Risk assessment and adaptation strategies for irrigated and rainfed cotton crop production under climate change

Abstract

Predicting the impacts of future climate on food and fibre production are essential for devising suitable adaptations strategy. This study aims to understand the impact of climate change on cotton crop change using Regional Climate Model (RCM) in the near and far future. The RCM model considered for the study is RegCM4 from CORDEX-SA experiment for the two RCP scenarios at RCP4.5 and RCP8.5. To refine these projections, we have bias-corrected the data using quantile mapping approach. This study is based on two locations: one in Hisar (mostly irrigated) and the other in Akola (mostly rainfed), located in the northern and central agro-climatic zones for cotton. The daily projected data have been summarised as 1971–2005(1990), 2006–2035(2020), 2036–2065(2050) and 2066–2095(2080). The RCM projections show good agreement with the observed climatology, but still bias exists, which is fine-tuned by bias-correction. The RCM model showed reduced diurnal temperature and night warming as it highly underestimates maximum temperature and slightly the minimum temperature. It also predicts rise in temperature at higher rates in northern than central zones. Also, the amount of rainfall is increasing in the northern region and decreasing in the central region at RCP8.5. The spatial variability is observed as the amount of rainfall is increasing in the northern irrigated region and decreasing in the central rainfed region. The rainfall intensity in Hisar is projected to increase till 2050 and a further decline in 2080. And in the central zone, it is presently higher than the northern region, but projected to decrease further from 1990 to 2080. These daily weather data were then employed in the cotton-CROPGRO model under DSSAT-CSM (v4.6) to assess its impact on future climate. The crop model has been simulated with these weather projections for the three sowing dates under rainfed, irrigated, and potential conditions. It is observed that the simulated crop yields and LAI in Akola are higher at RCP8.5 than RCP4.5, whereas in Hisar, it is lower at RCP8.5 than RCP4.5. So, in the cooler and wetter central zone, temperature may slightly rise at RCP8.5 along with increased rainfall and CO₂, favouring the cotton crop. This shows the suitability of crops in this region even at RCP8.5 and far future. Whereas in the hot and dry northern agro-climatic cotton zone, it is projected that the temperature slightly increases from present at RCP4.5 and further at RCP8.5, and the amount of rainfall increases at RCP4.5 and reduces at RCP8.5. So, the crop here could stand the increased temperature at RCP4.5 and is also favoured due to increased CO2 and precipitation. But, at RCP8.5, the comparatively higher rate of increase in temperature and decreasing amount of rainfall may affect cotton crops adversely, with its maximum effects in the far future. Also, in future climate with temporal variability in the amount of precipitation and increasing temperature, late sown cotton crops are favoured, especially with proper irrigation practices in both the regions. The study embraces utilisation of RCMs and crop models to study the vulnerability of crops to climate change, which could help to assess the site-specific adaptive potential and mitigation measures for future climate.