Influence of Land Surface Temperature and Rainfall on Surface Water Change: An Innovative Machine Learning Approach

Abstract The largest reservoir of drinkable water on Earth is surface water. It crucial for maintaining ecosystems and enabling people to adapt diverse climate changes. Despite freshwater essential life, the current research shows a striking lack understanding in its spatial temporal dynamics variations outflow storage across sizable country: India. Numerous restrictions apply research, including use insufficient machine learning techniques limited data series. This work uses cutting-edge SOTA-method available accurately understand using extended authors did examination thematic maps produced ArcMap 10.8 from June’2005 June’2020 JRC dataset track changes intensity Google Engine Python API has been devised detect levels quantifying shifting map trends. Raster image viewing, editing, calculation are done with ArcMap. For determining relationship between declines Surface levels, rainfall land temperature, variables were averaged over 13 rivers 15 years. change reliant independent temperature intensity. correlation these parameters achieve an average R-squared adjusted value 0.402. study's findings contribute better matter can be used world.