Investigation of Mathematical Model and Development of I-JAYA Method to Optimally Estimate the Parameters of Soil Water Retention Curve

Abstract

Direct soil water retention curve (SWRC) measurement is laborious, time-consuming, and expensive. To estimate its parameters, mathematical models and optimization approaches are applied. In this study, an improved alternative method to solve the optimization problem was introduced and developed. To evaluate the efficiency of this method, 12 soil samples with 6 different textures from 9 different regions of the world were used. The optimization equations were solved using a genetic algorithm (GA) and standard mathematical models, and the best model was chosen based on Taylor diagrams, R2, and computing time. The Bimodal versions of Fredlund-Xing (FX-b) and Brooks-Corney (BC) mathematical models represented the best and poorest findings of this stage, with R2 values of 0.913 and 0.825, respectively. Then, the optimization problem is solved with differential evolution (DE), Salp Swarm Algorithm (SSA), Jaya, and improved Jaya (I-Jaya) method, and the mean values of R2 were obtained 0.919, 0.931, 0.921, and 0.958, respectively. The results indicated a 16% improvement in the average R2, by selecting the suitable mathematical model and also using the I-Jaya.

Keywords

• matric potential
• meta-heuristic algorithms
• optimization
• soil texture
• statistical parameters