10).
4.2.3.1. IMPLICATIONS FOR NUTRIENT AVAILABILITY
The immobilisation of Ca, Mg, P, Fe and Mn in irrigation water will clearly affect
their availability in the soil solution, especially due to elevated soil pH (Huang et al.,
2012a). More importantly, P availability may be substantially reduced due to
precipitation of Ca-P compounds such as hydroxyapatite from irrigation water and/or
soil solution (Brady, 1990), including the adsorption of P to insoluble Fe and Mn
(hydr)oxide and lime particles (von Wandruszka, 2006, Elzinga and Sparks, 2007).
Likewise, (co-)precipitation and adsorption reactions may also have a major influence
on trace element availability (Han, 2007).
Precipitation and surface adsorption are two major mechanisms for P retention
(von Wandruszka, 2006). Geochemical modelling suggests that the precipitation of
hydroxyapatite from irrigation water could initially be an issue for P availability.
Investigating the impacts of groundwater on soil properties and pasture
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Furthermore, surface adsorption by Fe and Mn (hydr)oxides and Ca and Mg carbonates
added from irrigation water may also significantly contribute to P retention in the soil
(Kitano et al., 1978b, von Wandruszka, 2006) as reflected by increases in PRI over 15
months of sampling. In acid soils, P occlusion frequently occurs in the presence of Fe, Al
and Mn ions and even more extensively with their insoluble hydrous oxides by forming
insoluble hydroxy phosphate (Lewis et al., 1981, Brady, 1990, Søvik and Kløve, 2005, von
Wandruszka, 2006). In alkaline and calcareous soils (pH > 7), Ca2+ ions released from the
exchange complex or solubilised from carbonate phases (Tunesi et al., 1999) will have a
greater determining role by precipitating P as insoluble Ca-P compounds such as apatite
(Brady, 1990, Søvik and Kløve, 2005).
By comparing their relative importance, Ca and Mg carbonates will likely have a
greater influence on P availability than Fe and Mn (hydr)oxides because the amount of
carbonate added from irrigation water, relative to added P, greatly exceeds inputs of Fe
and Mn which are present in far lower concentrations. Hence, Fe and Mn (hydr)oxides
will generally make only a small contribution to P retention in these soils (e.g., Tunesi et
al., 1999). However, despite the potential net gain in CCE from irrigation water, there
was no significant change in soil CCE throughout the study (Table 4). Moreover, the real
CCE value could not be confirmed by either of the two procedures for determining soil
CCE (see Appendix E). Notwithstanding the stable CCE values over time, there remains
some doubt as to the amount of carbonate present in the soils.
Increases in the PRI, which were thought to be associated with soil carbonate,
were also not correlated (R2 ≤ 0.04; Tables 6 and 7). But despite clear evidence that PRI
had consistently increased, leaf P concentrations significantly increased from deficient
levels at the start of sampling to near-adequate levels after 15 months. This suggests the
P contained in fertigation mixture was counterbalancing any P sorption and thus the P
available for uptake by C. gayana. In the future, on-going precipitation and adsorption
reactions as a result of accumulating Ca and Mg carbonates, and possibly by Fe and Mn
(hydr)oxides, in the soil may continue to limit P uptake by C. gayana, however this can
be compensated by additional P applications in fertiliser.
The availability of certain micronutrients in the soil solution may also be greatly
affected by (1) dissolution and (co-)precipitation, (2) adsorption and desorption, (3)
complexation and (4) redox reactions (Han, 2007). Mineral dissolution and precipitation
reactions often govern the activities of trace elements (Deverel et al., 2011), particularly
Investigating the impacts of groundwater on soil properties and pasture
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62
in arid and semi-arid environments where carbonates, sulphates, phosphates and
hydroxides exert a major influence on their solubility (Han, 2007, Hooda, 2010).
Adsorption reactions are also relatively important mechanisms since trace element
activities are often too low to be controlled by precipitation and dissolution (Deverel et
al., 2011). This may involve adsorption to (hydr)oxides of Fe, Mn, and Al, organic matter,
clay minerals, and carbonates such as calcite and dolomite (Deverel et al., 2011, Hooda,
2010).
The precipitation of Ca and Mg carbonates and Fe and Mn (hydr)oxides from
irrigation water could thus have a significant role in the removal of plant micronutrients
(e.g., B, Cu, Fe, Mn, Ni and Zn) from the soil solution via (co-)precipitation and surface
adsorption (e.g., Kitano et al., 1978a). Though, in many instances, these mechanisms help
limit their toxicity and bioavailability (e.g., contaminated soils; Martinez and McBride,
1998, Bolan et al., 2003), micronutrient deficiencies may also occur if initial
concentrations in the soil are low (Yoshida and Tanaka, 1969, Keren and Bingham, 1985,
Manda, 2009). At this stage, no abnormalities were recorded in leaf tissue samples, but
ongoing monitoring of plant samples is needed.
4.2.3.2. CARBONATE ACCUMULATION AND SOIL CEMENTATION
Due to high evaporation and evapotranspiration rates in the study area, and
continuous irrigation with dolomitic waters, the concentrations of Ca2+, Mg2+ and HCO3-
in the soil will cause carbonates to increase (Nash and Smith, 2003, Durand et al., 2010).
Through time, carbonate precipitation may plug soil pores and develop soils with some
degree of cementation (Nash and Smith, 2003, Duniway et al., 2010) which may impede
the foraging ability of roots to uptake water and nutrients (Passioura, 1991). However,
the effect of reduced pore space and soil cementation will depend on the amount of
carbonate precipitation and its distribution (e.g., along the irrigation supply line, at the
soil surface and/or at a specific depth in the soil profile).
Although there was no observable increase in soil CCE, mass balance calculations
indicated that, on average, approximately 3.2 t CaCO3/ha could accumulate in the soil
annually. If carbonate accumulation occurs within the 0-10 cm depth, and assuming a
soil bulk density of 1.5 t/m3, CaCO3 and MgCO3 may comprise 4.3% of the soil mass after
20 years. That is, soil cementation may occur when sufficient amounts of carbonate have
accumulated in the future. Long-term investigations could measure changes in the
compressive strength of the soil where precipitation has occurred (e.g., Park et al., 2014).
Investigating the impacts of groundwater on soil properties and pasture
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However, it is still unclear as to whether reduced soil porosity and increased
cementation from carbonate precipitation will occur, including its effects on plant
growth (e.g., van Alphen and de los Rios Romero, 1971, Saporetti-Junior et al., 2012).
In addition, carbonate precipitation has the potential to cause equipment
blockages and damage pressure gauges due to excessive clogging (Yiasoumi et al., 2005),
but no significant problems have been reported at present (S. Mathwin 2014, HAP
Superintendent pers. Comm., 6 May).
4.3. MINOR FINDINGS
4.3.1. EFFECT ON EXCHANGEABLE BASE CATIONS
Significant decreases in exchangeable Ca2+ percentage (by 10.4% at 0-10 cm and
7.1% at 20-30 cm; Table 4), and to a lesser extent exchangeable K+ percentage (by 4.5%
at 0-10 cm and 3.0% at 20-30 cm), were primarily attributed to the increase of
exchangeable Mg2+ as a proportion of cation exchange capacity. Indeed, all exchangeable
cations, except K+ at 20-30 cm, increased in concentration with Mg2+ increasing more
than others. Although ESP also significantly increased (by 2.0% at 0-10 cm and 6.4% at
20-30 cm), Na+ was a lesser cation contributing to the decline in exchangeable Ca2+
percentage presumably because Na+ is weakly sorbed on exchange sites relative to the
divalent Ca2+. However, a subsequent study found that almost all the sodium in the soil
were as soluble Na+ and not found in the exchangeable form (Figures 70 and 71;
Samaraweera, 2015).
More importantly, increases in soil pHCa were strongly correlated with increases
in exchangeable Mg2+ at 0-10 cm (Table 6), suggesting the predominance of Mg
bicarbonates in irrigation water. Exchangeable Ca2+, on the other hand, was not
correlated with pH change. The prevalence of dolomite and, to a lesser degree, calcite
was also supported by geochemical models (Table 10). This type of water is generated
when the groundwater is in contact with dolomite formations (Mazor, 2004) which,
according to geological reports, is primarily attributed to the Wittenoom Formation that
constitutes the deeper aquifer unit at Marandoo (Rio Tinto Iron Ore, 2008).
Changes in the proportion of exchangeable bases in the soil may adversely affect
plant nutrition by causing deficiencies in cations such as Ca2+ (e.g., Davis et al., 2012).
Investigating the impacts of groundwater on soil properties and pasture
nutrition
64
When soil cation ratios are in balance, the relative proportions of exchangeable bases in
the soil are: Ca2+ 65-70 %, Mg2+ 15-20 %, K+ 5 % and Na+ < 5 % (Hall, 2008). After 15
months of irrigation, overall mean abundance of cations at 0-10 cm and 20-30 cm were
approximately: Ca2+ 48 and 55 %, Mg2+ 37 and 26 %, K+ 10 %, and Na+ 5 and 7 %,
respectively. The proportion of exchangeable Mg-2+ was thus relatively high at 0-10 cm,
while that of exchangeable Ca2+ was comparatively low. Excessive Mg2+ concentrations
may adversely affect C. gayana due to their relatively low tolerance as compared to that
of high Na+ (Pengelly et al., 2006). Moreover, high Mg2+ will alter soil physical properties,
such as hydraulic conductivity, by causing the clay to become dispersed with decreased
macroporosity which in turn limits drainage, root penetration and thus nutrient
availability (Hall, 2008). Leaf tissue analysis, however, showed no deficiencies in Ca or
K, and no excess of Na or Mg despite being slightly higher than the normal concentration
range reported by Cameron (2001; Table 15). While this suggests C. gayana growth was
not adversely affected, the consequences of ongoing loading of soils with Mg2+ and Na+
need to be monitored through plant analysis.
Table 15. Comparing mean leaf nutrient concentrations of C. gayana in December 2013 with
"normal"/adequate nutrient concentration ranges for C. gayana and Phalaris aquatica.
Parameter Units
Chloris gayana Phalaris aquatica
HAP Dec-13 Cameron (2001) Reuter and
Robinson (1997) Reuter and
Robinson (1997)
Total N % 2.10 (± 0.08) 1.0 - 2.0-3.2
P % 0.19 (± 0.01) 0.14-0.27 < 0.20 (deficient),
0.24-0.34 (adequate)
0.20-0.25
K % 1.85 (± 0.06) 1.60-1.70 > 0.50 1.7-2.0
Ca % 0.56 (± 0.01) 0.40 - 0.14-0.20
Mg % 0.22 (± 0.01) 0.13-0.14 - 0.16-0.22
Na % 0.47 (± 0.12) 0.34-0.38 - -
S % 0.31 (± 0.01) 0.19-0.27 >0.12 0.21-0.25
Cu mg/kg 7.3 (± 0.3) 4.0 - 2.0-4.0
Fe mg/kg 113 (± 6) 121-341 - 40-60
Mn mg/kg 208 (± 16) - > 700 (toxic) 20-30
Zn mg/kg 32.4 (± 1.7) 15-18 - 12-15
B mg/kg 8.1 (± 0.6) - > 150 (toxic) 8-15
4.3.2. HEAVY METALS AND METALLOIDS
Generally, heavy metals and metalloids including Al, B, Cd, Co, Cu, Fe, Pb, Mn, Mo
and Zn in irrigation water (Table 9) did not exceed long-term trigger values (i.e., for
irrigation up to 100 years), and Se concentrations did not exceed the short-term trigger
value (i.e., for irrigation up to 20 years; ANZECC/ARMCANZ, 2000). Thus, over the next
Investigating the impacts of groundwater on soil properties and pasture
nutrition
65
20 years, heavy metals and metalloids are unlikely to accumulate in excessive levels as a
direct response to irrigation.
Total As, Cd and Pb concentrations in the soil did not significantly change over
15 months of irrigation. However, Cd and Pb concentrations in leaf tissue were
significantly higher in December, but were not nearly high enough to induce
phytotoxicity. On the contrary, As was detected at reasonably high concentrations in the
soil, around 15-17 mg/kg (Table 4), which could raise concern for C. gayana. Although
different plant species may tolerate concentrations from 1 to 50 mg As/kg in the soil
(Mascher et al., 2002), rates of 10 mg As/kg may begin to impede plant growth
(ANZECC/ARMCANZ, 2000) by inhibiting root proliferation and biomass accumulation
(Finnegan and Chen, 2012), as well as reducing photosynthetic efficiency and chlorophyll
biosynthesis (Sharma, 2012). At higher concentrations, As will interfere with critical
metabolic processes which can lead to various physiological and structural disorders
including death (Burló et al., 1999, Azizur Rahman et al., 2007, Finnegan and Chen, 2012).
Since As usually interferes with P metabolism (Gomes et al., 2012), adequate P in the soil
is important.
Chromium concentrations in the soil were significantly higher after 15 months
(300-350 mg/kg) despite a lack of consistency with previous sampling times – i.e., 70%
higher than the mean concentration 3 months prior (~200 mg/kg; Figure 27). In
comparison, mean leaf tissue concentrations in December (~4.8 mg Cr/kg) were at least
15 times higher than in September (~0.3 mg Cr/kg; Figure 36), but analysis showed no
correlation between soil and leaf Cr concentrations (Table 17 and 18). The resulting
spike in leaf Cr concentration could be due to analytical error and should thus be verified
with March 2014 and subsequent sampling data.
Conversely, if subsequent monitoring confirms that leaf Cr concentrations were
high, it is likely that prevailing oxidative conditions (facilitated by Fe and Mn oxides from
irrigation water) and an increased soil pH caused Cr(VI) to predominate in the system
(Hooda, 2010). The extent of Cr accumulation and phytotoxicity will vary depending on
its oxidation state, with Cr(VI) highly toxic and more mobile than Cr(III) (Shanker et al.,
2005). Due to its greater solubility, Cr(VI) is more readily absorbed by plants which
causes Cr to bioaccumulate at higher concentrations (Hooda, 2010). There is, then, a
possibility that irrigation could have resulted in the increased mobility and availability
of Cr(VI) despite variation in the total Cr concentration in the soil solution. Toxicity limits
Investigating the impacts of groundwater on soil properties and pasture
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66
for Cr(VI) may range from 5 mg/kg to 500 mg/kg, while toxicity of Cr(III) may occur from
50 mg/kg to 5000 mg/kg, depending on the tolerance of plant species and soil type
(ANZECC/ARMCANZ, 2000). Should toxicity levels be verified, Cr could severely impair
photosynthetic and respiration processes, and the uptake of water and nutrients (Singh
et al., 2013). Based on the current leaf nutrient status of C. gayana, results suggest no
adverse impact from heavy metals and metalloids on plant growth.
4.3.2.1. IMPLICATIONS FOR FEED QUALITY
While it is important to ensure pastures and forage crops grow vigorously, it is
crucial that heavy metal and metalloid concentrations in the harvested forage hay are
maintained under maximum tolerable levels for livestock. Toxicosis may arise in
ruminant livestock (e.g., cattle), and subsequently in humans, as a result of excessive
exposure to elements such as Al, As, B, Cu, Cd, Cr, Fe, Mn, Ni, Pb, and Zn (Underwood and
Suttle, 1999).
Table 16. Comparing December 2013 concentrations in leaf tissue of C. gayana with maximum
tolerable levels (National Research Council, 2000) and overall toxicity limits (Underwood and
Suttle, 1999) for ruminant livestock (e.g., such as cattle and sheep).
Concentration in leaf tissue
of C. gayana (mg/kg) Maximum tolerable level
(mg/kg) Toxicity limit (mg/kg)
Ess
enti
al e
lem
ents
Cu 7.3 100 > 50 (calves) > 900 (after weaning)
Fe 113 1000 > 1000
Mn 208 1000 > 1000 (pre-ruminant calves) > 2600 (after weaning)
Zn 32.4 500 > 500-700 (pre-ruminant calves)
Occ
asio
nal
ly
ben
efic
ial B 8.1 > 10-100
Cr 4.6 1000 > 1000
Ni 2.0 50 > 50 (as NiCl3) > 250 (as NiCO3)
Po
ten
tial
ly t
oxi
c Al 31.5 1000 > 2000 (lambs)
As 0.08 50 (100 mg/kg for organic
forms)
Cd 0.03 0.5 > 50
Pb 0.09 30 > 2000
The maximum tolerable concentration for a mineral has been defined as the “dietary level that, when fed for a limited period, will not impair animal performance and should not produce unsafe residues in human food derived from the animal" (National Research Council, 2000).
Investigating the impacts of groundwater on soil properties and pasture
nutrition
67
To date, results show their overall mean concentrations were relatively low in
leaf tissue and well below the established maximum tolerable levels (National Research
Council, 2000; Table 16). Therefore, the current concentration of heavy metals and
metalloids should not adversely affect the feed quality of C. gayana.
4.3.3. VOLATILISATION OF NITROGEN FERTILISERS
It is well known that substantial amounts of N applied as urea to moist alkaline
soils under warm conditions can be lost via volatilisation of NH3 gas (Ryan et al., 1981,
Marlet et al., 1998). This may affect the efficiency of N use, particularly as soils become
more alkaline over time. The implications of this loss pathway are not explored in this
thesis, but are an area for future investigation, particularly in regards to the optimum
rates of N fertilizer required to maintain crop growth.
4.4. MANAGEMENT IMPLICATIONS
In the future, alkalinisation could emerge as an important issue for the HAP
whereby soil pH may increase to levels that can compromise soil nutritional balance for
C. gayana. Additionally, given suitable conditions for nucleation, the precipitation of
carbonate and (hydr)oxide minerals of Ca, Mg, Fe and Mn, as well as phosphate as apatite
may further reduce the bioavailability of nutrients in the soil, including other
micronutrients such as B, Cu, Fe, Mn, Ni and Zn due mainly to enhanced (co-
)precipitation and surface adsorption reactions. It is, therefore, important that irrigation
water and soil quality is managed effectively to alleviate or mitigate adverse impact(s)
on the long-term sustainability of pasture production, keeping in mind the fate of the site
after decommissioning (e.g., site rehabilitation).
A number of strategies could be assessed and trialled to determine an
appropriate treatment regime for HAP. This primarily includes the neutralisation of
excess alkalinity in irrigation water and/or in the soil, such that soil alkalinisation ceases
and soil pH can be maintained within an ideal range.
Excess alkalinity in irrigation water may be neutralised by injecting equivalent
quantities of sulphuric acid to the bulk solution before irrigation (Kidder and Hanlon,
1998). Applying elemental sulphur (Spiers and Braswell, 1992) and/or ammonium
sulphate fertiliser will also help lower the pH (Gearhart and Collamer, 2009). To prevent
mineral precipitation from occurring in irrigation water or the soil, the pH of the
Investigating the impacts of groundwater on soil properties and pasture
nutrition
68
fertigation solution should be adjusted ≤ 7.0 (Table 11) to ensure calcite and dolomite,
and Mn minerals, remain undersaturated in irrigation water. Note that Fe minerals and
hydroxyapatite will still remain oversaturated in the fertigation solution; however, P
availability may be corrected by addition of more P directly to the soil as granular
fertiliser (Scientific Staff of the International Plant Nutrition Institute, 2010).
In the same way that gypsum helps to improve soil flocculation (e.g., by
increasing the ionic strength of the soil solution and displacing exchangeable Na by Ca;
Sumner, 1993), resulting increases in SO42- and Ca2+ concentration after sulphuric acid
injection could also help reduce the risk of dispersion developing in the soil. Sulphuric
acid has been recognised as an effective agent for reclaiming sodic soils by releasing
soluble Ca2+ from free lime (Abrol et al., 1988).
Given that irrigation water per se already contains Ca2+ and Mg2+, this may also
be sufficient to prevent excessive dispersion should sodicity continue to rise in the long-
term – i.e., the system reaches equilibrium at a moderate but not harmful ESP. However,
further study should be undertaken to confirm this based on laboratory tests using
columns leached continuously with Ca-/Mg-rich water. The Hydrus model, a public
domain Windows-based modelling environment (Šimůnek et al., 2008), may also be used
to predict long term changes in cation retention and leaching. Moreover, soil properties
should be monitored for hydraulic conductivity and the Emerson aggregate test
(Emerson, 1967) conducted periodically to identify any potential problems with clay
dispersion. This can be done both on existing, retained soil samples, and future samples.
After neutralising excess irrigation alkalinity, ongoing monitoring should
examine consequential changes in: (1) soil pH, (2) exchangeable cations, and (3) nutrient
availability. This will determine if further treatment with gypsum is required to manage
sodicity. In cases of extreme sodicity, occasional deep cultivation with gypsum will
further improve water penetration and aeration (Hughes, 1999).
4.4.1. OTHER IRRIGATION PROJECTS IN THE REGION
Another irrigation project commencing in the Pilbara region is the Nammuldi-
Silvergrass Agricultural Project that utilises surplus water from the Nammuldi-
Silvergrass Rio Tinto Iron Ore Project (Rio Tinto Iron Ore, 2012). As the composition of
source water is relatively similar to that at Marandoo (e.g., Crisalis International Pty Ltd,
2012), this study should provide useful insights into the potential implications of
irrigation for long-term pasture production and soil management.
Investigating the impacts of groundwater on soil properties and pasture
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69
4.4.2. REHABILITATION AFTER DECOMMISSIONING
Following the cessation of below-watertable mining at Marandoo, the HAP will
undergo decommissioning and the disturbed land will require rehabilitation. Where
practicable, some areas will also be progressively rehabilitated as they are no longer
needed (Hamersley Iron Pty Ltd, 2011). Thus, it is imperative that current irrigation and
soil management practices, over the next 20 years, maintain conditions suitable for
restoring local provenance plant species. In the future, substantial changes in soil
properties may warrant research on the implications for rehabilitation.
Investigating the impacts of groundwater on soil properties and pasture
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5. CONCLUSION
The continuous irrigation of slightly alkaline and slightly brackish-sodic
groundwater at the HAP has caused significant changes to soil properties over 15
months. Although C. gayana was not adversely affected at this stage, irrigation is planned
to continue for the next 20 years, based on the life of the MMP2 project. While subsequent
analysis has shown that irrigation has not caused a measurable change in sodicity,
alkalinisation could however emerge as a problem by reducing the availability of various
nutrients under alkaline soil pH. Moreover, given suitable conditions for nucleation and
crystal growth, the precipitation of Ca and Mg carbonates, iron oxides and phosphorus
as apatite, may occur which could further immobilise plant nutrients. However, further
investigation is required to determine specifically the effect of mineral precipitation on
trace element mobility.
As the current rate of alkalinisation is relatively slow in the subsoil, nutrient
deficiencies should not occur rapidly and, due to limited solubility of Ca and Mg
carbonates, soil pH is unlikely to exceed ~8.2. Despite initial reports of high ESP levels
(> 5-7 %), a follow-up study suggested there was no significant change in the ESP and
hence no imminent risk of soil sodicity. It is therefore recommended that the
determination of ESP in soils samples in the future should be carried out by employing
methods that include pre-treatment for soluble salts to avoid overestimating the Na
concentration in the cation exchange complex. While the critical threshold value for
dispersion in these soils has not been determined, examining changes in hydraulic
conductivity and clay dispersion along with routine monitoring and field tests (e.g. the
Emerson aggregate test) may provide additional information.
Increases in soil pH may occur less gradually through time as the system reaches
equilibrium. But, to ensure that thresholds are not exceeded, the pH of the irrigation
water can be corrected to ≤ 7. Various methods, such as sulphuric acid injection or
applying elemental sulphur or ammonium sulphate fertiliser, may be used to neutralise
excess alkalinity. This may also help prevent mineral precipitation and arrest
alkalinisation, while also increasing SO42- and Ca+ concentrations that could counteract
sodicity by increasing the ionic strength of the soil solution and displacing exchangeable
Na+ by Ca2+.
