SWAP in action

Below you can find the list of publications that are relevant for SWAP.

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Alavi, S.A., A.A. Naseri, H. Ritzema, J. van Dam, and P. Hellegers. 2022. A combined model approach to optimize surface irrigation practice: SWAP and WinSRFR. Agricultural Water Management 271: 107741. doi: 10.1016/j.agwat.2022.107741.

Ali, A., Y.A. Al-Mulla, Y. Charabi, M. Al-Wardy, and G. Al-Rawas. 2021. Use of multispectral and thermal satellite imagery to determine crop water requirements using SEBAL, METRIC, and SWAP models in hot and hyper-arid oman. Arabian Journal of Geosciences 14(7). doi: 10.1007/s12517-021-06948-0.

Alves Rodrigues Pinheiro, E., and Q. de Jong van Lier. 2021. Propagation of uncertainty of soil hydraulic parameterization in the prediction of water balance components: A stochastic analysis in kaolinitic clay soils. Geoderma 388: 114910. doi: 10.1016/j.geoderma.2020.114910.

Alves Rodrigues Pinheiro, E., and M.R. Nunes. 2023. Long-term agro-hydrological simulations of soil water dynamic and maize yield in a tillage chronosequence under subtropical climate conditions. Soil and Tillage Research 229: 105654. doi: 10.1016/j.still.2023.105654.

Anupoju, V., B.P. Kambhammettu, and S.K. Regonda. 2021. Role of short-term weather forecast horizon in irrigation scheduling and crop water productivity of rice. Journal of Water Resources Planning and Management 147(8). doi: 10.1061/(asce)wr.1943-5452.0001406.

Auwalu, A., and J.H. Abdulkareem. 2023. Plant morphological structures as influenced by soil hydraulic properties: A review. Communications in Soil Science and Plant Analysis 54(21): 2915–2938. doi: 10.1080/00103624.2023.2253848.

Bartholomeus, R.P., J.H. Stagge, L.M. Tallaksen, and J.P.M. Witte. 2015. Sensitivity of potential evaporation estimates to 100 years of climate variability. Hydrology and Earth System Sciences 19(2): 997–1014. doi: 10.5194/hess-19-997-2015.

Bartholomeus, R.P., J.-P.M. Witte, P.M. van Bodegom, J.C. van Dam, and R. Aerts. 2008. Critical soil conditions for oxygen stress to plant roots: Substituting the feddes-function by a process-based model. Journal of Hydrology 360(1–4): 147–165. doi: 10.1016/j.jhydrol.2008.07.029.

Bartholomeus, R.P., J.-P.M. Witte, P.M. van Bodegom, J.C. van Dam, and R. Aerts. 2011. Climate change threatens endangered plant species by stronger and interacting water-related stresses. Journal of Geophysical Research 116(G4). doi: 10.1029/2011jg001693.

Belmans, C., J.G. Wesseling, and R.A. Feddes. 1983. Simulation model of the water balance of a cropped soil: SWATRE. Journal of Hydrology 63(3–4): 271–286. doi: 10.1016/0022-1694(83)90045-8.

Ben-Asher, J., J. van Dam, R.A. Feddes, and R.K. Jhorar. 2006. Irrigation of grapevines with saline water. Agricultural Water Management 83(1–2): 22–29. doi: 10.1016/j.agwat.2005.11.006.

Bennett, S.J., T.F.A. Bishop, and R.W. Vervoort. 2013. Using SWAP to quantify space and time related uncertainty in deep drainage model estimates: A case study from northern NSW, australia. Agricultural Water Management 130: 142–153. doi: 10.1016/j.agwat.2013.08.020.

Berg, F. van den, A. Tiktak, G.B.M. Heuvelink, S.L.G.E. Burgers, D.J. Brus, et al. 2012. Propagation of uncertainties in soil and pesticide properties to pesticide leaching. Journal of Environmental Quality 41(1): 253–261. doi: 10.2134/jeq2011.0167.

Bessembinder, J.J.E., P.A. Leffelaar, A.S. Dhindwal, and T.C. Ponsioen. 2005. Which crop and which drop, and the scope for improvement of water productivity. Agricultural Water Management 73(2): 113–130. doi: 10.1016/j.agwat.2004.10.004.

