Globally on an average 45,000 lives are lost each year due to natural hazards, out of which most lives are lost due to flood and drought but it has also been noticed that the loss of lives due to these two factors has reduced in recent years. An increase in deadly flash floods have been recorded in the Himalaya in the recent years. Since 2000, around 13 such incidents have been recorded. This increase has been ascribed to the climate change and it is also expected that the frequency of such events will increase in future with melting of the glaciers.
Events like Kedarnath (2013) and Rishiganga (2021) are examples of such flash floods. Hundreds of lives were lost in these events. So now, the question arises that can we develop an early warning system for the same. It appears that we already have all the elements required to develop an early warning system for the flash floods. We have a robust weather forecasting system (which is improving with time) that can predict rainfall and a high resolution landslides inventory. There are ongoing efforts to map the glacial lakes-an important cause for the flashfloods in higher Himalaya. Recent studies have shown, how geophysical methods can help in identifying the debris flow which are generally driven by lake outburst or cloud burst events. Apart from these elements, significant advancements have been made in the field of Artificial Intelligence and Machine learning. All these elements along with additional surface processes understanding can be brought together to develop an early warning system that can help us to warn the people in advance and also issue alerts to the most vulnerable zones in real time. This can help save precious lives that are lost in such events.
