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Plant Science Today (PST)

Review Articles

Vol. 13 No. sp5 (2026): Recent Advances in Agriculture

Applications of the HYDRUS model in irrigation management, groundwater recharge and crop studies: A review

DOI
https://doi.org/10.14719/pst.15604
Submitted
18 May 2026
Published
29-07-2026

Abstract

The computer software HYDRUS was developed for simulating water movement, heat transport and solute dynamics in variably saturated porous media. HYDRUS was first introduced as SWMS-2D in 1991, followed by HYDRUS-1D in 1995, since then it has been continuously developed and has become one of the most widely used models for vadose zone hydrology applications. In this review, HYDRUS model-based studies reported in the literature are organised under three broad categories: (i) irrigation management and efficiency; (ii) groundwater recharge estimation and (iii) crop growth and root water uptake modelling. Simulation studies using HYDRUS-1D and HYDRUS-2D/3D have reliably reproduced soil water content and soil water potential dynamics under drip, furrow, sprinkler and subsurface irrigation systems. Coefficient of determination (R²) values frequently exceeded 0.90 across the reviewed studies, which is consistent with findings reported in the majority of irrigation and recharge applications. HYDRUS has also been extensively used to quantify deep percolation fluxes from land surfaces under different land-use and climate conditions to estimate groundwater recharge potential, which is particularly useful for water budget closure in arid and semi-arid regions. Integration of HYDRUS with crop models (such as DSSAT, SWAP and HP2) has helped researchers understand the partitioning of evapotranspiration (ET), nitrate leaching potential and root zone salinity dynamics for precision agriculture applications. The HYDRUS model has recently been coupled with machine learning tools to estimate model parameters, assess climate-change impacts and enable multi-process coupling for modelling constructed wetlands. Some research gaps and rarely explored areas include tropical region applications, where hydrologic data may not be readily available and standardised protocols for model calibration in heterogeneous soils. Future directions identified in this review include coupling HYDRUS with remote sensing inputs and machine learning frameworks to extend vadose zone modelling from plot to regional scales, developing physics-informed neural networks as real-time irrigation advisory tools and building standardised calibration protocols for tropical and data-limited environments where heterogeneous soils and monsoon-driven hydrology currently limit model applicability.

References

  1. 1. FAO. The state of food and agriculture 2020: overcoming water challenges in agriculture. Rome: Food and Agriculture Organization of the United Nations; 2020. https://doi.org/10.4060/cb1447en
  2. 2. UNESCO. The United Nations world water development report 2019: leaving no one behind. Paris: UNESCO; 2019.
  3. 3. Dabach S, Shani U, Lazarovitch N. Optimal tensiometer placement for high-frequency subsurface drip irrigation management in heterogeneous soils. Agric Water Manag. 2015;152:91–8. https://doi.org/10.1016/j.agwat.2015.01.003
  4. 4. Kendy E, Gérard-Marchant P, Walter MT, Zhang Y, Liu C, Steenhuis TS. A soil-water-balance approach to quantify groundwater recharge from irrigated cropland in the North China Plain. Hydrol Process. 2003;17(10):2011–31. https://doi.org/10.1002/hyp.1240
  5. 5. Mailhol JC, Ruelle P, Walser S, Schütze N, Dejean C. Analysis of AET and yield predictions under surface and buried drip irrigation systems using the crop model HYDRUS-2D and PILOTE. Agric Water Manag. 2011;98(6):1033–44. https://doi.org/10.1016/j.agwat.2011.01.014
  6. 6. Šimůnek J, Šejna M, van Genuchten MT. The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat and multiple solutes in variably saturated media. Version 2.0. IGWMC-TPS-70. Golden (CO): International Ground Water Modeling Center, Colorado School of Mines; 1998.
