A rigorous approach of determining FAO56 dual crop coefficient using soil sensor measurements and inverse modeling techniques

Abstract

Accurate estimation of crop coefficients for evaporation and transpiration is of great importance in optimizing irrigation and modeling water and solute transfers in the soil-crop system. In this study we used inverse modeling techniques on soil sensor measurements at depths from the soil-crop system to estimate crop coefficients. An inverse model was rigorously formulated to infer the crop coefficients and the lengths of growth stages using the measured soil water potential at depths during crop growth. By applying a micro-genetic algorithm to the formulated inverse model, the optimum values of the crop coefficient and the corresponding length of growth stage were successfully deduced. It has been found that the lengths of both the initial and development growth stages of cabbage were 5 d shorter than those from the FAO56 (Irrigation and Drainage Paper by the FAO). The deduced crop coefficient for transpiration at the initial growth stage was 0.11; slightly smaller than 0.15 recommended by the FAO56, while at the mid-season growth stage, the deduced value of 0.95 was identical with the recommended value. Results show that the predictions of soil water potential using the obtained values of crop coefficients agreed well with the measurements throughout the entire growing period, indicating that the deduced crop coefficients were credible and appropriate for cabbage grown under the specific conditions of location and climate. It follows that the strategy presented in the study can enable accurate estimates of crop coefficients to be obtained from soil sensor measurements and inverse modeling techniques.