A Review on Different Methods for Determining Parameters of Infiltration Equations with Inverse Approach in Furrow Irrigation

Document Type : Research Paper

Authors

1 Ph.D. Student, Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran

2 . Ph.D. Student, Department of Irrigation and Drainage Engineering, Aboureihan Campus, University of Tehran, Tehran, Iran

3 Department of Water Engineering, Faculty of Agriculture, Urmia University, Urmia, Iran

4 Dept. of Irrigation Eng., Campus of Agriculture and Natural Resources, University of Tehran, Tehran, Iran

Abstract

In order to increase the efficiency of surface irrigation systems, it is necessary to estimate the coefficients of infiltration equations with high precision. Inverse modeling is a precise method for estimating the coefficients of infiltration equations. In this research in the first step, the performance of different infiltration equations including NRCS intake families, Kostiakov, modified Kostiakov, modified Kostiakov Branch Functions, Time-Rated Intake Family and Characteristic time were evaluated and compared. Then the best infiltration equation was determined so that it could estimate the advance, recession and runoff phases with the least error. By comparing different infiltration equations, the modified Kostiakov method with a mean percentage error of 2.14, 2.99 and 2.95 was determined as the best-performance infiltration equation in advance, recession and runoff phases, respectively. In the second step, based on the optimal infiltration equation (modified Kostiakov), three commonly used software for inverse estimation of infiltration equation parameters including: WinSRFR, IPARM and SIPAR-ID were compared using field data of four furrow irrigation under corn cultivation located at the research farm of agriculture and natural resources campus of university of Tehran in 2014. The results showed that the IPARM model with mean percentage errors of  2.40, 5.87, and 2.11, respectively, in advance, recession and runoff phases had a similar performance with the WinSRFR software, but it estimated the recession phase with an error of almost two times as compared to WinSRFR. The SIPAR-ID model in estimating the infiltration equation coefficients had poor performance with the highest volatility in the coefficients values.

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References

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Iranian Journal of Soil and Water Research
Volume 50, Issue 9
January 2020
Pages 2155-2170

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