The rapid advancement in Artificial Intelligence (AI) and big data has developed significance
in the water sector, particularly in hydrological time-series predictions. Recurrent Neural …

The agricultural sector is vulnerable to climate change (CC). Various climate-related
extremes, such as droughts, heat waves, unpredictable rainfall patterns, storms, floods, and …

Climate change and increasing water demands underscore the importance of water
resource management. Precise precipitation forecasting is critical to effective management …

Climate variability, trend analysis, and accurate forecasting are vital in a country's effective
water resource management and strategic planning. Precipitation and temperature are …

Selecting appropriate input variables for develo** a rainfall prediction model is
significantly difficult. The present study proposed an innovative framework for input variable …

This study compares the performance of satellite precipitation products (SPPs) and soil
moisture-based rainfall products (SM2RPPs) in capturing rainfall patterns in Burkina Faso …

Climate change (CC) is causing a significant threat to agriculture, a sector complicatedly tied
to natural resources. Changes in precipitation patterns, atmospheric water content, and …

Can artificial intelligence (AI) models beat traditional numerical weather prediction (NWP)
models based on physical principles? The rapid advancement of AI, inherent computational …

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 …

Geophysical domains typically exhibit intricate, irregular boundaries characterized by fractal-
like geometries, while underlying physical processes operate across a broad spectrum of …