Evaluation of HYDRUS- 2D/3D in Water Infiltration Simulation into Soil with Different Textures via Inverse Solution

Document Type : Original Article

Authors

1 Soil and Water Research Department, Isfahan Agricultural and Natural Resources Research and Education Center. Agricultural Research, Education and Extension organization (AREEO), Isfahan, Iran.

2 Soil and Water Research Department, Isfahan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Isfahan, Iran

Abstract

In recent years, inverse numerical solution methods have been considered by many researchers to address the problems of water movement in soil. In this study, HYDRUS-2D/3D software was used to simulate water infiltration through double-rings infiltrometers in soils with different textures using the inverse solution approach. For this purpose, the infiltration data obtained by double-rings method from 63 points of different regions in Isfahan were used as model input. The studied soils were classified into seven textural classes including Sandy Loam (SL), Sandy Clay Loam (SCL), Loam (L), Silty Loam (SiL), Clay Loam (CL), Silty Clay Loam (SiCL) and SiC (Silty Clay). Good agreement was observed between the measured and simulated cumulative infiltration data, in all soil textures. Coefficients of determination (R2) were 0.998, 0.999, 0.992, 0.996, 0.983, 0.976 and 995 for SL, SCL, L, SiL, CL, SiCL and SiC textures, respectively. Increasing the percentage of clay in the soil textures increased the simulation error. The highest simulation error was observed in SiC (NRMSE = 0.045) and the lowest simulation error was observed in SL (NRMSE = 0.015). In general, the simulated double-rings infiltration data using HYDRUS -2D / 3D software and the inverse numerical solution approach had acceptable accuracy and high reliability in all studied textures.

