Calibration and validation of soil water balance (SWB) model in the Inner Argentinian Pampas

VIDELA MENSEGUE, H.; CAVIGLIA, O.P.; DEGIOANNI, A.; MARCOS, J.; BONADEO, E.

COMPUTERS AND ELETRONICS IN AGRICULTURE

ELSEVIER SCI LTD

Año: 2021 vol. 181

0168-1699

Biophysical simulation modelscan help to satisfactorily estimate the crop performance for grain production, theirstability across years and their impact on components of hydrological balancein diverse areas once those models have been calibrated and validated withfield data. The Inner Argentinian Pampas (IAP) region is very susceptible toboth frequent flooding and random droughts due to flat landscape, sub-humid tosemi-arid climate, coarse- textured soils and shallow water tables. The SoilWater Balance (SWB) model appears to be suitable for the IAP region since itincludes most of the necessary requirements for the particular conditions ofsuch an environment. The objectives of this study were: i) to identify the mostsensitive crop parameters of the SWB model for a satisfactory estimation ofaerial biomass, grain yield and crop evapotranspiration in the IAP region; ii)to parameterise and calibrate the SWB model for simulation of aerial biomass,grain yield and crop evapotranspiration of wheat (Triticum aestivum L.), soybean [Glycinemax L. (Merr.)] and maize (Zea mays L.);iii) to validate the SWB model using an independent dataset over a wide area inthe IAP region. We used data from 9 field experiments for calibration and from116 field experiments for validation. The most critical parameters, as indicatedby a sensitivity analysis, were biomass-transpiration coefficient (Kb), radiation use efficiency (e),and extinction coefficient (k), suggesting that they should be locally obtainedbefore promoting the use of the SWB model in a given region. The SWB model,after calibration, was able to accurately estimate crop aerial biomass (d = 0.97?0.99, GSD= 9.5?23.9% and RMSE= 786?2,438 kg ha- 1),grain yield (d = 0.95?0.96,GSD = 4.5?10.7%and RMSE = 357?637kg ha- 1),crop evapotranspiration (d = 0.97?0.99;GSD = 8.1?16.1%,RMSE = 17?51mm) and soil water content (d = 0.87?0.96,GSD = 11.2?15.5%and RMSE = 9.6?13.2mm). The robustness to estimate water balance, aerial biomass and grain yieldfluctuations for wheat, soybean, and maize across different soil textures andrainfall variability reflects the potential of SWB model as a valuable tool toface the main challenges of the agricultural systems in our region.