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Author/Chair

Reed Maxwell

Princeton University

Notes

Meeting roles in:
High-Dimensional Calibration of Hydrologic Models Using Simulation-Based Inference (SBI)
From High in the Sky to Deep Underground: Coupling Remote Sensing with Integrated Hydrologic Modeling to Highlight how Groundwater Pumping Impacts Streamflow in the UCRB
Comparing Snow Water Equivalent Estimations from Long Short-Term Memory Networks and Physics-Based Models in the Western United States
Downscaling Surface Inundation Produced by Integrated Hydrologic Models Using a Random Forest Model
Toward Hyper-Resolution Transient Groundwater Modeling at Continental Scale Using Physics-Guided Machine Learning
High-Resolution Groundwater Pumping Estimation in New Jersey Using a Three-Stage Machine Learning Ensemble
Developing the next generation US integrated hydrologic model: recent progress and the path forward to a complete terrestrial hydrology digital twin
Assessing Graph Connectivity for Spatiotemporal Groundwater Level Forecasting in Graph Neural Networks
Effects of soil capillarity on multidimensional, integrated surface-subsurface hydrology at different spatial scales
Streamlining Integrated Hydrologic Modeling at Continental Scale: A Workflow for Quasi–Real-Time ParFlow-CLM Simulations over CONUS
High-Resolution Evidence of Plant Water Use of Shallow Groundwater in a Colorado Headwaters Catchment
A Random Forest Model to Estimate Water Table Depth Over Brazil
A Random Forest Model to Estimate Water Table Depth Over Brazil
A theoretical and numerical model for unconfined aquifers in cold firn
Modeling meltwater infiltration and ice layer formation in Greenland firn
Advancing integrated continental scale hydrology through democratized data and ml-accelerated modeling.
Integrating Creative Evaluation into Climate and Water Education: A Multi-Year Look at Student Engagement and Learning
Coupling ParFlow with the Common Land Model through a Hybrid Physical–Surrogate Framework
A General Method to Quantify Stream and Groundwater Vulnerability to Contaminants from Distributed and Non-point Sources Using Integrated Hydrologic and Particle Tracking Models.
Inverse Machine Learning for 3D Subsurface Characterization and Pumping Estimation in CONUS-Scale Models

Sessions

Links & Materials

Reed Maxwell

A34A-01: Advancing integrated continental scale hydrology through democratized data and ml-accelerated modeling. (invited) (highlighted)

My ORCID Profile

Advancing integrated continental scale hydrology through democratized data and ml-accelerated modeling.

A theoretical and numerical model for unconfined aquifers in cold firn

Modeling meltwater infiltration and ice layer formation in Greenland firn

Integrating Creative Evaluation into Climate and Water Education: A Multi-Year Look at Student Engagement and Learning

High-Dimensional Calibration of Hydrologic Models Using Simulation-Based Inference (SBI)

From High in the Sky to Deep Underground: Coupling Remote Sensing with Integrated Hydrologic Modeling to Highlight how Groundwater Pumping Impacts Streamflow in the UCRB

Comparing Snow Water Equivalent Estimations from Long Short-Term Memory Networks and Physics-Based Models in the Western United States

Downscaling Surface Inundation Produced by Integrated Hydrologic Models Using a Random Forest Model

Toward Hyper-Resolution Transient Groundwater Modeling at Continental Scale Using Physics-Guided Machine Learning

High-Resolution Groundwater Pumping Estimation in New Jersey Using a Three-Stage Machine Learning Ensemble

Developing the next generation US integrated hydrologic model: recent progress and the path forward to a complete terrestrial hydrology digital twin

Effects of soil capillarity on multidimensional, integrated surface-subsurface hydrology at different spatial scales

Streamlining Integrated Hydrologic Modeling at Continental Scale: A Workflow for Quasi–Real-Time ParFlow-CLM Simulations over CONUS

Assessing Graph Connectivity for Spatiotemporal Groundwater Level Forecasting in Graph Neural Networks

A Random Forest Model to Estimate Water Table Depth Over Brazil

High-Resolution Evidence of Plant Water Use of Shallow Groundwater in a Colorado Headwaters Catchment

Coupling ParFlow with the Common Land Model through a Hybrid Physical–Surrogate Framework

A General Method to Quantify Stream and Groundwater Vulnerability to Contaminants from Distributed and Non-point Sources Using Integrated Hydrologic and Particle Tracking Models.

Inverse Machine Learning for 3D Subsurface Characterization and Pumping Estimation in CONUS-Scale Models