Calibrated Models for Major Crops and Cropping System using Existing Datasets in Morocco and Uzbekistan - Devkota, Krishna; Devkota Wasti, Mina Kumari (International Center for Agricultural Research in the Dry Areas, 2022)
Simulation modeling is an approach that describes processes of crop growth, development, and yield formation as a function of biophysical (weather, soil, water, nutrients, and crop management) factors using mechanistic and process-based computer models (Hoogenboom et al., 2012; Keating et al., 2003). Those input datasets for the model are derived from different sources, such as field experiments, household surveys, web-based data sources, remote sensing data, published literature, etc. Crop and Cropping System Models are a valuable ex-ante decision support tool which generates useful outputs for the precision agricultural management, provides decision for climate change mitigation and adaptation with ecosystem services, and also provides decision for institutional and policy reform (Fig. 1). Such models can be used to evaluate the effects of various agronomic practices, varieties, and climate change impacts on crop production and food security at the field, farm, and landscape levels. Agricultural Production Systems Simulator (APSIM) (Keating et al., 2003), Cropping Systems Simulator (CropSyst) (Stöckle et al., 2003), Decision Support System for Agro-technology Transfer (DSSAT) are the process-based major cropping system models, and Hydrus-1/2/3D (Šimůnek et al., 2013) is a major hydrological model. Simulation models have the potential to quantify the magnitude of crop yield gaps and determine its factors.