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HYDRUS li ti t ibl i t f ti l t i i ti d tHYDRUS application to assess possible impacts of non-conventional water irrigation under two pp p p gdiff d i i idifferent vadose zone monitoring strategiesdifferent vadose zone monitoring strategies
J V ld Ab ll 1 J Ji é M tí 2 L C d l 3J. Valdes-Abellan1, J. Jiménez-Martínez2, L. Candela3
1Department of Civil Engineering, University of Alicante (Spain), [email protected] of Civil Engineering, University of Alicante (Spain), [email protected] Geosciences Rennes UMR 6118 CNRS Université de Rennes I Rennes (France) joaquin jimenez-martinez@univ-rennes1 fr3 Geosciences Rennes, UMR 6118 CNRS, Université de Rennes I. Rennes (France), [email protected]
2D t t f G t h i l E i i d G i UPC B l (S i ) l il d l @ d2Department of Geotechnical Engineering and Geoscience, UPC-Barcelona, (Spain), [email protected]
INTRODUCTIONScarcity of water resources in arid and semi‐arid areas has lead to the use of non conventional water sources, as desalination of both brackish groundwater and seawater, both for urbanScarcity of water resources in arid and semi arid areas has lead to the use of non conventional water sources, as desalination of both brackish groundwater and seawater, both for urbanand agricultural demands The non conventional water application on the vadose zone might produce impacts in porous media as changes in soil hydraulic properties among othersand agricultural demands. The non‐conventional water application on the vadose zone might produce impacts in porous media as changes in soil hydraulic properties, among others.
i i d d i i k d h ibl i di h il bl li diff i i h b i dMonitoring vadose zone water dynamics is a key aspect to study those possible impacts. According to the available literature, different monitoring systems have been carried outindependently, but less attention has received comparative studies between different techniques (Jiménez‐Martínez et al. 2009; Wallis et al. 2011; Wollschläger et al. 2009). In this study,p y, p q ( ; ; g ) y,a 9x5 m2 experimental plot was set with automatic and non‐automatic sensors to control VWC (volumetric water content) and h (soil pressure head) up to 1 5m depth Simulation ofa 9x5 m2 experimental plot was set with automatic and non‐automatic sensors to control VWC (volumetric water content) and h (soil pressure head) up to 1.5m depth. Simulation of
t fl i t ti d t ti d t i d t b HYDRUS 1Dwater flow using automatic and non‐automatic date was carried out by HYDRUS‐1D.
EXPERIMENTAL SETUPThe automatic system was composed of five 5TE sensors (Decagon Devices®) installed atThe automatic system was composed of five 5TE sensors (Decagon Devices ) installed at20 40 60 90 and 120 cm for VWC measurements and one MPS1 sensor (Decagon20, 40, 60, 90 and 120 cm for VWC measurements and one MPS1 sensor (Decagon
®) d h f h h d f llDevices®) at 60 cm depth for h. The non‐automatic system consisted of ten Jet Filltensiometers at 30, 45, 60, 90 and 120 cm (Soil Moisture®) and a polycarbonate accesstensiometers at 30, 45, 60, 90 and 120 cm (Soil Moisture ) and a polycarbonate accesstube of 44 mm (i d) for soil moisture measurements with a TRIME FM TDR portabletube of 44 mm (i.d) for soil moisture measurements with a TRIME FM TDR portable
b (IMKO®) D t th i i d t d i 9 ti th A d t il dprobe (IMKO®). Data gathering was carried out during 9 consecutive months. A detailedsoil characterization was made out in laboratory to determine the most important soily pparametersparameters.