In relation to in-stream discharge, similar physicochemical changes to the soil
could also occur and have significant implications for stream and riparian vegetation. In
Investigating the impacts of groundwater on soil properties and pasture
nutrition
71
particular, the uncontrolled and undisturbed accumulation of insoluble carbonates from
continuous discharge may have a greater potential for cementation in the creek-bed (e.g.,
as in the case at Weeli Wolli Creek; Wetland Research & Management, 2010, Crisalis
International Pty Ltd, 2012) than in irrigated soil. Therefore, as in-stream discharge
becomes increasingly practiced, this could become an important area of research.
Investigating the impacts of groundwater on soil properties and pasture
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APPENDIX A: CORRELATION ANALYSIS
SOIL PROPERTIES AND LEAF NUTRIENT COMPOSITION
Table 17. Correlation (R2) between leaf nutrient composition and soil properties at 0-10 cm, using only Span 3 data from March to December 2013
Leaf nutrients and trace elements Total N NO3-N P K Ca Mg Na Cl S Cu Fe Mn Zn B Al As Cd Cr Pb Ni
Soil
pro
per
ties
EC 0.01 0.08 0.00 0.00 0.17 0.00 0.04 0.00 0.01 0.00 0.01 0.01 0.06 0.02 0.00 0.05 0.09 0.04 0.00 0.00 pHCa 0.00 0.07 0.05 0.01 0.11 0.19 0.02 0.00 0.22 0.00 0.00 0.02 0.04 0.34 0.03 0.00 0.01 0.23 0.23 0.15
CCE 0.03 0.03 0.07 0.06 0.06 0.03 0.03 0.23 0.00 0.02 0.30 0.06 0.12 0.02 0.05 0.10 0.07 0.00 0.04 0.02 OC 0.00 0.00 0.00 0.01 0.19 0.04 0.00 0.02 0.04 0.01 0.00 0.01 0.00 0.11 0.02 0.00 0.04 0.01 0.01 0.05 NO3-N 0.07 0.09 0.02 0.04 0.12 0.07 0.09 0.11 0.07 0.00 0.00 0.06 0.02 0.14 0.01 0.17 0.01 0.00 0.10 0.27 NH4-N 0.05 0.03 0.00 0.08 0.03 0.04 0.02 0.07 0.05 0.01 0.00 0.02 0.07 0.01 0.00 0.05 0.00 0.07 0.04 0.01 Total N 0.03 0.09 0.04 0.05 0.06 0.00 0.04 0.13 0.06 0.00 0.00 0.04 0.08 0.04 0.00 0.09 0.07 0.37 0.03 0.01 C/N 0.03 0.06 0.02 0.03 0.01 0.02 0.03 0.06 0.15 0.01 0.01 0.02 0.13 0.17 0.02 0.06 0.01 0.32 0.07 0.01 Colwell P 0.06 0.01 0.10 0.02 0.04 0.07 0.12 0.01 0.00 0.05 0.04 0.01 0.22 0.00 0.05 0.00 0.04 0.07 0.06 0.17 Total P 0.01 0.06 0.10 0.00 0.03 0.06 0.06 0.03 0.09 0.00 0.02 0.03 0.07 0.01 0.00 0.00 0.32 0.05 0.06 0.05 PRI 0.08 0.11 0.03 0.03 0.01 0.01 0.08 0.04 0.01 0.05 0.03 0.05 0.00 0.02 0.01 0.03 0.16 0.02 0.06 0.08 Colwell K 0.03 0.01 0.06 0.03 0.00 0.02 0.00 0.01 0.00 0.19 0.14 0.13 0.13 0.03 0.05 0.02 0.16 0.04 0.00 0.02 Total K 0.03 0.03 0.00 0.00 0.18 0.01 0.01 0.00 0.04 0.10 0.02 0.00 0.02 0.05 0.14 0.01 0.10 0.00 0.02 0.13 Ex. Ca 0.02 0.09 0.02 0.00 0.02 0.10 0.00 0.01 0.02 0.07 0.00 0.00 0.01 0.06 0.01 0.00 0.11 0.14 0.16 0.03 Ex. Mg 0.04 0.23 0.04 0.03 0.00 0.20 0.01 0.00 0.07 0.02 0.01 0.01 0.07 0.20 0.00 0.00 0.11 0.32 0.32 0.11 Ex. Na 0.05 0.21 0.00 0.01 0.06 0.05 0.07 0.00 0.01 0.00 0.00 0.00 0.14 0.02 0.00 0.03 0.13 0.15 0.11 0.05 Ex. K 0.04 0.04 0.05 0.02 0.01 0.01 0.00 0.00 0.00 0.17 0.09 0.09 0.08 0.03 0.05 0.00 0.16 0.05 0.01 0.02 Ex. Al 0.00 0.00 0.15 0.00 0.03 0.00 0.09 0.03 0.00 0.26 0.27 0.00 0.19 0.03 0.24 0.00 0.08 0.25 0.07 0.08 ECEC 0.04 0.17 0.03 0.01 0.01 0.14 0.01 0.00 0.04 0.05 0.01 0.01 0.03 0.11 0.01 0.00 0.14 0.22 0.22 0.06 Ca % 0.03 0.14 0.01 0.09 0.08 0.06 0.04 0.09 0.03 0.02 0.00 0.06 0.06 0.09 0.00 0.02 0.01 0.06 0.04 0.06 Mg % 0.02 0.22 0.02 0.08 0.13 0.20 0.02 0.05 0.11 0.02 0.00 0.03 0.13 0.28 0.01 0.01 0.01 0.22 0.27 0.20 ESP 0.04 0.09 0.01 0.01 0.07 0.00 0.09 0.00 0.00 0.01 0.02 0.01 0.14 0.01 0.00 0.08 0.01 0.02 0.00 0.02 K % 0.01 0.08 0.01 0.00 0.00 0.12 0.04 0.00 0.05 0.04 0.10 0.07 0.33 0.05 0.05 0.01 0.00 0.09 0.20 0.23 Al % 0.02 0.06 0.14 0.00 0.04 0.02 0.03 0.02 0.01 0.26 0.17 0.00 0.07 0.09 0.16 0.00 0.13 0.28 0.19 0.01 As 0.17 0.26 0.02 0.04 0.22 0.00 0.08 0.00 0.09 0.10 0.05 0.06 0.01 0.02 0.02 0.01 0.00 0.01 0.02 0.00 Cd 0.20 0.11 0.06 0.13 0.01 0.01 0.18 0.14 0.10 0.00 0.10 0.00 0.00 0.05 0.08 0.02 0.11 0.19 0.00 0.02 Cr 0.03 0.00 0.02 0.04 0.00 0.00 0.20 0.24 0.06 0.01 0.05 0.00 0.01 0.15 0.09 0.11 0.03 0.47 0.10 0.03 Pb 0.07 0.01 0.02 0.07 0.17 0.09 0.08 0.11 0.00 0.02 0.00 0.14 0.00 0.00 0.07 0.06 0.00 0.04 0.00 0.03
Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).
Table 18. Correlation (R2) between leaf nutrient composition and soil properties at 20-30 cm, using only Span 3 data from March to December 2013
Leaf nutrients and trace elements Total N NO3-N P K Ca Mg Na Cl S Cu Fe Mn Zn B Al As Cd Cr Pb Ni
Soil
pro
per
ties
EC 0.00 0.09 0.17 0.00 0.00 0.12 0.01 0.01 0.10 0.03 0.10 0.02 0.06 0.16 0.02 0.02 0.31 0.51 0.13 0.02 pHCa 0.00 0.00 0.02 0.00 0.07 0.06 0.00 0.00 0.03 0.01 0.06 0.00 0.03 0.01 0.17 0.00 0.02 0.00 0.00 0.03 CCE 0.00 0.02 0.10 0.04 0.04 0.00 0.04 0.20 0.01 0.00 0.17 0.03 0.03 0.02 0.01 0.21 0.06 0.01 0.02 0.05 OC 0.00 0.11 0.04 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.01 0.02 0.03 0.08 0.01 0.07 0.03 0.33 0.12 0.03 NO3-N 0.12 0.14 0.03 0.02 0.01 0.15 0.06 0.08 0.08 0.00 0.00 0.02 0.08 0.10 0.01 0.00 0.06 0.05 0.09 0.20 NH4-N 0.00 0.04 0.01 0.03 0.09 0.00 0.00 0.06 0.02 0.03 0.09 0.12 0.25 0.00 0.00 0.07 0.00 0.02 0.02 0.03 Total N 0.13 0.00 0.00 0.11 0.09 0.03 0.11 0.19 0.00 0.00 0.01 0.03 0.00 0.00 0.03 0.15 0.00 0.11 0.01 0.27 C/N 0.09 0.04 0.01 0.06 0.06 0.01 0.07 0.15 0.02 0.02 0.01 0.07 0.04 0.02 0.01 0.24 0.01 0.30 0.02 0.06 Colwell P 0.00 0.08 0.00 0.01 0.06 0.22 0.00 0.03 0.23 0.07 0.05 0.00 0.42 0.22 0.12 0.05 0.02 0.15 0.29 0.28 Total P 0.04 0.06 0.04 0.00 0.04 0.02 0.08 0.04 0.06 0.00 0.01 0.06 0.06 0.01 0.02 0.03 0.20 0.00 0.05 0.06 PRI 0.00 0.07 0.06 0.00 0.01 0.00 0.01 0.01 0.01 0.02 0.01 0.09 0.01 0.01 0.00 0.01 0.11 0.03 0.00 0.00 Colwell K 0.04 0.05 0.07 0.08 0.00 0.01 0.01 0.05 0.01 0.21 0.29 0.17 0.13 0.02 0.20 0.05 0.26 0.03 0.02 0.01 Total K 0.02 0.00 0.02 0.00 0.34 0.12 0.01 0.03 0.14 0.12 0.01 0.05 0.03 0.15 0.06 0.00 0.00 0.01 0.08 0.09 Ex. Ca 0.01 0.04 0.03 0.00 0.00 0.12 0.00 0.00 0.03 0.02 0.03 0.01 0.04 0.04 0.01 0.01 0.24 0.11 0.08 0.01 Ex. Mg 0.07 0.24 0.00 0.04 0.01 0.13 0.04 0.01 0.02 0.02 0.01 0.02 0.07 0.08 0.00 0.01 0.09 0.11 0.14 0.04 Ex. Na 0.01 0.18 0.12 0.01 0.02 0.14 0.00 0.00 0.11 0.05 0.10 0.03 0.04 0.23 0.02 0.02 0.29 0.55 0.23 0.08 Ex. K 0.06 0.07 0.03 0.03 0.01 0.00 0.01 0.01 0.02 0.23 0.17 0.08 0.06 0.00 0.22 0.00 0.23 0.04 0.01 0.04 Ex. Al 0.00 0.03 0.06 0.00 0.00 0.00 0.04 0.02 0.01 0.19 0.06 0.00 0.07 0.00 0.02 0.00 0.03 0.14 0.00 0.10 ECEC 0.03 0.11 0.03 0.00 0.00 0.13 0.01 0.00 0.03 0.04 0.04 0.03 0.05 0.07 0.02 0.01 0.25 0.15 0.12 0.02 Ca % 0.02 0.11 0.01 0.11 0.04 0.00 0.02 0.04 0.00 0.00 0.00 0.02 0.00 0.02 0.00 0.00 0.03 0.00 0.01 0.02 Mg % 0.03 0.14 0.04 0.06 0.04 0.01 0.04 0.03 0.00 0.01 0.03 0.00 0.04 0.01 0.02 0.00 0.06 0.00 0.01 0.03 ESP 0.00 0.16 0.10 0.01 0.05 0.07 0.02 0.00 0.13 0.03 0.07 0.02 0.02 0.27 0.00 0.00 0.13 0.52 0.20 0.13 K % 0.00 0.01 0.00 0.03 0.04 0.19 0.00 0.00 0.22 0.17 0.11 0.01 0.43 0.09 0.22 0.02 0.00 0.07 0.13 0.27 Al % 0.01 0.09 0.07 0.00 0.00 0.00 0.01 0.01 0.00 0.20 0.06 0.00 0.02 0.02 0.02 0.00 0.11 0.18 0.02 0.03 As 0.03 0.13 0.01 0.00 0.12 0.03 0.02 0.00 0.00 0.00 0.06 0.03 0.10 0.00 0.00 0.03 0.01 0.08 0.07 0.03 Cd 0.10 0.14 0.03 0.10 0.00 0.03 0.12 0.11 0.01 0.01 0.09 0.01 0.02 0.00 0.03 0.00 0.09 0.04 0.01 0.12 Cr 0.07 0.00 0.09 0.06 0.00 0.00 0.14 0.21 0.06 0.01 0.08 0.01 0.01 0.10 0.07 0.07 0.04 0.41 0.04 0.01 Pb 0.00 0.00 0.01 0.00 0.00 0.01 0.06 0.01 0.00 0.10 0.00 0.05 0.02 0.00 0.02 0.01 0.00 0.19 0.00 0.00
Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).
LEAF NUTRIENT COMPOSITION
Table 19. Correlation (R2) between leaf composition, using only Span 3 data from March to December 2013
Total N P K Ca Mg Na Cl S Cu Fe Mn Zn B NO3-N Al As Cd Cr Pb Ni
Total N 1.00 0.08 0.53 0.01 0.00 0.45 0.18 0.18 0.47 0.13 0.13 0.00 0.03 0.67 0.06 0.19 0.16 0.01 0.00 0.18
P 0.08 1.00 0.18 0.01 0.01 0.20 0.02 0.44 0.01 0.03 0.00 0.00 0.23 0.00 0.02 0.04 0.16 0.24 0.09 0.01
K 0.53 0.18 1.00 0.12 0.02 0.56 0.46 0.24 0.26 0.00 0.00 0.02 0.01 0.35 0.00 0.08 0.07 0.01 0.01 0.10
Ca 0.01 0.01 0.12 1.00 0.18 0.06 0.28 0.08 0.03 0.12 0.12 0.00 0.18 0.00 0.02 0.03 0.00 0.00 0.02 0.18
Mg 0.00 0.01 0.02 0.18 1.00 0.02 0.03 0.09 0.02 0.03 0.22 0.21 0.22 0.00 0.00 0.05 0.06 0.05 0.14 0.10
Na 0.45 0.20 0.56 0.06 0.02 1.00 0.60 0.16 0.04 0.01 0.01 0.02 0.10 0.25 0.00 0.10 0.03 0.14 0.00 0.12
Cl 0.18 0.02 0.46 0.28 0.03 0.60 1.00 0.01 0.00 0.03 0.03 0.01 0.00 0.07 0.00 0.17 0.00 0.11 0.00 0.14
S 0.18 0.44 0.24 0.08 0.09 0.16 0.01 1.00 0.28 0.03 0.04 0.14 0.48 0.03 0.01 0.00 0.11 0.14 0.22 0.15
Cu 0.47 0.01 0.26 0.03 0.02 0.04 0.00 0.28 1.00 0.02 0.09 0.17 0.05 0.33 0.00 0.04 0.02 0.04 0.00 0.00
Fe 0.13 0.03 0.00 0.12 0.03 0.01 0.03 0.03 0.02 1.00 0.35 0.17 0.15 0.14 0.70 0.07 0.35 0.04 0.07 0.07
Mn 0.13 0.00 0.00 0.12 0.22 0.01 0.03 0.04 0.09 0.35 1.00 0.01 0.17 0.25 0.19 0.22 0.37 0.00 0.00 0.03
Zn 0.00 0.00 0.02 0.00 0.21 0.02 0.01 0.14 0.17 0.17 0.01 1.00 0.05 0.04 0.17 0.01 0.02 0.03 0.02 0.12
B 0.03 0.23 0.01 0.18 0.22 0.10 0.00 0.48 0.05 0.15 0.17 0.05 1.00 0.00 0.03 0.00 0.07 0.30 0.35 0.11
NO3-N 0.67 0.00 0.35 0.00 0.00 0.25 0.07 0.03 0.33 0.14 0.25 0.04 0.00 1.00 0.10 0.16 0.13 0.05 0.02 0.20
Al 0.06 0.02 0.00 0.02 0.00 0.00 0.00 0.01 0.00 0.70 0.19 0.17 0.03 0.10 1.00 0.10 0.15 0.00 0.03 0.13
As 0.19 0.04 0.08 0.03 0.05 0.10 0.17 0.00 0.04 0.07 0.22 0.01 0.00 0.16 0.10 1.00 0.11 0.04 0.03 0.35
Cd 0.16 0.16 0.07 0.00 0.06 0.03 0.00 0.11 0.02 0.35 0.37 0.02 0.07 0.13 0.15 0.11 1.00 0.08 0.02 0.05
Cr 0.01 0.24 0.01 0.00 0.05 0.14 0.11 0.14 0.04 0.04 0.00 0.03 0.30 0.05 0.00 0.04 0.08 1.00 0.18 0.00
Pb 0.00 0.09 0.01 0.02 0.14 0.00 0.00 0.22 0.00 0.07 0.00 0.02 0.35 0.02 0.03 0.03 0.02 0.18 1.00 0.18
Ni 0.18 0.01 0.10 0.18 0.10 0.12 0.14 0.15 0.00 0.07 0.03 0.12 0.11 0.20 0.13 0.35 0.05 0.00 0.18 1.00 Strength of relationship: 0.80 to 0.99 (very strong); 0.60 to 0.79 (strong); 0.40 to 0.59 (moderate); 0.20 to 0.39 (weak); and 0.00 to 0.19 (very weak). All moderate to very strong correlations are significant at the 0.01 level (2-tailed).
93
APPENDIX B: WEB-PHREEQ OUTPUT DATA
DEWATERING SURPLUS
TITLE Dewatering surplus (December 2013)
SOLUTION 1
pH 8.2
temp 29.5
pe
units mg/L
Alkalinity 240
Al 0.01
B 0.3
Cd 0.0005
Ca 61
C 270 as HCO3
Cl 120
Cu 0.016
Fe 0.01
Pb 0.01
Mg 50
Mn 0.007
N 0.36
P 0.01
K 13
Na 42
S 76 as SO4-2
Zn 0.08
END
-----
TITLE
-----
Dewatering surplus (December 2013)
-------------------------------------------
Beginning of initial solution calculations.
-------------------------------------------
Initial solution 1.
pH will be adjusted to obtain desired alkalinity.
