Assessing climate change impacts on rice yield using bias correction and DSSAT modeling with scenario projections: A case study of Dapoli, Maharashtra

Abstract

A study was conducted using the Institute Pierre-Simon Laplace (IPSL) and the Geophysical Fluid Dynamics Laboratory Earth System (GFDL) models to assess climate change impacts on maximum temperature (Tmax), minimum temperature (Tmin), and rainfall trends in Dapoli, Maharashtra. Historical data from 1983–2023 and projected trends from 2024–2099 under representative concentration pathways (RCP) 4.5 and 8.5 were analyzed using non-parametric tests and statistical methods. The study projects a rise in Tmax by approximately 3.2 °C under RCP 4.5 and 4.1 °C under RCP 8.5 by 2099, leading to increased heat stress risks. Rainfall variability also intensifies, with the GFDL model predicting more extreme rainfall events, especially under RCP 8.5. Projected Tmin shows significant warming, during the Northeast Monsoon (NEM) and winter, affecting crop cycles and vernalization requirements. The research indicates a steady rise in Tmax and Tmin across all scenarios, with RCP 8.5 exhibiting a more significant increase, whereas RCP 4.5 displays varied patterns. The DSSAT model analyzes the influence of climate trends on the performance of the Sahyadri-2 rice cultivar. The rice biomass and grain yield are a little bit steady in RCP 4.5, whereas RCP 8.5 demonstrates increased variability. Thermal stress, inundation, and irregular precipitation Decreased agricultural yields during essential growth phases, however, increased CO₂ concentrations under RCP 8.5 enhance water-use efficiency and photosynthesis, mitigating losses. The rice productivity in Dapoli can be markedly improved by appropriate adaptation measures as outlined.