Potential Impacts of Future Climate Changes on Crop Productivity of Cereals and Legumes in Tamil Nadu, India: A Mid-Century Time Slice Approach

Abstract

Climate change is a terrible global concern and one of the greatest future threats to societal development as a whole. The accelerating pace of climate change is becoming a major challenge for agricultural production and food security everywhere. The present study uses the midcentury climate derived from the ensemble of 29 general circulation models (GCMs) on a spatial grid to quantify the anticipated climate change impacts on rice, maize, black gram, and red gram productivity over Tamil Nadu state in India under RCP 4.5 and RCP 8.5 scenarios. The future climate projections show an unequivocal increase of annual maximum temperature varying from 0.9 to 2.2°C for RCP 4.5 and 1.4 to 2.7°C in RCP 8.5 scenario by midcentury, centered around 2055 compared to baseline (1981–2020). The projected rise in minimum temperature ranges from 1.0 to 2.2°C with RCP 4.5 and 1.8 to 2.7°C under RCP 8.5 scenario. Among the monsoons, the southwest monsoon (SWM) is expected to be warmer than the northeast monsoon (NEM). Annual rainfall is predicted to increase up to 20% under RCP 4.5 scenario in two-third of the area over Tamil Nadu. Similarly, RCP 8.5 scenario indicates the possibility of an increase in rainfall in the midcentury with higher magnitude than RCP 4.5. Both SWM and NEM seasons are expected to receive higher rainfall during midcentury under RCP 4.5 and RCP 8.5 than the baseline. In the midcentury, climate change is likely to pose a negative impact on the productivity of rice, maize, black gram, and red gram with both RCP 4.5 and RCP 8.5 scenarios in most places of Tamil Nadu. The magnitude of the decline in yield of all four crops would be more with RCP 8.5 over RCP 4.5 scenario in Tamil Nadu. Future climate projections made through multi-climate model ensemble could increase the plausibility of future climate change impact assessment on crop productivity. The adverse effects of climate change on cereal and legume crop productivity entail the potential adaptation options to ensure food security.

Incorporating Meteorological Data and Pesticide Information to Forecast Crop Yields Using Machine Learning

“…The agricultural sector in India is highly dependent on the monsoon season [14], [15]. In India, around 70% of the annual precipitation occurs during the monsoon season, facilitating irrigation for approximately half of the country's agricultural fields.…”