Water is the fundamental natural resource that supports life, ecosystems and human society.
Thus studying the water cycle is important for sustainable development. In the context of …

The African continent hosts some of the largest freshwater systems worldwide, characterized
by a large distribution and variability of surface waters that play a key role in the water …

Traditional, mainstream definitions of drought describe it as deficit in water‐related variables
or water‐dependent activities (eg, precipitation, soil moisture, surface and groundwater …

This paper is derived from a keynote talk given at the Google's 2020 Flood Forecasting
Meets Machine Learning Workshop. Recent experiments applying deep learning to rainfall …

Renewable sources of electricity, such as solar and wind, need to be paired with sources of
reliable baseload. Hydropower is a renewable, low‐emission source of electricity baseload …

High-quality datasets are essential to support hydrological science and modeling. Several
CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist …

This study investigates the ability of long short-term memory (LSTM) neural networks to
perform streamflow prediction at ungauged basins. A set of state-of-the-art, hydrological …

The hydrologic sciences and water resources management have long depended on a
combination of in situ measurements and remotely sensed data for research and regulatory …

The surface water quality monitoring network (WQMN) is crucial for effective water
environment management. How to design an optimal monitoring network is an important …

Hydrological model calibration combining Earth observations and in situ measurements is a
promising solution to overcome the limitations of the traditional streamflow‐only calibration …