An optimization model to estimate infiltration parameters and roughness coefficient based on advance and runoff data in border irrigation

Infiltration is the most important and the most difficult property in evaluation of surface irrigation systems. In this research an optimization technique based on the volume balance approach is developed and evaluated for estimating of Kostiakov-Lewis equation parameters and manning roughness coefficient for open-end downstream condition of border irrigation systems. The infiltration parameters and roughness coefficient were estimated using both advance and runoff data. Six field experiments data of border irrigation used to verify of the proposed method and results compared with the two-point and multilevel calibration methods. Based on the results, multilevel calibration method with average root mean square error (RMSE) 3.7 minutes for advance time and relative error (RE) 0.5% for the runoff volume indicated the highest accuracy. In additional, the proposed method with RMSE 5.3 minutes for advance time and RE 7.7% for runoff volume was in the second place. The two-point method with RMSE 5.8 minutes for advance time and RE 35.3% for runoff volume resulted to the lowest accuracy. The proposed optimization method estimated infiltration parameters and roughness coefficient with relatively good accuracy and it can easily converge and get quick to answers.