Machine learning (ML) applications in hydrology are revolutionizing our understanding and
prediction of hydrological processes, driven by advancements in artificial intelligence and …

Flooding occurs frequently compared to other natural disasters. Less developed countries
are severely affected by floods. This research provides an integrated hydrometeorological …

This study examines the ability of different methods such as machine learning, ensemble
models, and metaheuristic algorithms to predict streamflow. For this purpose, five different …

The current study focuses on analyzing the impacts of climate change and land use/land
cover (LULC) changes on sediment yield in the Puthimari basin, an Eastern Himalayan sub …

Water yield (WY) ecosystem service is an important ecological indicator in assessing water
availability and sustainability. Although it was widely acknowledged that WY was mainly …

Accurate precipitation estimates over space and time are critically important, particularly in
data-scarce areas, for effective hydrological modeling and efficient regional water resources …

Water yield, one of the most valuable and important ecological indicators, reflects the
renewable capacity of regional water resources. The Taihang Mountains are a natural …

Joint multivariate distribution and calculation of return period are essential in enhancing
drought risk assessment and promoting the sustainable development of water resources …

This study aims to investigate land use/land cover (LULC) and climate change for a better
understanding of the hydrological processes of the Bhavani watershed, India. The ANN-CA …

The determination of changes in wetland areas in global practice is based on the use of
remote sensing data. However, remote sensing does not provide an understanding of the …