Developing a simple method for estimating soil infiltration in furrow and border irrigation using advance, recession and runoff data

Estimating soil infiltration is important in designing and managing surface irrigation systems. To date, various methods have been proposed to estimate infiltration coefficients. In this research, a simple method for estimating the coefficients of the Kostiakov-Lewis infiltration equation in surface irrigation is presented. Then, the performance of this method is compared with other similar methods, including the Elliott-Walker two-point, IPARM and Merriam-Keller methods, using eight furrow irrigation datasets and six border irrigation datasets. The proposed method calculates the coefficients of the infiltration equation through the comparison between the measured and calculated infiltrated water amount by an optimization method, the normal decreasing gradient algorithm, using advance and recession data. The mean relative errors in estimating the infiltrated water volume were 13.63, 3.92, 0.005 and 0.00 for the two-point, IPARM, Merriam-Keller and proposed methods for border irrigation, respectively. Similarly, the respective mean relative error values were 14.35, 6.31, 1.90 and 0.00 for furrow irrigation. In addition, to ensure the optimality of the obtained coefficients, response surfaces were drawn. The coefficients obtained from the proposed method are located in the minimum place of the response surface, while no similar behaviour was observed in the other methods. These results prove the effectiveness of the proposed method in addition to its simplicity.