Evaluating Phenological Responses of Three Crop Models to Water Deficits in the Spatially Distributed Agricultural Ecosystem Services (AgES) Model.

Phenology is increasingly being used in scheduling management practices and is critical in accurately simulating crop production and hydrology. While extensive phenological research has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses to varying water deficits has been done, particularly for versions of the EPIC-based plant growth component used in many agroecosystem models. We evaluated how three EPIC-based plant growth components incorporated into the Agricultural Ecosystems Services (AgES) model (Soil Water Assessment Tool, SWAT; Wind Erosion Prediction System, WEPS; and the Unified Plant Growth Model, UPGM) simulated the phenological responses of winter wheat (Triticum aestivum L.) to varying water deficits, and whether including a water stress factor would improve the simulation of phenology. Two data sets from northeastern Colorado, USA were used in the evaluation: 1) 24 genotypes were grown in plots near Greeley for three years under variable irrigation ranging from rainfed to full irrigation, and 2) one genotype grown four years across a rainfed landscape near Ault. Five developmental stages were measured: jointing (J), flag leaf complete (FLC)/beginning of booting, heading (H), anthesis start (A), and physiological maturity (PM). The SWAT and WEPS components only simulated PM, and beginning of canopy senescence (estimated from the beginning of LAI decline). UPGM simulates the five measured developmental stages and is the only component that explicitly incorporates a phenological response to varying water deficits. All simulations used default crop parameter values. As expected, UPGM was the only component that simulated a response to variable water deficits and this did result in better prediction of phenology. For example, the Root Mean Square Error (RMSE, days) and Relative Error (RE, days) decreased and index of agreement (d) increased in predicting maturity from SWAT (RMSE=18.4; RE=9.2; d=0.34) to WEPS (RMSE=6.2; RE=1.0, d=0.634) to UPGM RMSE=6.1; RE=0.1; d=0.70).