Estimating Parameters for Soil Water Balance Models Using Adaptive Simulated Annealing

A desirable feature of crop simulation models is for the same model to be applicable in any region if oneprovides required soil, weather, and crop input information. However, this is not an easy task. Each model requires anumber of parameters that have to be measured or estimated. Moreover, many existing crop models have empiricalrelationships that represent important soil and crop processes, such as root growth and soil water extraction. Thus,objective methods are needed for estimating parameters for such crop models because they may not be known or easilyestimated from readily available field or laboratory data. An objective procedure based on the Adaptive SimulatedAnnealing (ASA) optimization technique has been developed to estimate soil and root growth parameters for both thecurrent (CROPGRO-Soybean v3.5) and revised models. We used this procedure to estimate a soil impedance factor(SIF) and a root hospitality factor (RHFAC) in the revised model; and the root weighting function (WR) in thecurrent model. This procedure uses field measurements of volumetric soil water content at different depth incrementsover time during a growing season. It estimates parameters that minimize the error sum of squares between observed andsimulated values. Data sets from East Campus, Nebraska (Specht et al., 1986), Gainesville, Florida (Hammond et al.,1978, unpublished), and Castana, Iowa (Mason et al., 1980), were used to evaluate the ASA optimization program and tocompare the performance of the two models. The results demonstrated that the ASA program was able to fit the predictedsoil water in the revised model. Except for the Nebraska experiment, the current model with the optimized WR alsofit soil water content over time. Although the two models predicted reasonably well final grain yield for the Florida andIowa experiments, the current model under predicted grain yield by more than 40% for the Nebraska location. Theabsolute percent errors in soil water contents estimated for the Nebraska experiment using the revised and currentmodels were less than 5% and 8%, respectively. The global Adaptive Simulated Annealing (ASA) optimization method canbe used successfully for estimating root growth and soil water extraction parameters for dynamic crop models.