Rebuilding efforts are ongoing, but the scale of the damage has placed considerable strain on resources as well. As we confront these challenges, it is imperative to delve into the causes, assess the impacts, and outline a path forward for policymakers. Learning from Odisha’s transformation in disaster management over the past 25 years, triggered by the devastating 1999 Super Cyclone, has made it a leader in this field. The state implemented innovative strategies, focusing on communities and infrastructure, and offers valuable lessons for disaster-prone regions worldwide as they confront increasing climate risks.
Harnessing the power of artificial intelligence (AI) in weather prediction and environmental management can significantly enhance our adaptive capacity and enable data-driven decision-making. AI is transforming weather prediction in multiple ways vis-à-vis data analysis, predictive modelling, real-time forecasting, climate modelling, weather radar systems by detecting severe weather events more accurately, satellite imaging, ensemble forecasting through combining multiple models to generate more accurate forecasts, and nowcasting for short-term forecasts (within two hours) for severe weather events; etc.
AI is being used by weather agencies worldwide, including the United States’ National Weather Service, the European Centre for Medium-Range Weather Forecasts, the China Meteorological Administration and the India Meteorological Department (IMD). In addition to the multiple ways in which AI can be useful, the IMD is also using it for flood forecasting through AI-powered models to predict flood risk and alert authorities to take preventive measures.
In India, the application of AI in disaster management is still in its nascent stages. However, the potential benefits are immense. Hopefully, a recently proposed upgradation to the National Monsoon Mission with a budget of Rs 10,000 crore, will serve to jumpstart IMD towards further improving its ability as regards localised forecasting and extreme weather events.
By investing in AI-powered disaster management systems, India can reduce the impact of natural disasters, saving lives and livelihoods. AI-driven predictive analytics can help identify high-risk areas, enabling authorities to take proactive measures to evacuate people and minimise damage. Moreover, AI-powered chatbots can disseminate critical information to citizens, ensuring they are informed and equipped to handle emergencies. Experience also shows that the return on investment in disaster prevention is almost invariably better than that from post-disaster reconstruction. In the US, AI-powered weather forecasting systems have improved prediction accuracy by up to 30 per cent, while in Japan, AI-driven early warning systems have reduced the response time to natural disasters by up to 50 per cent. The importance of integrating AI-driven solutions in disaster management cannot be overstated.