Bhuyan, M.I., I. Supit, S. Mia, M. Mulder, and F. Ludwig. 2023. Effect of soil and water salinity on dry season boro rice production in the south-central coastal area of bangladesh. Heliyon 9(8): e19180. doi: 10.1016/j.heliyon.2023.e19180.

Bonfante, A., A. Basile, M. Acutis, R. De Mascellis, P. Manna, et al. 2010. SWAP, CropSyst and MACRO comparison in two contrasting soils cropped with maize in northern italy. Agricultural Water Management 97(7): 1051–1062. doi: 10.1016/j.agwat.2010.02.010.

Bonfante, A., A. Basile, and J. Bouma. 2020. Exploring the effect of varying soil organic matter contents on current and future moisture supply capacities of six italian soils. Geoderma 361: 114079. doi: 10.1016/j.geoderma.2019.114079.

Bonfante, A., A. Basile, P. Manna, and F. Terribile. 2011. Use of physically based models to evaluate USDA soil moisture classes. Soil Science Society of America Journal 75(1): 181–191. doi: 10.2136/sssaj2009.0403.

Bonfante, A., and J. Bouma. 2015. The role of soil series in quantitative land evaluation when expressing effects of climate change and crop breeding on future land use. Geoderma 259–260: 187–195. doi: 10.1016/j.geoderma.2015.06.010.

Bonfante, A., E. Monaco, G. Langella, P. Mercogliano, E. Bucchignani, et al. 2018. A dynamic viticultural zoning to explore the resilience of terroir concept under climate change. Science of The Total Environment 624: 294–308. doi: 10.1016/j.scitotenv.2017.12.035.

Bonfante, A., M.H. Sellami, M.T. Abi Saab, R. Albrizio, A. Basile, et al. 2017. The role of soils in the analysis of potential agricultural production: A case study in lebanon. Agricultural Systems 156: 67–75. doi: 10.1016/j.agsy.2017.05.018.

Bonfante, A., F. Terribile, and J. Bouma. 2019. Refining physical aspects of soil quality and soil health when exploring the effects of soil degradation and climate change on biomass production: An italian case study. SOIL 5(1): 1–14. doi: 10.5194/soil-5-1-2019.

Bonten, L.T.C., J.G. Kroes, P. Groenendijk, and B. van der Grift. 2012. Modeling diffusive cd and zn contaminant emissions from soils to surface waters. Journal of Contaminant Hydrology 138–139: 113–122. doi: 10.1016/j.jconhyd.2012.06.008.

Boogaard, H., J. Wolf, I. Supit, S. Niemeyer, and M. van Ittersum. 2013. A regional implementation of WOFOST for calculating yield gaps of autumn-sown wheat across the european union. Field Crops Research 143: 130–142. doi: 10.1016/j.fcr.2012.11.005.

Chen, S., X. Mao, D.A. Barry, and J. Yang. 2019. Model of crop growth, water flow, and solute transport in layered soil. Agricultural Water Management 221: 160–174. doi: 10.1016/j.agwat.2019.04.031.

Chirico, G.B., H. Medina, and N. Romano. 2010. Functional evaluation of PTF prediction uncertainty: An application at hillslope scale. Geoderma 155(3–4): 193–202. doi: 10.1016/j.geoderma.2009.06.008.

Cirkel, D.G., J.-P.M. Witte, and S.E.A.T.M. van der Zee. 2010. Estimating seepage intensities from groundwater level time series by inverse modelling: A sensitivity analysis on wet meadow scenarios. Journal of Hydrology 385(1–4): 132–142. doi: 10.1016/j.jhydrol.2010.02.009.

Corona-López, E., A.D. Román-Gutiérrez, E.M. Otazo-Sánchez, F.A. Guzmán-Ortiz, and O.A. Acevedo-Sandoval. 2021. Water–food nexus assessment in agriculture: A systematic review. International Journal of Environmental Research and Public Health 18(9): 4983. doi: 10.3390/ijerph18094983.

