In hydrological modeling, predicting multiple tasks helps in identifying physical rules and generalizations.
Stefan Kollet
Editor, Water Resources Research
Posted inEditors' Highlights
Rock Solid Augmentation: AI-Driven Digital Rock Analysis
Boosting digital rock images with AI-powered augmentation and quality analysis could improve subsurface engineering decisions.
Posted inEditors' Highlights
Listening to Groundwater Dynamics
Deep learning from shallow passive seismic data reveals groundwater table depth information in space and time.
Posted inEditors' Highlights
Learning Data Assimilation Without the Help of the Gaussian Assumption
Major Earth system processes are non-linear and non-Gaussian, and so should be our data assimilation approaches.
Posted inEditors' Highlights
Using Big Data for Monitoring Network Design and Beyond
Large data sets can be generated using deep learning to improve the design of observation networks for monitoring subsurface flow and transport.
Posted inEditors' Highlights
Deep Learning for Hydrologic Projections Under Climate Change
Extrapolation or not? Big data may help deep learning to go places where it has not been before by transferring learned hydrologic relationships.