Investigating the Effect of Optimizing Soil Hydraulic Parameters with Inverse and Parametric Solution Methods in Increasing the Accuracy of Water Movement Simulation with HYDRUS

Document Type : Original Article

Authors

1 Ph.D. candidate, Department of Soil Science, Faculty of Agriculture, Shahid Bahonar University of Kerman.

2 Professor, Department of Soil Science, Faculty of Agriculture, Shahid Bahonar University of Kerman.

3 Associate Professor, Department of Water Engineering, Faculty of Agriculture, University of Birjand

4 Associate Professor, Department of Water Engineering, Faculty of Agriculture, University of Birjand.

Abstract

Iran is located in arid and semi-arid belt of the earth and also because of drought, climate changes and mismanagement of water use; its freshwater resources are declining. Therefore, the need to increase water productivity is obviously rational. New methods of irrigation can be mentioned to increase the efficiency of water resources management. Management and application of these new methods of irrigation also requires studying the process of soil moisture changes and its availability to the plant. The purpose of this study was to evaluate the performance of HYDRUS-1D hydrological model at two different depths using inverse solution method in relation to pedo-transfer functions in four-year alfalfa farm which irrigated with center pivot irrigation system. Therefore in this study, the Particle Swarm Optimization (PSO) algorithm (as inverse solution method) as well as three parametric functions including Rosetta, Gorbani Dashtaki and Homaee, and Sepaskhah and Bondar were used to estimate soil hydraulic parameters in simulating soil movement and moisture distribution in HYDRUS-1D hydrological model. So, among the three parametric functions, the best function was selected and then the efficiency of the inverse solution method was compared to the parametric method in the process of simulating the unsaturated flow with the HYDRUS model. The results indicated the acceptable ability of PSO algorithm to estimate soil moisture characteristic curve and its hydraulic parameters. Also by evaluating the statistical indices, it was shown that by linking HYDRUS model with PSO algorithm, this model was efficient to estimate the trend of soil moisture changes. The best model performance was obtained in the soil upper layer with E=0.89, d=0.94 and R2=0.98.

Keywords

References

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Applied Soil Research
Volume 9, Issue 2
September 2021
Pages 15-30

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History

  • Receive Date: 16 March 2020
  • Revise Date: 14 November 2020
  • Accept Date: 22 September 2021

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