Statistical models were developed for downscaling reanalysis data to monthly precipitation
at 48 observation stations scattered across the Australian State of Victoria belonging to wet …

The main objective of this work is the future prediction of the floods in India due to climate
and land change. Human activity and related carbon emissions are the primary cause of …

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

Climate change will increase the vulnerability of agricultural production systems, unless
scientists and farmers reorient their present approaches towards making them climate smart …

Researchers often examine hydro-climatological processes via Global Circulation Model
(GCM) and hydrological model, which have been shown to benefit water resources …

A variety of methods are available to estimate values of meteorological variables at future
times and at spatial scales that are appropriate for local climate change impact assessment …

Climate change is believed to have significant impacts on the water basin and region, such
as in a runoff and hydrological system. However, impact studies on the water basin and …

The study evaluates statistical downscaling model (SDSM) developed by annual and
monthly sub-models for downscaling maximum temperature, minimum temperature, and …

This work evaluates the impact of climate change on the water balance of a catchment in
India. Rainfall and hydro-meteorological variables for current (20C3M scenario, 1981–2000) …

Climate change would significantly affect many hydrologic systems, which in turn would
affect the water availability, runoff, and the flow in rivers. This study evaluates the impacts of …