Geospatial Data Based Modelling For Evaluation of Soil ...K. L. University, Greenfields, Vaddeswaram-522502, Guntur, A. P, India. Abstract The soil quality is attracting attention

International Journal of Applied Environmental Sciences

ISSN 0973-6077 Volume 11, Number 1 (2016), pp. 245-258

© Research India Publications

http://www.ripublication.com

Geospatial Data Based Modelling For Evaluation of

Soil Properties: A Modal Study

G. S. Sarma1, SS. Asadi2 and S. Lakshmi Narayana3

1Research Scholar, Department of Electronics & Communication Engineering,

K. L. University, Greenfields, Vaddeswaram-522502, Guntur, A. P, India.

2Associate Professor, Dept. of Civil Engineering, K.L. University,


Email: [email protected]

3Professor, Department of Electronics & Communication Engineering,


Abstract

The soil quality is attracting attention for the last couple of years due to the

unscientific and unplanned irrigation practices that are bringing a myriad

problem. Modern industrialization practices such as chemical industries and

indiscriminate use of fertilizers in agricultural activity containing toxic

substances contribute to the environmental degradation. Such anthropogenic

activities invariably result in the depletion of soil quality, deterioration of soil

quality, contamination of drinking water and various health hazards. Hence

there is need to study in a comprehensive way about the soil quality issues in

the catchment area.

The present study is an attempt made to analyze the physico-chemical

parameters and to generate the Soil Quality Index. The soil samples collected

at the predetermined locations are analyzed for physico-chemical parameters

for the generation of attribute database. Based on the analysis results spatial

distribution maps of selected soil quality parameters namely Bulk Density,

Moisture content, Organicmatter, C%, pH, EC, Ca, Mg, SO4, Nitrate,

Phosphorus, Potassium and Texture are prepared using curve-fitting method in

GIS software. The physico-chemical analysis properties and computation of

SQI are helpful in the grouping of soil samples into excellent, good, poor, very

poor and unfit. The spatial distribution of SQI generated in the current study

will be of much use for the planners in the management and monitoring of

land resources.

Keywords: Soilquality, spatial distribution maps, Soilpollution, physico-

chemical parameters

246 G. S. Sarma et al

Introduction The term soil has a different meaning to individuals in different scientific disciplines:

to the agronomist or botanist, soil is best defined as a medium for the growth of

plants; to the engineer, soil refers to the loose material that lies between the ground

surface and solid rock; and to the soil scientist, soil is described as the unconsolidated

mineral or organic matter at the earth’s surface which has been altered by pedogenetic

processes. Although there is no uniform definition for soil, it is apparent that the

functions of soil are many folds. Soil pollution is often thought of as resulting from

chemical contamination such as through the use of excessive amounts of pesticides

and fertilizers that can result in surface water and / or ground water contamination.

However, there are other forms of soil pollution or degradation, including erosion,

compaction, and salinity. Soils have often been neglected when they are used for on-

site land disposal of waste chemicals and unwanted materials. Most soils are capable,

to some degree, of adsorbing and neutralizing many pollutants to harmless levels

through chemical and biochemical processes. Healthy soils give us clean air and

water, bountiful crops and forests, product rangeland, diverse wild life, and beautiful

land scapes.

Description of Study Area:

The study area extends from the Nelloreayacut on PennaruptoBay of Bengal about 25

kms downstream of Nellore. The area is included in SOI Toposheets 66/B2andB3.

The study area is underlain by alluvium of recent age. It includes all the areas

irrigated by Pennar. The study area is a part of Nellore district, the southern most

coastal district of Andhra Pradesh with a sea coast of 38. 95 Km with a perimeter of

882. 79 Km it is an agrarian district and agriculture is the mainstay for about 42 per

cent of the population. (Census of India 2001). The area under study extends from the

Nellore to Bay of Bengal about 20 km down stream of Nellore. The extent to be

covered all area is included in Surrey of India toposheets 66B/2 and 66B/3 on 1:

50000 scales between longitude and latitude 800 0’, 140 45’ NW 800 15’ 140 25’ SE.

Figure 1: Location map of study area

Geospatial Data Based Modelling For Evaluation Of Soil Properties: 247

Objectives of the Study 1) To prepare the thematic maps of the study area using remote sensing and GIS

techniques.

2) To create attribute data consisting of selected soil quality parameters derived

from the analysis of soil samples collected from predetermined locations in the

study area.

3) To develop spatial distribution maps showing and soil quality index map by

integrating the spatial data and attribute data.

Methodology Data collection:

Different data products required for the study include Survey of India (SOI)

toposheets bearing with numbers 66/B2andB3 on 1: 50, 000 scale. Fused data of IRS–

1D PAN and LISS-III satellite imagery obtained from National Remote Sensing

Centre (NRSC), Hyderabad, India. Collateral data collected from related

organizations, comprises of soil quality and demographic data.