  7. 7. Šimůnek J, van Genuchten MT, Šejna M. Development and applications of the HYDRUS and STANMOD software packages and related codes. Vadose Zone J. 2008;7(2):587–600. https://doi.org/10.2136/vzj2007.0077
  8. 8. Šimůnek J, van Genuchten MT, Šejna M. Recent developments and applications of the HYDRUS computer software packages. Vadose Zone J. 2016;15(7):vzj2016.04.0033. https://doi.org/10.2136/vzj2016.04.0033
  9. 9. Šimůnek J, van Genuchten MT. The CHAIN_2D code for simulating the two-dimensional movement of water, heat and multiple solutes in variably saturated porous media. Research Report No. 136. Riverside (CA): U.S. Salinity Laboratory, USDA-ARS; 1994.
  10. 10. PC-Progress. HYDRUS software package. Prague (Czech Republic): PC-Progress Engineering Software; 2023. Available from: https://www.pc-progress.com
  11. 11. Šimůnek J, van Genuchten MT, Šejna M. Modeling of irrigation and related processes with HYDRUS. Adv Agron. 2023;180:107–80. https://doi.org/10.1016/bs.agron.2022.11.003
  12. 12. Skaggs TH, Trout TJ, Šimůnek J, Shouse PJ. Comparison of HYDRUS-2D simulations of drip irrigation with experimental observations. J Irrig Drain Eng. 2004;130(4):304–10. https://doi.org/10.1061/(ASCE)0733-9437(2004)130:4(304)
  13. 13. Jacques D, Šimůnek J, Mallants D, van Genuchten MT. Modeling coupled hydrological and chemical processes: long-term uranium transport following phosphorus fertilization. Vadose Zone J. 2008;7(2):698–711. https://doi.org/10.2136/vzj2007.0084
  14. 14. Ramos TB, Šimůnek J, Gonçalves MC, Martins JC, Prazeres A, Pereira LS. Two-dimensional modeling of water and nitrogen fate from sweet sorghum irrigated with fresh and blended saline waters. Agric Water Manag. 2012;111:87–104. https://doi.org/10.1016/j.agwat.2012.05.007
  15. 15. Leterme B, Mallants D, Jacques D. Sensitivity of groundwater recharge using climatic analogues and HYDRUS-1D. Hydrol Earth Syst Sci. 2012;16(8):2485–97. https://doi.org/10.5194/hess-16-2485-2012
  16. 16. Liao K, Lai X, Liu Z, Zhu Q. Applying machine learning to understand water use efficiency and the interannual variability. For Ecosyst. 2021;8:80.
  17. 17. Bandai T, Ghezzehei TA. Physics-informed neural networks with monotonicity constraints for Richardson-Richards equation: estimation of constitutive relationships and soil water flux density from volumetric water content measurements. Water Resour Res. 2021;57(2):e2020WR027642. https://doi.org/10.1029/2020WR027642
  18. 18. Phogat V, Skewes MA, McCarthy MG, Cox JW, Šimůnek J, Petrie PR. Evaluation of crop coefficients, water productivity and water balance components for wine grapes irrigated at different deficit levels by subsurface drip. Agric Water Manag. 2017;180(PA):22–34. https://doi.org/10.1016/j.agwat.2016.10.016
  19. 19. Šimůnek J, Brunetti G, Jacques D, van Genuchten MT, Šejna M. Developments and applications of the HYDRUS computer software packages since 2016. Vadose Zone J. 2024;23:e20310. https://doi.org/10.1002/vzj2.20310
  20. 20. Morianou G, Kourgialas NN, Karatzas GP. A review of HYDRUS-2D/3D applications for simulations of water dynamics, root uptake and solute transport in tree crops under drip irrigation. Water. 2023;15(4):741. https://doi.org/10.3390/w15040741
  21. 21. Langergraber G, Šimůnek J. Modeling variably saturated water flow and multicomponent reactive transport in constructed wetlands. Vadose Zone J. 2005;4(4):924–38. https://doi.org/10.2136/vzj2004.0166
  22. 22. Twarakavi NKC, Šimůnek J, Seo HS. Evaluating interactions between groundwater and vadose zone using HYDRUS-based flow package for MODFLOW. Vadose Zone J. 2008;7(2):757–68. https://doi.org/10.2136/vzj2007.0082
  23. 23. Wang TT, Zhang B, Chen HH, Hui JW, Hao L, Chen L. Progress in developments and applications of the HYDRUS model and associated coupling model packages. Hydrogeol Eng Geol. 2025;52(2):72–84.
