Parameter Identification for Root Growth based on Soil Water Potential Measurements – An Inverse Modeling Approach

Abstract

In this study a strategy to calibrate process-based agro-hydrological models for water dynamics in the soil-crop system with soil sensor measurements was developed. An inverse problem was formulated to infer the root parameters based on the measured soil water potential at depths during crop growth. The root penetration down the soil profile is assumed to be driven by the accumulative daily mean air temperature, and root length density distribution in the soil profile is exponential. The forward agro-hydrological model for water dynamics in the soil- crop system was proposed by Yang et al. (J. Hydrol. 2009; 370:177-190). A micro-Genetic Algorithm was employed to infer the parameters. Results show that the predictions of soil water potential using the inferred values of root parameters agree fairly well with the measurements throughout the entire growing period, indicating that the deduced root parameters are credible and appropriate for the studied case. It follows that the strategy presented in the study enables accurate estimates of root parameters to be obtained from soil sensor measurements at various depths, and thus provides an effective way to calibrate models.