Keywords

References

Abbasi F., Šimůnek J., Feyen J., van Genuchten MTh., and Shouse PJ. 2003. Simultaneous inverse estimation of soil hydraulic and solute transport parameters from transient field experiments: homogeneous soil. Transactions of ASAE, 46(4): 1085–1095.
Alletto L., Pot, V., Giuliano S., CostesM., Perdrieux F., and Justes E. 2015. Temporal variation in soil physical properties improves the water dynamics modeling in a conventionally-tilled soil. Geoderma, 243 (244): 18–28.
Cook F.J. 2002. The Twin-Ring Method for Measuring Saturated Hydraulic Conductivity and Sorptivity in the Field. McKenzie, N. Coughlan, K. and H. Cresswell (ed.), Soil Physical Measurement and Interpretation for Land Evaluation. CSIRO Publishing. Pp 108-118.
Duiker S.W., Flanagan D.C., and Lal R. 2001. Erodibility and infiltration characterstics of fire major soils of southwest Spain. Catena, 45(2): 103-121.
El-Nesr N. M., Alazba A. A., and Šimůnek J. 2014.  HYDRUS simulations of the effects of dual-drip subsurface irrigation and a physical barrier on water movement and solute transport in soils. Irrigation Scince, (32): 111–125.
Farasati M., and Shakeri H. 2017. Simulation of water infiltration in the soil using HYDRUS1D software and field data. Journal of Water and Soil Conservation, 25(3):113-128. (In Persian)
Gribb M. M., Forkutsa I., Hansen A., Chandler D. G., and McNamara J. P. 2009. The Effect of various soil hydraulic property esti mates on soil moisture simulations. Vadose Zone Journal, 8(2): 321–331
Huang J., Wu P., and Xining Z. 2013. Effects of rainfall intensity, underlying surface and slope gradient on soil infiltration under simulated rainfall experiments. Catena, 104: 93-102.
Jasper A., Vrugt P., Stauffer H., Wöhling T. H., Bruce A., and Velimir, V. 2008. Inverse modeling of Subsurface flow and transport properties: A review with new developments. Vadose Zone Journal, 7(2): 843–864.
Karimipour A., and Banitalebi G. 2020. Sensitivity analysis of meteorological data in estimating reference evapotranspiration with the minimum data using wavelet-neuro-fuzzy, ANN and ANFIS models. Water and Soil Resources Conservation, 9(3). (In Persian)
Lai J., and Ren L. 2016. Buffer index effects on hydraulic conductivity measurements using numerical simulations of double-ring infiltration. Soil Science Society American Journal, 74: 1526–1536.
Maa Y., Feng S., Sua D., Gao G., and Huo Z. 2010. Modeling water infiltration in a large layered soil column with a modified Green–Ampt model and HYDRUS-1D. Computers and Electronics in Agriculture, 71: 40–47.
Marquardt D W. 1963. An algorithm for least squares estimation of non-linear parameters. Journal of Industrial and Applied Mathematics, 11: 431–441.
Mashayekhi P., Ghorbani Dashtaki S., Mosaddeghi M.R., Shirani H., and Mohammadi Nodoushan A.R. 2016. Different scenarios for inverse estimation of soil hydraulic parameters from double ring infiltrometer data using HYDRUS 2D/3D. International Agrophysics, 30(2): 203-210.
Mashayekhi P., Ghorbani Dashtaki S., Mosaddeghi M.R., Shirani H., and Nouri M.R. 2017. Estimation of soil hydraulic parameters using double-ring infiltrometer data via inverse method. Iranian Journal of Water and Soil Research, 47(4): 829-838. (In Persian)
Mashayekhi P., Ghorbani Dashtaki S., Mosaddeghi M.R., Shirani H., Panahi M., and Nouri M.R. 2017. Inverse estimation of the soil water retention curve parameters using double-ring infiltration data. Applied Soil Research, 4(2): 26-37. (In Persian)
Minasny B., and McBratney A.B. 2002. The Neuro- m method for fitting neural network parametric pedotransfer functions. Soil Science Society of America journal, 66: 352– 361.
 Mousavi dehmurdi A., Ghorbani Dashtaki Sh., and Mashayekhi P. 2018. Evaluation of double-ring infiltrometers method for measuring the vertical infiltration in different soil textures using HYDRUS. Journal of Water and Soil conservation, 25 (3): 241-253. (In Persian)
Mousavi Dehmurdi A., Ghorbani-Dashtaki Sh. , and Mashayekhi P. 2019. Performance of some infiltration models based on obtained data from double-ring and HYDRUS-1D software. Applied Soil Research, 7(2): 182-195.
Mualem Y. 1976. A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resources Research, 12(3): 513–522.
Pollalis E. D., and Valiantzas J. D. 2015. Isolation of a 1D infiltration time interval under ring infiltrometers for determining sorptivity and saturated hydraulic conductivity: numerical, theoretical, and experimental approach. Journal of Irrigation and Drainage Engineering, 141(2). 10.1061/ (ASCE) IR.1943- 774.0000796.
Puhlmann H., von Wilpert K., Lukes M., and Dröge W. 2009. Multistep outflow experiments to derive a soil hydraulic database for forest soils. European Journal of Soil Science, 60: 792–806.
Ramos T. B., Šimůnek J., Gonҫalves M. C., Martins J. C., Prazeres A., and Pereira L. S. 2012. Two-dimensional modeling of water and nitrogen fate from sweet sorghum irrigated with fresh and blended saline waters. Agricultural Water Management, 111: 87–104.
Rashid, N.S.A., Askari, M., Tanaka, T., Šimůnek, J. and van Genuchten, M.Th. (2015). Inverse estimation of soil hydraulic properties under oil palm trees. Geoderma, (241–242), 306–312.
Russo D., Bresler E., Shani U., and Parker J.C. 1991. Analysis of infiltration events in relation to determining soil hydraulic properties by inverse problem methodology. Water Resources Research, (27): 1361–1373.
Raoof M., and Pilpayeh A. R. 2013. Estimating soil wetting profile under saturated infiltration process by numerical inversion solution in land slopes. Middle-East Journal of Scientific Research, 13(6): 732–736.
Santos F.L., Reis J.L., Martins O.C., Castanheria N.L., and Serralherio R.P. 2003. Comparative assessment of infiltration, runoff and erosion of sprinkler irrigation soils. Biosystems Engineering, 86(3): 355-364.
Schelle H., Iden S.C., Schlüter S., Vogel H. J., and Durner W. 2012. Identification of effective flow processes and properties from virtual soils using inverse modeling. Geophysical Research Abstracts 14.
Richards L. A. 1931. Capillary conduction of liquids through porous mediums. Physics, 1:318–333.
Šimůnek J., and van Genuchten M. Th. 1996. Estimating unsaturated soil hydraulic properties from tension disc data by numerical inversion. Water Resources Research, 32(9): 2683–2696.
Šimůnek J., Kodesová R., and Gribb M. M. 1999. Estimating hysteresis in the soil water retention function from modified cone penetrometer test. Water Resources Research, 35: 1329–1345.
Šimůnek J., Šejna M., and van Genuchten M. Th. 2012. HYDRUS: model use, calibration and validation. American Society of Agricultural and Biological Engineers, 55(4): 1261-1274.
Vanclooster M., Javaux M., and Lambot S. 2007. Recent advances in characterizing flow and transport in unsaturated soil at the core and field. Estudios de la Zona No Saturada del Suelo, 3: 19–35.
Van Genuchten M. Th. 1980. A closed–form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Science Society of America Journal, 44(5): 892–898.
Vereecken H., Weynants M., Javaux M., Pachepsky Y., Schaap M.G., and van Genuchten M.Th. 2010. Using pedotransfer functions to estimate the van Genuchten–Mualem soil hydraulic properti es: A review. Vadose Zone Journal, 9: 795–820. doi:10.2136/vzj2010.0045
Vogel H. J., Samouelian A., and Ippisch O. 2008. Multi-step and twostep experiments in heterogeneous porous media to evaluate the relevance of dynamic effects. Advances in Water Resources, 3:181– 188.
Wakindiki I.I.C., and Ben-Hur M. 2002. Soil mineralogy and texture effects on crust micromorphology, infiltration, erosion. Soil Science Society of America Journal, 66(3): 897-905.
Wang Q.J., Horton R., and Shao M. A. 2002. Horizontal infiltration method for determining Brooks-Corey model parameters. Soil Science Society of America Journal, 66: 1733–1739.
Applied Soil Research
Volume 10, Issue 1
June 2022
Pages 98-110

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History

  • Receive Date: 04 December 2020
  • Revise Date: 23 January 2021
  • Accept Date: 27 January 2021

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