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

Document Type : Research Paper


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


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.


Main Subjects

Alazba, A. A. (1994). Efficiency of irrigation borders as affected by inflow hydrograph shape. The University of Arizona.
Amali, S., Rolston, D.E., Fulton, A.E., Hanson, B.R., Phene, C.J. and Oster, J.D. (1997). Soil water variability under subsurface drip and furrow irrigation. Irrigation Science, 17(4), 151-155.
Bautista, E., Clemmens, A. J., Strelkoff, T. S. and Schlegel, J. (2009). Modern analysis of surface irrigation systems with WinSRFR. Agricultural Water Management, 96(7), 1146-1154.
Benham, B. L., Reddell, D. L. and Marek, T. H. (2000). Performance of three infiltration models under surge irrigation. Irrigation Science, 20(1), 37-43.
Cahoon, J. (1998). Kostiakov infiltration parameters from kinematic wave model. Journal of Irrigation and Drainage Engineering, 124(2), 127-130.
Cavero, J., Playán, E., Zapata, N. and Faci, J. M. (2001). Simulation of maize grain yield variability within a surface-irrigated field. Agronomy Journal, 93(4), 773-782.
Childs, J., Wallender, W. W. and Hopmans, J. W. (1993). Spatial and seasonal variation of furrow infiltration. Journal of Irrigation and Drainage Engineering, 119(1), 74-90.
Clemmens, A. J. (1981). Evaluation of infiltration measurements for border irrigation. Agricultural Water Management, 3(4), 251-267.
Clemens, A. J. (1991). Direct solution to surface irrigation advance inverse problem. Journal of Irrigation and Drainage Engineering, 117(4), 578-594.
Corradini, C., Melone, F. and Smith, R. E. (1997). A unified model for infiltration and redistribution during complex rainfall patterns. Journal of Hydrology, 192(1-4), 104-124.
Elliott, R. L. and Walker, W. R. (1982). Field evaluation of furrow infiltration and advance functions. Transactions of the ASAE, 25, 396-400.
Ebrahimian, H., Liaghat, A., Ghanbarian-Alavijeh, B. and Abbasi, F. (2010). Evaluation of various quick methods for estimating furrow and border infiltration parameters. Irrigation Science, 28(6), 479-488.
Ebrahimian, H. (2014). Soil infiltration characteristics in alternate and conventional furrow irrigation using different estimation methods. KSCE Journal of Civil Engineering, 18(6), 1904-1911.
Etedali, H. R., Ebrahimian, H., Abbasi, F. and Liaghat, A. (2011). Evaluating models for the estimation of furrow irrigation infiltration and roughness. Spanish Journal of Agricultural Research, (2), 641-649.
Gillies, M. H. and Smith, R. J. (2005). Infiltration parameters from surface irrigation advance and run-off data. Irrigation Science, 24(1), 25-35.
Gillies, M. H., Smith, R. J. and Raine, S. R. (2007). Accounting for temporal inflow variation in the inverse solution for infiltration in surface irrigation. Irrigation Science, 25(2), 87-97.
Gillies, M. H. (2008). Managing the effect of infiltration variability on the performance of surface irrigation.  Doctoral dissertation, University of Southern Queenslan, Australia.
Gillies, M. H. and Smith, R. J. (2015). SISCO: surface irrigation simulation, calibration and optimisation. Irrigation Science, 33(5), 339-355.
Hall, W. A. (1956). Permeability and infiltration relationships in one dimensional infiltration in a uniform soil. Eos, Transactions American Geophysical Union, 37(5), 602-604.
Holzapfel, E. A., Jara, J., Zuniga, C., Marino, M. A., Paredes, J. and Billib, M. (2004). Infiltration parameters for furrow irrigation. Agricultural Water Management, 68(1), 19-32.
Kazeroonian, S. M., Abbasi, F. and Sedghi, H. (2017). Statistical study of infiltration parameters variations of kostiakov-lewis equation in furrow irrigation during three farming seasons. Journal of Water and Soil Conservation, 24(4), 83-101 (In Farsi).
Kamali, P., Ebrahimian, H. and Rezaverdinejad, V. (2015). Evaluation and comparison of multilevel optimization method and IPARM model to estimate infiltration parameters in furrow.  Journal of Water and Irrigation Management, 5(1), 43-54 (In Farsi).
Kamali, P., Ebrahimian, H. and Parsinejad, M. (2018). Estimation of Manning roughness coefficient for vegetated furrows. Irrigation Science, 36(6), 339-348.
Khatri, K. L. and Smith, R. J. (2005). Evaluation of methods for determining infiltration parameters from irrigation advance data. Irrigation and Drainage, 54(4), 467-482.
Khatri, K. L. (2007). Toward real-time control of surface irrigation. Doctoral dissertation, University of Southern Queensland, Australia.
Kostiakov, A. N. (1932). On the dynamics of the coefficient of water percolation in soils and the necessity of studying it from the dynamic point of view for the purposes of amelioration. Trans. Sixth Comm. Int. Soc. Soil Sci., 1, 7-21.
Maheshwari, B. L. and Jayawardane, N. S. (1992). Infiltration characteristics of some clayey soils measured during border irrigation. Agricultural Water Management, 21(4), 265-279.
