Andrew Wood

Research Professor

Colorado School of Mines

United States

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Andrew Wood is a Research Professor at the Colorado School of Mines, located in the United States. His research focuses on land and hydrology modeling, particularly in the context of artificial intelligence and climate forecasting. Recent publications highlight his work on hydrological process simulations, flood risk predictions, and the development of data-driven methodologies for streamflow forecasting.

Articles (19)

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2025

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2020

Collaborators (12)

Wim Thiery

Professor at Vrije Universiteit Brussel

Vrije Universiteit Brussel

BELGIUM

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Marie-Amélie Boucher

Professor

Université de Sherbrooke

CANADA

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Linda Speight

University of Oxford

UNITED KINGDOM

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Chaopeng Shen

Assistant Professor

Pennsylvania State University

UNITED STATES

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Yalan Song

Pennsylvania State University

UNITED STATES

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Daniel L. Swain

University of California

UNITED STATES

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Yifan Cheng

Assistant Professor

University at Albany, State University of New York

UNITED STATES

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Robert Wilby

Loughborough University

UNITED KINGDOM

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Lifeng Luo

Associate Professor

Michigan State University

UNITED STATES

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Louise Slater

University of Oxford

UNITED KINGDOM

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Elizabeth Payton

Senior Professional Research Assistant

University of Colorado Boulder

UNITED STATES

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Simon Michael Papalexiou

Assistant Professor

University of Calgary

CANADA

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Andrew Wood

Research Interests

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Articles (19)

Technical note: How many models do we need to simulate hydrologic processes across large geographical domains?

Calibrating a large-domain land/hydrology process model in the age of AI: the SUMMA CAMELS emulator experiments

On Using AI‐Based Large‐Sample Emulators for Land/Hydrology Model Calibration and Regionalization

Skilful probabilistic predictions of UK flood risk months ahead using a large-sample machine learning model trained on multimodel ensemble climate forecasts

GPEP v1.0: the Geospatial Probabilistic Estimation Package to support Earth science applications

FROSTBYTE: a reproducible data-driven workflow for probabilistic seasonal streamflow forecasting in snow-fed river basins across North America

Improving Earth System Model Selection Methodologies for Projecting Hydroclimatic Change: Case Study in the Pacific Northwest

Toward Understanding Parametric Controls on Runoff Sensitivity to Climate in the Community Land Model: A Case Study Over the Colorado River Headwaters

Hybrid forecasting: blending climate predictions with AI models

Mass‐Conserving Downscaling of Climate Model Precipitation Over Mountainous Terrain for Water Resource Applications

EMDNA: an Ensemble Meteorological Dataset for North America

Generating Ensemble Streamflow Forecasts: A Review of Methods and Approaches Over the Past 40 Years

Space–time dependence of compound hot–dry events in the United States: assessment using a multi-site multi-variable weather generator

Increasing importance of temperature as a contributor to the spatial extent of streamflow drought

Flood spatial coherence, triggers, and performance in hydrological simulations: large-sample evaluation of four streamflow-calibrated models

Probabilistic Spatial Meteorological Estimates for Alaska and the Yukon

SCDNA: a serially complete precipitation and temperature dataset for North America from 1979 to 2018

Future streamflow regime changes in the United States: assessment using functional classification

Spatial Dependence of Floods Shaped by Spatiotemporal Variations in Meteorological and Land‐Surface Processes

Collaborators (12)

Wim Thiery

Marie-Amélie Boucher

Linda Speight

Chaopeng Shen

Yalan Song

Daniel L. Swain

Yifan Cheng

Robert Wilby

Lifeng Luo

Louise Slater

Elizabeth Payton

Simon Michael Papalexiou

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