Crescimanno, G., and P. Garofalo. 2005. Application and evaluation of the SWAP model for simulating water and solute transport in a cracking clay soil. Soil Science Society of America Journal 69(6): 1943–1954. doi: 10.2136/sssaj2005.0051.

Dam, J.C. van, and R.A. Feddes. 2000. Numerical simulation of infiltration, evaporation and shallow groundwater levels with the richards equation. Journal of Hydrology 233(1–4): 72–85. doi: 10.1016/s0022-1694(00)00227-4.

Dam, J.C. van, P. Groenendijk, R.F.A. Hendriks, and J.G. Kroes. 2008. Advances of modeling water flow in variably saturated soils with SWAP. Vadose Zone Journal 7(2): 640–653. doi: 10.2136/vzj2007.0060.

Dam, J.C. van, J.H.M. Wösten, and A. Nemes. 1996. Unsaturated soil water movement in hysteretic and water repellent field soils. Journal of Hydrology 184(3–4): 153–173. doi: 10.1016/0022-1694(95)02996-6.

Dokoohaki, H., M. Gheysari, S.-F. Mousavi, S. Zand-Parsa, F.E. Miguez, et al. 2016. Coupling and testing a new soil water module in DSSAT CERES-maize model for maize production under semi-arid condition. Agricultural Water Management 163: 90–99. doi: 10.1016/j.agwat.2015.09.002.

Droogers, P., W.G.M. Bastiaanssen, M. Beyazgül, Y. Kayam, G.W. Kite, et al. 2000. Distributed agro-hydrological modeling of an irrigation system in western turkey. Agricultural Water Management 43(2): 183–202. doi: 10.1016/s0378-3774(99)00055-4.

Droogers, P., A. Van Loon, and W.W. Immerzeel. 2008. Quantifying the impact of model inaccuracy in climate change impact assessment studies using an agro-hydrological model. Hydrology and Earth System Sciences 12(2): 669–678. doi: 10.5194/hess-12-669-2008.

Eberhard, J., N.L.M.B. van Schaik, A. Schibalski, and T. Gräff. 2020. Simulating future salinity dynamics in a coastal marshland under different climate scenarios. Vadose Zone Journal 19(1). doi: 10.1002/vzj2.20008.

Eitzinger, J., M. Trnka, J. Hösch, Z. Žalud, and M. Dubrovský. 2004. Comparison of CERES, WOFOST and SWAP models in simulating soil water content during growing season under different soil conditions. Ecological Modelling 171(3): 223–246. doi: 10.1016/j.ecolmodel.2003.08.012.

Farmaha, B.S., Pritpal-Singh, and Bijay-Singh. 2021. Spatial and temporal assessment of nitrate-n under rice-wheat system in riparian wetlands of punjab, north-western india. Agronomy 11(7): 1284. doi: 10.3390/agronomy11071284.

Faúndez Urbina, C.A., F. van den Berg, J.C. van Dam, D.W.S. Tang, and C.J. Ritsema. 2020. Parameter sensitivity of SWAP–PEARL models for pesticide leaching in macroporous soils. Vadose Zone Journal 19(1). doi: 10.1002/vzj2.20075.

Feddes, R.A., P. Kabat, P.J.T. Van Bakel, J.J.B. Bronswijk, and J. Halbertsma. 1988. Modelling soil water dynamics in the unsaturated zone — state of the art. Journal of Hydrology 100(1–3): 69–111. doi: 10.1016/0022-1694(88)90182-5.

Feddes, R.A., P. Kowalik, K. Kolinska-Malinka, and H. Zaradny. 1976. Simulation of field water uptake by plants using a soil water dependent root extraction function. Journal of Hydrology 31(1–2): 13–26. doi: 10.1016/0022-1694(76)90017-2.

Gelsinari, S., V.R.N. Pauwels, E. Daly, J. van Dam, R. Uijlenhoet, et al. 2021. Unsaturated zone model complexity for the assimilation of evapotranspiration rates in groundwater modelling. Hydrology and Earth System Sciences 25(4): 2261–2277. doi: 10.5194/hess-25-2261-2021.