Majdzadeh, B., Ojaghloo, H., Ghobadi-Nia, M., Sohrabi, T. and Abbasi, F. (2009). Estimating infiltration parameter for simulation of advance flow in furrow irrigation. In International Conference on Water Resources (ICWR 2009).
Maroufpoor, E., Seyedzadeh, A. and Behzadynasab, M. (2017). Investigation of the accuracy of Non-point infiltration measurement methods in designing of furrow irrigation system. Journal of Water and Soil Conservation, 24(2), 257-271 (In Farsi).
McClymont, D. J. and Smith, R. J. (1996). Infiltration parameters from optimization on furrow irrigation advance data. Irrigation Science, 17(1), 15-22.
Merriam, J. L., & Keller, J. (1978). Farm irrigation system evaluation: A guide for management. Farm irrigation system evaluation: a guide for management. Utah State University.
Merriam, J. L. and Clemmens, A. J. (1985). Time rated infiltrated depth families. In Development and management aspects of irrigation and drainage systems,  ASCE, 67-74.
Nash J. E. and Sutcliffe J. V. (1970). River flow forecasting through conceptual models. A discussion of principles. Journal of Hydrology, 10, 282–290.
Nie, W.B., Fei, L.J. and Ma, X.Y. (2014). Applied closed-end furrow irrigation optimized design based on field and simulated advance data. Journal of Agricultural Science and Technology, 16, 395-408.
Ramezani, E.H., Ebrahimian, H., Abbasi, F. and Liaghat, A. (2012). Evaluation of EVALUE, SIPAR_ID and INFILT models for estimating of Kostiakov infiltration parameters in furrow irrigation. Irrigation Sciences and Engineering, 35(1), 1-9 (In Farsi).
Rodriguez, J.A. and Martos, J.C. (2010). SIPAR_ID: freeware for surface irrigation parameter identification. Environmental Modelling & Software, 25(11), 1487-1488.
Oyonarte, N. A., Mateos, L. and Palomo, M. J. (2002). Infiltration variability in furrow irrigation. Journal of Irrigation and Drainage Engineering, 128(1), 26-33.
Parhi, P. K., Mishra, S. K. and Singh, R. (2007). A modification to Kostiakov and modified Kostiakov infiltration models. Water Resources Management, 21(11), 1973-1989.
Sayah, B., Gil-Rodríguez, M. and Juana, L. (2016). Development of one-dimensional solutions for water infiltration. Analysis and parameters estimation. Journal of Hydrology, 535, 226-234.
Scaloppi, E. J., Merkley, G. P. and Willardson, L. S. (1995). Intake parameters from advance and wetting phases of surface irrigation. Journal of Irrigation and Drainage Engineering, 121(1), 57-70.
Shepard, J. S., Wallender, W. W. and Hopmans, J. W. (1993). One-point method for estimating furrow infiltration. Transactions of the ASAE, 36(2), 395-404.
Sedaghatdoost, A. and Ebrahimian, H. (2015). Calibration of infiltration, roughness and longitudinal dispersivity coefficients in furrow fertigation using inverse modelling with a genetic algorithm. Biosystems Engineering136, 129-139.
Strelkoff, T. and Katopodes, N. D. (1977). Border-irrigation hydraulics with zero inertia. Journal of the Irrigation and Drainage Division, 103(3), 325-342.
Strelkoff, T. S., Clemmens, A. J. and Schmidt, B. V. (1998). SRFR, Version 3.31—A model for simulating surface irrigation in borders, basins and furrows. US Department of Agriculture Agricultural Research Service, US Water Conservation Laboratory, Phoenix, Arizona.
Strelkoff, T. S., Clemmens, A. J. and Bautista, E. (2009). Estimation of soil and crop hydraulic properties. Journal of Irrigation and Drainage Engineering, 135(5), 537-555.
Smerdon, E. T., Blair, A. W. and Reddell, D. L. (1988). Infiltration from irrigation advance data. I: Theory. Journal of Irrigation and Drainage Engineering, 114(1), 4-17.
Soroush, F. (2016). Accurate assessment of modified NRCS intake families using field data and zero inertia models. 5th Integrated water Resources Management Conference, Iranian Irrigation and Water Engineering Society, Kerman, Iran (In Farsi).
US Department of Agriculture, Natural Resources and Conservation Service. (1974). National Engineering Handbook. Section 15. Border Irrigation. National Technical Information Service, Washington, DC, Chapter 4.
Valiantzas, J. D., Aggelides, S. and Sassalou, A. (2001). Furrow infiltration estimation from time to a single advance point. Agricultural Water Management, 52(1), 17-32.
Valipour, M., Sefidkouhi, M. A. G. and Eslamian, S. (2015). Surface irrigation simulation models: a review. International Journal of Hydrology Science and Technology, 5(1), 51-70.
Walker, W. R. (2005). Multilevel calibration of furrow infiltration and roughness. Journal of Irrigation and Drainage Engineering, 131(2), 129-136.
Walker, W. R., Prestwich, C. and Spofford, T. (2006). Development of the revised USDA–NRCS intake families for surface irrigation. Agricultural water management, 85(1-2), 157-164.
Weibo, N., Liangjun, F. and Xiaoyi, M. (2012). Estimated infiltration parameters and Manning roughness in border irrigation. Irrigation and Drainage, 61(2), 231-239.
Xiaoyan, G., Peiling, Y. and Ye, L. (2008). Estimation of soil infiltration parameters during furrow irrigation based on IPARM method. Transactions of the Chinese Society of Agricultural Engineering, 2008 (1).