Database creation:

Spatial Database:

Thematic maps like base map and drainage network maps are prepared from the SOI

toposheets on 1: 50, 000 scale using AutoCAD and Arc/Info GIS software to obtain a

baseline data maps of the study area was prepared using visual interpretation

technique from the fused satellite imagery (IRS-ID PAN + IRS-ID LISS-III) and SOI

toposheets along with ground truth analysis. All the maps are scanned and digitized to

generate a digital output.

Attribute database:

Fieldwork is conducted and soil samples are collected from 24predetermined

locations based on the land use and drainage network maps in the study area. Care is

taken in collecting the soil samples for uniform distribution and density of sampling

locations. The soil samples were analyzed for various parameters adopting standard

protocols (APHA, AWWA, WPCF 1998). The soil quality data thus obtained forms

the attribute database for the present study (Table 1).

Integration of spatial and attribute database:

The spatial and the attribute database thus generated are integrated for the preparation

of spatial distribution maps of selected soil quality parameters like Bulk Density,

Moisturecontent, Organicmatter, pH, EC, Sulphates, calcium, Magnesium, carbon,

nitratespotassium, phosphorus and Soil Quality Index (SQI). The soil quality data

(attribute) is linked to the sampling location (spatial) in ARCGIS and maps showing

spatial distribution were prepared to easily identify the variation in concentrations of

the above parameters in the ground water at various locations of the study area using

curve fitting technique of ARCGIS software.


Spatial Modelling and Surface Interpolation through IDW:

Though there are a number of spatial modelling techniques available with respect to

application in GIS, spatial interpolation technique through Inverse Distance Weighted

(IDW) approach has been used in the present study to delineate the locational

distribution of soil pollutants or constituents. This method uses a defined or selected

set of sample points for estimating the output grid cell value. It determines the cell

values using a linearly weighted combination of a set of sample points and controls

the significance of known points upon the interpolated values based upon their

distance from the output point thereby generating a surface grid as well as thematic

isolines. Important soil quality indicating parameters and their distribution patterns

were studied with the help of cartographic techniques. The generated figures are self-

explanatory and obviously convey the quality of each parameter for all the samples.

Thus, GIS enables us to look into the cause and effect relationship with visual

presentation.

Estimation of Soil Quality Index (SQI):

Soil Quality Index (SQI) is a very useful and efficient method for assessing the

quality of soil. It is a useful tool forcommunicating the information on overall quality

of soil. Five soil attributes namely acidity (pH), Organic Matter (OM), Phosphorus

(P), Potassium (K), and Electrical Conductivity (EC), have been combined to

construct an index to represent the soil quality.

The soil quality index has been constructed by the following method given by 13.

SQI = ( DpH + DOM + DP + DK + DEC ) / 5

Where,

DpH = 1 if pH > 6. 5 and 0 otherwise

DOM = 1 if OM> 2 and 0 otherwise

DP = 1if P > 20 and 0 other wise

DK= 1if K > 80 and 0 otherwise

DEC= 1if EC < 2 and 0 otherwise

The Soil Quality Index (SQI) is computed for all sites of the study area. SQI is

bounded between 0 to 1, and the higher the SQI the better the quality of soil. Based on

the SQI values, the soil quality scale is rated as good (>0. 7), average (0. 4 – 0. 7)

andpoor (0 – 0. 4).

Results and Discussion In the present study soil samples have been taken 24 sampleswelldistributed locations

in the study area. The samples have been analyzed for different parameters like Bulk

Density, Moisturecontent, Organicmatter, pH, EC, Sulphates, calcium, Magnesium,

nitrates, carbon, potassium, phosphorus.

Physico-chemical analysis of 24 samples in the study area reveals minimum bulk

density of 1. 6 and maximum of 18. 5 at sample no. 4. Maximum variation of 15. 5%


in a year occurs atsample no. 4 and minimum variation of 2. 1 sampleno. 1 and 1. 6%

in a year occurs at sample no. 1Bulk density values of all the samples are well within

the permissible limits.

Organic matter value of 0. 8 is observed as minimum in sample no. 4 and the

maximum value was found to be 17. 27 at sample no. 18. Organic matter values

observed in all the samples of study area are lower than the desired values. The

variation of organic matter in a year is higher on downstreamside when compared to

upstream side of the study area.

The moisture content value of 3. 1 is observed as minimum in sample no. 13 and the

maximum value was found to be 41. 66 at sample no. 15.

The Electrical Conductivity (EC) values of soil in study area is range of minimum 3. 8

at sample no. 4. and the maximum value was found to be 32. 77 at sample no. 24. all

the samples in the study area are within the permissible limits.

Minimum pH value of 1 was observed in sample no. 13, and a maximumpH value of

7. 4 was observed in sample no. 18.

