Paper Title :Mobile Application for Drought Forecasting With Vulnerability Scale Indexing Using Machine Learning Algorithm

Author :K Anand, Akhila Vignesh, Anagha Nambiar, Ananthi S

Article Citation :K Anand ,Akhila Vignesh ,Anagha Nambiar ,Ananthi S , (2023 ) " Mobile Application for Drought Forecasting With Vulnerability Scale Indexing Using Machine Learning Algorithm " , International Journal of Advance Computational Engineering and Networking (IJACEN) , pp. 94-98, Volume-11,Issue-4

Abstract : Abstract - There can be no clear origin or finish to the beginning of drought because of its gradual development and withdrawal. This can be decreased by creating an algorithm based on the crisis analysis framework suggested in the National Crisis Management Plan for Drought (2019), which rates the vulnerability of each state on a scale from 0 to 10. The drought forecast is then fabricated by looking at trends in various metrics, comprising soil moisture, precipitation, water table levels, and surface water levels. A mobile application is then created that gives users a forecast that is displayed on a map with colors based on the scale of the vulnerabilities. The best accurate approach for predicting this drought was determined by contrasting numerous algorithms. Keywords - Soil Moisture, Rainfall, Groundwater Level, and Surface Water Level

Type : Research paper

Published : Volume-11,Issue-4

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