Effect of Evapotranspiration on Soil Moisture Dynamics in Top Surface Layer of a Loamy Land in Climate Change Condition


Authors: Janarul Shaikh and Sanjeet Sahoo

Volume/Issue: Volume 27: Issue 1

Published online: 23 Apr 2024

Pages: 6 - 14

DOI: https://doi.org/10.2478/ahr-2024-0002


Evapotranspiration affects uncertain changes in volumetric soil moisture content (θ) of earth surface, which is considerably controlled by temporal variability of weather parameters like rainfall and ambient temperature. Accurate measurement of temporal variation and spatial distribution of θ in a particular land is very challenging. Numerical modelling with any suitable computer code might be useful in such cases. Thus, Hydrus 2D modelling of θ variation in the soil at Odisha University of Agriculture and Technology (OUAT) in Bhubaneswar is undertaken as main objective of present study to investigate soil moisture dynamics in top surface layer. For the study, the θ in OUAT land was measured daily by 5 TM water content sensor for the duration of two years spanning from January 2021 to December 2022. Meteorological data for these 2 years are collected from a nearby weather station at OUAT and used for calculating evapotranspiration (ET) based on five different well known ET models. Soil hydraulic parameters of OUAT land were also evaluated by laboratory investigation. The evapotranspiration so calculated along with precipitation and materials properties were then assigned as the inputs in Hydrus 2D simulations. The simulated results are found to be in good agreement with field observations. It is proven by Pearson’s coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) which are found to be 0.83 and 0.84 respectively. The soil moisture simulation was the most accurate only when measured soil parameters along with atmospheric boundary involving Penman-Monteith (PM) ET model were considered as model inputs.

Keywords: soil moisture, evapotranspiration model, simulation, weather data, hydraulic parameter



Autovino, D., Rallo, G., & Provenzano, G. (2018). Predicting soil and plant water status dynamic in olive orchards under different irrigation systems with Hydrus-2D: Model performance and scenario analysis. Agricultural water management, 203, 225–235. https://ideas.repec.org/a/eee/agiwat/v203y2018icp225-235.html

Borah, D. K., & Bera, M. (2003). Watershed-scale hydrologic and nonpoint-source pollution models: Review of mathematical bases. Transactions of the ASAE, 46(6), 1553–1566. https://www.isws.illinois.edu/iswsdocs/journals/BorahTransASAE47-3-789803.pdf

Brocca, L., Ciabatta, L., Massari, C., Camici, S., & Tarpanelli, A. (2017). Soil moisture for hydrological applications: Open questions and new opportunities. Water, 9(2), 140. https://doi.org/10.3390/w9020140

Daniel, E. B., Camp, J. V., LeBoeuf, E. J., Penrod, J. R., Dobbins, J. P., & Abkowitz, M. D. (2011). Watershed modeling and its applications: A state-of-the-art review. The Open Hydrology Journal, 5(1). https://benthamopen.com/ABSTRACT/TOHYDJ-5-26

Jenny, H. (2012). The soil resource: origin and behavior (vol. 37). Springer Science & Business Media. https://link.springer.com/book/10.1007/978-1-4612-6112-4

Kadyampakeni, D. M., Morgan, K. T., Nkedi‐Kizza, P., Schumann, A. W., & Jawitz, J. W. (2018). Modeling Water and Nutrient Movement in Sandy Soils Using HYDRUS‐2D. Journal of environmental quality, 47(6), 1546–1553. https://doi.org/10.2134/jeq2018.02.0056

Legates, D. R., & McCabe Jr, G. J. (1999). Evaluating the use of “goodness‐of‐fit” measures in hydrologic and hydroclimatic model validation. Water resources research, 35(1), 233–241. https://doi.org/10.1029/1998WR900018

Li, Y., Yu, Y., Sun, R., Shen, M., & Zhang, J. (2021). Simulation of soil water dynamics in a black locust plantation on the Loess Plateau, western Shanxi Province, China. Water, 13(9), 1213. https://doi.org/10.3390/w13091213

Marquardt, D. W. (1963). An algorithm for least-squares estimation of nonlinear parameters. Journal of the society for Industrial and Applied Mathematics, 11(2), 431–441. https://www.jstor.org/stable/2098941

Melone, F., Barbetta, S., Diomede, T., Peruccacci, S., Rossi, M., Tessarolo, A., & Verdecchia, M. (2005). Review and selection of hydrological models – Integration of hydrological models and meteorological inputs. Contract, 12. http://cronfa.swan.ac.uk/Record/cronfa43733

Mohanty, B. P., Cosh, M. H., Lakshmi, V., & Montzka, C. (2017). Soil moisture remote sensing: State-of-the-science. Vadose Zone Journal, 16(1), 1–9. https://doi.org/10.2136/vzj2016.10.0105