Sulfate minimum value of 1. 72 was observed in sample no. 1 and a maximum value

of 263 was observed in sample no. 1, magnesium minimum value of 4. 4 was

observed in sample no. 15 and a maximum value of 22. 57 was observed in sample

no. 20

Nitrates minimum value of 2. 01 was observed in sample no. 20 and a maximum

value of 24. 12 was observed in sample no. 3. Analysis of phosphorusrevealed a

minimum value of 6 at sample no. 18 and maximum of 29. 4at sample no. 19.

Potassium (K) value of 8. 1 was observed as minimum in sample no. 13 and

maximum value of 15. 78 was found in samples no. 23Carbon value of 2. 2 was

observed as minimum in sample no. 4 and maximum value of 24. 51 was found in

samples no. 11.

Table 1: Soil Sample Analysis of Pallepadu, Leguntapadu, Inamadugu

PALLEPADU LEGUNTAPADU INAMADUGU

Mar 11 Jun 11 Sep 11 Dec 11 Mar 11 Jun 11 Sep 11 Dec 11 Mar 11 Jun 11 Sep 11 Dec 11

Bulk Density

gm/cm3

1.007 1.008 1.002 0.986 1.032 1.023 1.124 1.012 0.976 0.963 0.984 1.004

Moisture

content %

0.215 0.205 0.295 0.303 0.106 0.103 0.183 0.203 0.33 0.293 0.354 0.364

Organicmatter

mg/g

0.726 0.716 0.707 0.685 0.815 0.796 0.785 0.794 0.675 0.72 0.75 0.726

C% 0.422 0.414 0.413 0.394 0.474 0.0457 0.454 0.452 0.394 0.414 0.425 0.421

pH 7.26 7.21 7.22 7.12 6.7 6.84 6.94 7.13 7.34 7.34 7.14 7.14

EC mhos/cm 0.22 0.224 0.235 0.265 0.18 0.187 0.173 0.184 0.16 0.174 0.154 0.194

Ca mg/g 0.373 0.382 0.361 0.293 0.343 0.324 0.317 0.298 0.384 0.375 0.364 0.313

Mg mg/g 0.0452 0.0464 0.0494 0.0484 0.044 0.0484 0.0413 0.0413 0.043 0.0443 0.0413 0.0394

SO4 mg/g 0.244 0.2132 0.2894 0.2783 0.1853 0.1835 0.1802 0.1784 0.1933 0.1943 0.1894 0.1903

Nitrate mg/g 0.00946 0.0102 0.00921 0.00986 0.01703 0.01784 0.01695 0.01714 0.00905 0.0114 0.0123 0.00985

Phosphorus

(P) ppm

22 23 22 18 25 23 23 24 21 23 25 22

Potassium

(K) ppm

75 73 73 72 81 74 75 72 68 73 77 78


% Sand 45.5 Sandy Clay loam 49.71 Sandy Clay loam 46.21 Sandy Clay

Texture %

Silt

24 18.32 18.61

% Clay 31.7 27.52 35.21

Table 2: Soil Samples Analysis of Cherlapalem, Monegnpalem, Ramannapalem

CHERLAPALEM MONEGNPALEM RAMANNAPALEM


Bulk Density

gm/cm3

0.924 1.092 0.985 0.954 0.979 1.088 1.002 0.986 1.007 1.014 1.013 0.98

Moisture

content%

0.142 0.146 0.265 0.285 0.337 0.4 0.383 0.394 0.48 0.43 0.566 0.675

Organicmatter

mg/g

1.156 1.17 1.178 1.173 0.815 0.87 0.847 0.849 1.155 1.137 1.196 1.183

C% 0.669 0.667 0.682 0.680 0.472 0.470 0.489 0.492 0.669 0.658 0.692 0.687

pH 7.87 7.84 7.74 7.62 7.73 7.75 7.63 7.59 7.15 7.13 7.11 7.11

EC mhos/cm 0.27 0.255 0.265 0.254 0.28 0.275 0.266 0.257 0.2 0.106 0.114 0.113

Ca mg/g 0.3941 0.385 0.398 0.401 0.353 0.368 0.382 0.397 0.415 0.427 0.489 0.465

Mg mg/g 0.0362 0.0322 0.0383 0.0373 0.0375 0.0375 0.0364 0.0324 0.046 0.041 0.0412 0.0467

SO4 mg/g 0.1376 0.1372 0.1321 0.1313 0.0968 0.1022 0.1043 0.1084 0.2283 0.2193 0.2202 0.2011

Nitrate mg/g 0.0172 0.0163 0.0173 0.0165 0.01123 0.01102 0.01234 0.01202 0.01312 0.01373 0.01295 0.01334