  24. 24. Zhang Q, Shen X. Progress of water and salt transport in saline lands and HYDRUS model: a review. Acad J Sci Technol. 2023;6(1):33–9. https://doi.org/10.54097/ajst.v6i1.8279
  25. 25. Richards LA. Capillary conduction of liquids through porous mediums. Physics. 1931;1(5):318–33. https://doi.org/10.1063/1.1745010
  26. 26. Van Genuchten MT. A closed-form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci Soc Am J. 1980;44(5):892–8. https://doi.org/10.2136/sssaj1980.03615995004400050002x
  27. 27. Feddes RA, Kowalik PJ, Zaradny H. Simulation of field water use and crop yield. Wageningen: PUDOC; 1978.
  28. 28. Šimůnek J, Šejna M, van Genuchten MT. The HYDRUS-2D software package for simulating the two-dimensional movement of water, heat and multiple solutes in variably saturated media. Version 2.0. IGWMC-TPS-53. Golden (CO): International Ground Water Modeling Center, Colorado School of Mines; 1999.
  29. 29. Šimůnek J, van Genuchten MT, Šejna M. The HYDRUS software package for simulating the two- and three-dimensional movement of water, heat and multiple solutes in variably saturated media. Technical Manual. Version 1.0. Prague (Czech Republic): PC Progress; 2006.
  30. 30. Šimůnek J, Jarvis NJ, van Genuchten MT, Gärdenäs A. Review and comparison of models for describing non-equilibrium and preferential flow and transport in the vadose zone. J Hydrol. 2003;272(1–4):14–35. https://doi.org/10.1016/S0022-1694(02)00252-4
  31. 31. Javaux M, Schröder T, Vanderborght J, Vereecken H. Use of a three-dimensional detailed modeling approach for predicting root water uptake. Vadose Zone J. 2008;7(3):1079–88. https://doi.org/10.2136/vzj2007.0115
  32. 32. Shelia V, Šimůnek J, Boote K, Hoogenboom G. Coupling DSSAT and HYDRUS-1D for simulations of soil water dynamics in the soil-plant-atmosphere system. J Hydrol Hydromech. 2018;66(2):232–45. https://doi.org/10.1515/johh-2017-0055
  33. 33. Asseng S, Ewert F, Martre P, Rötter RP, Lobell DB, Cammarano D, et al. Rising temperatures reduce global wheat production. Nat Clim Chang. 2015;5(2):143–7. https://doi.org/10.1038/nclimate2470
  34. 34. Liu Y, Zeng W, Ao C, Lei G, Wu J, Huang J, et al. Optimization of winter irrigation management for salinized farmland using a coupled model of soil water flow and crop growth. Agric Water Manag. 2022;270:107765. https://doi.org/10.1016/j.agwat.2022.107765
  35. 35. Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE. 2007;50(3):885–900. https://doi.org/10.13031/2013.23153
  36. 36. Šimůnek J, van Genuchten MT, Šejna M. HYDRUS: model use, calibration and validation. Trans ASABE. 2012;55(4):1261–74. https://doi.org/10.13031/2013.42239
  37. 37. Feddes RA, Hoff H, Bruen M, Dawson T, de Rosnay P, Dirmeyer P, et al. Modeling root water uptake in hydrological and climate models. Bull Am Meteorol Soc. 2001;82(12):2797–809. https://doi.org/10.1175/1520-0477(2001)082<2797:MRWUIH>2.3.CO;2
  38. 38. Kandelous MM, Šimůnek J. Comparison of numerical, analytical and empirical models to estimate wetting patterns for surface and subsurface drip irrigation. Irrig Sci. 2010;28(5):435–44. https://doi.org/10.1007/s00271-009-0205-9
  39. 39. Ajdary K, Singh DK, Singh AK, Khanna M. Modelling of nitrogen leaching from experimental onion field under drip fertigation. Agric Water Manag. 2007;89(1–2):15–28. https://doi.org/10.1016/j.agwat.2006.12.014
