The prediction of groundwater level is a viable strategy for attaining sustainable water
resource management. Recently, machine learning techniques have gained popularity as …

Satellite and reanalysis precipitation estimates of high quality are widely used for
hydrological modeling, especially in ungauged or data-scarce regions. To improve flood …

Climate change (CC) and land-use change (LUC) will alter a basin's hydrological processes
and water balance. Quantifying their significance is imperative in formulating appropriate …

This Paper examines the interesting topic of weather forecasting using ML. From kaggle.
com, there is an extensive list of daily weather records for a Seattle dataset. In this chapter …

The frequency and intensity of extreme precipitation events are on the rise worldwide.
Despite extensive efforts, regional climate models still show significant biases for extreme …

Rainfall prediction, based on meteorological data and models, forecasts the possible rainfall
conditions for a period in the future. It is one of the important issues in meteorology and …

Floods in southwestern Saudi Arabia, especially in the Asir region, are among the major
natural disasters caused by natural and human factors. In this region, flash floods that occur …

The primary innovation of this study lies in the development of an integrated modeling
framework that combines downscaled climate projections, land-use-change simulations …

The Cantareira Water Production System (CWPS), which supplies water to the most
populous region in Brazil, is facing significant challenges due to hydroclimate change, thus …

The **n'anjiang hydrological model (XHM) is the practical tool for runoff simulation and flood
forecasting in most regions in China, but it still presents some challenges when applied to …