Extreme heat, drought and moisture excess are increasingly co-occurring within a single
growing season, impacting crop yields in global breadbasket regions. In this Review, we …

Over the past few years, Deep Learning (DL) methods have garnered substantial
recognition within the field of hydrology and water resources applications. Beginning with a …

We propose a new architecture based on a fully connected feed-forward Artificial Neural
Network (ANN) model to estimate surface soil moisture from satellite images on a large …

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 …

Droughts of the future are likely to be more frequent, severe, and longer lasting than they
have been in recent decades, but drought risks will be lower if greenhouse gas emissions …

In 2009, the International Soil Moisture Network (ISMN) was initiated as a community effort,
funded by the European Space Agency, to serve as a centralised data hosting facility for …

A poor understanding of the fraction of global plant biomass occurring belowground as roots
limits our understanding of present and future ecosystem function and carbon pools. Here …

Soil moisture (SM) is an essential parameter for understanding the interactions and
feedbacks between the atmosphere and the Earth's surface through energy and water …

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for
numerous Earth and environmental science applications that directly impact the global …

Drought is a common hydrometeorological phenomenon and a pervasive global hazard. As
our climate changes, it is likely that drought events will become more intense and frequent …