  40. 40. Varavipour M, Alipour A, Khaledian MR. Simulation of nitrogen uptake and dry matter for estimation of nitrogen nutrition index during the maize growth period. J Plant Nutr. 2022;45(6):920–36. https://doi.org/10.1080/01904167.2021.1994603
  41. 41. Šimůnek J, Hopmans JW. Modeling compensated root water and nutrient uptake. Ecol Modell. 2009;220(4):505–21. https://doi.org/10.1016/j.ecolmodel.2008.11.004
  42. 42. Ranjbar A, Rahimikhoob A, Ebrahimian H, Varavipour M. Simulation of nitrogen uptake and distribution under furrows and ridges during the maize growth period using HYDRUS-2D. Irrig Sci. 2019;37(4):495–509. https://doi.org/10.1007/s00271-019-00627-5
  43. 43. Li Y, Wang Z, Zhang J, Zhao W, Liu X, Li D. Simulation effect of water and nitrogen transport under wide ridge and furrow irrigation in winter wheat using HYDRUS-2D. Agronomy. 2023;13(2):457. https://doi.org/10.3390/agronomy13020457
  44. 44. Nie WB, Nie KK, Li YB, Ma XY. HYDRUS-2D simulations of nitrate nitrogen and potassium transport characteristics under fertilizer solution infiltration of furrow irrigation. Water Supply. 2021;21(6):2665–80. https://doi.org/10.2166/ws.2020.266
  45. 45. Feng ZJ, Nie WB, Ma YP. Modeling of soil water and nitrogen transport characteristics of the furrow irrigation for urea fertilizer using HYDRUS. Int J Agric Biol Eng. 2025;18(2):169–78. https://doi.org/10.25165/j.ijabe.20251802.8850
  46. 46. Kumar N, Rai V, Kumar M, Chandra R, Aggarwal P, Jain SK. Assessing soil water dynamics and wheat growth under different irrigation and planting strategies using HYDRUS-2D. Hydrol Res. 2025;56(9):878–901. https://doi.org/10.2166/nh.2025.026
  47. 47. Ouerfel SH, Gharbi E, Feki N, Hachicha M, Provenzano G, Antonellini M, et al. Modeling water and salt dynamics by HYDRUS 2D/3D under drip and surface irrigated carrot in arid regions. Land. 2025;15(1):197. https://doi.org/10.3390/land15010197
  48. 48. Gärdenäs AI, Hopmans JW, Hanson BR, Šimůnek J. Two-dimensional modeling of nitrate leaching for various fertigation scenarios under micro-irrigation. Agric Water Manag. 2005;74(3):219–42. https://doi.org/10.1016/j.agwat.2004.11.011
  49. 49. Im SJ, Park JY, Jang CH, Jang TI. Simulation of soil water movement in upland soils under sprinkler and spray hose irrigation using HYDRUS-1D. J Biosyst Eng. 2022;47(4):412–21. https://doi.org/10.1007/s42853-022-00158-6
  50. 50. Er-Raki S, Ezzahar J, Merlin O, Amazirh A, Ait Hssaine B, Kharrou MH, et al. Performance of the HYDRUS-1D model for water balance components assessment of irrigated winter wheat under different water managements in semi-arid region of Morocco. Agric Water Manag. 2021;244:106455. https://doi.org/10.1016/j.agwat.2020.106455
  51. 51. Naghedifar SM, Ziaei AN, Ansari H. Simulation of irrigation return flow from a Triticale farm under sprinkler and furrow irrigation systems using experimental data: a case study in arid region. Agric Water Manag. 2018;210:185–97. https://doi.org/10.1016/j.agwat.2018.07.036
  52. 52. Wang Y, Sun H, Qu Z, Zhang X, Xu Y. Evaluating the effects of irrigation water salinity on water movement, crop yield and water use efficiency by means of a coupled hydrologic/crop growth model. Agric Water Manag. 2015;160:62–73. https://doi.org/10.1016/j.agwat.2015.07.007
