The analysis of morphometric parameters plays a crucial role in understanding and
managing watersheds, making it a fundamental component of hydrological investigations …

Abstract Long Short-Term Memory (LSTM) has recently emerged as a crucial tool for
scientific research in hydrology and water resources. Despite its widespread use, a …

Climate change is intensifying the occurrence of extreme rainfall events, drawing attention to
the importance of understanding the return period concept within the realm of extreme …

Abstract The Soil and Water Assessment Tool (SWAT) is an ecohydrological model that has
been widely applied to assess water quality and watershed management. This tool also has …

In recent years, there has been a growing interest in using artificial intelligence (AI) for
rainfall-runoff modelling, as it has shown promising adaptability in this context. The current …

The current investigation was conducted in the Murredu watershed, situated in India. The
essential datasets, such as the digital elevation model (DEM), soil, land use land cover …

The present investigation was carried out within the Peddavagu watershed, which is located
in India. The necessary datasets, including soil, land-use land cover (LULC), rainfall, and …

The present study analyzes the capability of convolutional neural network (CNN), long short-
term memory (LSTM), CNN-LSTM, fuzzy CNN, fuzzy LSTM, and fuzzy CNN-LSTM to mimic …

Water scarcity is a pressing global issue exacerbated by climate change and population
growth. Traditional water management methods often fall short in addressing this challenge …

This research examines the impacts of climate change and socio-economic variables on the
hydrological cycle, reservoir water management, and hydropower capacity at the Gezhouba …