Chickpea Modeling Under Rainfed Conditions

Abstract

Climate variability and extreme weather might increase in frequency due to climate change, which could have significant effect on chickpea production. Recently, a study was conducted, aided with simulation modeling approach, in different rainfed regions of Pakistan to check the potential impacts of climate variability on chickpea. Initially, varieties were screened on the basis of germination percentage. Two varieties, Balkasar and Thal 2006, performed best in the germination test and thus grown at two locations, i.e., University Research Farm (URF), Koont, Chakwal Road, Rawalpindi (medium), and Bijwal Farm, Fateh Jang (low), rainfall zones of Pothwar, for field evaluation of best-performing varieties of chickpea. During the course of study, different phenological and yield component parameters have been recorded. Collected data was analyzed statistically to see the performance of varieties under different climatic conditions of these two sites. DSSAT_CROPGRO_Chickpea model was used to simulate crop phenology and yield, i.e., above-ground mass and grain yield of chickpea under rainfed conditions. The model was calibrated and validated on the basis of experimental data. Values obtained from model runs were compared with observed values by using validation scores. Simulation outcomes from days to anthesis, days to maturity, and above-ground mass, i.e., biological yield and grain yield, showed that the location URF-Koont proved better for chickpea crop. Observed and simulated data were compared for model efficiency. At both locations, Thal 2006 performed best under water-limited conditions of Pothwar. Based upon these values, further yield was predicted for varying environmental scenarios in order to recommend best-performing varieties in this particular climate.