Development of a generic auto-calibration package for regional ecological modeling and application in the Central Plains of the United States

article i nfo Process-orientedecologicalmodels are frequentlyusedfor predicting potentialimpactsof global changes suchas climate and land-cover changes, which can be useful for policy making. It is critical but challenging to automat- ically derive optimal parametervaluesat different scales,especially at regional scale, and validate the model per- formance. In this study, we developed an automatic calibration (auto-calibration) function for a well-established biogeochemical model—the General Ensemble Biogeochemical Modeling System (GEMS)-Erosion Deposition Carbon Model (EDCM)—using data assimilation technique: the Shuffled Complex Evolution algorithm and a model-inversion R package—Flexible Modeling Environment (FME). The new functionality can support multi- parameter and multi-objectiveauto-calibration of EDCM atthe both pixel and regional levels. Wealsodeveloped a post-processing procedure for GEMS to provide options to save the pixel-based or aggregated county-land cover specific parameter values for subsequent simulations. In our case study, we successfully applied the up- dated model (EDCM-Auto) for a single crop pixel with a corn-wheat rotation and a large ecological region (Level II)—Central USA Plains. The evaluation results indicate that EDCM-Auto is applicable at multiple scales and is capable to handle land cover changes (e.g., crop rotations). The model also performs well in capturing the spatial pattern of grain yield production for crops and net primary production (NPP) for other ecosystems across the region, which is a good example for implementing calibration and validation of ecological models with readily available survey data (grain yield) and remote sensing data (NPP) at regional and national levels. The developed platform for auto-calibration can be readily expanded to incorporate other model inversion algorithms and potential R packages, and also be applied to other ecological models. Published by Elsevier B.V.