Evaluation of DSSAT-CROPGRO Module for Spatial Yield Estimation of Chickpea in Vidisha (Madhya Pradesh) and Nagaur (Rajasthan), India

Abstract

Crop simulation models are often used to characterize, develop and assess field crop production practices. The present study was carried out for chickpea spatial yield estimation at Vidisha of Madhya Pradesh and Nagaur district of Rajasthan employing the DSSAT model. In this study, the DSSAT-CROPGRO module was used to estimate chickpea yield during rabi 2022. To simulate the yield, DSSAT required datasets of crop growth and management, daily weather data, and soil data were provided. The simulated yield was validated using the observed yield through CCEs from farmers’ fields. When the observed and simulated yields were compared, their deviation was found to be less than 20 percent for all varieties at experimental locations of the Vidisha and Nagaur districts. The observed yield of Chickpea matched well after calibration which showed that model could simulate the yield with high accuracy as it showed R2, d, and MAPE of 0.87, 0.92, and 7.30 for calibration and 0.88, 0.90, and 7.60 for the validation, respectively. The model has been successfully calibrated and validated for the chickpea at spatial level and it can be taken for further applications in natural resources management and climate change impact studies.