This paper offers a comprehensive overview of machine learning (ML) methodologies and
algorithms, highlighting their practical applications in the critical domain of water resource …

Big data analytics (BDA) is a novel concept focusing on leveraging large volumes of
heterogeneous data through advanced analytics to drive information discovery. This paper …

Accurate prediction of crop evapotranspiration (ET c) can provide a scientific basis for
improving water use efficiency, rational allocation of water resources, and sustainable …

Accurate information about groundwater level prediction is crucial for effective planning and
management of groundwater resources. In the present study, the Artificial Neural Network …

Developing models that can accurately simulate groundwater level is important for water
resource management and aquifer protection. In particular, machine learning tools provide a …

Due to its heterogeneous and complex nature, groundwater modeling needs great effort to
quantify the aquifer, a crucial tool for policymakers and hydrogeologists to understand the …

The real biological effect is not generated by the total content of heavy metals (HMs), but
rather by bioavailable content. A new bioavailability-based ecological risk assessment (BA …

In this study, we have investigated rainfall induced landslide susceptibility of the Uttarkashi
district of India through the developmentof different novel GIS based soft computing …

Coastal harmful algal blooms (HABs) have become one of the challenging environmental
problems in the world's thriving coastal cities due to the interference of multiple stressors …

This paper proposes s-LSTM, a top-down deep learning model, for efficiently modelling and
predicting the spatiotemporal dynamics of groundwater recharge. The model's effectiveness …