Latest publication in Journal of Hydrometeorology: https://lnkd.in/gjb9sv4S Majority of flash flood research is concentrated on predicting discharge and timing of floods. But the receding period of floods is vital for disaster relief, community recovery, public health etc and attracts little attention in comparison. Generally, we use Recession curves for this, but they can be difficult to use from an operational point of view. Here, we propose a new metric called 'Recoveriness', based on the physical definition of floods by an operational agency. And mapped it across the country using machine learning. Because the metric is based on operational definitions of floods and flash floods, it has the potential for wide usage for both climatology and events. Led by Principal Project Scientist of HydroSense Lab: Anil Kumar. In collaboration with Prof. Pierre-Emmanuel Kirstetter.
Interesting. We are working on something similar.
Great work! Many congratulations Anil Kumar Manabendra Saharia
Congratulations on the latest publication in the Journal of Hydrometeorology! Your research on the receding period of floods and the development of the 'Recoveriness' metric is a valuable contribution to the field. It's great to see a focus on the often-overlooked aspect of disaster relief and community recovery. The use of machine learning to map the metric across the country is an innovative approach that has the potential to benefit both climatology and events. Keep up the excellent work!
Interesting! Congratulations! 🎉
Associate Professor at Indian Institute of Technology, Bombay
3moCongratulations!!