Satellite sensing has transformed hydrology by providing global information on variables and fluxes. Breakthroughs will come from integrating sensing information and cross-disciplinary approaches.
Remote sensing
Posted inEditors' Highlights
Thickness and Strength of Slow-moving Landslides Revealed
Hundreds of slow-moving landslides’ deformation patterns were inverted to obtain their thickness and frictional strength, revealing that larger landslides are weaker and thinner than smaller ones.
Posted inEditors' Highlights
Gauging Ungauged River Basins with Smart Remote Sensing
A clever combination of hydrologic modelling and discharge estimates from the Landsat satellite provides good discharge estimates throughout the Missouri river basin.
Posted inScience Updates
Measuring, Monitoring, and Modeling Ecosystem Cycling
Scientists leverage long-term environmental measurements, emerging satellite observations, and recent modeling advances to examine changes in ecosystem carbon and water cycling.
Posted inEditors' Highlights
Ensemble Learning Estimates Terrestrial Water Storage Changes
Ensemble learning models for estimating past changes of terrestrial water storage from climate are presented and tested in the Pearl River basin, China.
Posted inEditors' Highlights
Machine Learning Improves Satellite Rainfall Estimates
A new deep learning approach bridges ground rain gauge and radar data with spaceborne radar observations of Tropical Rainfall Measuring Mission to improve precipitation estimation.
Posted inEditors' Vox
The Paramount Societal Impact of Soil Moisture
Recent technological innovations offer new opportunities for soil moisture characterization and monitoring from the pedon to global scales.
Posted inResearch Spotlights
A More Accurate Global River Map
A new map of global river systems is based on crowdsourcing and the latest topography data sets.
Posted inResearch Spotlights
Precipitation in the Tropics: A New View
The first study to simultaneously investigate precipitation and cloud structures in tropical weather systems concludes observation systems significantly overestimate the height of raining clouds.
Posted inResearch Spotlights
Are Soil Moisture and Latent Heat Overcoupled in Land Models?
A novel statistical approach demonstrates how to reduce bias in remote sensing estimates of soil moisture and latent heat flux coupling strength and clarifies the relationship between the variables.