Evaluating the effects of limited irrigation on crop water productivity and reducing deep groundwater exploitation in the North China Plain using an agro-hydrological model: I. Parameter sensitivity analysis, calibration and model validation

Abstract

The agro-hydrological Soil-Water-Atmosphere-Plant-WOrld-FOod-STudy (SWAP-WOFOST) model in a distributed manner represents an important tool for evaluating agro-hydrological cycles and irrigation strategies at different spatiotemporal scales. The reliability of the model simulations and evaluations is dependent on the generation of the distributed simulation units that account for the spatial heterogeneity of various factors, as well as parameter calibration and model validation. In this study, we focused on the most typical overexploited deep groundwater area in the North China Plain (NCP). First, the extended Fourier amplitude sensitivity test (EFAST) was used to conduct global sensitivity analyses for three modules in the SWAP-WOFOST model to identify the parameters that significantly influence the objective variables for calibration at the six experimental stations in the study area. On this basis, the parameters were calibrated and validated in detail using abundant observed data from each station. The normalized root mean square error (NRMSE) values for soil water content, soil salt concentration, winter wheat leaf area index (LAI), winter wheat aboveground biomass, winter wheat yield, summer maize LAI, summer maize aboveground biomass and summer maize yield were 14.93%, 27.20%, 24.60%, 25.27%, 23.12%, 24.55%, 21.33% and 17.94%, respectively, during the calibration period; and the corresponding NRMSE values were 16.26%, 29.36%, 24.20%, 22.75%, 21.77%, 22.03%, 24.38% and 18.62%, respectively, during the validation period. The model provided a good simulation for the soil water contents and summer maize yields and a fair simulation for the other objective variables. Furthermore, a distributed SWAP-WOFOST model was generated by overlaying 12 maps involving meteorology, soil, crops, land use, water resources and administrative divisions, yielding 2809 simulation units. Finally, the simulation accuracy of the distributed model was evaluated under the current irrigation conditions. The results showed that the simulated yields of winter wheat and summer maize were consistent with the statistical values, and the simulated evapotranspiration matched the remote sensing data with acceptable precision. In summary, the distributed SWAP-WOFOST model could be used as an effective tool for simulating crop water productivity in time and space under limited irrigation scenarios and for evaluating the effect of optimized limited irrigation schemes on reducing deep groundwater exploitation in this region.