NUMERICAL MODELLINGNUMERICAL MODELLINGR k d l d f ll i F dd (1978) d W li (1985) ERoot water uptake was modeled following Feddes (1978) and Wesseling (1985). Evapo‐transpiration was computed with Penman‐Monteith equation. A good agreement of data andp p q g gmodeled results from collected automatic and non‐automatic can be recognized General trendmodeled results from collected automatic and non‐automatic can be recognized. General trend
t d b b th t t i t f tli l t d P k t b ttwas captured by both strategies, except for outlier values, as expected. Peak events were betterregistered by automatic sensors. Slightly differences were found between hydraulic propertiesg y g y y p pobtained from laboratory determinations and from inverse modeling from the two approachesobtained from laboratory determinations, and from inverse modeling from the two approaches.Differences up to 14% of flux through the lower boundary were detected between the twoDifferences up to 14% of flux through the lower boundary were detected between the twostrategies.According to results, automatic sensors were more accurate and so more appropriated to detectAccording to results, automatic sensors were more accurate and so more appropriated to detectsubtle changes of soil hydraulic properties Nevertheless if the aim of the research is to control thesubtle changes of soil hydraulic properties. Nevertheless, if the aim of the research is to control the
l t d f t d i i ifi t diff b d b t th tgeneral trend of water dynamics, no significant differences were observed between the twosystems.y
PA i i i S i i
Pressure h d h
Volumetric water content, θAcquisition Statistic head, h
,
60 cm 30 cm 45 cm 60 cm 90 cm 120 cm All All (h and θ)
RMSE 0.21 0.05 0.04 0.02 - 0.05 0.04
A t ti
RMSE 0.21 0.05 0.04 0.02 0.05 0.04
EF 0 72 0 81 0 74 0 94 0 5 0 76Automatic EF 0.72 0.81 0.74 0.94 - 0.5 0.76
A conservative tracer test with a LiBr solution. Br‐ was considered due to R2 0.96co se at e t ace test t a so ut o . as co s de ed due tothe low background concentration of it in the soil profile In June 27th 2012 RMSE 0 16 0 07 0 05 0 10 0 12 0 14 0 10the low background concentration of it in the soil profile. In June 27th 2012
l ti f LiB (131 73 l /L) i kl d 10 2 f th l t Non-RMSE 0.16 0.07 0.05 0.10 0.12 0.14 0.10
a solution of LiBr (131.73 mmol /L) was sprinkled over 10 m2 of the plot. Nonautomatic EF 0.80 0.00 0.43 0.24 -0.02 -0.37 0.44
After 7, 37 and 57 days, undisturbed soil samples were collected at differentautomatic
R2 0.98, y , pdepths and total bromine concentration (Br) was determined by X‐ray
R 0.98depths and total bromine concentration (Br) was determined by X rayfluorescence following the methodology proposed by Abderrahim et al
CONCLUSIONSfluorescence following the methodology proposed by Abderrahim et al.( )
CONCLUSIONSThe HYDRUS simulation was able to reproduce the responses of a field scale instrumented plot with
(2011).The HYDRUS simulation was able to reproduce the responses of a field‐scale instrumented plot with
Movement of Br along the profile was well simulated with the HP1automatic and non‐automatic data. A good agreement between the predicted and measured soil water
Movement of Br along the profile was well simulated with the HP1software Soil hydraulic parameters used in that model were those obtained
content and pressure head values was obtainedsoftware. Soil hydraulic parameters used in that model were those obtainedd i t fl d li i d ith t ti i t l d t t
content and pressure head values was obtainedHydraulic parameters monitoring results complex being one of the main limitations the inability to measure
during water flux modeling period with automatic experimental data set,Hydraulic parameters monitoring results complex, being one of the main limitations the inability to measureh ff i i d ib h ll Th i d ll l d i
which validates the flow model parameterization.the effective properties to describe the overall system. The instruments used normally explore a domain
p
which is notoriously too small to describe the average property. Field measurements obtained with non‐y g p p yautomatic (vertical‐installed) instruments need to be carefully analyzed since the installation process canautomatic (vertical installed) instruments need to be carefully analyzed since the installation process canlead to preferential flow paths through the device wall even with careful installation procedures Ilead to preferential flow paths through the device wall, even with careful installation procedures. IWithout previous information on soil characteristics from laboratory determinations, inverse approachcould lead to unrealistic soil hydraulic parameters‐based simulated values using both the automatic andcould lead to unrealistic soil hydraulic parameters based simulated values using both the automatic andnon automatic datanon‐automatic data.H h d b di d h i d Si ifi diff b hHowever, the trend was better predicted than extreme episodes. Significant differences between themodeled parameters from the non‐automatic and automatic experimental data were observed. On average,p p g ,the statistics revealed that adjustments to the θ data proved better than those to the h data This fact couldthe statistics revealed that adjustments to the θ data proved better than those to the h data. This fact couldb l t d t th ilib i ti ith il th t h d d i i t bt i li blbe related to the equilibrium time with soil that pressure head devices require to obtain reliablemeasurements. For the tracer test, a good agreement between measured and predicted total bromine (Br)g g p ( )concentration along the soil profile was obtained, which validate the flow model.concentration along the soil profile was obtained, which validate the flow model.
References:dd l k d d l f ld d ld lFeddes, R.A., Kowalik, P.J. and Zaradny, H., 1978. Simulation of Field Water Use and Crop Yield. Wiley.
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