Phosphorus

(P) ppm

32 31 34 35 26 23 24 23 32 28 35 35

Potassium

(K) ppm

84 93 93 91 82 81 84 87 96 86 96 96

% Sand 48.6 Sandy Clay loam 47.50 Sandy Clay loam 49.41 Sandy Clay

Texture

% Silt

21.4 18.21 22.11

% Clay 30.4 34.21 28.51

Table 3: Soil Sample Analysis of Kodurpadu, Jammipalem, Narayanreddipet

KODURPADU JAMMIPALEM NARAYANREDDIPET


Bulk Density

gm/cm3

0.927 1.024 1.036 1.046 1.034 1.086 1.035 1.023 1.022 1.044 1.038 1.027

Moisture content% 0.157 0.164 0.173 0.185 0.097 0.094 0.103 0.124 0.164 0.162 0.176 0.185

Organicmatter

mg/g

0.622 0.624 0.555 0.533 0.272 0.263 0.252 0.245 0.673 0.657 0.643 0.625

C% 0.855 0.361 0.314 0.303 0.153 0.153 0.143 0.143 0.394 0.373 0.363 0.362

pH 7.22 7.33 7.12 7.13 7.84 7.85 7.64 7.52 7.27 7.32 7.22 7.14

EC mhos/cm 0.181 0.187 0.163 0.173 0.243 0.193 0.164 0.154 0.192 0.174 0.166 0.185

Ca mg/g 0.382 0.376 0.362 0.354 0.364 0.376 0.356 0.353 0.387 0.389 0.372 0.366

Mg mg/g 0.034 0.0364 0.0403 0.0381 0.0376 0.0388 0.0364 0.0364 0.035 0.035 0.0414 0.035

SO4 mg/g 0.2203 0.2102 0.2193 0.203 0.1703 0.1765 0.1705 0.1695 0.2145 0.2193 0.2102 0.2003

Nitrate mg/g 0.01234 0.01223 0.01204 0.01274 0.01304 0.01304 0.01385 0.01404 0.01235 0.01225 0.01223 0.01284

Phosphorus

(P) ppm

14 12 16 22 13 13 21 15 15 14 16 21

Potassium

(K) ppm

74 65 73 75 64 72 74 71 76 62 74 74

% Sand 45.24 sandy clay loam 55.12 Sandy Clay loam 50.21 Sandy Clay loam

Texture

% Silt

23 22.33 18.22

% Clay 32.73 22.64 31.62


Table 4: Soil Sample Analysis of Alipuram, Indukurpeta, Gudipallipadu

ALIPURAM INDUKURPETA GUDIPALLIPADU


Bulk Density

gm/cm3

1.034 1.087 1.004 1.015 1.043 1.038 1.067 1.073 1.038 1.026 1.024 1.015

Moisture

content%

0.098 0.096 0.115 0.123 0.35 0.33 0.394 0.396 0.118 0.117 0.176 0.196

Organicmatter

mg/g

0.615 0.627 0.68 0.595 0.674 0.669 0.77 0.655 0.813 0.717 0.803 0.838

C% 0.355 0.365 0.387 0.345 0.394 0.385 0.416 0.375 0.477 0.413 0.465 0.488

pH 6.86 6.87 7.07 7.04 7.55 7.53 7.34 7.22 7.25 7.29 7.23 7.19

EC mhos/cm 0.12 0.116 0.105 0.114 0.125 0.114 0.127 0.124 0.25 0.236 0.196 0.216

Ca mg/g 0.36 0.346 0.318 0.357 0.377 0.378 0.367 0.358 0.37 0.376 0.296 0.358

Mg mg/g 0.039 0.0333 0.0412 0.0396 0.0505 0.0512 0.0492 0.0487 0.034 0.0355 0.0385 0.0325

SO4 mg/g 0.2145 0.2115 0.2219 0.212 0.2257 0.2177 0.2012 0.2005 0.243 0.2172 0.2202 0.2111

Nitrate mg/g 0.0186 0.01914 0.01864 0.01822 0.01238 0.01222 0.01287 0.01302 0.01404 0.01328 0.01397 0.01401

Phosphorus

(P) ppm

19 21 24 19 22 23 24 18 26 24 25 26

Potassium

(K) ppm

73 77 82 73 82 83 81 74 82 74 84 85

% Sand 49.4 Sandy Clay loam 20.02 Silt Clay loam 48.42 Sandy Clay loam

Texture

% Silt

23.4 47.60 27.12

% Clay 27.6 32.52 24.52

Table 5: Soil Samples Analysis of Kandaleru Reservoir, Krishnareddypalli and

Gundavolu Ground

UTUKURU ALAGANIPADU RAMUDUPALEM


Bulk Density

gm/cm3

1.03 1.041 1.037 1.027 0.996 0.995 0.986 1.013 1.074 1.085 0.976 0.995

Moisture

content%

0.191 0.184 0.184 0.194 0.214 0.215 0.245 0.297 0.124 0.116 0.185 0.195

Organicmatter

mg/g

1.23 1.274 1.294 1.295 1.153 1.072 1.051 1.176 0.677 0.654 0.612 0.661

C% 0.743 0.742 0.752 0.751 0.667 0.621 0.612 0.685 0.392 0.314 0.354 0.382

pH 6.94 6.93 6.95 7.02 7.16 7.24 7.14 7.11 6.74 6.86 6.5 6.93

EC mhos/cm 0.14 0.126 0.114 0.114 0.163 0.165 0.154 0.164 0.151 0.154 0.154 0.144