-----------------------------Solution composition------------------------------
Elements Molality Moles
Al 3.709e-07 3.709e-07
Alkalinity 4.800e-03 4.800e-03
B 2.778e-05 2.778e-05
C 4.429e-03 4.429e-03
Ca 1.523e-03 1.523e-03
Cd 4.452e-09 4.452e-09
Cl 3.388e-03 3.388e-03
Cu 2.520e-07 2.520e-07
Fe 1.792e-07 1.792e-07
K 3.328e-04 3.328e-04
Mg 2.058e-03 2.058e-03
Mn 1.275e-07 1.275e-07
N 2.572e-05 2.572e-05
Na 1.828e-03 1.828e-03
P 3.231e-07 3.231e-07
Pb 4.831e-08 4.831e-08
S 7.918e-04 7.918e-04
Zn 1.225e-06 1.225e-06
----------------------------Description of solution----------------------------
pH = 8.672 Adjust alkalinity
pe = 8.200
Activity of water = 1.000
Ionic strength = 1.241e-02
Investigating the impacts of groundwater on soil properties and pasture
nutrition
94
Mass of water (kg) = 1.000e+00
Total CO2 (mol/kg) = 4.429e-03
Temperature (deg C) = 29.500
Electrical balance (eq) = -4.423e-04
Percent error, 100*(Cat-|An|)/(Cat+|An|) = -2.57
Iterations = 10
Total H = 1.110166e+02
Total O = 5.552275e+01
----------------------------Distribution of species----------------------------
Log Log Log
Species Molality Activity Molality Activity Gamma
OH- 7.370e-06 6.558e-06 -5.133 -5.183 -0.051
H+ 2.350e-09 2.128e-09 -8.629 -8.672 -0.043
H2O 5.551e+01 9.998e-01 -0.000 -0.000 0.000
Al 3.709e-07
Al(OH)4- 3.706e-07 3.306e-07 -6.431 -6.481 -0.050
Al(OH)3 3.482e-10 3.492e-10 -9.458 -9.457 0.001
Al(OH)2+ 4.103e-12 3.661e-12 -11.387 -11.436 -0.050
AlOH+2 1.071e-15 6.784e-16 -14.970 -15.168 -0.198
Al+3 2.652e-19 1.088e-19 -18.576 -18.963 -0.387
AlSO4+ 1.578e-19 1.408e-19 -18.802 -18.851 -0.050
Al(SO4)2- 1.969e-21 1.757e-21 -20.706 -20.755 -0.050
AlHSO4+2 4.376e-29 2.773e-29 -28.359 -28.557 -0.198
B 2.778e-05
H3BO3 2.089e-05 2.095e-05 -4.680 -4.679 0.001
H2BO3- 6.885e-06 6.143e-06 -5.162 -5.212 -0.050
C(-4) 0.000e+00
CH4 0.000e+00 0.000e+00 -115.987 -115.986 0.001
C(4) 4.429e-03
HCO3- 3.944e-03 3.533e-03 -2.404 -2.452 -0.048
CO3-2 1.316e-04 8.481e-05 -3.881 -4.072 -0.191
CaCO3 1.293e-04 1.297e-04 -3.888 -3.887 0.001
MgCO3 1.000e-04 1.003e-04 -4.000 -3.999 0.001
MgHCO3+ 5.480e-05 4.889e-05 -4.261 -4.311 -0.050
CaHCO3+ 4.424e-05 3.964e-05 -4.354 -4.402 -0.048
CO2 1.604e-05 1.609e-05 -4.795 -4.793 0.001
NaCO3- 3.596e-06 3.208e-06 -5.444 -5.494 -0.050
NaHCO3 3.218e-06 3.227e-06 -5.492 -5.491 0.001
Zn(CO3)2-2 8.349e-07 5.290e-07 -6.078 -6.277 -0.198
ZnCO3 2.909e-07 2.917e-07 -6.536 -6.535 0.001
MnCO3 9.826e-08 9.854e-08 -7.008 -7.006 0.001
PbCO3 3.582e-08 3.592e-08 -7.446 -7.445 0.001
Pb(CO3)2-2 1.208e-08 7.652e-09 -7.918 -8.116 -0.198
ZnHCO3+ 8.595e-09 7.669e-09 -8.066 -8.115 -0.050
MnHCO3+ 5.163e-09 4.606e-09 -8.287 -8.337 -0.050
CdHCO3+ 2.417e-10 2.156e-10 -9.617 -9.666 -0.050
CdCO3 1.296e-10 1.300e-10 -9.887 -9.886 0.001
PbHCO3+ 7.666e-11 6.840e-11 -10.115 -10.165 -0.050
Cd(CO3)2-2 5.502e-11 3.487e-11 -10.259 -10.458 -0.198
FeCO3 2.232e-16 2.238e-16 -15.651 -15.650 0.001
FeHCO3+ 4.357e-17 3.887e-17 -16.361 -16.410 -0.050
Ca 1.523e-03
Ca+2 1.283e-03 8.262e-04 -2.892 -3.083 -0.191
CaCO3 1.293e-04 1.297e-04 -3.888 -3.887 0.001
CaSO4 6.622e-05 6.641e-05 -4.179 -4.178 0.001
CaHCO3+ 4.424e-05 3.964e-05 -4.354 -4.402 -0.048
CaOH+ 7.220e-08 6.442e-08 -7.141 -7.191 -0.050
CaPO4- 4.332e-08 3.865e-08 -7.363 -7.413 -0.050
CaHPO4 3.188e-08 3.197e-08 -7.496 -7.495 0.001
CaH2PO4+ 5.606e-11 5.001e-11 -10.251 -10.301 -0.050
CaHSO4+ 9.839e-13 8.778e-13 -12.007 -12.057 -0.050
Cd 4.452e-09
Cd+2 3.045e-09 1.930e-09 -8.516 -8.715 -0.198
CdCl+ 6.322e-10 5.641e-10 -9.199 -9.249 -0.050
CdHCO3+ 2.417e-10 2.156e-10 -9.617 -9.666 -0.050
CdSO4 2.204e-10 2.210e-10 -9.657 -9.656 0.001
CdCO3 1.296e-10 1.300e-10 -9.887 -9.886 0.001
CdOH+ 1.174e-10 1.048e-10 -9.930 -9.980 -0.050
Cd(CO3)2-2 5.502e-11 3.487e-11 -10.259 -10.458 -0.198
CdCl2 7.188e-12 7.208e-12 -11.143 -11.142 0.001
Cd(OH)2 1.897e-12 1.902e-12 -11.722 -11.721 0.001
Cd(SO4)2-2 1.439e-12 9.115e-13 -11.842 -12.040 -0.198
Investigating the impacts of groundwater on soil properties and pasture
nutrition
95
CdCl3- 1.644e-14 1.466e-14 -13.784 -13.834 -0.050
Cd(OH)3- 1.124e-16 1.003e-16 -15.949 -15.999 -0.050
Cd(OH)4-2 6.627e-22 4.199e-22 -21.179 -21.377 -0.198
Cl 3.388e-03
Cl- 3.388e-03 3.016e-03 -2.470 -2.521 -0.050
CdCl+ 6.322e-10 5.641e-10 -9.199 -9.249 -0.050
MnCl+ 2.014e-10 1.797e-10 -9.696 -9.745 -0.050
ZnCl+ 1.907e-10 1.702e-10 -9.720 -9.769 -0.050
CdCl2 7.188e-12 7.208e-12 -11.143 -11.142 0.001
PbCl+ 3.661e-12 3.266e-12 -11.436 -11.486 -0.050
ZnCl2 5.455e-13 5.470e-13 -12.263 -12.262 0.001
MnCl2 2.359e-13 2.366e-13 -12.627 -12.626 0.001
CdCl3- 1.644e-14 1.466e-14 -13.784 -13.834 -0.050
PbCl2 1.433e-14 1.437e-14 -13.844 -13.843 0.001
ZnCl3- 2.131e-15 1.901e-15 -14.671 -14.721 -0.050
MnCl3- 2.203e-16 1.965e-16 -15.657 -15.707 -0.050
PbCl3- 3.965e-17 3.538e-17 -16.402 -16.451 -0.050
ZnCl4-2 4.697e-18 2.976e-18 -17.328 -17.526 -0.198
FeCl+ 5.134e-19 4.580e-19 -18.290 -18.339 -0.050
PbCl4-2 8.340e-20 5.284e-20 -19.079 -19.277 -0.198
FeCl+2 3.512e-22 2.225e-22 -21.454 -21.653 -0.198
FeCl2+ 2.920e-24 2.605e-24 -23.535 -23.584 -0.050
FeCl3 7.834e-28 7.856e-28 -27.106 -27.105 0.001
Cu(1) 2.131e-16
Cu+ 2.131e-16 1.889e-16 -15.671 -15.724 -0.052
Cu(2) 2.520e-07
Cu(OH)2 2.516e-07 2.523e-07 -6.599 -6.598 0.001
CuOH+ 2.884e-10 2.571e-10 -9.540 -9.590 -0.050
Cu+2 8.427e-11 5.472e-11 -10.074 -10.262 -0.187
Cu(OH)3- 8.006e-12 7.143e-12 -11.097 -11.146 -0.050
CuSO4 4.440e-12 4.452e-12 -11.353 -11.351 0.001
Cu(OH)4-2 1.057e-15 6.696e-16 -14.976 -15.174 -0.198
Fe(2) 4.704e-16
FeCO3 2.232e-16 2.238e-16 -15.651 -15.650 0.001
Fe+2 1.694e-16 1.100e-16 -15.771 -15.959 -0.187
FeHCO3+ 4.357e-17 3.887e-17 -16.361 -16.410 -0.050
FeOH+ 2.551e-17 2.276e-17 -16.593 -16.643 -0.050
FeSO4 8.177e-18 8.200e-18 -17.087 -17.086 0.001
FeCl+ 5.134e-19 4.580e-19 -18.290 -18.339 -0.050
FeHPO4 2.838e-20 2.846e-20 -19.547 -19.546 0.001
FeH2PO4+ 1.343e-22 1.198e-22 -21.872 -21.922 -0.050
FeHSO4+ 1.310e-25 1.169e-25 -24.883 -24.932 -0.050
Fe(HS)2 0.000e+00 0.000e+00 -235.142 -235.141 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -347.120 -347.170 -0.050
Fe(3) 1.792e-07
Fe(OH)3 1.127e-07 1.130e-07 -6.948 -6.947 0.001
Fe(OH)4- 6.484e-08 5.785e-08 -7.188 -7.238 -0.050
Fe(OH)2+ 1.725e-09 1.539e-09 -8.763 -8.813 -0.050
FeOH+2 1.319e-14 8.360e-15 -13.880 -14.078 -0.198
FeSO4+ 1.112e-20 9.925e-21 -19.954 -20.003 -0.050
Fe+3 5.175e-21 2.123e-21 -20.286 -20.673 -0.387
FeCl+2 3.512e-22 2.225e-22 -21.454 -21.653 -0.198
Fe(SO4)2- 9.570e-23 8.539e-23 -22.019 -22.069 -0.050
FeHPO4+ 4.809e-23 4.290e-23 -22.318 -22.367 -0.050
FeCl2+ 2.920e-24 2.605e-24 -23.535 -23.584 -0.050
FeH2PO4+2 1.959e-24 1.241e-24 -23.708 -23.906 -0.198
Fe2(OH)2+4 9.717e-27 1.566e-27 -26.012 -26.805 -0.793
FeCl3 7.834e-28 7.856e-28 -27.106 -27.105 0.001
FeHSO4+2 8.942e-29 5.666e-29 -28.049 -28.247 -0.198
Fe3(OH)4+5 5.793e-33 3.345e-34 -32.237 -33.476 -1.238
H(0) 2.435e-37
H2 1.218e-37 1.221e-37 -36.914 -36.913 0.001
K 3.328e-04
K+ 3.318e-04 2.954e-04 -3.479 -3.530 -0.050
KSO4- 9.713e-07 8.666e-07 -6.013 -6.062 -0.050
KOH 4.798e-10 4.811e-10 -9.319 -9.318 0.001
KHPO4- 4.194e-11 3.742e-11 -10.377 -10.427 -0.050
Mg 2.058e-03
Mg+2 1.783e-03 1.157e-03 -2.749 -2.937 -0.188
MgSO4 1.172e-04 1.175e-04 -3.931 -3.930 0.001
MgCO3 1.000e-04 1.003e-04 -4.000 -3.999 0.001
MgHCO3+ 5.480e-05 4.889e-05 -4.261 -4.311 -0.050
MgOH+ 3.300e-06 2.945e-06 -5.481 -5.531 -0.050
MgPO4- 8.182e-08 7.300e-08 -7.087 -7.137 -0.050
MgHPO4 6.036e-08 6.053e-08 -7.219 -7.218 0.001
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MgH2PO4+ 9.996e-11 8.918e-11 -10.000 -10.050 -0.050
Mn(2) 1.275e-07
MnCO3 9.826e-08 9.854e-08 -7.008 -7.006 0.001
Mn+2 2.253e-08 1.463e-08 -7.647 -7.835 -0.187
MnHCO3+ 5.163e-09 4.606e-09 -8.287 -8.337 -0.050
MnSO4 1.091e-09 1.094e-09 -8.962 -8.961 0.001
MnOH+ 2.842e-10 2.535e-10 -9.546 -9.596 -0.050
MnCl+ 2.014e-10 1.797e-10 -9.696 -9.745 -0.050
MnCl2 2.359e-13 2.366e-13 -12.627 -12.626 0.001
MnCl3- 2.203e-16 1.965e-16 -15.657 -15.707 -0.050
Mn(NO3)2 1.801e-30 1.806e-30 -29.745 -29.743 0.001
Mn(3) 3.821e-25
Mn+3 3.821e-25 1.369e-25 -24.418 -24.864 -0.446
N(-3) 0.000e+00
NH4+ 0.000e+00 0.000e+00 -46.481 -46.534 -0.052
NH3 0.000e+00 0.000e+00 -46.971 -46.970 0.001
NH4SO4- 0.000e+00 0.000e+00 -48.787 -48.836 -0.050
N(0) 2.572e-05
N2 1.286e-05 1.290e-05 -4.891 -4.889 0.001
N(3) 1.408e-17
NO2- 1.408e-17 1.251e-17 -16.851 -16.903 -0.052
N(5) 6.302e-12
NO3- 6.302e-12 5.597e-12 -11.201 -11.252 -0.052
PbNO3+ 2.261e-21 2.017e-21 -20.646 -20.695 -0.050
Mn(NO3)2 1.801e-30 1.806e-30 -29.745 -29.743 0.001
Na 1.828e-03
Na+ 1.818e-03 1.624e-03 -2.740 -2.789 -0.049
NaSO4- 3.627e-06 3.236e-06 -5.440 -5.490 -0.050
NaCO3- 3.596e-06 3.208e-06 -5.444 -5.494 -0.050
NaHCO3 3.218e-06 3.227e-06 -5.492 -5.491 0.001
NaOH 5.027e-09 5.042e-09 -8.299 -8.297 0.001
NaHPO4- 2.307e-10 2.058e-10 -9.637 -9.687 -0.050
O(0) 1.502e-17
O2 7.510e-18 7.531e-18 -17.124 -17.123 0.001
P 3.231e-07
HPO4-2 1.029e-07 6.498e-08 -6.988 -7.187 -0.199
MgPO4- 8.182e-08 7.300e-08 -7.087 -7.137 -0.050
MgHPO4 6.036e-08 6.053e-08 -7.219 -7.218 0.001
CaPO4- 4.332e-08 3.865e-08 -7.363 -7.413 -0.050
CaHPO4 3.188e-08 3.197e-08 -7.496 -7.495 0.001
H2PO4- 2.432e-09 2.172e-09 -8.614 -8.663 -0.049
NaHPO4- 2.307e-10 2.058e-10 -9.637 -9.687 -0.050
MgH2PO4+ 9.996e-11 8.918e-11 -10.000 -10.050 -0.050
CaH2PO4+ 5.606e-11 5.001e-11 -10.251 -10.301 -0.050
PO4-3 4.227e-11 1.504e-11 -10.374 -10.823 -0.449
KHPO4- 4.194e-11 3.742e-11 -10.377 -10.427 -0.050
FeHPO4 2.838e-20 2.846e-20 -19.547 -19.546 0.001
FeH2PO4+ 1.343e-22 1.198e-22 -21.872 -21.922 -0.050
FeHPO4+ 4.809e-23 4.290e-23 -22.318 -22.367 -0.050
FeH2PO4+2 1.959e-24 1.241e-24 -23.708 -23.906 -0.198
Pb 4.831e-08
PbCO3 3.582e-08 3.592e-08 -7.446 -7.445 0.001
Pb(CO3)2-2 1.208e-08 7.652e-09 -7.918 -8.116 -0.198
PbOH+ 2.502e-10 2.232e-10 -9.602 -9.651 -0.050
PbHCO3+ 7.666e-11 6.840e-11 -10.115 -10.165 -0.050
Pb(OH)2 4.069e-11 4.080e-11 -10.391 -10.389 0.001
Pb+2 3.846e-11 2.437e-11 -10.415 -10.613 -0.198
PbSO4 5.282e-12 5.297e-12 -11.277 -11.276 0.001
PbCl+ 3.661e-12 3.266e-12 -11.436 -11.486 -0.050
Pb(OH)3- 2.467e-13 2.201e-13 -12.608 -12.657 -0.050
Pb(SO4)2-2 1.696e-14 1.074e-14 -13.771 -13.969 -0.198
PbCl2 1.433e-14 1.437e-14 -13.844 -13.843 0.001
Pb(OH)4-2 3.738e-16 2.369e-16 -15.427 -15.625 -0.198
PbCl3- 3.965e-17 3.538e-17 -16.402 -16.451 -0.050
Pb2OH+3 3.400e-19 1.218e-19 -18.469 -18.914 -0.446
PbCl4-2 8.340e-20 5.284e-20 -19.079 -19.277 -0.198
PbNO3+ 2.261e-21 2.017e-21 -20.646 -20.695 -0.050
S(-2) 0.000e+00
HS- 0.000e+00 0.000e+00 -114.015 -114.066 -0.051
H2S 0.000e+00 0.000e+00 -115.854 -115.853 0.001
S-2 0.000e+00 0.000e+00 -117.987 -118.180 -0.193
Fe(HS)2 0.000e+00 0.000e+00 -235.142 -235.141 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -347.120 -347.170 -0.050
S(6) 7.918e-04
SO4-2 6.039e-04 3.865e-04 -3.219 -3.413 -0.194
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MgSO4 1.172e-04 1.175e-04 -3.931 -3.930 0.001
CaSO4 6.622e-05 6.641e-05 -4.179 -4.178 0.001
NaSO4- 3.627e-06 3.236e-06 -5.440 -5.490 -0.050
KSO4- 9.713e-07 8.666e-07 -6.013 -6.062 -0.050
ZnSO4 1.612e-09 1.616e-09 -8.793 -8.791 0.001
MnSO4 1.091e-09 1.094e-09 -8.962 -8.961 0.001
CdSO4 2.204e-10 2.210e-10 -9.657 -9.656 0.001
HSO4- 9.905e-11 8.837e-11 -10.004 -10.054 -0.050
Zn(SO4)2-2 7.744e-12 4.907e-12 -11.111 -11.309 -0.198
PbSO4 5.282e-12 5.297e-12 -11.277 -11.276 0.001
CuSO4 4.440e-12 4.452e-12 -11.353 -11.351 0.001
Cd(SO4)2-2 1.439e-12 9.115e-13 -11.842 -12.040 -0.198
CaHSO4+ 9.839e-13 8.778e-13 -12.007 -12.057 -0.050
Pb(SO4)2-2 1.696e-14 1.074e-14 -13.771 -13.969 -0.198
FeSO4 8.177e-18 8.200e-18 -17.087 -17.086 0.001
AlSO4+ 1.578e-19 1.408e-19 -18.802 -18.851 -0.050
FeSO4+ 1.112e-20 9.925e-21 -19.954 -20.003 -0.050
Al(SO4)2- 1.969e-21 1.757e-21 -20.706 -20.755 -0.050
Fe(SO4)2- 9.570e-23 8.539e-23 -22.019 -22.069 -0.050
FeHSO4+ 1.310e-25 1.169e-25 -24.883 -24.932 -0.050
FeHSO4+2 8.942e-29 5.666e-29 -28.049 -28.247 -0.198
AlHSO4+2 4.376e-29 2.773e-29 -28.359 -28.557 -0.198
NH4SO4- 0.000e+00 0.000e+00 -48.787 -48.836 -0.050
Zn 1.225e-06
Zn(CO3)2-2 8.349e-07 5.290e-07 -6.078 -6.277 -0.198
ZnCO3 2.909e-07 2.917e-07 -6.536 -6.535 0.001
Zn(OH)2 4.777e-08 4.791e-08 -7.321 -7.320 0.001
Zn+2 2.691e-08 1.724e-08 -7.570 -7.763 -0.193
ZnOH+ 1.393e-08 1.243e-08 -7.856 -7.905 -0.050
ZnHCO3+ 8.595e-09 7.669e-09 -8.066 -8.115 -0.050
ZnSO4 1.612e-09 1.616e-09 -8.793 -8.791 0.001
ZnCl+ 1.907e-10 1.702e-10 -9.720 -9.769 -0.050
Zn(OH)3- 7.977e-11 7.117e-11 -10.098 -10.148 -0.050
Zn(SO4)2-2 7.744e-12 4.907e-12 -11.111 -11.309 -0.198
ZnCl2 5.455e-13 5.470e-13 -12.263 -12.262 0.001
Zn(OH)4-2 8.363e-15 5.299e-15 -14.078 -14.276 -0.198
ZnCl3- 2.131e-15 1.901e-15 -14.671 -14.721 -0.050
ZnCl4-2 4.697e-18 2.976e-18 -17.328 -17.526 -0.198
------------------------------Saturation indices-------------------------------
Phase SI log IAP log KT
Al(OH)3(a) -3.46 7.05 10.51 Al(OH)3
Alunite -13.27 -15.21 -1.95 KAl3(SO4)2(OH)6
Anglesite -6.26 -14.03 -7.77 PbSO4
Anhydrite -2.11 -6.50 -4.38 CaSO4
Aragonite 1.21 -7.15 -8.37 CaCO3
Calcite 1.35 -7.15 -8.51 CaCO3
Cd(OH)2 -5.02 8.63 13.65 Cd(OH)2
CdSO4 -11.87 -12.13 -0.26 CdSO4
Cerrusite -1.61 -14.68 -13.08 PbCO3
CH4(g) -113.09 -156.39 -43.30 CH4
CO2(g) -3.27 -21.42 -18.14 CO2
Dolomite 3.03 -14.16 -17.19 CaMg(CO3)2
Fe(OH)3(a) 0.45 18.26 17.81 Fe(OH)3
FeS(ppt) -117.44 -154.35 -36.91 FeS
Gibbsite -0.81 7.05 7.86 Al(OH)3
Goethite 6.50 18.26 11.76 FeOOH
Gypsum -1.91 -6.50 -4.58 CaSO4:2H2O
H2(g) -33.74 -33.74 -0.00 H2
H2O(g) -1.40 -0.00 1.40 H2O
H2S(g) -114.81 -155.73 -40.93 H2S
Halite -6.90 -5.31 1.59 NaCl
Hausmannite 2.34 62.27 59.93 Mn3O4
Hematite 15.03 36.51 21.48 Fe2O3
Hydroxyapatite 1.53 -39.21 -40.74 Ca5(PO4)3OH
Jarosite-K -10.79 18.40 29.19 KFe3(SO4)2(OH)6
Mackinawite -116.70 -154.35 -37.64 FeS
Manganite 1.04 26.38 25.34 MnOOH
Melanterite -17.22 -19.37 -2.16 FeSO4:7H2O
N2(g) -1.61 -208.57 -206.95 N2
NH3(g) -48.65 -154.90 -106.25 NH3
O2(g) -14.14 67.49 81.63 O2
Otavite -0.69 -12.79 -12.10 CdCO3
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Pb(OH)2 -1.27 6.73 8.00 Pb(OH)2
Pyrite -191.99 -276.34 -84.34 FeS2
Pyrochroite -5.69 9.51 15.20 Mn(OH)2
Pyrolusite 2.58 43.25 40.67 MnO2
Rhodochrosite -0.76 -11.91 -11.15 MnCO3
Siderite -9.11 -20.03 -10.92 FeCO3
Smithsonite -1.79 -11.83 -10.05 ZnCO3
Sphalerite -101.63 -146.15 -44.52 ZnS
Sulfur -86.89 -121.99 -35.10 S
Vivianite -33.52 -69.52 -36.00 Fe3(PO4)2:8H2O
Zn(OH)2(e) -1.92 9.58 11.50 Zn(OH)2
------------------
End of simulation.
------------------
SENSITIVITY ANALYSIS
TITLE Dewatering surplus (December 2013): adjusted pH
SOLUTION 1
pH 7.0
temp 29.5
pe
units mg/L
Alkalinity 240
Al 0.01
B 0.3
Cd 0.0005
Ca 61
Cl 120
Cu 0.016
Fe 0.01
Pb 0.01
Mg 50
Mn 0.007
N 0.36
P 0.01
K 13
Na 42
S 76 as SO4-2
Zn 0.08
END
-----
TITLE
-----
Dewatering surplus (December 2013): adjusted pH
-------------------------------------------
Beginning of initial solution calculations.
-------------------------------------------
Initial solution 1.