Hack-ten Broeke, M.J.D. 2001. Irrigation management for optimizing crop production and nitrate leaching on grassland. Agricultural Water Management 49(2): 97–114. doi: 10.1016/s0378-3774(00)00141-4.

Hack-ten Broeke, M.J.D., J.G. Kroes, R.P. Bartholomeus, J.C. van Dam, A.J.W. de Wit, et al. 2016. Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions. SOIL 2(3): 391–402. doi: 10.5194/soil-2-391-2016.

Hack-ten Broeke, M.J.D., H.M. Mulder, R.P. Bartholomeus, J.C. van Dam, G. Holshof, et al. 2019. Quantitative land evaluation implemented in dutch water management. Geoderma 338: 536–545. doi: 10.1016/j.geoderma.2018.11.002.

Hamada, K., H. Inoue, H. Mochizuki, M. Asakura, Y. Shimizu, et al. 2020. Evaluating maize drought and wet stress in a converted japanese paddy field using a SWAP model. Water 12(5): 1363. doi: 10.3390/w12051363.

Hamada, K., H. Inoue, H. Mochizuki, T. Miyamoto, M. Asakura, et al. 2021. Effect of hardpan on the vertical distribution of water stress in a converted paddy field. Soil and Tillage Research 214: 105161. doi: 10.1016/j.still.2021.105161.

Hao, F., S. Chen, W. Ouyang, Y. Shan, and S. Qi. 2013. Temporal rainfall patterns with water partitioning impacts on maize yield in a freeze–thaw zone. Journal of Hydrology 486: 412–419. doi: 10.1016/j.jhydrol.2013.02.008.

Hassanli, M., H. Ebrahimian, E. Mohammadi, A. Rahimi, and A. Shokouhi. 2016. Simulating maize yields when irrigating with saline water, using the AquaCrop, SALTMED, and SWAP models. Agricultural Water Management 176: 91–99. doi: 10.1016/j.agwat.2016.05.003.

Heinen, M., M. Mulder, J. van Dam, R. Bartholomeus, Q. de Jong van Lier, et al. 2024. SWAP 50 years: Advances in modelling soil-water-atmosphere-plant interactions. Agricultural Water Management 298: 108883. doi: 10.1016/j.agwat.2024.108883.

Huang, X., C. Yu, J. Fang, G. Huang, S. Ni, et al. 2018. A dynamic agricultural prediction system for large-scale drought assessment on the sunway TaihuLight supercomputer. Computers and Electronics in Agriculture 154: 400–410. doi: 10.1016/j.compag.2018.07.027.

Hupet, F., J.C. van Dam, and M. Vanclooster. 2004. Impact of within‐field variability in soil hydraulic properties on transpiration fluxes and crop yields: A numerical study. Vadose Zone Journal 3(4): 1367–1379. doi: 10.2136/vzj2004.1367.

Hupet, F., S. Lambot, R.A. Feddes, J.C. van Dam, and M. Vanclooster. 2003. Estimation of root water uptake parameters by inverse modeling with soil water content data. Water Resources Research 39(11). doi: 10.1029/2003wr002046.

Hu, S., L. Shi, K. Huang, Y. Zha, X. Hu, et al. 2019. Improvement of sugarcane crop simulation by SWAP-WOFOST model via data assimilation. Field Crops Research 232: 49–61. doi: 10.1016/j.fcr.2018.12.009.

Hu, S., L. Shi, Y. Zha, M. Williams, and L. Lin. 2017. Simultaneous state-parameter estimation supports the evaluation of data assimilation performance and measurement design for soil-water-atmosphere-plant system. Journal of Hydrology 555: 812–831. doi: 10.1016/j.jhydrol.2017.10.061.

Immerzeel, W.W., C.C. van Heerwaarden, and P. Droogers. 2009. Modelling climate change in a dutch polder system using the FutureViewR modelling suite. Computers & Geosciences 35(3): 446–458. doi: 10.1016/j.cageo.2008.04.010.

Inforsato, L., and Q. de Jong van Lier. 2021. Polynomial functions to predict flux-based field capacity from soil hydraulic parameters. Geoderma 404: 115308. doi: 10.1016/j.geoderma.2021.115308.