Ca mg/g 0.436 0.426 0.414 0.466 0.355 0.353 0.341 0.312 0.383 0.314 0.326 0.382

Mg mg/g 0.0354 0.0364 0.0376 0.0334 0.0373 0.0363 0.0293 0.0313 0.072 0.0702 0.0724 0.0692

SO4 mg/g 0.2146 0.2034 0.2124 0.2002 0.1913 0.1985 0.1902 0.1972 0.1916 0.1901 0.1895 0.1884

Nitrate mg/g 0.02884 0.02724 0.0284 0.02815 0.02662 0.02613 0.02785 0.02924 0.01763 0.01812 0.01795 0.01784

Phosphorus (P) ppm 33 37 36 31 31 29 31 35 21 18 22 24

Potassium

(K) ppm

92 91 95 96 95 85 87 95 75 74 75 81

% Sand 38.31 Clay loam 47.09 Sandy Clay loam 39.54 Sandy Clay loam

Texture

% Silt

24.21 22.21 27.26

% Clay 37.51 30.73 33.24


Table 6: Soil Sample Anlysis of Mudivartipalem, Gangapatnam, Narsapuram

MUDIVARTIPALEM GANGAPATNAM NARSAPURAM


Bulk Density

gm/cm3

1.017 1.014 1.044 1.017 0.976 1.016 1.023 1.015 1.032 1.075 1.036 1.016

Moisture

content%

0.121 0.182 0.194 0.207 0.315 0.332 0.384 0.394 0.098 0.103 0.104 0.128

Organicmatter

mg/g

0.63 0.565 0.613 0.636 0.776 0.707 0.717 0.756 0.514 0.534 0.615 0.623

C% 0.364 0.323 0.354 0.364 0.413 0.407 0.415 0.432 0.292 0.303 0.353 0.356

pH 6.95 7.03 7.05 7.13 7.43 7.55 7.31 7.24 7.75 7.64 7.43 7.16

EC mhos/cm 0.334 0.357 0.344 0.338 0.103 0.112 0.105 0.102 0.213 0.193 0.173 0.164

Ca mg/g 0.345 0.342 0.354 0.335 0.367 0.343 0.35 0.324 0.316 0.354 0.38 0.297

Mg mg/g 0.0314 0.03187 0.0313 0.0295 0.0551 0.0569 0.0522 0.0512 0.0369 0.0378 0.0363 0.0383

SO4 mg/g 0.1796 0.1802 0.1903 0.1894 0.2195 0.2093 0.2005 0.1995 0.1784 0.1693 0.1704 0.1724

Nitrate

mg/g

0.01012 0.01103 0.00993 0.0097 0.01556 0.01515 0.01416 0.01516 0.01383 0.01303 0.01393 0.01401

Phosphorus

(P) ppm

22 14 18 15 17 17 16 18 17 21 19 18

Potassium

(K) ppm

76 65 68 64 75 66 68 78 65 65 74 75

% Sand 37.24 clay loam 38.63 clay loam 39.24 sandy clay loam

Texture %

Silt

22.23 23.73 27.24

% Clay 40.53 37.63 33.44

Table 7: Soil Sample Analysis of Nidimusali, Veguru, Tumagunta

NIDIMUSALI VEGURU TUMAGUNTA


Bulk

Densitygm/

cm3

0.985 1.013 0.993 0.987 0.995 1.002 1.002 0.988 0.975 1.015 1.024 1.012

Moisture

content%

0.137 0.124 0.145 0.184 0.164 0.162 0.174 0.184 0.332 0.313 0.383 0.392

Organic

mattermg/g

1.083 1.093 1.054 1.034 1.152 1.172 1.053 1.157 0.764 0.796 0.705 0.754

C% 0.632 0.633 0.614 0.595 0.667 0.684 0.614 0.674 0.444 0.463 0.413 0.435

pH 7.24 7.24 7.24 7.22 7.04 7.04 7.04 6.91 7.54 7.62 7.32 7.24

EC mhos/cm 0.174 0.174 0.165 0.155 0.134 0.135 0.136 0.124 0.103 0.105 0.114 0.106

Ca mg/g 0.366 0.367 0.325 0.312 0.364 0.313 0.294 0.334 0.363 0.365 0.345 0.333

Mg mg/g 0.0477 0.0483 0.0465 0.0394 0.0362 0.0323 0.0384 0.0296 0.0552 0.0573 0.0524 0.0514

SO4 mg/g 0.1815 0.1825 0.1804 0.1798 0.2324 0.2354 0.2485 0.2685 0.2095 0.2193 0.2004 0.1984

Nitrate mg/g 0.01153 0.01152 0.01263 0.01166 0.01291 0.01284 0.01263 0.01284 0.01554 0.01522 0.01427 0.01503