-----------------------------Solution composition------------------------------
Elements Molality Moles
Al 3.708e-07 3.708e-07
Alkalinity 4.799e-03 4.799e-03
B 2.777e-05 2.777e-05
Ca 1.523e-03 1.523e-03
Cd 4.451e-09 4.451e-09
Cl 3.387e-03 3.387e-03
Cu 2.519e-07 2.519e-07
Fe 1.792e-07 1.792e-07
K 3.327e-04 3.327e-04
Mg 2.058e-03 2.058e-03
Investigating the impacts of groundwater on soil properties and pasture
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Mn 1.275e-07 1.275e-07
N 2.572e-05 2.572e-05
Na 1.828e-03 1.828e-03
P 3.230e-07 3.230e-07
Pb 4.829e-08 4.829e-08
S 7.916e-04 7.916e-04
Zn 1.225e-06 1.225e-06
----------------------------Description of solution----------------------------
pH = 7.000
pe = 7.000
Activity of water = 1.000
Ionic strength = 1.288e-02
Mass of water (kg) = 1.000e+00
Total carbon (mol/kg) = 5.673e-03
Total CO2 (mol/kg) = 5.673e-03
Temperature (deg C) = 29.500
Electrical balance (eq) = -4.422e-04
Percent error, 100*(Cat-|An|)/(Cat+|An|) = -2.45
Iterations = 11
Total H = 1.110173e+02
Total O = 5.552560e+01
----------------------------Distribution of species----------------------------
Log Log Log
Species Molality Activity Molality Activity Gamma
OH- 1.571e-07 1.396e-07 -6.804 -6.855 -0.052
H+ 1.106e-07 1.000e-07 -6.956 -7.000 -0.044
H2O 5.551e+01 9.997e-01 -0.000 -0.000 0.000
Al 3.708e-07
Al(OH)4- 3.470e-07 3.090e-07 -6.460 -6.510 -0.050
Al(OH)3 1.529e-08 1.534e-08 -7.816 -7.814 0.001
Al(OH)2+ 8.483e-09 7.555e-09 -8.071 -8.122 -0.050
AlOH+2 1.046e-10 6.579e-11 -9.980 -10.182 -0.201
Al+3 1.224e-12 4.958e-13 -11.912 -12.305 -0.392
AlSO4+ 7.076e-13 6.302e-13 -12.150 -12.201 -0.050
Al(SO4)2- 8.669e-15 7.720e-15 -14.062 -14.112 -0.050
AlHSO4+2 9.269e-21 5.830e-21 -20.033 -20.234 -0.201
B 2.777e-05
H3BO3 2.758e-05 2.766e-05 -4.559 -4.558 0.001
H2BO3- 1.938e-07 1.726e-07 -6.713 -6.763 -0.050
C(4) 5.673e-03
HCO3- 4.649e-03 4.158e-03 -2.333 -2.381 -0.048
CO2 8.871e-04 8.897e-04 -3.052 -3.051 0.001
MgHCO3+ 6.724e-05 5.988e-05 -4.172 -4.223 -0.050
CaHCO3+ 5.622e-05 5.029e-05 -4.250 -4.299 -0.048
NaHCO3 3.785e-06 3.796e-06 -5.422 -5.421 0.001
CaCO3 3.492e-06 3.502e-06 -5.457 -5.456 0.001
CO3-2 3.320e-06 2.124e-06 -5.479 -5.673 -0.194
MgCO3 2.607e-06 2.615e-06 -5.584 -5.583 0.001
ZnHCO3+ 2.632e-07 2.344e-07 -6.580 -6.630 -0.050
ZnCO3 1.892e-07 1.898e-07 -6.723 -6.722 0.001
NaCO3- 9.017e-08 8.030e-08 -7.045 -7.095 -0.050
PbCO3 4.134e-08 4.146e-08 -7.384 -7.382 0.001
MnHCO3+ 2.388e-08 2.126e-08 -7.622 -7.672 -0.050
Zn(CO3)2-2 1.370e-08 8.618e-09 -7.863 -8.065 -0.201
MnCO3 9.652e-09 9.680e-09 -8.015 -8.014 0.001
PbHCO3+ 4.166e-09 3.710e-09 -8.380 -8.431 -0.050
Pb(CO3)2-2 3.517e-10 2.212e-10 -9.454 -9.655 -0.201
CdHCO3+ 3.008e-10 2.679e-10 -9.522 -9.572 -0.050
FeHCO3+ 7.737e-11 6.890e-11 -10.111 -10.162 -0.050
FeCO3 8.418e-12 8.443e-12 -11.075 -11.073 0.001
CdCO3 3.427e-12 3.437e-12 -11.465 -11.464 0.001
Cd(CO3)2-2 3.671e-14 2.309e-14 -13.435 -13.637 -0.201
Ca 1.523e-03
Ca+2 1.393e-03 8.906e-04 -2.856 -3.050 -0.194
CaSO4 7.009e-05 7.029e-05 -4.154 -4.153 0.001
CaHCO3+ 5.622e-05 5.029e-05 -4.250 -4.299 -0.048
CaCO3 3.492e-06 3.502e-06 -5.457 -5.456 0.001
CaHPO4 3.404e-08 3.414e-08 -7.468 -7.467 0.001
CaH2PO4+ 2.818e-09 2.509e-09 -8.550 -8.600 -0.050
CaOH+ 1.659e-09 1.478e-09 -8.780 -8.830 -0.050
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100
CaPO4- 9.860e-10 8.781e-10 -9.006 -9.056 -0.050
CaHSO4+ 4.903e-11 4.366e-11 -10.310 -10.360 -0.050
Cd 4.451e-09
Cd+2 3.239e-09 2.037e-09 -8.490 -8.691 -0.201
CdCl+ 6.673e-10 5.943e-10 -9.176 -9.226 -0.050
CdHCO3+ 3.008e-10 2.679e-10 -9.522 -9.572 -0.050
CdSO4 2.285e-10 2.291e-10 -9.641 -9.640 0.001
CdCl2 7.555e-12 7.577e-12 -11.122 -11.120 0.001
CdCO3 3.427e-12 3.437e-12 -11.465 -11.464 0.001
CdOH+ 2.643e-12 2.354e-12 -11.578 -11.628 -0.050
Cd(SO4)2-2 1.475e-12 9.280e-13 -11.831 -12.032 -0.201
Cd(CO3)2-2 3.671e-14 2.309e-14 -13.435 -13.637 -0.201
CdCl3- 1.727e-14 1.538e-14 -13.763 -13.813 -0.050
Cd(OH)2 9.069e-16 9.096e-16 -15.042 -15.041 0.001
Cd(OH)3- 1.146e-21 1.020e-21 -20.941 -20.991 -0.050
Cd(OH)4-2 1.445e-28 9.092e-29 -27.840 -28.041 -0.201
Cl 3.387e-03
Cl- 3.387e-03 3.009e-03 -2.470 -2.522 -0.051
ZnCl+ 4.952e-09 4.410e-09 -8.305 -8.356 -0.050
MnCl+ 7.898e-10 7.034e-10 -9.102 -9.153 -0.050
CdCl+ 6.673e-10 5.943e-10 -9.176 -9.226 -0.050
PbCl+ 1.687e-10 1.502e-10 -9.773 -9.823 -0.050
ZnCl2 1.410e-11 1.415e-11 -10.851 -10.849 0.001
CdCl2 7.555e-12 7.577e-12 -11.122 -11.120 0.001
MnCl2 9.212e-13 9.240e-13 -12.036 -12.034 0.001
FeCl+ 7.730e-13 6.884e-13 -12.112 -12.162 -0.050
PbCl2 6.574e-13 6.594e-13 -12.182 -12.181 0.001
ZnCl3- 5.508e-14 4.905e-14 -13.259 -13.309 -0.050
CdCl3- 1.727e-14 1.538e-14 -13.763 -13.813 -0.050
PbCl3- 1.819e-15 1.620e-15 -14.740 -14.791 -0.050
MnCl3- 8.599e-16 7.658e-16 -15.066 -15.116 -0.050
ZnCl4-2 1.218e-16 7.662e-17 -15.914 -16.116 -0.201
FeCl+2 3.355e-17 2.110e-17 -16.474 -16.676 -0.201
PbCl4-2 3.838e-18 2.414e-18 -17.416 -17.617 -0.201
FeCl2+ 2.768e-19 2.465e-19 -18.558 -18.608 -0.050
FeCl3 7.395e-23 7.417e-23 -22.131 -22.130 0.001
Cu(1) 4.074e-12
Cu+ 4.074e-12 3.603e-12 -11.390 -11.443 -0.053
Cu(2) 2.519e-07
Cu(OH)2 1.372e-07 1.376e-07 -6.863 -6.861 0.001
Cu+2 1.021e-07 6.588e-08 -6.991 -7.181 -0.190
CuOH+ 7.401e-09 6.586e-09 -8.131 -8.181 -0.051
CuSO4 5.248e-09 5.263e-09 -8.280 -8.279 0.001
Cu(OH)3- 9.306e-14 8.287e-14 -13.031 -13.082 -0.050
Cu(OH)4-2 2.628e-19 1.653e-19 -18.580 -18.782 -0.201
Fe(2) 3.564e-10
Fe+2 2.569e-10 1.657e-10 -9.590 -9.781 -0.190
FeHCO3+ 7.737e-11 6.890e-11 -10.111 -10.162 -0.050
FeSO4 1.209e-11 1.213e-11 -10.917 -10.916 0.001
FeCO3 8.418e-12 8.443e-12 -11.075 -11.073 0.001
FeOH+ 8.193e-13 7.296e-13 -12.087 -12.137 -0.050
FeCl+ 7.730e-13 6.884e-13 -12.112 -12.162 -0.050
FeHPO4 4.233e-14 4.246e-14 -13.373 -13.372 0.001
FeH2PO4+ 9.430e-15 8.398e-15 -14.025 -14.076 -0.050
FeHSO4+ 9.123e-18 8.124e-18 -17.040 -17.090 -0.050
Fe(HS)2 0.000e+00 0.000e+00 -179.683 -179.682 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -267.021 -267.071 -0.050
Fe(3) 1.788e-07
Fe(OH)3 1.032e-07 1.035e-07 -6.986 -6.985 0.001
Fe(OH)2+ 7.436e-08 6.622e-08 -7.129 -7.179 -0.050
Fe(OH)4- 1.266e-09 1.127e-09 -8.898 -8.948 -0.050
FeOH+2 2.688e-11 1.691e-11 -10.571 -10.772 -0.201
FeSO4+ 1.040e-15 9.262e-16 -14.983 -15.033 -0.050
Fe+3 4.981e-16 2.018e-16 -15.303 -15.695 -0.392
FeCl+2 3.355e-17 2.110e-17 -16.474 -16.676 -0.201
Fe(SO4)2- 8.786e-18 7.825e-18 -17.056 -17.107 -0.050
FeH2PO4+2 8.730e-18 5.491e-18 -17.059 -17.260 -0.201
FeHPO4+ 4.535e-18 4.039e-18 -17.343 -17.394 -0.050
FeCl2+ 2.768e-19 2.465e-19 -18.558 -18.608 -0.050
Fe2(OH)2+4 4.093e-20 6.406e-21 -19.388 -20.193 -0.805
FeHSO4+2 3.950e-22 2.485e-22 -21.403 -21.605 -0.201
FeCl3 7.395e-23 7.417e-23 -22.131 -22.130 0.001
Fe3(OH)4+5 1.068e-24 5.888e-26 -23.971 -25.230 -1.259
H(0) 1.351e-31
H2 6.754e-32 6.774e-32 -31.170 -31.169 0.001
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K 3.327e-04
K+ 3.317e-04 2.947e-04 -3.479 -3.531 -0.051
KSO4- 9.535e-07 8.492e-07 -6.021 -6.071 -0.050
KHPO4- 4.153e-11 3.698e-11 -10.382 -10.432 -0.050
KOH 1.019e-11 1.022e-11 -10.992 -10.991 0.001
Mg 2.058e-03
Mg+2 1.868e-03 1.204e-03 -2.729 -2.919 -0.191
MgSO4 1.197e-04 1.201e-04 -3.922 -3.921 0.001
MgHCO3+ 6.724e-05 5.988e-05 -4.172 -4.223 -0.050
MgCO3 2.607e-06 2.615e-06 -5.584 -5.583 0.001
MgOH+ 7.323e-08 6.522e-08 -7.135 -7.186 -0.050
MgHPO4 6.222e-08 6.240e-08 -7.206 -7.205 0.001
MgH2PO4+ 4.851e-09 4.320e-09 -8.314 -8.365 -0.050
MgPO4- 1.798e-09 1.601e-09 -8.745 -8.796 -0.050
Mn(2) 1.275e-07
Mn+2 8.895e-08 5.738e-08 -7.051 -7.241 -0.190
MnHCO3+ 2.388e-08 2.126e-08 -7.622 -7.672 -0.050
MnCO3 9.652e-09 9.680e-09 -8.015 -8.014 0.001
MnSO4 4.202e-09 4.214e-09 -8.377 -8.375 0.001
MnCl+ 7.898e-10 7.034e-10 -9.102 -9.153 -0.050
MnOH+ 2.376e-11 2.116e-11 -10.624 -10.674 -0.050
MnCl2 9.212e-13 9.240e-13 -12.036 -12.034 0.001
MnCl3- 8.599e-16 7.658e-16 -15.066 -15.116 -0.050
Mn(NO3)2 0.000e+00 0.000e+00 -61.215 -61.214 0.001
Mn(3) 9.616e-26
Mn+3 9.616e-26 3.388e-26 -25.017 -25.470 -0.453
N(-3) 6.499e-37
NH4+ 6.424e-37 5.682e-37 -36.192 -36.246 -0.053
NH3 4.415e-39 4.428e-39 -38.355 -38.354 0.001
NH4SO4- 3.119e-39 2.778e-39 -38.506 -38.556 -0.050
N(0) 2.572e-05
N2 1.286e-05 1.290e-05 -4.891 -4.890 0.001
N(3) 7.267e-28
NO2- 7.267e-28 6.441e-28 -27.139 -27.191 -0.052
N(5) 5.864e-28
NO3- 5.864e-28 5.197e-28 -27.232 -27.284 -0.052
PbNO3+ 9.696e-36 8.634e-36 -35.013 -35.064 -0.050
Mn(NO3)2 0.000e+00 0.000e+00 -61.215 -61.214 0.001
Na 1.828e-03
Na+ 1.821e-03 1.624e-03 -2.740 -2.790 -0.050
NaHCO3 3.785e-06 3.796e-06 -5.422 -5.421 0.001
NaSO4- 3.567e-06 3.176e-06 -5.448 -5.498 -0.050
NaCO3- 9.017e-08 8.030e-08 -7.045 -7.095 -0.050
NaHPO4- 2.288e-10 2.037e-10 -9.641 -9.691 -0.050
NaOH 1.069e-10 1.072e-10 -9.971 -9.970 0.001
O(0) 4.881e-29
O2 2.441e-29 2.448e-29 -28.613 -28.611 0.001
P 3.230e-07
H2PO4- 1.134e-07 1.011e-07 -6.945 -6.995 -0.050
HPO4-2 1.027e-07 6.436e-08 -6.989 -7.191 -0.203
MgHPO4 6.222e-08 6.240e-08 -7.206 -7.205 0.001
CaHPO4 3.404e-08 3.414e-08 -7.468 -7.467 0.001
MgH2PO4+ 4.851e-09 4.320e-09 -8.314 -8.365 -0.050
CaH2PO4+ 2.818e-09 2.509e-09 -8.550 -8.600 -0.050
MgPO4- 1.798e-09 1.601e-09 -8.745 -8.796 -0.050
CaPO4- 9.860e-10 8.781e-10 -9.006 -9.056 -0.050
NaHPO4- 2.288e-10 2.037e-10 -9.641 -9.691 -0.050
KHPO4- 4.153e-11 3.698e-11 -10.382 -10.432 -0.050
PO4-3 9.063e-13 3.170e-13 -12.043 -12.499 -0.456
FeHPO4 4.233e-14 4.246e-14 -13.373 -13.372 0.001
FeH2PO4+ 9.430e-15 8.398e-15 -14.025 -14.076 -0.050
FeH2PO4+2 8.730e-18 5.491e-18 -17.059 -17.260 -0.201
FeHPO4+ 4.535e-18 4.039e-18 -17.343 -17.394 -0.050
Pb 4.829e-08
PbCO3 4.134e-08 4.146e-08 -7.384 -7.382 0.001
PbHCO3+ 4.166e-09 3.710e-09 -8.380 -8.431 -0.050
Pb+2 1.786e-09 1.123e-09 -8.748 -8.950 -0.201
Pb(CO3)2-2 3.517e-10 2.212e-10 -9.454 -9.655 -0.201
PbOH+ 2.459e-10 2.190e-10 -9.609 -9.660 -0.050
PbSO4 2.390e-10 2.397e-10 -9.622 -9.620 0.001
PbCl+ 1.687e-10 1.502e-10 -9.773 -9.823 -0.050
Pb(OH)2 8.491e-13 8.516e-13 -12.071 -12.070 0.001
Pb(SO4)2-2 7.591e-13 4.775e-13 -12.120 -12.321 -0.201
PbCl2 6.574e-13 6.594e-13 -12.182 -12.181 0.001
PbCl3- 1.819e-15 1.620e-15 -14.740 -14.791 -0.050
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Pb(OH)3- 1.098e-16 9.775e-17 -15.960 -16.010 -0.050
Pb2OH+3 1.563e-17 5.506e-18 -16.806 -17.259 -0.453
PbCl4-2 3.838e-18 2.414e-18 -17.416 -17.617 -0.201
Pb(OH)4-2 3.559e-21 2.239e-21 -20.449 -20.650 -0.201
PbNO3+ 9.696e-36 8.634e-36 -35.013 -35.064 -0.050
S(-2) 0.000e+00
HS- 0.000e+00 0.000e+00 -89.374 -89.426 -0.052
H2S 0.000e+00 0.000e+00 -89.542 -89.540 0.001
S-2 0.000e+00 0.000e+00 -95.015 -95.212 -0.196
Fe(HS)2 0.000e+00 0.000e+00 -179.683 -179.682 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -267.021 -267.071 -0.050
S(6) 7.916e-04
SO4-2 5.972e-04 3.795e-04 -3.224 -3.421 -0.197
MgSO4 1.197e-04 1.201e-04 -3.922 -3.921 0.001
CaSO4 7.009e-05 7.029e-05 -4.154 -4.153 0.001
NaSO4- 3.567e-06 3.176e-06 -5.448 -5.498 -0.050
KSO4- 9.535e-07 8.492e-07 -6.021 -6.071 -0.050
ZnSO4 4.110e-08 4.122e-08 -7.386 -7.385 0.001
CuSO4 5.248e-09 5.263e-09 -8.280 -8.279 0.001
HSO4- 4.579e-09 4.078e-09 -8.339 -8.390 -0.050
MnSO4 4.202e-09 4.214e-09 -8.377 -8.375 0.001
PbSO4 2.390e-10 2.397e-10 -9.622 -9.620 0.001
CdSO4 2.285e-10 2.291e-10 -9.641 -9.640 0.001
Zn(SO4)2-2 1.954e-10 1.229e-10 -9.709 -9.910 -0.201
CaHSO4+ 4.903e-11 4.366e-11 -10.310 -10.360 -0.050
FeSO4 1.209e-11 1.213e-11 -10.917 -10.916 0.001
Cd(SO4)2-2 1.475e-12 9.280e-13 -11.831 -12.032 -0.201
Pb(SO4)2-2 7.591e-13 4.775e-13 -12.120 -12.321 -0.201
AlSO4+ 7.076e-13 6.302e-13 -12.150 -12.201 -0.050
Al(SO4)2- 8.669e-15 7.720e-15 -14.062 -14.112 -0.050
FeSO4+ 1.040e-15 9.262e-16 -14.983 -15.033 -0.050
FeHSO4+ 9.123e-18 8.124e-18 -17.040 -17.090 -0.050
Fe(SO4)2- 8.786e-18 7.825e-18 -17.056 -17.107 -0.050
AlHSO4+2 9.269e-21 5.830e-21 -20.033 -20.234 -0.201
FeHSO4+2 3.950e-22 2.485e-22 -21.403 -21.605 -0.201
NH4SO4- 3.119e-39 2.778e-39 -38.506 -38.556 -0.050
Zn 1.225e-06
Zn+2 7.039e-07 4.478e-07 -6.153 -6.349 -0.196
ZnHCO3+ 2.632e-07 2.344e-07 -6.580 -6.630 -0.050
ZnCO3 1.892e-07 1.898e-07 -6.723 -6.722 0.001
ZnSO4 4.110e-08 4.122e-08 -7.386 -7.385 0.001
Zn(CO3)2-2 1.370e-08 8.618e-09 -7.863 -8.065 -0.201
ZnOH+ 7.716e-09 6.871e-09 -8.113 -8.163 -0.050
ZnCl+ 4.952e-09 4.410e-09 -8.305 -8.356 -0.050
Zn(OH)2 5.618e-10 5.635e-10 -9.250 -9.249 0.001
Zn(SO4)2-2 1.954e-10 1.229e-10 -9.709 -9.910 -0.201
ZnCl2 1.410e-11 1.415e-11 -10.851 -10.849 0.001
ZnCl3- 5.508e-14 4.905e-14 -13.259 -13.309 -0.050
Zn(OH)3- 2.000e-14 1.781e-14 -13.699 -13.749 -0.050
ZnCl4-2 1.218e-16 7.662e-17 -15.914 -16.116 -0.201
Zn(OH)4-2 4.488e-20 2.823e-20 -19.348 -19.549 -0.201
------------------------------Saturation indices-------------------------------
Phase SI log IAP log KT
Al(OH)3(a) -1.82 8.69 10.51 Al(OH)3
Alunite -3.34 -5.29 -1.95 KAl3(SO4)2(OH)6
Anglesite -4.60 -12.37 -7.77 PbSO4
Anhydrite -2.09 -6.47 -4.38 CaSO4
Aragonite -0.36 -8.72 -8.37 CaCO3
Calcite -0.22 -8.72 -8.51 CaCO3
Cd(OH)2 -8.34 5.31 13.65 Cd(OH)2
CdSO4 -11.85 -12.11 -0.26 CdSO4
Cerrusite -1.55 -14.62 -13.08 PbCO3
CO2(g) -1.53 -19.67 -18.14 CO2
Dolomite -0.12 -17.32 -17.19 CaMg(CO3)2
Fe(OH)3(a) 0.41 18.22 17.81 Fe(OH)3
FeS(ppt) -88.29 -125.20 -36.91 FeS
Gibbsite 0.83 8.69 7.86 Al(OH)3
Goethite 6.46 18.22 11.76 FeOOH
Gypsum -1.89 -6.47 -4.58 CaSO4:2H2O
H2(g) -28.00 -28.00 -0.00 H2
H2O(g) -1.40 -0.00 1.40 H2O
H2S(g) -88.49 -129.42 -40.93 H2S
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Halite -6.90 -5.31 1.59 NaCl
Hausmannite -11.66 48.28 59.93 Mn3O4
Hematite 14.95 36.44 21.48 Fe2O3
Hydroxyapatite -5.01 -45.75 -40.74 Ca5(PO4)3OH
Jarosite-K -5.91 23.29 29.19 KFe3(SO4)2(OH)6
Mackinawite -87.56 -125.20 -37.64 FeS
Manganite -4.58 20.76 25.34 MnOOH
Melanterite -11.05 -13.20 -2.16 FeSO4:7H2O
N2(g) -1.61 -4.89 -3.27 N2
NH3(g) -40.03 -44.44 -4.41 NH3
O2(g) -25.63 56.00 81.63 O2
Otavite -2.26 -14.36 -12.10 CdCO3
Pb(OH)2 -2.95 5.05 8.00 Pb(OH)2
Pyrite -142.28 -226.62 -84.34 FeS2
Pyrochroite -8.44 6.76 15.20 Mn(OH)2
Pyrolusite -5.91 34.76 40.67 MnO2
Rhodochrosite -1.77 -12.91 -11.15 MnCO3
Siderite -4.54 -15.45 -10.92 FeCO3
Smithsonite -1.97 -12.02 -10.05 ZnCO3
Sphalerite -77.25 -121.77 -44.52 ZnS
Sulfur -66.32 -101.42 -35.10 S
Vivianite -18.34 -54.34 -36.00 Fe3(PO4)2:8H2O
Zn(OH)2(e) -3.85 7.65 11.50 Zn(OH)2
------------------
End of simulation.
------------------
FERTIGATION MIXTURE
TITLE Fertigation mixture (December 2013)
SOLUTION 1
pH 8.0
temp 31.9
pe
units mg/L
Alkalinity 220
Al 0.01
B 0.3
Cd 0.0005
Ca 61
Cl 120
Cu 0.005
Fe 0.01
Pb 0.01
Mg 50
Mn 0.21
N 60
P 7.2
K 31
Na 43
S 92 as SO4-2
Zn 0.26
END
-----
TITLE
-----
Fertigation mixture (December 2013)
-------------------------------------------
Beginning of initial solution calculations.
-------------------------------------------
Initial solution 1.