Ismail, H., M.R. Kamal, A.F. bin Abdullah, and M.S.F. bin Mohd. 2020. Climate-smart agro-hydrological model for a large scale rice irrigation scheme in malaysia. Applied Sciences 10(11): 3906. doi: 10.3390/app10113906.

Jhorar, R.K., W.G.M. Bastiaanssen, R.A. Feddes, and J.C. Van Dam. 2002. Inversely estimating soil hydraulic functions using evapotranspiration fluxes. Journal of Hydrology 258(1–4): 198–213. doi: 10.1016/s0022-1694(01)00564-9.

Jiang, J., S. Feng, Z. Huo, Z. Zhao, and B. Jia. 2011. Application of the SWAP model to simulate water–salt transport under deficit irrigation with saline water. Mathematical and Computer Modelling 54(3–4): 902–911. doi: 10.1016/j.mcm.2010.11.014.

Jiang, Y., L. Xiong, Z. Xu, and G. Huang. 2021. A simulation-based optimization model for watershed multi-scale irrigation water use with considering impacts of climate changes. Journal of Hydrology 598: 126395. doi: 10.1016/j.jhydrol.2021.126395.

Jiang, Y., X. Xu, Q. Huang, Z. Huo, and G. Huang. 2015. Assessment of irrigation performance and water productivity in irrigated areas of the middle heihe river basin using a distributed agro-hydrological model. Agricultural Water Management 147: 67–81. doi: 10.1016/j.agwat.2014.08.003.

Jiang, Y., X. Xu, Q. Huang, Z. Huo, and G. Huang. 2016. Optimizing regional irrigation water use by integrating a two-level optimization model and an agro-hydrological model. Agricultural Water Management 178: 76–88. doi: 10.1016/j.agwat.2016.08.035.

Jin, H., W. Zhongfu, and G. Shengxiu. 2011. Simulation of water dynamics of farmland in the piedmont plain of the taihang mountains in the north china plain. Procedia Engineering 12: 66–73. doi: 10.1016/j.proeng.2011.05.012.

Jong van Lier, Q. de. 2017. Field capacity, a valid upper limit of crop available water? Agricultural Water Management 193: 214–220. doi: 10.1016/j.agwat.2017.08.017.

Jong van Lier, Q. de, J.C. van Dam, A. Durigon, M.A. dos Santos, and K. Metselaar. 2013. Modeling water potentials and flows in the soil–plant system comparing hydraulic resistances and transpiration reduction functions. Vadose Zone Journal 12(3): 1–20. doi: 10.2136/vzj2013.02.0039.

Jong van Lier, Q. de, J.C. van Dam, and K. Metselaar. 2009. Root water extraction under combined water and osmotic stress. Soil Science Society of America Journal 73(3): 862–875. doi: 10.2136/sssaj2008.0157.

Jong van Lier, Q. de, J.C. van Dam, K. Metselaar, R. de Jong, and W.H.M. Duijnisveld. 2008. Macroscopic root water uptake distribution using a matric flux potential approach. Vadose Zone Journal 7(3): 1065–1078. doi: 10.2136/vzj2007.0083.

Jong van Lier, Q. de, M.L.A. de Melo, and E.A.R. Pinheiro. 2024. Stochastic analysis of plant available water estimates and soil water balance components simulated by a hydrological model. Vadose Zone Journal 23(3). doi: 10.1002/vzj2.20306.

Jong van Lier, Q. de, O. Wendroth, and J.C. van Dam. 2015. Prediction of winter wheat yield with the SWAP model using pedotransfer functions: An evaluation of sensitivity, parameterization and prediction accuracy. Agricultural Water Management 154: 29–42. doi: 10.1016/j.agwat.2015.02.011.

Kamble, B., and A. Irmak. 2008. Assimilating remote sensing-based ET into SWAP model for improved estimation of hydrological predictions. IGARSS 2008 - 2008 IEEE international geoscience and remote sensing symposium. IEEE

Kapourchal, S.A., A. Abdi, M. Vazifedoust, and M. Rezaei. 2022. SPECIFIC LEAF AREA OF RICE (HASHEMI CULTIVAR) AT FIELD SCALE. Environmental Engineering and Management Journal 21(12): 2093–2102. doi: 10.30638/eemj.2022.185.