Phosphorus

(P) ppm

35 32 25 33 27 37 31 33 24 26 24 18

Potassium

(K) ppm

97 95 83 94 84 97 95 92 77 86 83 84

% Sand 39.31 Sandy Clay loam 43.24 Sandy Clay loam 49.3 Sandy Clay loam

Texture

% Silt

26.51 24.07 22.2

% Clay 34.23 32.72 28.6


Table 8: SoilSampleAnalysis of Otukuru, Mopuru, Talanchi

OTUKURU MOPURU TALANCHI


Bulk Density

gm/cm3

1.015 1.006 1.034 1.023 1.016 1.015 1.035 1.043 0.994 1.084 1.094 1.002

Moisture

content%

0.258 0.241 0.287 0.294 0.18 0.122 0.195 0.202 0.156 0.146 0.174 0.187

Organicmatter

mg/g

1.28 1.254 1.207 1.129 0.677 0.668 0.632 0.654 0.785 0.784 0.87 0.855

C% 0.733 0.724 0.693 0.651 0.392 0.383 0.364 0.376 0.454 0.451 0.511 0.495

pH 6.94 7.03 7.05 7.11 6.85 6.95 7.06 7.06 7.36 7.34 7.25 7.23

EC mhos/cm 0.213 0.244 0.203 0.194 0.123 0.114 0.124 0.127 0.07 0.095 0.115 0.116

Ca mg/g 0.372 0.373 0.335 0.313 0.33 0.354 0.343 0.334 0.364 0.353 0.313 0.294

Mg mg/g 0.0305 0.0314 0.0303 0.0293 0.0313 0.0315 0.0315 0.0297 0.054 0.056 0.045 0.044

SO4 mg\g 0.2295 0.2217 0.2114 0.2103 0.1805 0.1903 0.1802 0.1794 0.1786 0.1795 0.1715 0.1713

Nitrate mg/g 0.01278 0.01213 0.01202 0.01201 0.00994 0.01102 0.00986 0.00922 0.01027 0.01003 0.01032 0.01043

Phosphorus

(P) ppm

36 32 36 27 16 16 17 23 24 23 23 23

Potassium

(K) ppm

93 94 94 84 66 73 74 75 74 71 84 81

% Sand 42.4 Clay loam 44.21 Sandy Clay loam 41.22 Sandy Clay loam

Texture

% Silt

25.2 26.21 26.41

% Clay 32.7 29.62 32.23

Table 9: Percentage of soil parameters variation in a year

Villeges/Places Bulk

Density

Moisture

content

Organicmatter C pH EC Ca Mg SO4 Nitrate Phosphorus

(P)

Potassium

(K)