-----------------------------Solution composition------------------------------
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Elements Molality Moles
Al 3.709e-07 3.709e-07
Alkalinity 4.399e-03 4.399e-03
B 2.777e-05 2.777e-05
Ca 1.523e-03 1.523e-03
Cd 4.451e-09 4.451e-09
Cl 3.387e-03 3.387e-03
Cu 7.874e-08 7.874e-08
Fe 1.792e-07 1.792e-07
K 7.933e-04 7.933e-04
Mg 2.058e-03 2.058e-03
Mn 3.825e-06 3.825e-06
N 4.287e-03 4.287e-03
Na 1.872e-03 1.872e-03
P 2.326e-04 2.326e-04
Pb 4.830e-08 4.830e-08
S 9.584e-04 9.584e-04
Zn 3.980e-06 3.980e-06
----------------------------Description of solution----------------------------
pH = 8.000
pe = 8.000
Activity of water = 1.000
Ionic strength = 1.291e-02
Mass of water (kg) = 1.000e+00
Total carbon (mol/kg) = 4.128e-03
Total CO2 (mol/kg) = 4.128e-03
Temperature (deg C) = 31.900
Electrical balance (eq) = -9.121e-05
Percent error, 100*(Cat-|An|)/(Cat+|An|) = -0.51
Iterations = 10
Total H = 1.110167e+02
Total O = 5.552338e+01
----------------------------Distribution of species----------------------------
Log Log Log
Species Molality Activity Molality Activity Gamma
OH- 1.866e-06 1.656e-06 -5.729 -5.781 -0.052
H+ 1.106e-08 1.000e-08 -7.956 -8.000 -0.044
H2O 5.551e+01 9.997e-01 -0.000 -0.000 0.000
Al 3.709e-07
Al(OH)4- 3.692e-07 3.286e-07 -6.433 -6.483 -0.051
Al(OH)3 1.562e-09 1.567e-09 -8.806 -8.805 0.001
Al(OH)2+ 7.368e-11 6.558e-11 -10.133 -10.183 -0.051
AlOH+2 7.485e-14 4.697e-14 -13.126 -13.328 -0.202
Al+3 7.534e-17 3.039e-17 -16.123 -16.517 -0.394
AlSO4+ 5.412e-17 4.817e-17 -16.267 -16.317 -0.051
Al(SO4)2- 8.109e-19 7.218e-19 -18.091 -18.142 -0.051
AlHSO4+2 7.280e-26 4.568e-26 -25.138 -25.340 -0.202
B 2.777e-05
H3BO3 2.587e-05 2.595e-05 -4.587 -4.586 0.001
H2BO3- 1.898e-06 1.689e-06 -5.722 -5.772 -0.051
C(4) 4.128e-03
HCO3- 3.866e-03 3.455e-03 -2.413 -2.461 -0.049
CO2 7.211e-05 7.232e-05 -4.142 -4.141 0.001
MgHCO3+ 5.326e-05 4.740e-05 -4.274 -4.324 -0.051
CaHCO3+ 4.555e-05 4.072e-05 -4.341 -4.390 -0.049
CaCO3 3.031e-05 3.040e-05 -4.518 -4.517 0.001
CO3-2 2.882e-05 1.840e-05 -4.540 -4.735 -0.195
MgCO3 2.202e-05 2.209e-05 -4.657 -4.656 0.001
NaHCO3 3.217e-06 3.226e-06 -5.493 -5.491 0.001
ZnCO3 1.717e-06 1.723e-06 -5.765 -5.764 0.001
MnCO3 1.607e-06 1.612e-06 -5.794 -5.793 0.001
Zn(CO3)2-2 1.080e-06 6.775e-07 -5.967 -6.169 -0.202
NaCO3- 8.980e-07 7.993e-07 -6.047 -6.097 -0.051
MnHCO3+ 3.817e-07 3.397e-07 -6.418 -6.469 -0.051
ZnHCO3+ 2.294e-07 2.041e-07 -6.639 -6.690 -0.051
PbCO3 4.403e-08 4.416e-08 -7.356 -7.355 0.001
Pb(CO3)2-2 3.252e-09 2.041e-09 -8.488 -8.690 -0.202
PbHCO3+ 4.260e-10 3.791e-10 -9.371 -9.421 -0.051
CdHCO3+ 2.461e-10 2.191e-10 -9.609 -9.659 -0.051
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CdCO3 2.921e-11 2.930e-11 -10.534 -10.533 0.001
Cd(CO3)2-2 2.716e-12 1.705e-12 -11.566 -11.768 -0.202
FeCO3 6.724e-15 6.744e-15 -14.172 -14.171 0.001
FeHCO3+ 5.932e-15 5.280e-15 -14.227 -14.277 -0.051
Ca 1.523e-03
Ca+2 1.322e-03 8.434e-04 -2.879 -3.074 -0.195
CaSO4 8.206e-05 8.231e-05 -4.086 -4.085 0.001
CaHCO3+ 4.555e-05 4.072e-05 -4.341 -4.390 -0.049
CaHPO4 3.282e-05 3.292e-05 -4.484 -4.483 0.001
CaCO3 3.031e-05 3.040e-05 -4.518 -4.517 0.001
CaPO4- 9.937e-06 8.844e-06 -5.003 -5.053 -0.051
CaH2PO4+ 2.687e-07 2.392e-07 -6.571 -6.621 -0.051
CaOH+ 1.572e-08 1.399e-08 -7.803 -7.854 -0.051
CaHSO4+ 5.938e-12 5.285e-12 -11.226 -11.277 -0.051
Cd 4.451e-09
Cd+2 3.195e-09 2.005e-09 -8.496 -8.698 -0.202
CdCl+ 6.618e-10 5.890e-10 -9.179 -9.230 -0.051
CdSO4 2.759e-10 2.767e-10 -9.559 -9.558 0.001
CdHCO3+ 2.461e-10 2.191e-10 -9.609 -9.659 -0.051
CdOH+ 3.089e-11 2.749e-11 -10.510 -10.561 -0.051
CdCO3 2.921e-11 2.930e-11 -10.534 -10.533 0.001
CdCl2 7.548e-12 7.570e-12 -11.122 -11.121 0.001
Cd(CO3)2-2 2.716e-12 1.705e-12 -11.566 -11.768 -0.202
Cd(SO4)2-2 2.131e-12 1.337e-12 -11.671 -11.874 -0.202
Cd(OH)2 8.924e-14 8.950e-14 -13.049 -13.048 0.001
CdCl3- 1.787e-14 1.590e-14 -13.748 -13.799 -0.051
Cd(OH)3- 1.128e-18 1.004e-18 -17.948 -17.998 -0.051
Cd(OH)4-2 1.426e-24 8.945e-25 -23.846 -24.048 -0.202
Cl 3.387e-03
Cl- 3.387e-03 3.008e-03 -2.470 -2.522 -0.052
MnCl+ 1.518e-08 1.351e-08 -7.819 -7.869 -0.051
ZnCl+ 5.746e-09 5.114e-09 -8.241 -8.291 -0.051
CdCl+ 6.618e-10 5.890e-10 -9.179 -9.230 -0.051
PbCl+ 2.196e-11 1.955e-11 -10.658 -10.709 -0.051
MnCl2 1.769e-11 1.774e-11 -10.752 -10.751 0.001
ZnCl2 1.650e-11 1.655e-11 -10.782 -10.781 0.001
CdCl2 7.548e-12 7.570e-12 -11.122 -11.121 0.001
PbCl2 8.191e-14 8.216e-14 -13.087 -13.085 0.001
ZnCl3- 6.534e-14 5.816e-14 -13.185 -13.235 -0.051
CdCl3- 1.787e-14 1.590e-14 -13.748 -13.799 -0.051
MnCl3- 1.651e-14 1.470e-14 -13.782 -13.833 -0.051
PbCl3- 2.299e-16 2.046e-16 -15.638 -15.689 -0.051
ZnCl4-2 1.474e-16 9.248e-17 -15.832 -16.034 -0.202
FeCl+ 7.128e-17 6.344e-17 -16.147 -16.198 -0.051
PbCl4-2 4.944e-19 3.103e-19 -18.306 -18.508 -0.202
FeCl+2 3.785e-20 2.375e-20 -19.422 -19.624 -0.202
FeCl2+ 2.895e-22 2.577e-22 -21.538 -21.589 -0.051
FeCl3 7.727e-26 7.750e-26 -25.112 -25.111 0.001
Cu(1) 2.360e-15
Cu+ 2.360e-15 2.086e-15 -14.627 -14.681 -0.054
Cu(2) 7.874e-08
Cu(OH)2 7.770e-08 7.793e-08 -7.110 -7.108 0.001
Cu+2 5.798e-10 3.732e-10 -9.237 -9.428 -0.191
CuOH+ 4.195e-10 3.731e-10 -9.377 -9.428 -0.051
CuSO4 3.656e-11 3.666e-11 -10.437 -10.436 0.001
Cu(OH)3- 5.275e-13 4.695e-13 -12.278 -12.328 -0.051
Cu(OH)4-2 1.492e-17 9.364e-18 -16.826 -17.029 -0.202
Fe(2) 4.266e-14
Fe+2 2.374e-14 1.528e-14 -13.625 -13.816 -0.191
FeCO3 6.724e-15 6.744e-15 -14.172 -14.171 0.001
FeHCO3+ 5.932e-15 5.280e-15 -14.227 -14.277 -0.051
FeHPO4 3.807e-15 3.818e-15 -14.419 -14.418 0.001
FeSO4 1.407e-15 1.412e-15 -14.852 -14.850 0.001
FeOH+ 8.984e-16 7.996e-16 -15.047 -15.097 -0.051
FeH2PO4+ 8.376e-17 7.455e-17 -16.077 -16.128 -0.051
FeCl+ 7.128e-17 6.344e-17 -16.147 -16.198 -0.051
FeHSO4+ 1.076e-22 9.575e-23 -21.968 -22.019 -0.051
Fe(HS)2 0.000e+00 0.000e+00 -218.236 -218.235 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -322.832 -322.883 -0.051
Fe(3) 1.792e-07
Fe(OH)3 1.493e-07 1.498e-07 -6.826 -6.825 0.001
Fe(OH)4- 2.012e-08 1.791e-08 -7.696 -7.747 -0.051
Fe(OH)2+ 9.738e-09 8.667e-09 -8.012 -8.062 -0.051
FeOH+2 3.231e-13 2.027e-13 -12.491 -12.693 -0.202
FeHPO4+ 4.994e-18 4.445e-18 -17.302 -17.352 -0.051
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FeSO4+ 1.387e-18 1.235e-18 -17.858 -17.909 -0.051
FeH2PO4+2 8.817e-19 5.533e-19 -18.055 -18.257 -0.202
Fe+3 5.235e-19 2.112e-19 -18.281 -18.675 -0.394
FeCl+2 3.785e-20 2.375e-20 -19.422 -19.624 -0.202
Fe(SO4)2- 1.431e-20 1.273e-20 -19.844 -19.895 -0.051
FeCl2+ 2.895e-22 2.577e-22 -21.538 -21.589 -0.051
Fe2(OH)2+4 5.400e-24 8.372e-25 -23.268 -24.077 -0.810
FeCl3 7.727e-26 7.750e-26 -25.112 -25.111 0.001
FeHSO4+2 5.297e-26 3.324e-26 -25.276 -25.478 -0.202
Fe3(OH)4+5 1.498e-29 8.137e-31 -28.825 -30.090 -1.265
H(0) 1.320e-35
H2 6.600e-36 6.620e-36 -35.180 -35.179 0.001
K 7.933e-04
K+ 7.904e-04 7.019e-04 -3.102 -3.154 -0.052
KSO4- 2.862e-06 2.548e-06 -5.543 -5.594 -0.051
KHPO4- 9.651e-08 8.589e-08 -7.015 -7.066 -0.051
KOH 2.426e-10 2.433e-10 -9.615 -9.614 0.001
Mg 2.058e-03
Mg+2 1.759e-03 1.132e-03 -2.755 -2.946 -0.192
MgSO4 1.445e-04 1.449e-04 -3.840 -3.839 0.001
MgHPO4 5.954e-05 5.972e-05 -4.225 -4.224 0.001
MgHCO3+ 5.326e-05 4.740e-05 -4.274 -4.324 -0.051
MgCO3 2.202e-05 2.209e-05 -4.657 -4.656 0.001
MgPO4- 1.798e-05 1.601e-05 -4.745 -4.796 -0.051
MgOH+ 8.484e-07 7.551e-07 -6.071 -6.122 -0.051
MgH2PO4+ 4.591e-07 4.086e-07 -6.338 -6.389 -0.051
Mn(2) 3.825e-06
Mn+2 1.713e-06 1.103e-06 -5.766 -5.957 -0.191
MnCO3 1.607e-06 1.612e-06 -5.794 -5.793 0.001
MnHCO3+ 3.817e-07 3.397e-07 -6.418 -6.469 -0.051
MnSO4 1.021e-07 1.024e-07 -6.991 -6.990 0.001
MnCl+ 1.518e-08 1.351e-08 -7.819 -7.869 -0.051
MnOH+ 5.518e-09 4.911e-09 -8.258 -8.309 -0.051
MnCl2 1.769e-11 1.774e-11 -10.752 -10.751 0.001
MnCl3- 1.651e-14 1.470e-14 -13.782 -13.833 -0.051
Mn(NO3)2 1.152e-34 1.155e-34 -33.939 -33.937 0.001
Mn(3) 2.604e-23
Mn+3 2.604e-23 9.127e-24 -22.584 -23.040 -0.455
N(-3) 0.000e+00
NH4+ 0.000e+00 0.000e+00 -42.257 -42.311 -0.054
NH3 0.000e+00 0.000e+00 -43.349 -43.348 0.001
NH4SO4- 0.000e+00 0.000e+00 -44.488 -44.539 -0.051
N(0) 4.287e-03
N2 2.143e-03 2.150e-03 -2.669 -2.668 0.001
N(3) 4.079e-19
NO2- 4.079e-19 3.613e-19 -18.389 -18.442 -0.053
N(5) 5.834e-15
NO3- 5.834e-15 5.168e-15 -14.234 -14.287 -0.053
PbNO3+ 1.186e-23 1.056e-23 -22.926 -22.976 -0.051
Mn(NO3)2 1.152e-34 1.155e-34 -33.939 -33.937 0.001
Na 1.872e-03
Na+ 1.863e-03 1.660e-03 -2.730 -2.780 -0.050
NaSO4- 4.481e-06 3.989e-06 -5.349 -5.399 -0.051
NaHCO3 3.217e-06 3.226e-06 -5.493 -5.491 0.001
NaCO3- 8.980e-07 7.993e-07 -6.047 -6.097 -0.051
NaHPO4- 2.283e-07 2.032e-07 -6.641 -6.692 -0.051
NaOH 1.093e-09 1.097e-09 -8.961 -8.960 0.001
O(0) 2.846e-20
O2 1.423e-20 1.427e-20 -19.847 -19.845 0.001
P 2.326e-04
HPO4-2 1.003e-04 6.277e-05 -3.999 -4.202 -0.204
MgHPO4 5.954e-05 5.972e-05 -4.225 -4.224 0.001
CaHPO4 3.282e-05 3.292e-05 -4.484 -4.483 0.001
MgPO4- 1.798e-05 1.601e-05 -4.745 -4.796 -0.051
H2PO4- 1.093e-05 9.734e-06 -4.962 -5.012 -0.050
CaPO4- 9.937e-06 8.844e-06 -5.003 -5.053 -0.051
MgH2PO4+ 4.591e-07 4.086e-07 -6.338 -6.389 -0.051
CaH2PO4+ 2.687e-07 2.392e-07 -6.571 -6.621 -0.051
NaHPO4- 2.283e-07 2.032e-07 -6.641 -6.692 -0.051
KHPO4- 9.651e-08 8.589e-08 -7.015 -7.066 -0.051
PO4-3 9.305e-09 3.238e-09 -8.031 -8.490 -0.458
FeHPO4 3.807e-15 3.818e-15 -14.419 -14.418 0.001
FeH2PO4+ 8.376e-17 7.455e-17 -16.077 -16.128 -0.051
FeHPO4+ 4.994e-18 4.445e-18 -17.302 -17.352 -0.051
FeH2PO4+2 8.817e-19 5.533e-19 -18.055 -18.257 -0.202
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Pb 4.830e-08
PbCO3 4.403e-08 4.416e-08 -7.356 -7.355 0.001
Pb(CO3)2-2 3.252e-09 2.041e-09 -8.488 -8.690 -0.202
PbHCO3+ 4.260e-10 3.791e-10 -9.371 -9.421 -0.051
PbOH+ 3.025e-10 2.692e-10 -9.519 -9.570 -0.051
Pb+2 2.201e-10 1.381e-10 -9.657 -9.860 -0.202
PbSO4 3.557e-11 3.567e-11 -10.449 -10.448 0.001
PbCl+ 2.196e-11 1.955e-11 -10.658 -10.709 -0.051
Pb(OH)2 1.044e-11 1.047e-11 -10.981 -10.980 0.001
Pb(SO4)2-2 1.370e-13 8.597e-14 -12.863 -13.066 -0.202
PbCl2 8.191e-14 8.216e-14 -13.087 -13.085 0.001
Pb(OH)3- 1.350e-14 1.202e-14 -13.870 -13.920 -0.051
PbCl3- 2.299e-16 2.046e-16 -15.638 -15.689 -0.051
Pb(OH)4-2 4.387e-18 2.753e-18 -17.358 -17.560 -0.202
Pb2OH+3 2.376e-18 8.325e-19 -17.624 -18.080 -0.455
PbCl4-2 4.944e-19 3.103e-19 -18.306 -18.508 -0.202
PbNO3+ 1.186e-23 1.056e-23 -22.926 -22.976 -0.051
S(-2) 0.000e+00
HS- 0.000e+00 0.000e+00 -106.633 -106.685 -0.052
H2S 0.000e+00 0.000e+00 -107.828 -107.827 0.001
S-2 0.000e+00 0.000e+00 -111.205 -111.402 -0.197
Fe(HS)2 0.000e+00 0.000e+00 -218.236 -218.235 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -322.832 -322.883 -0.051
S(6) 9.584e-04
SO4-2 7.243e-04 4.593e-04 -3.140 -3.338 -0.198
MgSO4 1.445e-04 1.449e-04 -3.840 -3.839 0.001
CaSO4 8.206e-05 8.231e-05 -4.086 -4.085 0.001
NaSO4- 4.481e-06 3.989e-06 -5.349 -5.399 -0.051
KSO4- 2.862e-06 2.548e-06 -5.543 -5.594 -0.051
MnSO4 1.021e-07 1.024e-07 -6.991 -6.990 0.001
ZnSO4 5.305e-08 5.321e-08 -7.275 -7.274 0.001
HSO4- 5.856e-10 5.212e-10 -9.232 -9.283 -0.051
Zn(SO4)2-2 3.005e-10 1.886e-10 -9.522 -9.724 -0.202
CdSO4 2.759e-10 2.767e-10 -9.559 -9.558 0.001
CuSO4 3.656e-11 3.666e-11 -10.437 -10.436 0.001
PbSO4 3.557e-11 3.567e-11 -10.449 -10.448 0.001
CaHSO4+ 5.938e-12 5.285e-12 -11.226 -11.277 -0.051
Cd(SO4)2-2 2.131e-12 1.337e-12 -11.671 -11.874 -0.202
Pb(SO4)2-2 1.370e-13 8.597e-14 -12.863 -13.066 -0.202
FeSO4 1.407e-15 1.412e-15 -14.852 -14.850 0.001
AlSO4+ 5.412e-17 4.817e-17 -16.267 -16.317 -0.051
FeSO4+ 1.387e-18 1.235e-18 -17.858 -17.909 -0.051
Al(SO4)2- 8.109e-19 7.218e-19 -18.091 -18.142 -0.051
Fe(SO4)2- 1.431e-20 1.273e-20 -19.844 -19.895 -0.051
FeHSO4+ 1.076e-22 9.575e-23 -21.968 -22.019 -0.051
AlHSO4+2 7.280e-26 4.568e-26 -25.138 -25.340 -0.202
FeHSO4+2 5.297e-26 3.324e-26 -25.276 -25.478 -0.202
NH4SO4- 0.000e+00 0.000e+00 -44.488 -44.539 -0.051
Zn 3.980e-06
ZnCO3 1.717e-06 1.723e-06 -5.765 -5.764 0.001
Zn(CO3)2-2 1.080e-06 6.775e-07 -5.967 -6.169 -0.202
Zn+2 7.392e-07 4.692e-07 -6.131 -6.329 -0.197
ZnHCO3+ 2.294e-07 2.041e-07 -6.639 -6.690 -0.051
ZnOH+ 9.639e-08 8.579e-08 -7.016 -7.067 -0.051
Zn(OH)2 5.887e-08 5.904e-08 -7.230 -7.229 0.001
ZnSO4 5.305e-08 5.321e-08 -7.275 -7.274 0.001
ZnCl+ 5.746e-09 5.114e-09 -8.241 -8.291 -0.051
Zn(SO4)2-2 3.005e-10 1.886e-10 -9.522 -9.724 -0.202
Zn(OH)3- 2.097e-11 1.867e-11 -10.678 -10.729 -0.051
ZnCl2 1.650e-11 1.655e-11 -10.782 -10.781 0.001
ZnCl3- 6.534e-14 5.816e-14 -13.185 -13.235 -0.051
Zn(OH)4-2 4.713e-16 2.957e-16 -15.327 -15.529 -0.202
ZnCl4-2 1.474e-16 9.248e-17 -15.832 -16.034 -0.202
------------------------------Saturation indices-------------------------------
Phase SI log IAP log KT
Al(OH)3(a) -2.88 7.48 10.36 Al(OH)3
Alunite -9.15 -11.38 -2.23 KAl3(SO4)2(OH)6
Anglesite -5.44 -13.20 -7.75 PbSO4
Anhydrite -2.01 -6.41 -4.40 CaSO4
Aragonite 0.57 -7.81 -8.38 CaCO3
Calcite 0.71 -7.81 -8.52 CaCO3
Cd(OH)2 -6.35 7.30 13.65 Cd(OH)2
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CdSO4 -11.69 -12.04 -0.34 CdSO4
Cerrusite -1.55 -14.59 -13.05 PbCO3
CO2(g) -2.60 -20.74 -18.14 CO2
Dolomite 1.76 -15.49 -17.25 CaMg(CO3)2
Fe(OH)3(a) 0.43 18.18 17.75 Fe(OH)3
FeS(ppt) -108.59 -145.15 -36.57 FeS
Gibbsite -0.25 7.48 7.73 Al(OH)3
Goethite 6.56 18.18 11.62 FeOOH
Gypsum -1.83 -6.41 -4.59 CaSO4:2H2O
H2(g) -32.00 -32.00 -0.00 H2
H2O(g) -1.34 -0.00 1.34 H2O
H2S(g) -106.75 -147.34 -40.58 H2S
Halite -6.90 -5.30 1.60 NaCl
Hausmannite 2.77 62.13 59.36 Mn3O4
Hematite 15.17 36.37 21.20 Fe2O3
Hydroxyapatite 8.04 -32.84 -40.88 Ca5(PO4)3OH
Jarosite-K -8.13 20.72 28.85 KFe3(SO4)2(OH)6
Mackinawite -107.85 -145.15 -37.30 FeS
Manganite 0.70 26.04 25.34 MnOOH
Melanterite -15.02 -17.15 -2.13 FeSO4:7H2O
N2(g) 0.61 -2.67 -3.28 N2
NH3(g) -44.98 -49.33 -4.35 NH3
O2(g) -16.85 64.00 80.85 O2
Otavite -1.33 -13.43 -12.10 CdCO3
Pb(OH)2 -1.78 6.14 7.92 Pb(OH)2
Pyrite -176.89 -260.49 -83.60 FeS2
Pyrochroite -5.16 10.04 15.20 Mn(OH)2
Pyrolusite 1.74 42.04 40.30 MnO2
Rhodochrosite 0.46 -10.69 -11.15 MnCO3
Siderite -7.62 -18.55 -10.93 FeCO3
Smithsonite -0.99 -11.06 -10.07 ZnCO3
Sphalerite -93.53 -137.67 -44.13 ZnS
Sulfur -80.55 -115.34 -34.79 S
Vivianite -22.43 -58.43 -36.00 Fe3(PO4)2:8H2O
Zn(OH)2(e) -1.83 9.67 11.50 Zn(OH)2
------------------
End of simulation.
------------------
SENSITIVITY ANALYSIS
TITLE Fertigation mixture (December 2013): adjusted pH
SOLUTION 1
pH 7
temp 31.9
pe
units mg/L
Alkalinity 220
Al 0.01
B 0.3
Cd 0.0005
Ca 61
Cl 120
Cu 0.005
Fe 0.01
Pb 0.01
Mg 50
Mn 0.21
N 60
P 7.2
K 31
Na 43
S 92 as SO4-2
Zn 0.26
END
-----
TITLE
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-----
Fertigation mixture (December 2013): adjusted pH
-------------------------------------------
Beginning of initial solution calculations.
-------------------------------------------
Initial solution 1.
