Abstract
Agroecosystem modelling has increasingly focused on the integration of soil biogeochemical processes and crop growth. However, few models are available that offer high computing efficiencies for region-scale simulations, integrated decision support tools, and a structure that allows for easy extension. This paper introduces a new modelling tool to fill this gap: the GDNDC (Gridded DNDC) system for gridded agro-biogeochemical simulations. Based on the established DeNitrification and DeComposition (DNDC) model version-95, its main advancements include (i) implementation of parallel computation to significantly reduce computation time across multiple scales; (ii) a built-in parameter optimization algorithm to improve the predictive accuracy, and (iii) several decision support tools. We demonstrate each of these for county-level maize growth simulations in Liaoning Province (China) and reveal the potential of this new modelling tool to guide both long-term policy decisions regarding optimal fertilizer application and near-term crop yield forecasting for reactive decisions required in times of drought.
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