  53. 53. Martello M, Dal Ferro N, Bortolini L, Morari F. Effect of incident rainfall redistribution by maize canopy on soil moisture at the crop row scale. Water. 2015;7(5):2254–71. https://doi.org/10.3390/w7052254
  54. 54. Scanlon BR, Keese K, Reedy RC, Šimůnek J, Andraski BJ. Variations in flow and transport in thick desert vadose zones in response to paleoclimatic forcing (0–90 kyr): field measurements, modeling and uncertainties. Water Resour Res. 2003;39(7):1179. https://doi.org/10.1029/2002WR001604
  55. 55. Dripps WR, Bradbury KR. A simple daily soil-water balance model for estimating the spatial and temporal distribution of groundwater recharge in temperate humid areas. Hydrogeol J. 2007;15(3):433–44. https://doi.org/10.1007/s10040-007-0160-6
  56. 56. Šimůnek J, Bradford SA. Vadose zone modeling: introduction and importance. Vadose Zone J. 2008;7(2):581–6. https://doi.org/10.2136/vzj2008.0012
  57. 57. Kurtzman D, Scanlon BR. Groundwater recharge through vertisols: irrigated cropland vs. natural land, Israel. Vadose Zone J. 2011;10(2):662–74. https://doi.org/10.2136/vzj2010.0109
  58. 58. Coppola A, Basile A, Comegna A, Lamaddalena N. Monte Carlo analysis of field water flow comparing uni- and bimodal effective hydraulic parameters for structured soil. J Contam Hydrol. 2009;104(1–4):153–65. https://doi.org/10.1016/j.jconhyd.2008.09.007
  59. 59. Ma Y, Feng S, Su D, Gao G, Huo Z. Modeling water infiltration in a large layered soil column with a modified Green-Ampt model and HYDRUS-1D. Comput Electron Agric. 2010;71(S1):S40–7. https://doi.org/10.1016/j.compag.2009.10.001
  60. 60. Sasidharan S, Bradford SA, Šimůnek J, DeJong B, Kraemer SR. Evaluating drywells for stormwater management and enhanced aquifer recharge. Adv Water Resour. 2018;116:167–77. https://doi.org/10.1016/j.advwatres.2018.04.003
  61. 61. Sasidharan S, Bradford SA, Šimůnek J, Kraemer SR. Drywell infiltration and hydraulic properties in heterogeneous soil profiles. J Hydrol. 2019;570:598–611. https://doi.org/10.1016/j.jhydrol.2018.12.073
  62. 62. Sasidharan S, Bradford SA, Šimůnek J, Kraemer SR. Groundwater recharge from drywells under constant head conditions. J Hydrol. 2020;583:124569. https://doi.org/10.1016/j.jhydrol.2020.124569
  63. 63. Sasidharan S, Bradford SA, Šimůnek J, Kraemer SR. Virus transport from drywells under constant head conditions: a modeling study. Water Res. 2021;197:117040. https://doi.org/10.1016/j.watres.2021.117040
  64. 64. Sasidharan S, Bradford SA. Assessing drywell designs for managed aquifer recharge via canals and repurposed wells. Sci Rep. 2025;15:1829. https://doi.org/10.1038/s41598-024-84865-4
  65. 65. Bali KH, Mohamed AZ, Begna S, Wang D, Putnam D, Dahlke HE, et al. The use of HYDRUS 2D to simulate intermittent agricultural managed aquifer recharge in alfalfa in the San Joaquin Valley. Agric Water Manag. 2023;282:108296. https://doi.org/10.1016/j.agwat.2023.108296
  66. 66. Schmidt I, Schulz S, Brindha K, Schneider M. Effectiveness of irrigation tanks for enhancing groundwater recharge. Hydrol Process. 2025;39:e70328. https://doi.org/10.1002/hyp.70328
  67. 67. Eshtawi T. Modeling recharge rates of stormwater ponds into the vadose zone: a case study in a semi-arid region. Jordan J Earth Environ Sci. 2025;16(1):67–74.
