National spatial crop yield simulation using GIS-based crop production model

Traditional decision support systems based on crop simulation models are normally site-specific. In policy formulation, however, spatial variability of crop production often need to be evaluated due to different soil conditions, weather conditions and agricultural practices within a target-region. To address the spatial variability, a spatial model ‘Spatial EPIC’ was developed based on a crop simulation model EPIC (Erosion Productivity Impact Calculator). Since site-specific crop simulation models require point-based or fine resolution data, it is necessary to feed the fine resolution data at each grid-cell in order to ‘spatialize’ crop simulation models. The authors proposed a method to generate fine resolution data from coarse resolution data, which are usually available at regional or national level. In addition, since the original EPIC crop management practices are static in nature, a dynamic adaptation loop is added to evaluate the impacts of agricultural practice changes over temporal scale. Validation of the spatial EPIC was conducted at different spatial scales, i.e. national scale (approx. 50 km cell-size) and regional scale (approx. 10 km cell-size) in India. Results showed that at both resolutions level crop yield varied significantly as a function of seasonal climatic variation, soil water holding characteristics and applied crop management strategies. Also, the study successfully demonstrated model applicability in evaluating an impact of climate changes over major cereal crops productivity at national level taking spatial variability into account.