-----------------------------Solution composition------------------------------
Elements Molality Moles
Al 3.709e-07 3.709e-07
Alkalinity 4.399e-03 4.399e-03
B 2.777e-05 2.777e-05
Ca 1.523e-03 1.523e-03
Cd 4.451e-09 4.451e-09
Cl 3.387e-03 3.387e-03
Cu 7.874e-08 7.874e-08
Fe 1.792e-07 1.792e-07
K 7.933e-04 7.933e-04
Mg 2.058e-03 2.058e-03
Mn 3.825e-06 3.825e-06
N 4.287e-03 4.287e-03
Na 1.872e-03 1.872e-03
P 2.326e-04 2.326e-04
Pb 4.830e-08 4.830e-08
S 9.584e-04 9.584e-04
Zn 3.980e-06 3.980e-06
----------------------------Description of solution----------------------------
pH = 7.000
pe = 7.000
Activity of water = 1.000
Ionic strength = 1.311e-02
Mass of water (kg) = 1.000e+00
Total carbon (mol/kg) = 5.006e-03
Total CO2 (mol/kg) = 5.006e-03
Temperature (deg C) = 31.900
Electrical balance (eq) = -9.121e-05
Percent error, 100*(Cat-|An|)/(Cat+|An|) = -0.50
Iterations = 10
Total H = 1.110171e+02
Total O = 5.552532e+01
----------------------------Distribution of species----------------------------
Log Log Log
Species Molality Activity Molality Activity Gamma
OH- 1.867e-07 1.656e-07 -6.729 -6.781 -0.052
H+ 1.107e-07 1.000e-07 -6.956 -7.000 -0.044
H2O 5.551e+01 9.997e-01 -0.000 -0.000 0.000
Al 3.709e-07
Al(OH)4- 3.491e-07 3.105e-07 -6.457 -6.508 -0.051
Al(OH)3 1.476e-08 1.480e-08 -7.831 -7.830 0.001
Al(OH)2+ 6.966e-09 6.195e-09 -8.157 -8.208 -0.051
AlOH+2 7.094e-11 4.437e-11 -10.149 -10.353 -0.204
Al+3 7.155e-13 2.871e-13 -12.145 -12.542 -0.397
AlSO4+ 5.077e-13 4.515e-13 -12.294 -12.345 -0.051
Al(SO4)2- 7.549e-15 6.714e-15 -14.122 -14.173 -0.051
AlHSO4+2 6.845e-21 4.282e-21 -20.165 -20.368 -0.204
B 2.777e-05
H3BO3 2.757e-05 2.765e-05 -4.560 -4.558 0.001
H2BO3- 2.024e-07 1.800e-07 -6.694 -6.745 -0.051
C(4) 5.006e-03
HCO3- 4.116e-03 3.677e-03 -2.385 -2.435 -0.049
CO2 7.673e-04 7.696e-04 -3.115 -3.114 0.001
MgHCO3+ 5.791e-05 5.150e-05 -4.237 -4.288 -0.051
CaHCO3+ 4.971e-05 4.441e-05 -4.304 -4.353 -0.049
NaHCO3 3.421e-06 3.432e-06 -5.466 -5.464 0.001
CaCO3 3.306e-06 3.316e-06 -5.481 -5.479 0.001
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CO3-2 3.075e-06 1.958e-06 -5.512 -5.708 -0.196
MgCO3 2.392e-06 2.400e-06 -5.621 -5.620 0.001
ZnHCO3+ 7.779e-07 6.918e-07 -6.109 -6.160 -0.051
MnHCO3+ 6.443e-07 5.730e-07 -6.191 -6.242 -0.051
ZnCO3 5.820e-07 5.838e-07 -6.235 -6.234 0.001
MnCO3 2.711e-07 2.719e-07 -6.567 -6.566 0.001
NaCO3- 9.559e-08 8.501e-08 -7.020 -7.071 -0.051
PbCO3 4.126e-08 4.138e-08 -7.384 -7.383 0.001
Zn(CO3)2-2 3.906e-08 2.443e-08 -7.408 -7.612 -0.204
PbHCO3+ 3.995e-09 3.553e-09 -8.398 -8.449 -0.051
Pb(CO3)2-2 3.253e-10 2.035e-10 -9.488 -9.691 -0.204
CdHCO3+ 2.641e-10 2.348e-10 -9.578 -9.629 -0.051
FeHCO3+ 4.543e-11 4.040e-11 -10.343 -10.394 -0.051
FeCO3 5.145e-12 5.160e-12 -11.289 -11.287 0.001
CdCO3 3.131e-12 3.141e-12 -11.504 -11.503 0.001
Cd(CO3)2-2 3.108e-14 1.944e-14 -13.507 -13.711 -0.204
Ca 1.523e-03
Ca+2 1.359e-03 8.644e-04 -2.867 -3.063 -0.196
CaSO4 8.345e-05 8.370e-05 -4.079 -4.077 0.001
CaHCO3+ 4.971e-05 4.441e-05 -4.304 -4.353 -0.049
CaHPO4 2.484e-05 2.491e-05 -4.605 -4.604 0.001
CaCO3 3.306e-06 3.316e-06 -5.481 -5.479 0.001
CaH2PO4+ 2.035e-06 1.810e-06 -5.691 -5.742 -0.051
CaPO4- 7.525e-07 6.693e-07 -6.123 -6.174 -0.051
CaOH+ 1.613e-09 1.434e-09 -8.792 -8.843 -0.051
CaHSO4+ 6.043e-11 5.374e-11 -10.219 -10.270 -0.051
Cd 4.451e-09
Cd+2 3.229e-09 2.020e-09 -8.491 -8.695 -0.204
CdCl+ 6.667e-10 5.929e-10 -9.176 -9.227 -0.051
CdSO4 2.758e-10 2.766e-10 -9.559 -9.558 0.001
CdHCO3+ 2.641e-10 2.348e-10 -9.578 -9.629 -0.051
CdCl2 7.591e-12 7.614e-12 -11.120 -11.118 0.001
CdCO3 3.131e-12 3.141e-12 -11.504 -11.503 0.001
CdOH+ 3.114e-12 2.769e-12 -11.507 -11.558 -0.051
Cd(SO4)2-2 2.120e-12 1.326e-12 -11.674 -11.877 -0.204
Cd(CO3)2-2 3.108e-14 1.944e-14 -13.507 -13.711 -0.204
CdCl3- 1.797e-14 1.598e-14 -13.745 -13.796 -0.051
Cd(OH)2 8.990e-16 9.017e-16 -15.046 -15.045 0.001
Cd(OH)3- 1.137e-21 1.011e-21 -20.944 -20.995 -0.051
Cd(OH)4-2 1.441e-28 9.011e-29 -27.841 -28.045 -0.204
Cl 3.387e-03
Cl- 3.387e-03 3.005e-03 -2.470 -2.522 -0.052
MnCl+ 2.407e-08 2.141e-08 -7.619 -7.669 -0.051
ZnCl+ 1.830e-08 1.628e-08 -7.737 -7.788 -0.051
CdCl+ 6.667e-10 5.929e-10 -9.176 -9.227 -0.051
PbCl+ 1.934e-10 1.720e-10 -9.713 -9.764 -0.051
ZnCl2 5.247e-11 5.263e-11 -10.280 -10.279 0.001
MnCl2 2.800e-11 2.808e-11 -10.553 -10.552 0.001
CdCl2 7.591e-12 7.614e-12 -11.120 -11.118 0.001
PbCl2 7.202e-13 7.224e-13 -12.143 -12.141 0.001
FeCl+ 5.126e-13 4.558e-13 -12.290 -12.341 -0.051
ZnCl3- 2.078e-13 1.848e-13 -12.682 -12.733 -0.051
MnCl3- 2.614e-14 2.324e-14 -13.583 -13.634 -0.051
CdCl3- 1.797e-14 1.598e-14 -13.745 -13.796 -0.051
PbCl3- 2.021e-15 1.798e-15 -14.694 -14.745 -0.051
ZnCl4-2 4.693e-16 2.936e-16 -15.329 -15.532 -0.204
FeCl+2 2.728e-17 1.707e-17 -16.564 -16.768 -0.204
PbCl4-2 4.354e-18 2.723e-18 -17.361 -17.565 -0.204
FeCl2+ 2.080e-19 1.850e-19 -18.682 -18.733 -0.051
FeCl3 5.543e-23 5.560e-23 -22.256 -22.255 0.001
Cu(1) 1.294e-12
Cu+ 1.294e-12 1.143e-12 -11.888 -11.942 -0.054
Cu(2) 7.874e-08
Cu(OH)2 4.258e-08 4.271e-08 -7.371 -7.369 0.001
Cu+2 3.187e-08 2.045e-08 -7.497 -7.689 -0.193
CuOH+ 2.301e-09 2.045e-09 -8.638 -8.689 -0.051
CuSO4 1.988e-09 1.994e-09 -8.702 -8.700 0.001
Cu(OH)3- 2.893e-14 2.573e-14 -13.539 -13.590 -0.051
Cu(OH)4-2 8.204e-20 5.132e-20 -19.086 -19.290 -0.204
Fe(2) 2.576e-10
Fe+2 1.712e-10 1.099e-10 -9.767 -9.959 -0.193
FeHCO3+ 4.543e-11 4.040e-11 -10.343 -10.394 -0.051
FeHPO4 2.021e-11 2.027e-11 -10.694 -10.693 0.001
FeSO4 1.004e-11 1.007e-11 -10.998 -10.997 0.001
FeCO3 5.145e-12 5.160e-12 -11.289 -11.287 0.001
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FeH2PO4+ 4.451e-12 3.958e-12 -11.352 -11.403 -0.051
FeOH+ 6.465e-13 5.750e-13 -12.189 -12.240 -0.051
FeCl+ 5.126e-13 4.558e-13 -12.290 -12.341 -0.051
FeHSO4+ 7.682e-18 6.832e-18 -17.115 -17.165 -0.051
Fe(HS)2 0.000e+00 0.000e+00 -180.386 -180.385 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -267.985 -268.036 -0.051
Fe(3) 1.789e-07
Fe(OH)3 1.074e-07 1.077e-07 -6.969 -6.968 0.001
Fe(OH)2+ 7.008e-08 6.233e-08 -7.154 -7.205 -0.051
Fe(OH)4- 1.448e-09 1.288e-09 -8.839 -8.890 -0.051
FeOH+2 2.331e-11 1.458e-11 -10.633 -10.836 -0.204
FeH2PO4+2 4.696e-15 2.937e-15 -14.328 -14.532 -0.204
FeHPO4+ 2.653e-15 2.360e-15 -14.576 -14.627 -0.051
FeSO4+ 9.905e-16 8.809e-16 -15.004 -15.055 -0.051
Fe+3 3.785e-16 1.519e-16 -15.422 -15.819 -0.397
FeCl+2 2.728e-17 1.707e-17 -16.564 -16.768 -0.204
Fe(SO4)2- 1.014e-17 9.017e-18 -16.994 -17.045 -0.051
FeCl2+ 2.080e-19 1.850e-19 -18.682 -18.733 -0.051
Fe2(OH)2+4 2.827e-20 4.329e-21 -19.549 -20.364 -0.815
FeHSO4+2 3.791e-22 2.372e-22 -21.421 -21.625 -0.204
FeCl3 5.543e-23 5.560e-23 -22.256 -22.255 0.001
Fe3(OH)4+5 5.678e-25 3.026e-26 -24.246 -25.519 -1.273
H(0) 1.320e-31
H2 6.600e-32 6.620e-32 -31.180 -31.179 0.001
K 7.933e-04
K+ 7.904e-04 7.013e-04 -3.102 -3.154 -0.052
KSO4- 2.840e-06 2.526e-06 -5.547 -5.598 -0.051
KHPO4- 7.125e-08 6.337e-08 -7.147 -7.198 -0.051
KOH 2.424e-11 2.431e-11 -10.616 -10.614 0.001
Mg 2.058e-03
Mg+2 1.802e-03 1.155e-03 -2.744 -2.937 -0.193
MgSO4 1.464e-04 1.468e-04 -3.834 -3.833 0.001
MgHCO3+ 5.791e-05 5.150e-05 -4.237 -4.288 -0.051
MgHPO4 4.488e-05 4.502e-05 -4.348 -4.347 0.001
MgH2PO4+ 3.464e-06 3.081e-06 -5.460 -5.511 -0.051
MgCO3 2.392e-06 2.400e-06 -5.621 -5.620 0.001
MgPO4- 1.357e-06 1.207e-06 -5.867 -5.918 -0.051
MgOH+ 8.670e-08 7.710e-08 -7.062 -7.113 -0.051
Mn(2) 3.825e-06
Mn+2 2.724e-06 1.749e-06 -5.565 -5.757 -0.193
MnHCO3+ 6.443e-07 5.730e-07 -6.191 -6.242 -0.051
MnCO3 2.711e-07 2.719e-07 -6.567 -6.566 0.001
MnSO4 1.607e-07 1.612e-07 -6.794 -6.793 0.001
MnCl+ 2.407e-08 2.141e-08 -7.619 -7.669 -0.051
MnOH+ 8.755e-10 7.786e-10 -9.058 -9.109 -0.051
MnCl2 2.800e-11 2.808e-11 -10.553 -10.552 0.001
MnCl3- 2.614e-14 2.324e-14 -13.583 -13.634 -0.051
Mn(NO3)2 0.000e+00 0.000e+00 -55.739 -55.737 0.001
Mn(3) 4.158e-24
Mn+3 4.158e-24 1.447e-24 -23.381 -23.840 -0.458
N(-3) 5.615e-36
NH4+ 5.538e-36 4.891e-36 -35.257 -35.311 -0.054
NH3 4.472e-38 4.486e-38 -37.349 -37.348 0.001
NH4SO4- 3.229e-38 2.871e-38 -37.491 -37.542 -0.051
N(0) 4.287e-03
N2 2.143e-03 2.150e-03 -2.669 -2.668 0.001
N(3) 4.083e-26
NO2- 4.083e-26 3.613e-26 -25.389 -25.442 -0.053
N(5) 5.839e-26
NO3- 5.839e-26 5.168e-26 -25.234 -25.287 -0.053
PbNO3+ 1.046e-33 9.298e-34 -32.981 -33.032 -0.051
Mn(NO3)2 0.000e+00 0.000e+00 -55.739 -55.737 0.001
Na 1.872e-03
Na+ 1.864e-03 1.660e-03 -2.730 -2.780 -0.050
NaSO4- 4.449e-06 3.956e-06 -5.352 -5.403 -0.051
NaHCO3 3.421e-06 3.432e-06 -5.466 -5.464 0.001
NaHPO4- 1.686e-07 1.500e-07 -6.773 -6.824 -0.051
NaCO3- 9.559e-08 8.501e-08 -7.020 -7.071 -0.051
NaOH 1.093e-10 1.096e-10 -9.961 -9.960 0.001
O(0) 2.846e-28
O2 1.423e-28 1.427e-28 -27.847 -27.846 0.001
P 2.326e-04
H2PO4- 8.073e-05 7.187e-05 -4.093 -4.143 -0.050
HPO4-2 7.432e-05 4.634e-05 -4.129 -4.334 -0.205
MgHPO4 4.488e-05 4.502e-05 -4.348 -4.347 0.001
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CaHPO4 2.484e-05 2.491e-05 -4.605 -4.604 0.001
MgH2PO4+ 3.464e-06 3.081e-06 -5.460 -5.511 -0.051
CaH2PO4+ 2.035e-06 1.810e-06 -5.691 -5.742 -0.051
MgPO4- 1.357e-06 1.207e-06 -5.867 -5.918 -0.051
CaPO4- 7.525e-07 6.693e-07 -6.123 -6.174 -0.051
NaHPO4- 1.686e-07 1.500e-07 -6.773 -6.824 -0.051
KHPO4- 7.125e-08 6.337e-08 -7.147 -7.198 -0.051
PO4-3 6.920e-10 2.390e-10 -9.160 -9.622 -0.462
FeHPO4 2.021e-11 2.027e-11 -10.694 -10.693 0.001
FeH2PO4+ 4.451e-12 3.958e-12 -11.352 -11.403 -0.051
FeH2PO4+2 4.696e-15 2.937e-15 -14.328 -14.532 -0.204
FeHPO4+ 2.653e-15 2.360e-15 -14.576 -14.627 -0.051
Pb 4.830e-08
PbCO3 4.126e-08 4.138e-08 -7.384 -7.383 0.001
PbHCO3+ 3.995e-09 3.553e-09 -8.398 -8.449 -0.051
Pb+2 1.945e-09 1.216e-09 -8.711 -8.915 -0.204
Pb(CO3)2-2 3.253e-10 2.035e-10 -9.488 -9.691 -0.204
PbSO4 3.108e-10 3.117e-10 -9.508 -9.506 0.001
PbOH+ 2.666e-10 2.371e-10 -9.574 -9.625 -0.051
PbCl+ 1.934e-10 1.720e-10 -9.713 -9.764 -0.051
Pb(SO4)2-2 1.192e-12 7.456e-13 -11.924 -12.128 -0.204
Pb(OH)2 9.195e-13 9.222e-13 -12.036 -12.035 0.001
PbCl2 7.202e-13 7.224e-13 -12.143 -12.141 0.001
PbCl3- 2.021e-15 1.798e-15 -14.694 -14.745 -0.051
Pb(OH)3- 1.190e-16 1.059e-16 -15.924 -15.975 -0.051
Pb2OH+3 1.856e-17 6.458e-18 -16.732 -17.190 -0.458
PbCl4-2 4.354e-18 2.723e-18 -17.361 -17.565 -0.204
Pb(OH)4-2 3.875e-21 2.424e-21 -20.412 -20.615 -0.204
PbNO3+ 1.046e-33 9.298e-34 -32.981 -33.032 -0.051
S(-2) 0.000e+00
HS- 0.000e+00 0.000e+00 -89.636 -89.688 -0.052
H2S 0.000e+00 0.000e+00 -89.832 -89.830 0.001
S-2 0.000e+00 0.000e+00 -95.207 -95.405 -0.199
Fe(HS)2 0.000e+00 0.000e+00 -180.386 -180.385 0.001
Fe(HS)3- 0.000e+00 0.000e+00 -267.985 -268.036 -0.051
S(6) 9.584e-04
SO4-2 7.209e-04 4.557e-04 -3.142 -3.341 -0.199
MgSO4 1.464e-04 1.468e-04 -3.834 -3.833 0.001
CaSO4 8.345e-05 8.370e-05 -4.079 -4.077 0.001
NaSO4- 4.449e-06 3.956e-06 -5.352 -5.403 -0.051
KSO4- 2.840e-06 2.526e-06 -5.547 -5.598 -0.051
ZnSO4 1.677e-07 1.682e-07 -6.776 -6.774 0.001
MnSO4 1.607e-07 1.612e-07 -6.794 -6.793 0.001
HSO4- 5.815e-09 5.172e-09 -8.235 -8.286 -0.051
CuSO4 1.988e-09 1.994e-09 -8.702 -8.700 0.001
Zn(SO4)2-2 9.455e-10 5.914e-10 -9.024 -9.228 -0.204
PbSO4 3.108e-10 3.117e-10 -9.508 -9.506 0.001
CdSO4 2.758e-10 2.766e-10 -9.559 -9.558 0.001
CaHSO4+ 6.043e-11 5.374e-11 -10.219 -10.270 -0.051
FeSO4 1.004e-11 1.007e-11 -10.998 -10.997 0.001
Cd(SO4)2-2 2.120e-12 1.326e-12 -11.674 -11.877 -0.204
Pb(SO4)2-2 1.192e-12 7.456e-13 -11.924 -12.128 -0.204
AlSO4+ 5.077e-13 4.515e-13 -12.294 -12.345 -0.051
Al(SO4)2- 7.549e-15 6.714e-15 -14.122 -14.173 -0.051
FeSO4+ 9.905e-16 8.809e-16 -15.004 -15.055 -0.051
Fe(SO4)2- 1.014e-17 9.017e-18 -16.994 -17.045 -0.051
FeHSO4+ 7.682e-18 6.832e-18 -17.115 -17.165 -0.051
AlHSO4+2 6.845e-21 4.282e-21 -20.165 -20.368 -0.204
FeHSO4+2 3.791e-22 2.372e-22 -21.421 -21.625 -0.204
NH4SO4- 3.229e-38 2.871e-38 -37.491 -37.542 -0.051
Zn 3.980e-06
Zn+2 2.361e-06 1.495e-06 -5.627 -5.825 -0.199
ZnHCO3+ 7.779e-07 6.918e-07 -6.109 -6.160 -0.051
ZnCO3 5.820e-07 5.838e-07 -6.235 -6.234 0.001
ZnSO4 1.677e-07 1.682e-07 -6.776 -6.774 0.001
Zn(CO3)2-2 3.906e-08 2.443e-08 -7.408 -7.612 -0.204
ZnOH+ 3.073e-08 2.733e-08 -7.512 -7.563 -0.051
ZnCl+ 1.830e-08 1.628e-08 -7.737 -7.788 -0.051
Zn(OH)2 1.875e-09 1.881e-09 -8.727 -8.726 0.001
Zn(SO4)2-2 9.455e-10 5.914e-10 -9.024 -9.228 -0.204
ZnCl2 5.247e-11 5.263e-11 -10.280 -10.279 0.001
ZnCl3- 2.078e-13 1.848e-13 -12.682 -12.733 -0.051
Zn(OH)3- 6.685e-14 5.945e-14 -13.175 -13.226 -0.051
ZnCl4-2 4.693e-16 2.936e-16 -15.329 -15.532 -0.204
Zn(OH)4-2 1.506e-19 9.419e-20 -18.822 -19.026 -0.204
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------------------------------Saturation indices-------------------------------
Phase SI log IAP log KT
Al(OH)3(a) -1.90 8.46 10.36 Al(OH)3
Alunite -3.23 -5.46 -2.23 KAl3(SO4)2(OH)6
Anglesite -4.50 -12.26 -7.75 PbSO4
Anhydrite -2.01 -6.40 -4.40 CaSO4
Aragonite -0.39 -8.77 -8.38 CaCO3
Calcite -0.25 -8.77 -8.52 CaCO3
Cd(OH)2 -8.34 5.31 13.65 Cd(OH)2
CdSO4 -11.69 -12.04 -0.34 CdSO4
Cerrusite -1.57 -14.62 -13.05 PbCO3
CO2(g) -1.57 -19.71 -18.14 CO2
Dolomite -0.17 -17.42 -17.25 CaMg(CO3)2
Fe(OH)3(a) 0.29 18.04 17.75 Fe(OH)3
FeS(ppt) -88.73 -125.30 -36.57 FeS
Gibbsite 0.73 8.46 7.73 Al(OH)3
Goethite 6.42 18.04 11.62 FeOOH
Gypsum -1.82 -6.40 -4.59 CaSO4:2H2O
H2(g) -28.00 -28.00 -0.00 H2
H2O(g) -1.34 -0.00 1.34 H2O
H2S(g) -88.76 -129.34 -40.58 H2S
Halite -6.90 -5.30 1.60 NaCl
Hausmannite -6.63 52.73 59.36 Mn3O4
Hematite 14.88 36.08 21.20 Fe2O3
Hydroxyapatite 3.70 -37.18 -40.88 Ca5(PO4)3OH
Jarosite-K -5.56 23.29 28.85 KFe3(SO4)2(OH)6
Mackinawite -88.00 -125.30 -37.30 FeS
Manganite -3.10 22.24 25.34 MnOOH
Melanterite -11.17 -13.30 -2.13 FeSO4:7H2O
N2(g) 0.61 -2.67 -3.28 N2
NH3(g) -38.98 -43.33 -4.35 NH3
O2(g) -24.85 56.00 80.85 O2
Otavite -2.30 -14.40 -12.10 CdCO3
Pb(OH)2 -2.83 5.08 7.92 Pb(OH)2
Pyrite -143.04 -226.64 -83.60 FeS2
Pyrochroite -6.96 8.24 15.20 Mn(OH)2
Pyrolusite -4.06 36.24 40.30 MnO2
Rhodochrosite -0.31 -11.47 -11.15 MnCO3
Siderite -4.74 -15.67 -10.93 FeCO3
Smithsonite -1.46 -11.53 -10.07 ZnCO3
Sphalerite -77.03 -121.17 -44.13 ZnS
Sulfur -66.55 -101.34 -34.79 S
Vivianite -13.12 -49.12 -36.00 Fe3(PO4)2:8H2O
Zn(OH)2(e) -3.33 8.17 11.50 Zn(OH)2
------------------
End of simulation.