PALLEPADU 2.2 33.3 5.3 5.3 2.5 17.54 21.44 8.82 26.3 8.7 13.65 10.26

LENGUNTAPADU 9.8 49.26 3.18 18.3 4.4 9.5 12.6 15.5 3.65 4.8 15.37 10.98

INAMADUGU 3.8 19.7 8.3 7.8 3.6 21.88 18.36 11.56 2.41 24.13 16.7 10.39

CHERLAPALEM 15.6 51.3 2.2 2.3 3.4 3.9 3.99 16.98 4.8 2.4 16.7 10.3

MONEGNPALEM 9.8 23.5 4.5 4.48 2.6 6.7 11.09 14.35 11.03 10.9 21.6 9.18

RAMANNAPALEM 2.3 37.6 5.3 4.8 5.7 10.9 15.3 12.5 11.97 6.04 21.8 9.16

KODURPADU 10.7 15.9 14.6 14.7 3.3 13.8 6.03 21.6 8.7 6.03 24 12.68

JAMMIPALEM 6.08 20.34 8.43 12.3 4.5 36 6.87 6.8 3.7 7.2 26 15.55

NARAYANREDDIPET 2.69 11.6 7.37 18.4 1.8 14.75 5.8 19.8 8.7 4.89 24 16.3

ALIPURAM 7.8 24.13 7.36 15.44 3.2 12.83 10.8 19.23 4.7 4.77 17.86 11.12

INDUKURPETA 3.08 22.13 7.47 24.52 5.2 7.04 5.06 4.85 11.25 6.16 17.33 10.94

GUDIPALLIPADU 2.6 42.8 13.6 13.5 1.4 17.6 20.4 15.25 12.5 5.5 17.86 10.47

UTUKURU 1.8 3.2 2.02 1.97 1.1 13.7 10.9 11.47 6.9 5.7 16.7 8.2

ALAGANIPADU 2.45 29.8 10.62 10.53 1.02 5.4 12.13 21.57 4.2 10.7 19.44 9.3

RAMUDUPALEM 9.67 41.67 9.73 20.83 4.02 5.8 18.6 4.5 1.73 1.02 17.38 10.1

MUDIVARTIPALEM 2.8 40.2 12.04 11.7 3.06 6.5 3.97 9.4 5.4 1.5 26 15.56

GANGAPATNAM 5.4 21.5 8.4 8.7 3.7 9.4 11.93 9.3 9.4 9.3 18.74 13.74

NARSAPURAM 13.8 17.18 17.25 17.23 7.6 24.09 17.27 4.5 5.6 6.6 6.1 15.19

NIDIMUSALI 2.5 32.3 5.47 5.56 1.3 11.5 15.74 18.4 2.4 8.6 29.45 14.59

VEGURU 1.7 12.06 18.4 10.265 2.4 3.02 19.25 22.58 13.18 2.03 27.78 15.34

TUMAGUNTA 4.78 20.6 11.07 11.08 3.7 10.5 9.7 9.7 9.4 8.2 29.7 15.27

OTUKURU 3.2 17.45 11.3 12.7 2.6 17.6 17.48 7.9 8.46 6.03 24.5 15.43

MOPURU 2.4 39.5 7.7 18.4 2.7 8.53 3.2 6.55 5.5 16.14 28.54 15.79

TALAMANCHI 9.3 20.42 11.13 17.43 2.6 32.76 17.23 28.9 4.59 3.9 28.54 15.68


Sspatial distribution map for bulk density

in Soil

Spatial distribution map for Moisture

Content in soil

Spatial distribution map for Organic

Matter in soil

Spatial distribution map for pH in soil

Spatial distribution map for EC in soil Spatial distribution map for Sulphates in

soil


Spatial distribution map for Calcium in

soil

Spatial distribution map for Magnesium

in soil

Spatial distribution map for Carbon in

soil

Spatial distribution map for Potassium in

soil

[ Spatial distribution map for Phosphorus in soil ]

Soil Quality Index (SQI):

A soil quality index (SQI) is an aggregate measurement of a soil’s performance of

critical ecological and agronomic functions. The complexity of co-evaluating the

status of many soil parameters has prompted investigators of many soil parameters

has prompted investigators to integrate multiple indicators in a soil quality index.

Researchers, Farmers, and Policymakers could use a soil quality index to assist with


management and Environmental decisions. Of the numerous proposals set for

quantitative soil quality index, the most common approach suggest that soil quality

index is a function of a set of number of specific soil quality elements and that it

should be based on conditions that maximize production and Environmental

performance criteria for each element of ecosystem.

Recently much discussion in scientific literature has focused on the soil quality index

concept, as well as on its theory and assessment. As far as soil quality indexes are

concerned, a number of proposals have been made, but no general accepted

methodology has been identified yet (Bourma 2002, Gardi et al. 2002) According to

an emerging concept which attempts to balance multiple soil uses, soil quality should

no longer be limited to mere productive aspects, but broader Environmental effects

should be included as well (Karden et al. 1997, Andrews et al. 2002). One of the main

problems with the implementation of soil quality index is related to the cost and

difficulty of collecting data on the soil attributes, especially when they are needed in

time series format.

The quality of soil is believed to have effects on Environment and on the in efficiency

of agricultural production. Five soil attributes namely acidity (pH), Organic Matter

(OM), Phosphorus (P), Potassium (K), and Electrical Conductivity (EC), have been

combined to construct an index to represent the soil quality.

The soil quality index has been constructed by the following Method given by

“Brejda and Moorman”:

SQI = ( DpH + DOM + DP + DK + DEC ) / 5

Where DpH = 1 if pH > 6. 5 and 0 otherwise

DOM = 1 if OM> 2 and 0 otherwise

DP = 1 if P > 20 and 0 other wise

DK = 1 if K > 80 and 0 otherwise

DEC = 1 if EC < 2 and 0 otherwise

So SQI is bounded between 0 to 1, and the higher the SQI the better the quality of

soil. The SQI in between 0 to 0. 4 is treated as soil of poor quality, 0. 5 to 0. 7is

treated as soil of average quality and 0. 8 to 1. 0 is treated as soil of good quality.

The Soil Quality Index (SQI) is computed for all twenty sites of the study area. The

calculated values of soil quality index are shown in Table. 10

Spatial Distribution Maps For SQI:

Spatial distribution maps for soil quality index are prepared based on the index

computed from the results of the laboratory analysis using ARC INFO software.

According to earlier investigations carried out by several authors on water quality

index, a four point scale namely Very good, good, average and poor.

The surface could be visualized as representing a third dimension to the 2-

Dimensional x y data and the third axis can be represented by any attribute. The

procedure for the generation of maps is given in detail in the earlier sections. The


ranges of soilquality index for 4 point scale are as given below:

INDEX RATING

0. 4-0. 05 Poor

0. 5 – 0. 6 Average

0. 6 – 0. 7 Good

>7 Very Good

The soil quality map consists of number of polygons categorized into four groups’ for

preparation of spatial distribution of soil quality index and each group is colored with

a different color, which is shown in maps. The soil quality index map is shown in Fig.

