A calibration procedure to improve global rice yield simulations with EPIC

摘要: Abstract Crop models are increasingly used to assess impacts of climate change/variability and management practices on productivity environmental performance alternative cropping systems. Calibration is an important procedure improve reliability model simulations, especially for large area applications. However, global-scale crop calibration has rarely been exercised due limited data availability expensive computing cost. Here we present a simple approach calibrate Environmental Policy Integrated Climate (EPIC) global implementation rice. We identify four parameters (potential heat unit – PHU, planting density PD, harvest index HI, biomass energy ratio BER) them regionally capture the spatial pattern reported rice yield in 2000. Model assessed by comparing simulated outputs with independent FAO national data. The comparison demonstrates that scheme performs satisfactorily reproducing yield, particularly main production areas. Spatial agreement increases substantially when more selected calibrated, but varying efficiencies. Among parameters, PHU HI exhibit highest efficiencies increasing agreement. Simulations different strategies generate pronounced discrepancy 5–35% mean yields across latitude bands, small moderate difference estimated variability changing trend period 1981–2000. Present little effects improving trends at both regional levels, suggesting further works needed reproduce temporal yields. This study highlights importance models’ calibration, presents possibility transparent consistent up scaling simulations given current databases weather, soil, calendar, fertilizer irrigation information, yield.