Abstract
This study employs random forest regressor to forecast future flow in Kabul River. Utilizing CMIP6 projected climate data for the SSP585 scenario from the IPSL-CM6A-LR climate model. The random forest regressor demonstrate efficacy in predicting flow, achieving an R2 of 0.77. The study highlights the importance of modern artificial intelligence-based techniques for precise flow and flood predictions and suggests an increase in flash flood events in Kabul River in response to a warming climate.
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