Kersebaum, K., J. Kroes, A. Gobin, J. Takáč, P. Hlavinka, et al. 2016. Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat. Water 8(12): 571. doi: 10.3390/w8120571.

Kite, G.W., and P. Droogers. 2000. Comparing evapotranspiration estimates from satellites, hydrological models and field data. Journal of Hydrology 229(1–2): 3–18. doi: 10.1016/s0022-1694(99)00195-x.

Kokoreva, A.A., A.V. Dembovetskiy, Z.S. Ezhelev, A.G. Bolotov, V.M. Stepanenko, et al. 2021. Simulating water transport in porous media of urban soil. IOP Conference Series: Earth and Environmental Science 862(1): 012042. doi: 10.1088/1755-1315/862/1/012042.

Kramers, G., J.C. van Dam, C.J. Ritsema, F. Stagnitti, K. Oostindie, et al. 2005. A new modelling approach to simulate preferential flow and transport in water repellent porous media: Parameter sensitivity, and effects on crop growth and solute leaching. Soil Research 43(3): 371. doi: 10.1071/sr04098.

Kroes, J., J. van Dam, I. Supit, D. de Abelleyra, S. Verón, et al. 2019. Agrohydrological analysis of groundwater recharge and land use changes in the pampas of argentina. Agricultural Water Management 213: 843–857. doi: 10.1016/j.agwat.2018.12.008.

Kroes, J.G., and I. Supit. 2011. Impact analysis of drought, water excess and salinity on grass production in the netherlands using historical and future climate data. Agriculture, Ecosystems & Environment 144(1): 370–381. doi: 10.1016/j.agee.2011.09.008.

Kroes, J., I. Supit, J. Van Dam, P. Van Walsum, and M. Mulder. 2017. Impact of capillary rise and recirculation on crop yields. doi: 10.5194/hess-2017-223.

Kumar, P., A. Sarangi, D.K. Singh, S.S. Parihar, and R.N. Sahoo. 2015. Simulation of salt dynamics in the root zone and yield of wheat crop under irrigated saline regimes using SWAP model. Agricultural Water Management 148: 72–83. doi: 10.1016/j.agwat.2014.09.014.

Lee, T., W.S. Jang, B. Chun, M.J. Ahmad, Y. Jung, et al. 2022. Development of irrigation schedule and management model for sustaining optimal crop production under agricultural drought. Paddy and Water Environment 21(1): 31–45. doi: 10.1007/s10333-022-00911-9.

LEI, G., W. ZENG, Y. JIANG, C. AO, J. WU, et al. 2021. Sensitivity analysis of the SWAP (soil-water-atmosphere-plant) model under different nitrogen applications and root distributions in saline soils. Pedosphere 31(5): 807–821. doi: 10.1016/s1002-0160(21)60038-3.

Lier, Q. de J. van, K. Metselaar, and J.C. van Dam. 2006. Root water extraction and limiting soil hydraulic conditions estimated by numerical simulation. Vadose Zone Journal 5(4): 1264–1277. doi: 10.2136/vzj2006.0056.

Li, Y., L. Liu, and S. Sun. 2022. Study on soil water and salt information model of digital farmland. 2022 international conference on virtual reality, human-computer interaction and artificial intelligence (VRHCIAI). IEEE

Li, P., and L. Ren. 2019. Evaluating the effects of limited irrigation on crop water productivity and reducing deep groundwater exploitation in the north china plain using an agro-hydrological model: II. Scenario simulation and analysis. Journal of Hydrology 574: 715–732. doi: 10.1016/j.jhydrol.2019.03.034.

Li, P., and L. Ren. 2021. Evaluating the saline water irrigation schemes using a distributed agro-hydrological model. Journal of Hydrology 594: 125688. doi: 10.1016/j.jhydrol.2020.125688.

Li, P., and L. Ren. 2023. Evaluating the differences in irrigation methods for winter wheat under limited irrigation quotas in the water-food-economy nexus in the north china plain. Agricultural Water Management 289: 108497. doi: 10.1016/j.agwat.2023.108497.

