Earth observation (EO) satellite missions have been providing detailed images about the
state of Earth and its land cover for over 50 years. Long-term missions, such as those of …

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 …

There exists a substantial disparity in the distribution of streamflow gauge and basin
characteristic information, with a majority of flood observations being recorded from a limited …

High-quality gridded soil moisture products are essential for many Earth system science
applications, while the recent reanalysis and remote sensing soil moisture data are often …

Accurate prediction of soil moisture (SM) and soil temperature (ST) plays an important role in
Earth system science, hel** to forecast and understand ecosystem changes. They present …

This study examines whether deep learning models can produce reliable future projections
of streamflow under warming. We train a regional long short‐term memory network (LSTM) …

The current study proposes a new method to downscale the monthly GRACE-derived
Terrestrial Water Storage Anomaly (TWSA) to 10 km spatial resolution over Iran using deep …

In the underground mining process, the evolution of fissures, fractures, and breakages in
overlying rock strata can lead to water inrush and many other serious risks, including rock …

Abstract Synthetic Aperture Radar (SAR) data is increasingly popular as a data source for
global near-surface soil moisture map**, but large-scale applications are still challenging …

Deep learning (DL) models trained on hydrologic observations can perform extraordinarily
well, but they can inherit deficiencies of the training data, such as limited coverage of in situ …