Climate Change Impact Assessment on Rice Yield Using DSSAT and Geospatial Methods

Abstract

Rice is a major staple crop in Telangana, India, and its productivity is highly influenced by climatic variability and changing environmental conditions. Understanding the potential impacts of climate change on rice production is essential for developing locally relevant adaptation strategies. This study assessed the impacts of historical climate variability and projected future climate change on rice productivity in five representative agricultural fields located in Hanumakonda district, Telangana, India. The DSSAT-CERES Rice model was calibrated and applied using field-level crop management information obtained from Crop Cutting Experiments (CCE) conducted by the Chief Planning Office, Hanumakonda District. Historical rice yields were simulated for the period 2007–2023 and evaluated using available district-level rice yield statistics. The model demonstrated acceptable performance, with mean normalized root mean square error (NRMSE) values of 13.02% and 17.12% for Kharif and Rabi seasons, respectively. Future rice yields were projected for the period 2024–2040 under SSP245 and SSP585 climate scenarios using MIROC6 climate projections. The results suggest a general decline in rice productivity under both climate scenarios, with average reductions of 7.38% and 14.64% during the Kharif season and 10.7% and 11.5% during the Rabi season under SSP245 and SSP585, respectively, which pose challenges for local food security and highlight the need for adaptation strategies. The analyses indicated that variations in rainfall, temperature, and solar radiation influenced simulated yield responses across seasons. However, the results should be interpreted considering the limitations associated with district-level validation data, the use of a single climate model, and assumptions regarding future crop management practices. The study provides a local-scale assessment of potential climate-related risks to rice production in Hanumakonda district and may support the development of region-specific adaptation strategies.