------------------
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APPENDIX C: ASH ALKALINITY
STANDARDISATION OF STRONG ACID WITH WEAK BASE
Known volume of ~0.05 M hydrochloric acid, HCl, was standardised against
0.05 M sodium carbonate, Na2CO3, and Table 20 summarises the volume of Na2CO3 used
to reach endpoint.
Table 20. Standardisation of ~0.05 M HCl with 0.05 M Na2CO3
Trial Initial (ml) Final (ml) Titre (ml) 1 0 24.8 24.8 2 0 24.6 24.6 3 0 24.7 24.7 4 0 24.7 24.7 Mean titre 24.7 ± 0.02
Based on equation [5], two moles of HCl are required for every one mole of
Na2CO3. Stoichiometric calculations using equation [6] therefore show that 24.7 ml of
0.05 M Na2CO3 was required to reach endpoint with 50 ml of 0.0494 (or 0.05 M) M HCl.
2HCl (aq) + Na2CO3 (aq) ⇄ 2NaCl (aq) + H2O (l) + CO2 (g) [5]
c1v2 = c2v2 [6]
where, c1 and v1 is the concentration and volume of HCl, and c2 and v2 is the
concentration and volume of Na2CO3.
COMPARISON OF FINELY MILLED AND NON-MILLED SAMPLES
With regards to the preparation of hay samples for ash alkalinity determination,
results showed no significant difference between finely milled and non-milled hay
samples (P = 0.99). Table 21 summarises these results for the November 2013 to January
2014 growth cycle.
NEUTRALISING EXCESS ALKALINITY TO PREVENT SOIL ALKALINISATION
The equivalent quantity of sulphuric required to neutralise net alkalinity gained
from irrigation can be calculated. The mean net gain in alkalinity in the system was
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approximately 409 (± 51) kg CaCO3/ha between November 2013 and January 2014
growth cycle. This is equivalent to a mean total alkalinity of 185 (± 2) mg CaCO3/L
present in excess in irrigation water (Table 22). This shows that pasture production has
the capacity to neutralise approximately 45 mg CaCO3/L and thus the remaining 185 mg
CaCO3/L should be neutralised by equivalent quantities of H2SO4 to cease soil
alkalinisation.
Due to 1:1 acid:base stoichiometry, the number of moles of H2SO4 is equivalent
to the number of moles of CaCO3. Therefore, assuming 1.83 x 10-3 mol CaCO3 is present
in excess for every 1 L of irrigation water, approximately 1.83 x 10-3 mol of H2SO4 is
required to completely neutralise CaCO3. According to equation [6], the acid can be
prepared by adding 1.0 ml H2SO4 (98%, 18.4 M) to 100 ml deionised water and diluted
to 10.0 L. That is, for every 10 L of irrigation water, 1 ml of 18.4 M H2SO4 is required for
neutralisation.
Table 21. Comparing ash alkalinity and net alkalinity results for finely milled and non-milled
duplicate hay subsamples for Pivots 1-5 between November 2013 and January 2014
Pivot #
Total alkalinity
from irrigation (kg
CaCO3 /ha)
Ash alkalinity (kg CaCO3 /ha)
Net alkalinity (kg CaCO3 /ha): added - removed
Milled Non-milled Milled Non-milled
1 408.0 94 81 314 327
1 408.0 94 89 314 319
2 667.0 119 140 548 527
2 667.0 146 134 521 533
3 645.4 116 136 529 509
3 645.4 121 110 524 536
4 457.7 97 80 361 377
4 457.7 86 85 372 373
5 360.6 58 69 303 291
5 360.6 62 65 299 295
Mean 99 (± 9) 99 (± 9) 409 (± 34) 409 (± 33)
Min 58 65 299 291
Max 146 140 548 536
Table 22. Calculated excess total alkalinity (mg CaCO3/L) in irrigation water to be neutralised
by sulphuric acid (H2SO4) to cease soil alkalinisation, based on results in Table 17
Pivot # Gross
irrigation (ML/ha)
Total alkalinity (mg CaCO3/L) in irrigation water
Overall net gain in alkalinity (kg
CaCO3/ha) from irrigation
*Excess total alkalinity (mg CaCO3/L) in irrigation water
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1 1.774 230 314.0 (± 0.1) 177.0 (± 0.0)
2 2.900 230 534.7 (± 13.4) 184.4 (± 4.6)
3 2.806 230 526.6 (± 2.6) 187.7 (± 0.9)
4 1.990 230 366.5 (± 5.5) 184.2 (± 2.8)
5 1.568 230 300.9 (± 1.9) 191.9 (± 1.2)
Overall mean 408.6 (± 51.1) 185.0 (± 2.4)
*excess total alkalinity (mg CaCO3/L) in irrigation water to be neutralized
117
APPENDIX D: CLUSTER ANALYSIS – STRATIFYING IRRIGATION
PIVOTS
As an exploratory data analysis tool that combines the principles of hierarchical
and partitioning methods, the SPSS two-step cluster analysis was used to stratify the
remaining 10 irrigation pivots by their soil characteristics. One-way ANOVA and
bivariate correlation analysis were also used in diagnostics for determining suitable soil
properties for cluster analysis. Here, cluster analysis is used to identify representative
pivots for future monitoring where stratified sampling can be achieved.
RESULTS
Two independent variables were selected from a suite of soil properties to
construct a specified 4-cluster solution, employing Span 3 results from December 2013
at the 20-30 cm soil layer. Additionally, soil particle size from March 2014 was used to
determine if pivots were similar by soil texture (e.g., clay percentage). Two variables
were used since using too many could increase the odds that the variables are "no longer
dissimilar" (Mooi and Sarstedt, 2011). Suitable variables should not be highly correlated
with one another (Table 7) and not be significantly different between monitoring spans
(Table 1).
As the quality of variables will reflect the quality of the cluster solution, multiple
tests were performed using different combinations of 'high quality' solutions. The quality
of these solutions can be determined by the ‘predictor importance’ generated from the
output data. Variables equally important in the clustering algorithm are considered a
good combination and hence should reflect a high quality cluster solution. Figure 49
provides an example of a three-variable combination.
Three cluster solutions were selected from a variety of tests and the cluster
membership of each pivot is summarised in Table 23 and colour-coded for convenience.
Of the 10 pivots, results show distinct groups of pivots that are similar in all three tests:
(a) Pivots 2 and 3, (b) Pivots 6, 7 and 11, and (c) Pivots 8 and 10.
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Figure 49. Comparing a good combination (left) and a bad combination (right) of three variables
used in two-step cluster analysis
Table 23. Designated cluster memberships for irrigation pivots using a specified 4-cluster
solution, based on Span 3 soil properties from December 2013 and particle size from March
2014 at the 20-30 cm layer. Colour coding is independent for each test.
Pivot # Test 1: EC, Ex. Al% Test 2: CCE, C/N ratio Test 3: clay%, As
1 2 4 1
2* 2 1 2
3* 2 1 2
4 1 3 2
5 3 2 4
6* 3 4 3
7* 3 4 3
8* 4 4 3
10* 4 4 3
11* 3 4 3
*consistent clustering of irrigation pivots throughout all three tests
Test 1 (Figure 50) shows Pivots 2 and 3 were grouped in Cluster 2, with a mean
EC of 0.20 dS/m and a mean exchangeable Al percentage of 1.2%. Pivots 6, 7 and 11 were
grouped in Cluster 3, with a mean EC of 0.13 dS/m and a mean exchangeable Al
percentage of 2.3%. Lastly, Pivots 8 and 10 were grouped in Cluster 4, with a mean EC of
0.20 dS/m and a mean exchangeable Al percentage of 2.1%.
Test 2 (Figure 51) shows Pivots 2 and 3 were grouped in Cluster 1, with a mean
CCE of 0.39% and a mean C/N ratio of 5.0. Pivots 6, 7, 8, 10 and 11 were grouped together
in Cluster 4, with a mean CCE of 0.22% and a mean C/N ratio of 5.3.
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Figure 50. Test 1 clustering of 10 active irrigation pivots at the HAP, based on electrical
conductivity (EC, dS/m) and exchangeable Al percentage (%) and colour coded: Cluster 1
(red), Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green).
Figure 51. Test 2 clustering of 10 active irrigation pivots at the HAP, based on CaCO3
equivalent (CCE, %) and carbon/nitrogen (C/N) ratio and colour coded: Cluster 1 (red),
Cluster 2 (blue), Cluster 3 (purple) and Cluster 4 (green).
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Test 3 (Figure 52) shows Pivots 2 and 3 were grouped in Cluster 2, with a mean
clay content of 28.8% and a mean As concentration of 14.2 mg/kg. Pivots 6, 7, 8, 10 and
11 were grouped together in Cluster 3, with a mean clay content of 26.6% and a mean As
concentration of 16.2 mg/kg.
Figure 52. Test 3 clustering of 10 active irrigation pivots at the HAP, based on clay content
(%) and arsenic concentration (mg As/kg) and colour coded: Cluster 1 (red), Cluster 2 (blue),
Cluster 3 (purple) and Cluster 4 (green).
Consistent with all three cluster solutions, Pivots 2 and 3, Pivots 6, 7 and 11, and
Pivots 8 and 10 are, to a degree, similar in terms of EC, CCE, C/N ratio, exchangeable Al
percentage, As concentration and clay content. One-way ANOVA was also used to identify
any significant differences in soil properties among these clusters (Table 24), as
summarised:
1. Clusters in Test 1 were significantly different in exchangeable Ca (P < 0.05) and
Na concentrations (P < 0.05), exchangeable Ca (P < 0.01) and Mg percentages (P
< 0.01), and As (P < 0.01) and Cd concentrations (P = 0.05).
2. Clusters in Test 2 were significantly different in OC (P < 0.05), and exchangeable
Ca (P = 0.01) and Mg percentages (P < 0.01).
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3. Clusters in Test 3 were significantly different in OC (P = 0.05), C/N ratio (P < 0.05),
PRI (P < 0.05), exchangeable Al concentration (P < 0.05) and percentage (P <
0.01), and sand content (P < 0.05).
It is uncertain as to why Pivots 4 and 5 were not similar given their close
proximity and similar gross irrigation use (Figure 53). However, Pivot 1 was somewhat
similar to Pivots 2 and 3 (Test 1), and Pivots 6, 7, 8, 10 and 11 (Test 2), but this was not
confirmed in Test 3. Nonetheless, stratified monitoring is an option where only
representative pivots of the irrigated HAP area are monitored rather than every pivot.
From the three groups presented, it is then possible to decide which pivots require
monitoring. For example, monitoring may cease in Pivots 3, 7, 10 and 11, leaving the
remaining six (Pivots 1, 2, 4, 5, 6 and 8) to be routinely monitored. However, note cluster
analysis cannot guarantee absolute similarity since: (1) results depend on the variables
used (i.e., soil properties), (2) soil properties change over time and with irrigation, (2)
results are only as accurate as the data provided, and (3) random error due to variability.
Table 24. One-way ANOVA between clusters for soil properties at 20-30 cm, using Span 3
December 2013 results
Parameters Test 1 Test 2 Test 3
F P F P F P Electrical conductivity, EC - - 1.88 0.23 1.59 0.29 pHCa 1.49 0.31 0.70 0.58 0.85 0.52 CaCO3 equivalent, CCE 1.30 0.36 - - 3.93 0.07 Organic carbon, OC 0.30 0.83 6.51 0.03 4.78 0.05 NO3-N 2.80 0.13 1.60 0.29 4.00 0.07 NH4-N 0.70 0.59 1.60 0.29 0.70 0.59 Total N 0.50 0.69 0.40 0.76 0.57 0.65 C/N ratio 0.62 0.63 - - 5.68 0.03 Colwell P - - 3.04 0.11 4.30 0.06 Total P 0.61 0.63 1.89 0.23 2.40 0.17 Phosphorus retention index, PRI 0.26 0.85 3.03 0.12 6.92 0.02 Colwell K 1.89 0.23 2.62 0.15 2.04 0.21 Total K 1.75 0.26 3.69 0.08 2.39 0.17 Ex. Ca 5.34 0.04 3.07 0.11 1.41 0.33 Ex. Mg 1.50 0.31 0.34 0.80 1.16 0.40 Ex. Na 6.33 0.03 1.63 0.28 4.06 0.07 Ex. K 2.37 0.17 2.39 0.17 1.30 0.36 Ex. Al 3.95 0.07 0.56 0.66 6.29 0.03 ECEC 3.58 0.09 1.90 0.23 1.41 0.33 Ex. Ca percentage 16.43 0.00 10.20 0.01 1.16 0.40 Ex. Mg percentage 17.05 0.00 16.63 0.00 1.09 0.42 Ex. Na percentage, ESP 1.33 0.35 0.48 0.71 1.38 0.34 Ex. K percentage 0.13 0.94 2.29 0.18 2.12 0.20 Ex. Al percentage - - 1.13 0.41 18.44 0.00 As 14.10 0.00 1.39 0.33 - - Cd 5.10 0.04 0.91 0.49 0.93 0.48 Cr 2.67 0.14 1.01 0.45 1.42 0.33
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Pb 2.49 0.16 0.57 0.65 0.78 0.55 Sand 1.33 0.35 1.13 0.41 5.77 0.03 Silt 0.36 0.79 0.12 0.95 0.64 0.62 Clay 1.63 0.28 1.13 0.41 - -
Figure 53. Gross irrigation volumes used at each irrigation pivot at the Hamersley Agricultural Project (HAP) for the baseline (blue) period, and periods between
baseline and December 2013 (red), and baseline and February 2014 (green), based on unpublished data (Rio Tinto Iron Ore, 2014).
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
Gro
ss ir
riga
tio
n (
ML/
ha)
Irrigation pivot
Gross irrigation (ML/ha) duringbaseline period (October 2012 toFebruary 2013)
Gross irrigation (ML/ha) betweenbaseline period (October 2012 toFebruary 2013) and December2013
Gross irrigation (ML/ha) betweenbaseline period (October 2012 toFebruary 2013) and February 2014
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TEST 1: ELECTRICAL CONDUCTIVITY AND EXCHANGEABLE ALUMINIUM PERCENTAGE
Figure 54. Level of importance of variables (EC and exchangeable Al %) used
in test 1
Figure 55. Description of cluster size and mean values for variables (EC and
exchangeable Al %) in test 1
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Figure 56. Comparing the distribution of individual clusters in test 1 (EC and exchangeable Al %) with the overall distribution of the December 2013 soil (20-30
cm layer, Span 3) data set
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TEST 2: CALCIUM CARBONATE EQUIVALENT AND CARBON/NITROGEN RATIO
Figure 57. Level of importance of variables (CCE and C/N ratio) used in test
2
Figure 58. Description of cluster size and mean values for variables (CCE and C/N
ratio) in test 2
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Figure 59. Comparing the distribution of individual clusters in test 2 (CCE and C/N ratio) with the overall distribution of the December 2013 soil (20-30 cm layer,
Span 3) data set
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TEST 3: CLAY CONTENT AND ARSENIC CONCENTRATION
Figure 60. Level of importance of variables (clay % and As concentration)
used in test 3
Figure 61. Description of cluster size and mean values for variables (clay % and
As concentration) in test 3
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Figure 62. Comparing the distribution of individual clusters in test 3 (clay % and As concentration) with the overall distribution of the December 2013 soil (20-
30 cm layer, Span 3) data set
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APPENDIX E: SOIL CARBONATE DETERMINATION – A
METHODOLOGY DEVELOPMENT EXERCISE
METHODS AND MATERIALS
Two routine methods for determination of soil CaCO3 equivalent (CCE) were
used in a methodology development exercise to: (1) verify the CCE of several September
2013 and December 2013 samples from the HAP; and, (2) determine the precision and
accuracy of Method 1 and 2 for carbonate determine based on standard additions of
CaCO3.
METHOD 1
Method 1 is a procedure based on pressure changes in carbon dioxide, CO2, from
reaction with dilute hydrochloric acid, HCl (see Rayment and Lyons, 2011, p. 420). The
pressure is measured in a closed vessel at constant temperature using a corrosion-
resistant gas pressure transducer with a direct current voltage. Assuming the reaction
goes to completion, the pressure increase is proportional to the amount of carbonate in
the soil (Rayment and Lyons, 2011). This method was performed externally by the CSBP
Soil and Plant Analysis Laboratory, Western Australia.
METHOD 2
An alternative procedure involves measuring the pH of the soil supernatant after
reaction with dilute acetic acid, CH3COOH (Loeppert et al., 1984, Moore et al., 1987). The
equivalent CaCO3 content is empirically calculated from the pH by means of an algorithm
obtained from calibration runs using standards prepared from known masses of CaCO3
(Ashworth, 1997).
Soils were air-dried and weighed to 2.0 g (< 2 mm particle size) to the nearest 1
mg and transferred to 50 ml polypropylene centrifuge tubes. The standard curve was
prepared using 2.0 g samples with known masses of powdered CaCO3: 10, 30, 50, 70, 90,
110 and 130 mg CaCO3. Note, the sole use of CaCO3 in calibration runs (e.g., Loeppert et
al., 1984, Moore et al., 1987) was highlighted by Ashworth (1997) to give "false positive"
readings for soils with no free lime (e.g., acidic soils). Thus, to reduce this tendency, tests
were calibrated against soils amended with known weights of CaCO3 and not pure CaCO3
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alone (Ashworth, 1997). As a further modification to Ashworth (1997), standards were
added with deionised water to form a saturated paste/mixture and later left to air-dry in
a glasshouse for a week. This aims to encourage physical and chemical bonding between
soil and CaCO3 particles similar to how carbonates would naturally occur in the soil
environment. Samples were stirred to break up any remaining aggregates.
All samples were treated with 25 ml aliquot of 0.4 M acetic acid and swirled by
hand for 10 seconds before being placed on a reciprocating shaking water bath (model
RW1812) for approximately 16 hours overnight. To allow the evolved CO2 gas to escape
as well as minimising the evaporative losses of H2O and CH3COOH, all lids were
punctured with nine 1 mm pinholes. Following total dissolution and equilibration, the
pH of the supernatant was determined using a HI8424 pH meter, swirling by hand for 1
minute and allowing the suspension to settle for another minute before recording.
The addition of a known excess quantity of acetic acid, CH3COOH, to a given
quantity of sample is based on the reaction with soil carbonates, as summarised below:
CaCO3 + 2CH3COOH → Ca2+ + 2CH3OO- + H2O + CO2 [7]
The equivalents of CH3COO- produced by the reaction are stoichiometrically
equal to the equivalents of CaCO3 dissolved from the soil sample (Moore et al., 1987). The
dissolution of acetic acid in equation [7] is expressed as:
CH3COOH ⇄ H+ + CH3COO- [8]
In terms of pH, the thermodynamic equilibrium expression of equation [8] is:
pH = pKa + log [CH3COO−]
[CH3COOH] [9]
and, based on the assumption that the quantity of CH3COO- is proportional to
equivalents of CaCO3, equation [9] may be rewritten as:
pH = 𝑎 × log [CaCO3
𝑇−CaCO3] + 𝑏
[10]
where, T is the total amount of CaCO3 (i.e., 500 mg) for complete neutralisation
with the added 25 ml aliquot of 0.4 M acetic acid; CaCO3 is the unknown amount of CaCO3
(mg) present in the sample; and coefficients a and b are the gradient and y-intercept of
the standard curve, respectively. In accordance with equation [10], the plot of pH versus
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log[CaCO3 / (T – CaCO3)] is linear, thus the CaCO3 content (mg) of a soil sample can be
empirically determined (Figure 63).
Figure 63. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights
of 10, 30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.767x + 4.409 and
R2 = 0.996)
To determine CCE, equation [10] was combined with equation [11]:
CCE = CaCO3
𝑆× 100
[11]
where, S is the air-dried soil weight (mg), to form equation [12]:
CCE = 100𝑇
𝑆(1+10[(𝑏−pH) 𝑎⁄ ])
[12]
PRECISION AND ACCURACY OF METHODS 1 AND 2
Standard additions of CaCO3 prepared from three unknown soil samples were
used to assess the precision and accuracy of Methods 1 and 2. To determine appropriate
CaCO3 weights for standard additions, preliminary tests were conducted using Method
3.0
3.2
3.4
3.6
3.8
4.0
4.2
-2.0 -1.5 -1.0 -0.5 0.0
pH
log[CaCO3 / (T - CaCO3)]
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2, based on the standard curve from Figure 63. Results indicate samples contained an
average CCE of 0.20% (or ~2.0 mg/g; Table 25) and hence bulk samples were prepared
with standard additions of 0, 2, 4, 6, 8, 10 and 100 mg CaCO3/g.
Table 25. Preliminary CaCO3 content (mg) and calculated CaCO3 equivalent (CCE, %) of
unknown samples using Method 2
Sample Trial CaCO3 (mg) in
2 g soil CCE (%)
A 1 3.30 0.17 2 3.40 0.17 3 3.02 0.15 B 1 4.19 0.21 2 4.19 0.21 3 3.61 0.18 C 1 5.17 0.26 2 4.87 0.24 3 4.72 0.24 Mean 4.05 (± 0.25) 0.20 (± 0.01)
RESULTS
Since carbonate should not persist as stable compounds in acid soils due to
neutralisation, an overall mean CCE of 0.23% (or 2300 mg/kg CaCO3) in soils with pHCa
~5.0 (see Table 3 and 4) raised question about the accuracy of CaCO3 determination
using Method 1. The CCE of 8 samples from both September and December 2013 batches
were thus verified using Method 2 and a re-calibrated standard curve (Figure 64).
Figure 64. Standard curve for Method 2 using 0.4 M CH3COOH and CaCO3 weights of
10, 30, 50, 70, 90, 110 and 130 mg (linear relationship: y = 0.772x + 4.435 and R2 =
0.999)
3.0
3.2
3.4
3.6
3.8
4.0
4.2
-2.0 -1.5 -1.0 -0.5 0.0
pH
log[CaCO3 / (T - CaCO3)]
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Results showed soil CCE reported by Method 1 were 0.17% ± 0.03% higher than
values reported by Method 2 (Table 26) – i.e., roughly double. When plotted together
(Figure 65), CCE values from Methods 1 and 2 did not correlate which may further raise
question about analytical error. To further compare results, CCE values were plotted
against their respective soil pHCa (Figure 66). However, results showed no correlation
between pHCa and Method 1 (R2 = 0.00), although a moderate positive correlation is
evident with Method 2 (R2 = 0.56).