Mualem, Y. (1976). A new model for predicting the hydraulic conductivity of unsaturated porous media. Water resources research, 12(3), 513–522. https://doi.org/10.1029/WR012i003p00513

Nanda, A., Sen, S., Jirwan, V., Sharma, A., & Kumar, V. (2018). Understanding plot‐scale hydrology of Lesser Himalayan watershed – A field study and HYDRUS‐2D modelling approach. Hydrological Processes, 32(9), 1254–1266. https://doi.org/10.1002/hyp.11499

Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I – A discussion of principles. Journal of hydrology, 10(3), 282–290. https://doi.org/10.1016/0022-1694(70)90255-6

Pan, Z., Tong, Y., Hou, J., Zheng, J., Kang, Y., Wang, Y., & Cao, C. (2021). Hole irrigation process simulation using a soil water dynamical model with parameter inversion method. Agricultural Water Management, 245, 106542. https://doi.org/10.1016/j.agwat.2020.106542

Pearson, E. S., & Tukey, J. W. (1965). Approximate means and standard deviations based on distances between percentage points of frequency curves. Biometrika, 52(3/4), 533–546. https://doi.org/10.2307/2333703

Richards, L. A. (1931). Capillary conduction of liquids through porous mediums. physics, 1(5), 318–333. https://doi.org/10.1063/1.1745010

Saifadeen, A., & Gladneyva, R. (2012). Modeling of solute transport in the unsaturated zone using HYDRUS-1D. TVVR12/5020. https://www.lunduniversity.lu.se/lup/publication/3051081

Shaikh, J., Yamsani, S. K., Sekharan, S., & Rakesh, R. R. (2019). Performance evaluation of 5TM sensor for real-time monitoring of volumetric water content in landfill cover system. Advances in Civil Engineering Materials, 8(1), 322–335. https://www.astm.org/acem20180091.html

Šimunek, J., Sejna, M., & Van Genuchten, M. T. (1999). The HYDRUS-2d software package. International Ground Water Modeling Center, 251. https://www.pc-progress.com/Downloads/Pgm_Hydrus2D/HYDRUS2D.PDF

Šimunek, J., Van Genuchten, M. T., & Šejna, M. (2012). HYDRUS: Model use, calibration, and validation. Transactions of the ASABE, 55(4), 1263–1274. https://elibrary.asabe.org/abstract.asp?aid=42239

Singh, V. P., & David. A. (2002). Mathematical modeling of watershed hydrology. Journal of hydrologic engineering, 7(4), 270–292. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:4(270)

Singh, V. P., & Woolhiser, D. A. (2002). Mathematical modeling of watershed hydrology. Journal of hydrologic engineering, 7(4), 270–292. https://doi.org/10.1061/(ASCE)1084-0699(2002)7:4(270)

Spelman, D., Kinzli, K. D., & Kunberger, T. (2013). Calibration of the 10HS soil moisture sensor for southwest Florida agricultural soils. Journal of Irrigation and Drainage Engineering, 139(12), 965–971. https://doi.org/10.1061/(ASCE)IR.1943-4774.0000647

Srivastava, P. K., Pandey, P. C., Petropoulos, G. P., Kourgialas, N. N., Pandey, V., & Singh, U. (2019). GIS and remote sensing aided information for soil moisture estimation: A comparative study of interpolation techniques. Resources, 8(2), 70. https://doi.org/10.3390/resources8020070

Tárník, A., & Igaz, D. (2015). Determination of plant available soil water storage in agricultural land of the Nitra River Catchment. Acta Horticulturae et Regiotecturae, 18(1), 16–19. https://doi.org/10.1515/ahr-2015-0004

Tárník, A., & Igaz, D. (2017). Validation of HYDRUS 1D model in selected catchment of Slovakia. Acta Horticulturae et Regiotecturae, 20(1), 24–27. https://doi.org/10.1515/ahr-2017-0006

Vereecken, H., Huisman, J. A., Pachepsky, Y., Montzka, C., Van Der Kruk, J., Bogena, H., ... & Vanderborght, J. (2014). On the spatio-temporal dynamics of soil moisture at the field scale. Journal of Hydrology, 516, 76–96. https://doi.org/10.1016/j.jhydrol.2013.11.061

Wang, J., Gong, S., Xu, D., Juan, S., & Mu, J. (2013). Numerical simulations and validation of water flow and heat transport in a subsurface drip irrigation system using HYDRUS‐2D. Irrigation and Drainage, 62(1), 97–106. https://doi.org/10.1002/ird.1699

Wösten, J. H. M., Lilly, A., Nemes, A., & Le Bas, C. (1999). Development and use of a database of hydraulic properties of European soils. Geoderma, 90(3–4), 169–185. https://doi.org/10.1016/S0016-7061(98)00132-3