  68. 68. Mavundla KP, Okedi J, Kalumba D, Armitage NP. Estimation of infiltration parameters for groundwater augmentation in Cape Town, South Africa. Hydrology. 2025;12:87. https://doi.org/10.3390/hydrology12040087
  69. 69. Guram S, Bashir R. Designing effective low-impact developments for a changing climate: a HYDRUS based vadose zone modeling approach. Water. 2024;16(13):1803. https://doi.org/10.3390/w16131803
  70. 70. Yuan Y, Carroll KC, Shukla MK, Rucker DF, Fuchs EH, Pearson AJ, et al. Intermittent and transient river-groundwater transitions from disconnection to connection. Water Resour Res. 2025;61:e2024WR038069. https://doi.org/10.1029/2024WR038069
  71. 71. Ruhan A, Li S, Liu B, Rene ER, Ma W. Precise simulation of PAHs infiltration from surface water to groundwater with LSTM modified loosely coupled HYDRUS GMS model. J Environ Chem Eng. 2025;13(6):118954. https://doi.org/10.1016/j.jece.2025.118954
  72. 72. Meixner T, Manning AH, Stonestrom DA, Allen DM, Ajami H, Blasch KW, et al. Implications of projected climate change for groundwater recharge in the western United States. J Hydrol. 2016;534:124–38. https://doi.org/10.1016/j.jhydrol.2015.12.027
  73. 73. Jackson CR, Meister R, Prudhomme C. Modelling the effects of climate change and its uncertainty on UK Chalk groundwater resources from an ensemble of global climate model projections. J Hydrol. 2011;399(1–2):12–28. https://doi.org/10.1016/j.jhydrol.2010.12.028
  74. 74. Vrugt JA, van Wijk MT, Hopmans JW, Šimůnek J. One-, two- and three-dimensional root water uptake functions for transient modeling. Water Resour Res. 2001;37(10):2457–70. https://doi.org/10.1029/2000WR000027
  75. 75. Cai G, Vanderborght J, Couvreur V, Mboh CM, Vereecken H. Parameterization of root water uptake models considering dynamic root distributions and water uptake compensation. Vadose Zone J. 2018;17(1):160125. https://doi.org/10.2136/vzj2016.12.0125
  76. 76. Hupet F, Lambot S, Javaux M, Vanclooster M. On the identification of macroscopic root water uptake parameters from soil water content observations. Water Resour Res. 2003;39(12):1345. https://doi.org/10.1029/2003WR002046
  77. 77. Schelle H, Iden SC, Fank J, Durner W. Inverse estimation of soil hydraulic and root distribution parameters from lysimeter data. Vadose Zone J. 2012;11(4):vzj2011.0169. https://doi.org/10.2136/vzj2011.0169
  78. 78. Mathieu JA, Haas T, de Jong van Lier Q. Mathematical description of rooting profiles of agricultural crops and its effect on transpiration prediction by a hydrological model. Soil Systems. 2019;3(3):44. https://doi.org/10.3390/soilsystems3030044
  79. 79. Whalley WR, Jenkins M, Atkinson BSA. The relationship between the sensitivity of root water uptake to soil water potential and rooting depth in wheat lines. Plant Soil. 2020;448:157–73. https://doi.org/10.1007/s11104-020-04414-w
  80. 80. Bufon VB, Lascano RJ, Bednarz C, Booker JD, Gitz DC. Soil water content on drip irrigated cotton: comparison of measured and simulated values obtained with the Hydrus 2-D model. Irrig Sci. 2012;30(4):259–72. https://doi.org/10.1007/s00271-011-0279-z
  81. 81. Nazari E, Parsinezhad M, Dehghani Sanij H, Khaledian M. Measurement and simulation of the water flow and root uptake in soil under subsurface drip irrigation of apple tree. Agric Water Manag. 2021;255:107026. https://doi.org/10.1016/j.agwat.2021.107026
  82. 82. Autovino D, Rallo G, Provenzano G. Predicting soil and plant water status dynamic in olive orchards under different irrigation systems with Hydrus-2D: model performance and scenario analysis. Agric Water Manag. 2018;203:225–35. https://doi.org/10.1016/j.agwat.2018.03.015