Table 26. Comparing calcium carbonate equivalent (CCE, %) assessed by Method 1 and 2 for
eight September 2013 and December 2013 soil samples and their respective soil pHCa values –
pivot and span denoted as ‘P’ and ‘S’, respectively
R² = 0.020.05
0.07
0.09
0.11
0.13
0.15
0.17
0.19
0.21
0 0.1 0.2 0.3 0.4 0.5 0.6
Me
tho
d 2
(%
)
Method 1 (%)
Sample Depth (cm) pHCa
CCE (%) Difference in CCE (%, M1-M2) Method 1 (M1) Method 2 (M2)
Sep
tem
ber
20
13
P2-S1 0-10 6.6 0.28 0.18 0.10 P5-S1 20-30 5.8 0.31 0.16 0.15 P6-S2 20-30 5.0 0.28 0.13 0.15 P12-S1 20-30 4.9 0.30 0.11 0.19 P14-S2 0-10 6.0 0.31 0.12 0.19 P17-S1 0-10 6.9 0.44 0.19 0.25 P17-S3 0-10 6.5 0.17 0.18 -0.01 P17-S3 20-30 5.6 0.10 0.14 -0.04
Dec
emb
er 2
01
3
P1-S1 0-10 6.7 0.19 0.16 0.03 P2-S3 20-30 4.9 0.37 0.10 0.27 P3-S3 20-30 5.5 0.41 0.11 0.30 P4-S1 20-30 5.1 0.46 0.11 0.35 P5-S1 20-30 6.1 0.24 0.11 0.13 P6-S1 0-10 6.4 0.51 0.13 0.38 P8-S1 0-10 6.8 0.29 0.14 0.15 P11-S3 20-30 5.2 0.19 0.10 0.09
Mean 0.30 (± 0.03) 0.14 (± 0.01) 0.17 (± 0.03)
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Figure 65. Calcium carbonate equivalent (CCE, %) of eight September 2013 and
December 2013 soil samples determined by Methods 1 and 2
Figure 66. Correlation between pH (CaCl2) and calcium carbonate equivalent (CCE, %) of eight
September and December 2013 soil samples determined using Method 1 (left) and Method 2
(right)
By making standard additions of 0, 2, 4, 6, 8, 10 and 100 mg/g CaCO3, reported
CCE values from Methods 1 and 2 were compared with expected values (Table 27).
Expected values were calculated from the sum of CaCO3 added and the mean CCE of soil
samples (0.20% ± 0.01%).
Table 27. Comparing expected soil calcium carbonate equivalent (CCE, %) and reported values
from Methods 1 and 2 using standard additions of 0, 2, 4, 6, 8, 10 and 100 mg CaCO3/g
Standard additions (mg CaCO3/g)
Expected CCE (%)
Reported CCE (%) Method 1 Method 2
0 0.20 0.32 0.21 (± 0.00) 2 0.40 0.79 0.28 (± 0.01) 4 0.60 0.81 0.30 (± 0.01) 6 0.80 1.04 0.47 (± 0.02) 8 1.00 1.26 0.47 (± 0.00) 10 1.20 1.43 0.64 (± 0.00) 100 10.20 11.54 8.27 (± 0.13) Reported values from Method 2 are a mean (± SE) of 3 replicates.
In Figure 67, standard additions of 100 mg/g CaCO3 were not included (outlier).
Results showed the reported CCE values from Method 1 were 0.24% ± 0.04% higher than
expected, while values reported from Method 2 were 0.31% ± 0.09% lower than
expected (Figure 67). By and large, CCE values reported from Method 1 were 0.55% ±
R² = 0.000
0.1
0.2
0.3
0.4
0.5
0.6
4.5 5.0 5.5 6.0 6.5 7.0 7.5
Me
tho
d 1
(%
)
pH
R² = 0.560.07
0.09
0.11
0.13
0.15
0.17
0.19
0.21
4.5 5.0 5.5 6.0 6.5 7.0 7.5
Me
tho
d 2
(%
)
pHCa
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0.10% higher than from Method 2, representing a marked difference (P < 0.01) between
these two routine methods in detecting CCE at relatively low levels.
Figure 67. Comparing expected and reported CCE (%) values from Method 1 (blue)
and Method 2 (red) from standard additions of 0, 2, 4, 6, 8 and 10 mg CaCO3/g
DISCUSSION
Methods were unable to determine the real CCE value of untreated soils. Method
1 tended to give a relatively higher CCE, but had quantitative recovery of added CaCO3.
On the other hand, Method 2 tended to give a relatively lower CCE and a lower recovery
of added CaCO3 and, but showed greater sensitivity to changes in soil pH than Method 1.
The precision of these methods could not be assessed properly due to insufficient or no
sample replication. Thus, a more thorough approach is required to properly compare the
accuracy and precision of both methods.
A possible factor affecting the overestimation of CCE in the soil sample could be
a result of clay content and organic matter by consuming H+ via a mechanism of ion
exchange onto surfaces (Loeppert et al., 1984, Moore et al., 1987). In contrast, this study
showed the corresponding method (Method 2) to underestimate CCE. Changes to the
original procedure for preparing standards are suspected to have influenced results to
some degree – i.e., the amendment of standard additions with CaCO3 and DI water to
make slurry, including air drying for 1 week (delayed treatment with acetic acid), rather
than the immediate treatment of a dry mixture of soil and powdered CaCO3 with acetic
acid. However, it is not known whether such procedural changes had affected soil
R² = 1
R² = 0.9513
R² = 0.934
0.0
0.2
0.4
0.6
0.8
1.0
1.2
1.4
1.6
0 2 4 6 8 10 12
CC
E (%
)
CaCO3 added (mg/g)
Expected
Method 1
Method 2
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carbonate concentration (e.g., carbonate loss during sample preparation) and/or
prevented complete neutralisation of soil carbonate with acetic acid.
Nonetheless,, Loeppert et al. (1984) noted soils with relatively low CaCO3
contents generally had greater potential for error, including (1) dissolution of soil
components other than CaCO3, (2) incomplete dissolution of CaCO3, (3) effect of high PCO2
on pH, (4) volatilisation of acetic acid, and (5) errors in pH determination (Loeppert et
al., 1984). Errors due to volatilisation of acetic acid would have been minimal by using
lids with several pin-holes. However, insufficient ventilation of CO2 gas generated from
the acid-base reaction would increase the partial pressure of CO2, causing the soil pH to
remain low and hence underestimate CCE. And, as mentioned, incomplete dissolution of
CaCO3 may also result in its underestimation.
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APPENDIX F: SOIL TEXTURE
Table 28. Texture classifications from physical observations of texture and particle size analysis
using mid-infrared reflectance (MIR) spectroscopy (Rayment and Lyons, 2011, p. 80)
Pivot# Depth (cm) Visual texture class Sand (%) Silt (%) Clay (%) MIR texture class 01-S1 0-10 3.5 59 7.7 33.3 Sandy clay loam 20-30 3.5 56.3 7 36.7 Sandy clay 01-S2 0-10 3 59.6 10.7 29.7 Sandy clay loam 20-30 3 57.8 7.6 34.6 Sandy clay loam 01-S3 0-10 3.5 57.9 13.8 28.3 Sandy clay loam 20-30 3.5 57.2 7 35.8 Sandy clay 02-S1 0-10 3.5 65.1 7.3 27.6 Sandy clay loam 20-30 3.5 57.4 6 36.6 Sandy clay 02-S2 0-10 3.5 58.4 13.3 28.3 Sandy clay loam 20-30 3.5 55.8 7.6 36.6 Sandy clay 02-S3 0-10 3.5 60.5 10.3 29.2 Sandy clay loam 20-30 3.5 66.7 7.5 25.8 Sandy clay loam 03-S1 0-10 3 63.4 7.8 28.8 Sandy clay loam 20-30 3 56.7 6.9 36.4 Sandy clay 03-S2 0-10 3 60.7 11.7 27.6 Sandy clay loam 20-30 3.5 61.7 8.7 29.6 Sandy clay loam 03-S3 0-10 3 66.4 7.2 26.4 Sandy clay loam 20-30 3.5 61.8 8.8 29.4 Sandy clay loam 04-S1 0-10 3.5 62.3 9.4 28.3 Sandy clay loam 20-30 3.5 54 6.8 39.2 Sandy clay 04-S2 0-10 3 59.2 9.6 31.2 Sandy clay loam 20-30 3 58.5 5.3 36.2 Sandy clay 04-S3 0-10 3.5 55 12.5 32.5 Sandy clay loam 20-30 3.5 60.9 8 31.1 Sandy clay loam 05-S1 0-10 3 66.8 12 21.2 Sandy clay loam 20-30 3 61.6 10.7 27.7 Sandy clay loam 05-S2 0-10 3 70.4 12.4 17.2 Sandy loam 20-30 3 71.8 5.8 22.4 Sandy clay loam 05-S3 0-10 3 65.7 15.2 19.1 Sandy loam 20-30 3.5 69.2 9 21.8 Sandy clay loam 06-S1 0-10 3.5 65.4 10 24.6 Sandy clay loam 20-30 3 62.3 6.5 31.2 Sandy clay loam 06-S2 0-10 3 63.2 9 27.8 Sandy clay loam 20-30 3.5 70.4 7.1 22.5 Sandy clay loam 06-S3 0-10 3 61.1 15 23.9 Sandy clay loam 20-30 3 64.8 7.2 28 Sandy clay loam 07-S1 0-10 3.5 71.5 10.9 17.6 Sandy loam 20-30 3.5 62.1 5.7 32.2 Sandy clay loam 07-S2 0-10 3.5 66.9 10.8 22.3 Sandy clay loam 20-30 3.5 68.5 7.7 23.8 Sandy clay loam 07-S3 0-10 3.5 66.9 9.7 23.4 Sandy clay loam 20-30 3 66.4 7.8 25.8 Sandy clay loam 08-S1 0-10 3.5 66.5 9.7 23.8 Sandy clay loam 20-30 3.5 65.3 4.9 29.8 Sandy clay loam 08-S2 0-10 3.5 64.7 8.7 26.6 Sandy clay loam 20-30 3 61.7 6.6 31.7 Sandy clay loam 08-S3 0-10 3.5 62.7 8.6 28.7 Sandy clay loam 20-30 3 65.6 8.1 26.3 Sandy clay loam 09-S2 0-10 2.5 80 5.3 14.7 Sandy loam 20-30 2.5 68.5 9.6 21.9 Sandy clay loam 10-S1 0-10 3.5 58.2 12.2 29.6 Sandy clay loam 20-30 3 56.9 7.2 35.9 Sandy clay 10-S2 0-10 3 67.2 8.4 24.4 Sandy clay loam 20-30 3 62.2 6.2 31.6 Sandy clay loam 10-S3 0-10 3.5 60.8 11.1 28.1 Sandy clay loam 20-30 3 62.7 9.1 28.2 Sandy clay loam 11-S1 0-10 3.5 68.4 4.9 26.7 Sandy clay loam 20-30 3.5 70 11.2 18.8 Sandy loam 11-S2 0-10 3.5 58.7 12.3 29 Sandy clay loam 20-30 3.5 63.2 7.9 28.9 Sandy clay loam 11-S3 0-10 3.5 61.6 12.1 26.3 Sandy clay loam 20-30 3.5 64.4 10.7 24.9 Sandy clay loam 12-S2 0-10 3 60.6 8.5 30.9 Sandy clay loam 20-30 3 59.2 5.7 35.1 Sandy clay Visual texture classes: sand (1.0), loamy sand (1.5), loam (2.0), clay loam (2.5), Clay (3.0) and heavy clay (3.5).
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IRRIGATION WATER QUALITY AND RISK FOR CLAY DISPERSION
According to the water quality guidelines of the California Fertilizer Association
(1995), the risk for clay dispersion in soils containing ≥ 30 % clay (as is the case at the
HAP) is reasonably low at this stage (Table 29). Thus, by using slightly brackish irrigation
water (EC = 0.99 dS/m, SAR = 0.99, TDS = 580 mg/L), the risk of causing clay dispersion
in sandy clay loam soils dominated by kaolinite should be relatively low as compared
with soils more finely-textured (i.e., greater clay content) and dominated by smectites.
Table 29. Water quality guidelines for risk of dispersion, crusting and swelling of soils with > 30
% swelling clay (California Fertilizer Association, 1995). The location of the HAP in this
framework is indicated by the highlighted row.
SAR Electrical
conductivity (dS/m) Total dissolved solids (mg/L)
*Risk
0-3 < 0.2 < 128 Very High 0.2-0.7 128-428 Moderate > 0.7 > 428 Low 3-6 < 0.3 < 192 Very High 0.3-1.2 192-768 Moderate > 1.2 > 768 Low 6-12 < 0.5 < 320 Very High 1.9-0.5 320 - 1216 Moderate > 1.9 > 1216 Low 12-20 < 1.3 < 832 Very High 2.9 - 1.3 832 - 1856 Moderate > 2.9 832-1856 Moderate 20-40 < 2.9 < 1856 Very High 2.9 - 5.0 1856 - 3200 Moderate > 5.0 > 3200 Low *Risk of dispersion, swelling, and crusting applies especially to soils with more than 30 % clay: clay loam, silty clay loam, sandy clay loam, or silty clay textural classes.
CALCULATING THE SODIUM ADSORPTION RATIO
The tendency of water to replace adsorbed calcium and magnesium with sodium
can be expressed by the sodium adsorption ratio (SAR; Gupta, 2011):
SAR =(Na+)
√[(Ca2+)+(Mg2+)]
2
[13]
where, Na+, Ca2+ and Mg2+ are concentrations expressed in meq/L of sodium,
calcium and magnesium ions.
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To convert a concentration in mg/L to meq/L, divide the concentration by the
equivalent weight (g/eq or mg/meq) of the substance. The equivalent weight of a
substance is equal to its atomic weight (g/mol) divided by its valence or ionic charge
(Vesilind et al., 2010, p. 296).
i. Na (meq/L) = 43 mg/L / 22.99 mg/meq = 1.87 meq/L
ii. Ca (meq/L) = 61 mg/L / 20.04 mg/meq = 3.04 meq/L
iii. Mg (meq/L) = 50 mg/L / 12.15 mg/meq = 4.12 meq/L
Therefore, from equation [12] the SAR of the fertigation mixture is equal to 0.99.
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APPENDIX G: FUTURE SOIL AND LEAF MONITORING
RECOMMENDATIONS
Routine monitoring for soil and plants is required to ensure that irrigation over
the next 20 years does not adversely affect soil quality and pasture productivity at the
HAP, including the conditions for rehabilitation after decommissioning. To date, the
sampling program has provided invaluable baseline information for soil properties and
has identified potential issues that could emerge in the future. However, as considerable
labour is involved, an efficient and a cost-effective method of sampling (e.g., minimal
sampling intensity) is desirable (Colwell, 1971) to detect significant changes as earlier
as possible.
Based on the magnitude of change and consistency of trends, the frequency and
intensity (sample size) of soil and leaf tissue sampling can be revised as a biannual,
stratified regime rather than a quarterly, systematic regime. These options are discussed.
SAMPLING FREQUENCY – TEMPORAL VARIABILITY
Sampling intervals may vary from several months to several years depending on
the purpose of monitoring. At the HAP, it is critical that any possible impacts as a result
of irrigation are identified and appropriately managed. Time trends have shown that
increased alkalinity and sodicity could become a problem for pasture growth and long-
term productivity due in part to their effects on nutrient availability and soil physical
condition. Monitoring should thus provide sufficient information for decision-makers to
identify any adverse trends to evaluate adequately the level of risk (Supervision of
Financial Institutions, 2007). This will in turn provide timely and effective management
responses for preventing threshold limits from being reached or exceeded.
Despite significant increases in soil pH and ESP, the rate at which these soil
properties change will likely slow down due to system equilibration. Therefore,
problems such as nutrient deficiencies/toxicities and soil dispersion are unlikely to arise
suddenly and unnoticed. For instance, alkalinisation is occurring at a slower rate at depth
than at the soil surface; therefore, it is possible to reduce the sampling frequency at this
stage, particularly for the subsoil. Other soil properties, such as EC, CCE, N, P, PRI,
exchangeable cations and ECEC, showed reasonably constant and/or consistent patterns
and hence increasing the sampling interval should not compromise the decision-makers’
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ability to discern temporal changes. However, current variability in leaf composition has
made it difficult to accurately discern real trends from random noise due to patterns of
'rise and fall' (e.g. P and Cd, concentrations). This may perhaps be explicable by seasonal
variation and/or natural variation in the physiological age of the plants being sampled,
because the nutritional status in plants may differ substantially at different stages of
growth (Hochmuth et al., 2012), including soil processes at that point in time (Vitosh et
al., 1995). Thus, to minimise error, it is crucial that soil and plant sampling is conducted
in a standardised manner - e.g., sampling technique and sampling period within growth
cycle.
With distinct summer wet and winter dry seasons, rainfall generally occurs
between December and March (Figure 68). However, the overall low rainfall in this
region is unlikely to significantly affect soil properties and plant nutrition compared to
continuous irrigation with added nutrients. This is consistent with time trends which
show no noticeable influence of rainfall on both soil properties and leaf composition over
the 15 month study period. However, heavy rainfall events from cyclones that pass
inland from the Pilbara coast could strongly influence soil and plant condition by causing
erosion, waterlogging, anaerobicity and reduced nutrient availability due to leaching
(Gornall et al., 2010).
Generally, soil properties in July appeared to be relatively inconsistent or ‘out of
place’ from current data set (e.g., soil properties such as EC, CCE, total N, C/N ratio and
ESP). Considering that July is typical of low temperatures and low rainfall, this may
coincide with such trends in soil properties (Figure 68).
Figure 68. Mean monthly rainfall and temperature at Wittenoom in the Pilbara region, Western
Australia
0
5
10
15
20
25
30
35
40
45
50
0
20
40
60
80
100
120
140
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Tem
per
atu
re (
oC
)
Rai
nfa
ll (m
m)
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In arid and semi-arid regions, abiotic factors such as temperature could have a
greater influence on irrigated pasture (e.g., evapotranspiration) than rainfall. Soil and
leaf tissue sampling should then occur in months with similar temperature ranges to
minimise error due to variations in temperature and evapotranspiration. For example,
biannual sampling of soil and plants in March and September, or April and October,
minimises effects of temperature on pasture growth and avoids months where heavy
rainfall and flooding events are likely to occur – this is usually between mid-December
and April (Bureau of Meteorology, 2014b). Therefore, as long as soil and leaf samples are
collected in a standardised way, this should reduce error attributed to temporal
variability.
By and large, a reduced soil and plant sampling regime from every 3 months
(quarterly) to every 6 months (biannually) is possible. Since alkalinisation is occurring
slowly in the subsoil, sampling at 20-30 cm may even occur once a year. In doing so,
information can be efficiently obtained. Where temporal changes are likely to occur less
gradually through time, routine monitoring thereafter may be generally reduced to
annual sampling as equilibrium becomes established. Nonetheless, further evaluation of
2014 monitoring data will be required.
SAMPLE SIZE – SPATIAL VARIABILITY
In general, the study site has low spatial variability since irrigation water quality
and soil type (i.e., sandy clay loam) are relatively homogenous (Kristiansen et al., 2010).
The variability among irrigation pivots, in terms of soil characteristics, provides a basis
for estimating desirable sampling intensities (Colwell, 1971). Given that most soil
properties and leaf nutrient parameters showed relatively little variation among
irrigation pivots, it is also possible to reduce the sampling intensity at the HAP.
Note seven irrigation pivots are no longer active (i.e., Pivots 9, and Pivots 12-17)
and therefore do not require monitoring. Pivots 12, 14, and 16 were non-operational
throughout the study, while Pivots 9, 15 and 17 ceased hay production after a certain
period of time (i.e., in October 2013, May 2013, and May 2013, respectively).
Reduced sampling intensity can be achieved by means of stratified sampling in
lieu of the current systematic procedure. Stratification improves the efficiency of
obtaining data (Mäkipää et al., 2012) while requiring fewer areas (irrigation pivots) for
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monitoring that would still provide the same degree of representation. In the stratified
area, systematic sampling should be conducted to ensure good representation.
Cluster analysis was employed to stratify the remaining known irrigation pivots
(Pivots 1-8, 10 and 11) by their soil characteristics (see Appendix D). Results show that
Pivots 2 and 3, Pivots 6, 7 and 11, and Pivots 8 and 10 shared a high degree of similarity
in terms of EC, CCE, C/N ratio, exchangeable Al percentage, As concentration and clay
content. Consequently, monitoring may cease in, for example, Pivots 3, 7, 10 and 11 while
leaving the remaining six (Pivots 1, 2, 4, 5, 6 and 8) to be routinely monitored. However,
note cluster analysis cannot guarantee absolute similarity since: (1) results depend on
the variables used (i.e., soil properties), (2) soil properties change over time and with
irrigation, (2) results are only as accurate as the data provided, and (3) random error
due to variability. Nonetheless, cluster analysis provides an effective method for
decision-makers to determine if stratified monitoring is practicable.
SOIL SAMPLING DEPTH
Differences in the magnitude of spatial variability also occur with soil depth
(Lawrence et al., 2013). As there are distinct changes and trends in soil properties at the
0-10 cm and 20-30 cm soil layers (e.g., pH and ESP), it is essential that soil be continually
monitored at 0-10 cm and 20-30 cm.
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APPENDIX H: CHANGES WITH TIME OF EXCHANGEABLE
SODIUM PERCENTAGE (ESP) AND SODICITY OF HAMERSLEY
AGRICULTURE PROJECT SOILS
By Sunil Samaraweera
Soil testing during the last 18 months has indicates that there is a steady increase in the
exchangeable sodium percentage (ESP) of the Hamersley Agriculture Project area; and
there is a tendency for the soil under irrigation to become sodic (ESP >6) and the HAP
soil in the long term may need amelioration (see Figure 69).
Figure 69. Trends in mean exchangeable sodium percentage (ESP,% ± SEM) at
two depths (0-10 cm and 20-30 cm)of the soil profile of the HAP area.
However, these determinations of ESP by the CSBP laboratory have been carried out
employing method 15A1 (Rayment and Lyons, 2011) and does not include the removal
of soluble salts prior to determination of the exchangeable cations. As such, ESP values
obtained by this method tend to overestimate the Na concentrations in the cation
exchange complex. Therefore, the impact of irrigation on soil sodicity was examined by
determining the Na concentrations in the cation complex by employing two methods: 15
A1 that does not include pre-treatment of soluble salts; and 15C1 that includes pre-
treatment for soluble salts (by washing with 60% aqueous ethanol and 20% aqueous
glycerol).
A total of 28 samples collected from 7 locations at 2 depths from HAP area were analysed
and the results are summarised in Figures 70 and 71. It can be seen that washing with
0
1
2
3
4
5
6
7
8
9
Baseline Mar-13 Jul-13 Sep-13 Dec-13 Mar-14
Exch
ange
able
Na
(%)
0-10 cm
20-30 cm
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aqueous ethanol and aqueous glycerol has removed the soluble salt in the soil and the
exchangeable sodium concentrations in most samples were below the detection limit (<
0.1 meq/100g of soil).
Figure 70. Mean (± SEM) of exchangeable Na (meq/100g of soil) of a total of
28 soil samples taken at two depths, 0-10 cm (14 samples) and 20-30 cm (14
samples).
Figure 71. Mean (± SEM) of exchangeable sodium percentage (ESP) of a total
of 28 soil samples taken at 0-10 cm (14 samples) and 20-30 cm (14 samples).
Conclusion
It can be concluded that:
1. addition of irrigation water has not caused a measurable change in the sodicity of the HAP soils;
0
0.1
0.2
0.3
0.4
0.5
0.6
Without pre-wash With pre-wash
Exc.
Na
(me
q/1
00
g)
0 - 10 cm
20 - 30 cm
0
1
2
3
4
5
6
7
8
Without pre-wash With pre-wash
ESP
(%
)
0 - 10 cm
20 - 30 cm
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2. the method currently employed by the CSBP laboratory tends to overestimate the Na concentrations (and hence the ESP) in the cation exchange complex;
3. almost all the sodium in the soil are as soluble Na+ and not found in the cation exchange complex; and
4. determination of ESP in the soils samples in future should be carried out by employing methods that include pre-treatment for soluble salts.
Reference
RAYMENT, G. E. & LYONS, D. J. 2011. Soil Chemical Methods – Australasia, Victoria, CSIRO
Publishing.