Liu, M., A. Bárdossy, J. Li, and Y. Jiang. 2012. Physically-based modeling of topographic effects on spatial evapotranspiration and soil moisture patterns through radiation and wind. Hydrology and Earth System Sciences 16(2): 357–373. doi: 10.5194/hess-16-357-2012.

Liu, L., Y. Cui, and Y. Luo. 2013. Integrated modeling of conjunctive water use in a canal-well irrigation district in the lower yellow river basin, china. Journal of Irrigation and Drainage Engineering 139(9): 775–784. doi: 10.1061/(asce)ir.1943-4774.0000620.

Liu, L., Z. Guo, G. Huang, and R. Wang. 2019. Water productivity evaluation under multi-GCM projections of climate change in oases of the heihe river basin, northwest china. International Journal of Environmental Research and Public Health 16(10): 1706. doi: 10.3390/ijerph16101706.

Liu, Y., W. Zeng, C. Ao, G. Lei, J. Wu, et al. 2022. Optimization of winter irrigation management for salinized farmland using a coupled model of soil water flow and crop growth. Agricultural Water Management 270: 107747. doi: 10.1016/j.agwat.2022.107747.

Ma, Y., S. Feng, Z. Huo, and X. Song. 2011. Application of the SWAP model to simulate the field water cycle under deficit irrigation in beijing, china. Mathematical and Computer Modelling 54(3–4): 1044–1052. doi: 10.1016/j.mcm.2010.11.034.

Maleki Tirabadi, M.S., M.E. Banihabib, and T.O. Randhir. 2022. An integrated framework for simultaneously modeling primary and secondary salinity at a watershed scale. Journal of Hydrology 612: 128171. doi: 10.1016/j.jhydrol.2022.128171.

Marinov, D., E. Querner, and J. Roelsma. 2005. Simulation of water flow and nitrogen transport for a bulgarian experimental plot using SWAP and ANIMO models. Journal of Contaminant Hydrology 77(3): 145–164. doi: 10.1016/j.jconhyd.2004.12.004.

Melo, M.L.A. de, and Q. de Jong van Lier. 2021. Revisiting the feddes reduction function for modeling root water uptake and crop transpiration. Journal of Hydrology 603: 126952. doi: 10.1016/j.jhydrol.2021.126952.

Melo, M.L.A. de, Q. de Jong van Lier, R. Cichota, J.A.P. Pollacco, J. Fernández-Gálvez, et al. 2023. Sensitivity analysis of land and water productivities predicted with an empirical and a process-based root water uptake function. Journal of Hydrology 626: 130241. doi: 10.1016/j.jhydrol.2023.130241.

Miegel, K., K. Bohne, and G. Wessolek. 2013. Prediction of long-term groundwater recharge by using hydropedotransfer functions. International Agrophysics 27(1): 31–37. doi: 10.2478/v10247-012-0065-z.

Minacapilli, M., C. Agnese, F. Blanda, C. Cammalleri, G. Ciraolo, et al. 2009. Estimation of actual evapotranspiration of mediterranean perennial crops by means of remote-sensing based surface energy balance models. Hydrology and Earth System Sciences 13(7): 1061–1074. doi: 10.5194/hess-13-1061-2009.

Mirbabaei, S.M., M. Shabanpour, J. van Dam, C. Ritsema, A. Zolfaghari, et al. 2021. Observation and simulation of water movement and runoff in a coarse texture water repellent soil. CATENA 207: 105637. doi: 10.1016/j.catena.2021.105637.

Mokhtari, A., H. Noory, A. Balkhi, and S. Alaghmand. 2021. Comparison of three different satellite-based approaches for aboveground biomass estimation. PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science 89(1): 33–47. doi: 10.1007/s41064-020-00134-9.

Mokhtari, A., H. Noory, and M. Vazifedoust. 2018. Improving crop yield estimation by assimilating LAI and inputting satellite-based surface incoming solar radiation into SWAP model. Agricultural and Forest Meteorology 250–251: 159–170. doi: 10.1016/j.agrformet.2017.12.250.

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