  83. 83. Zeng W, Lei G, Zha Y, Fang Y, Wu J, Huang J. Sensitivity and uncertainty analysis of the HYDRUS-1D model for root water uptake in saline soils. Crop Pasture Sci. 2018;69(2):163–73. https://doi.org/10.1071/CP17020
  84. 84. Daryanto S, Wang L, Jacinthe PA. Global synthesis of drought effects on maize and wheat production. PLoS ONE. 2016;11(5):e0156362. https://doi.org/10.1371/journal.pone.0156362
  85. 85. Zhang Y, Sun J, Liu H, Dong B, Liu M, Lu X. Integrated effects of soil moisture on wheat hydraulic properties and stomatal regulation. Plants. 2024;13(16):2263. https://doi.org/10.3390/plants13162263
  86. 86. Liao Q, Gu S, Kang S, Du T, Tong L, Wood JD, et al. Mild water and salt stress improve water use efficiency by decreasing stomatal conductance via osmotic adjustment in field maize. Sci Total Environ. 2022;805:150364. https://doi.org/10.1016/j.scitotenv.2021.150364
  87. 87. Neumann RB, Cardon ZG. The magnitude of hydraulic redistribution by plant roots: a review and synthesis of empirical and modelling studies. New Phytol. 2012;194(2):337–52. https://doi.org/10.1111/j.1469-8137.2012.04088.x
  88. 88. Langergraber G, Šimůnek J. Reactive transport modeling of subsurface flow constructed wetlands using the HYDRUS Wetland Module. Vadose Zone J. 2012;11(2):vzj2011.0104. https://doi.org/10.2136/vzj2011.0104
  89. 89. Phogat V, Šimůnek J, Skewes MA, Cox JW, McCarthy MG. Improving the estimation of evaporation by the FAO-56 dual crop coefficient approach under subsurface drip irrigation. Agric Water Manag. 2016;178:189–200. https://doi.org/10.1016/j.agwat.2016.09.011
  90. 90. Ranatunga K, Nation ER, Barratt DG. Review of soil water models and their applications in Australia. Environ Model Softw. 2008;23(9):1182–206. https://doi.org/10.1016/j.envsoft.2008.02.003
  91. 91. Karandish F, Šimůnek J. A comparison of numerical and machine-learning modeling of soil water content with limited input data. J Hydrol. 2016;543:892–909. https://doi.org/10.1016/j.jhydrol.2016.11.007
  92. 92. Karandish F, Šimůnek J. Two-dimensional simulation of nitrate leaching under variable-rate nitrogen fertigation for various on-farm irrigation systems. Agric Water Manag. 2017;193:174–90. https://doi.org/10.1016/j.agwat.2017.08.006
  93. 93. Andarzian B, Bannayan M, Steduto P, Mazraeh H, Barati ME, Barati MA, et al. Validation and testing of the AquaCrop model under full and deficit irrigated wheat production in Iran. Agric Water Manag. 2011;100(1):1–8. https://doi.org/10.1016/j.agwat.2011.08.023
  94. 94. Pot V, Šimůnek J, Benoit P, Coquet Y, Yra A, Martínez-Cordón MJ. Impact of rainfall intensity on the transport of two herbicides in undisturbed grassed filter strip soil cores. J Contam Hydrol. 2005;81(1–4):63–88. https://doi.org/10.1016/j.jconhyd.2005.06.013
  95. 95. Filipović V, Mallmann FJK, Coquet Y, Šimůnek J. Numerical simulation of water flow in tile and mole drainage systems. Agric Water Manag. 2014;146:105–14. https://doi.org/10.1016/j.agwat.2014.07.020
  96. 96. Vereecken H, Schnepf A, Hopmans JW, Javaux M, Or D, Roose T, et al. Modeling soil processes: review, key challenges and new perspectives. Vadose Zone J. 2016;15(5):vzj2015.09.0131. https://doi.org/10.2136/vzj2015.09.0131
  97. 97. Seo HS, Šimůnek J, Poeter EP. Documentation of the HYDRUS Package for MODFLOW-2000, the U.S. Geological Survey Modular Ground-Water Model. GWMI 2007–01. Golden (CO): International Ground Water Modeling Center, Colorado School of Mines; 2007.

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