Geospatial Modeling for Drought Risk and Hazard Using Earth Observations and Multiscale Indicators

Abstract

Understanding various aspects of drought is essential due to its intricate newlinerelationship with socioeconomic and environmental conditions. Drought assessment and newlineprojection are challenging but a prerequisite task for minimizing risk and vulnerability newlineand developing appropriate management frameworks and strategies. India is amongst the newlinemost vulnerable and drought-prone countries in the world. Recurrent droughts are also a newlinesignificant problem in the Bundelkhand region of Uttar Pradesh, located in the Indo- newlineGangetic plain and has fertile cropland with immense potential. This region is a data newlinedeficit one, with complex and diverse topography where drought monitoring primarily newlinedepends on limited gauge site data. The drought characterization is of utmost importance newlinefor preventive measures, adaptations against similar droughts in the future, and newlinedeveloping unified management policies for the vulnerable areas. The current study newlineexplores the suitability of remote sensing data and hydrological models for near real-time newlinedrought mapping and their long-term monitoring. Moreover, a novel approach has been newlineproposed that combines multiple drought indicators and assess their effect on crop yield newlineusing Machine Learning techniques to fulfill the following research gaps newline