Table 10: Values of Soil Quality Index (SQI)

SL: NO NAME OF THE VILLAGE SQI CONDITION

1 PALLEPADU 0. 6 AVERAGE

2 LEGUNTAPADU 0. 7 GOOD

3 MONEGNPALEM 0. 6 AVERAGE

4 INAMADUGU 0. 7 GOOD

5 CHERLAPALM 0. 7 GOOD

6 RAMANNAPALEM 0. 7 GOOD

7 INDUKURPETA 0. 7 GOOD

8 NIDIMUSALI 0. 7 GOOD

9 KODURPADU 0. 6 AVERAGE

10 UTUKURU 0. 4 POOR

11 JAMMIPALEM 0. 6 AVARAGE

12 ALAGANIPADU 0. 4 POOR

13 RAMUDUPALEM 0. 4 POOR

14 VEGURU 0. 7 GOOD

15 TUMAGUNTA 0. 7 GOOD

16 NARSAPURAM 0. 8 VERY GOOD

17 OTUKURU 0. 7 GOOD

18 MOPURU 0. 7 GOOD

19 NARAYANA REDDIPALEM 0. 6 AVERAGE

20 ALLIPURAM 0. 6 AVERAGE

21 TALAMANCHI 0. 8 VERY GOOD

22 GUDIPALLIPADU 0. 4 AVERAGE

23 GANGAPATNAM 0. 4 AVERAGE

24 MUDIVARTIPALEM 0. 4 AVERAGE

Conclusions Based on the all above parameters, SQI was computed to determine the soil quality

and categorized into good, average and poor From the analysis results and soil quality

rating scale, it revealed that eleven samples (41. 65%) were of good with SQI ranging

from (>7), six samples i. e. 24% are rated as average (SQI of 0. 4 to 0. 7)andeight


samples i. e. 33. 36% are considered poor with SQI ranging between (0 to 0. 4). On

downstream side of study area26% samples are good, 16. 5% average and 58. 4% are

poor. While on upstream side of study area, 58. 2% of samples are good, 33. 4%

average and 8. 35% are poor.

Soil quality is largely a function of chemical proportion such as organic matter,

calcium, magnesium, sulfur, pH, nitrate, potassium and phosphorous. Assessment of

these parameters is essential in determining the effect on soil quality. The overall

study reveals that soil quality parameters organic matter, potassium and phosphorous

are with in the permissible limits of study area. 57% of the samples collected around

industries are of poor/average quality, while remaining 43% are of good quality. The

areas of poor soil quality are observed to be located on down stream of study area and

good water quality is observed on upstream of the study area

References

[1] Karlen, D. L., Andrews, S. S., and Doran. J. W., Soil quality, current concepts

and applications, Advances in agronomy, 2001, 74, 1-40.

[2] Thomos. M., Lillesand and Ralph W., Keifer, Remote sensing and image

interpretation, Fourth edition, John Willey and sons, Inc, Newyork, 2000.

[3] Doran, J. W., and Parkin, T. B., Qualitative indicators of soil quality, A

minimum data set, 25-37, pub. 49, SSSA, Madison, WI, 1996.

[4] Doran, J. W., and ParkinT. B., Defining and Assessing soil quality, p 1-22.

SSSA, Pub 35, 1994.

[5] Eswaran, H., Beinroth, F. H., Reich, P. F., and Quandt, L. A.,. Soils: their

properties, classification, distribution and management. NRCS, 1999.

[6] Fritton, D. D., and G. W., Olson., Bulk density of fragi pan soil in natural and

distributed profiles, SSSA, proc, 1972, 36, 686-89.

[7] Herrick, J. E., soil quality an indication for sustainable land management,

Applied soil ecology, 2000, 15, 75-83.

[8] Hrinink, J. T. M., Soil requirements for use in urban environments, Soil till,

Res, 1998, 47, 157-162.

[9] Karlen, D. L., EashN. S., and Unger, P. W., Soil and crop management effects

on soil quality indicators, AJAA, 1992, 7, 48-55.

[10] District Census Handbook of Nellore, Directorate of Census Operations,

Andhra Pradesh, Census of India, 1991.

[11] Abassi, S. A., Water quality indices: state –of-the art, Journal IPHE, 1999, 21,

22-25.

[12] Larson, W. E., and Pierce, F. J., Construction and enhancement of soil quality,

SSSA, 1991, 35, 176.

[13] NyleC. Brady., The nature and properties of soils, 12th edition, EEE, Prenctic-

Hall, 2002.

[14] Parr, J. F., Papendic, R. I., Hornic, S. B., and R. E., Mayer, Soil quality,

Attributes and relationship to alternative and sustainable agriculture, AJAA,

1992, 7, 5.

Documents

Geospatial Data Based Modelling For Evaluation of Soil ...K. L. University, Greenfields, Vaddeswaram-522502, Guntur, A. P, India. Abstract The soil quality is attracting attention