Estimating Parameters of Van Genuchten Model for Soil Water Retention Curve by Intelligent Algorithms

Abstract: An improved particle swarm optimization (IPSO) was proposed and the intelligent algorithms such as IPSO, genetic algorithm (GA), and simulated annealing algorithm (SA) were introduced to determine parameters of Van Genuchten (VG) model for soil water retention curve (SWRC) of four typical agricultural soil textures (clay, clay loam, silt loam and sand loam) in China. For comparison, the SWRC in term of VG model was also fitted by a computer program RETC and pedotransfer function Rosetta, respectively. For four soil textures, the value of determination coefficient (R 2) and root mean square error (RMSE) in the estimation of VG equation parameters by IPSO are the highest and lowest in the above three intelligent algorithms, respectively. The simulated values of water content by IPSO are much closed to the measured values (R 2 = 0.990). It was found that the Rosetta is unable to estimate the SWRC adequately and the highest RMSE value is up to 1.096E − 01cm 3 cm −3. The predicted values of moisture content by Rosetta are far away from the measured values (R 2 = 0.585). The RETC provided good simulation results of water content (R 2 = 0.974). However, the soil residual water content (θr), of VG equation can not be obtained. It was concluded that the IPSO presented here is more reasonable and reliable to estimate the SWRC in term of VG model than the method of GA, SA, RETC and Rosetta.