Andrew Bennett

Assistant Professor

University of Arizona

United States

Research Interests

Explore related searches

Professors in United States

Contact this professor

Get a free first email built on one of their papers, ready for you to edit and send yourself.

About

Andrew Bennett is an Assistant Professor at the University of Arizona in the United States. His research focuses on hydrology, machine learning applications for environmental modeling, and the reproducibility of hydrologic models. Recent publications include studies on flood insurance sensitivity, regionalized catchment dynamics, and parameter inversion frameworks for groundwater models.

Articles (10)

Year:

2025

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Collaborators (7)

Peter Melchior

Assistant Professor

Princeton University

UNITED STATES

View details

Laura Condon

Assistant Professor

University of Arizona

UNITED STATES

View details

Kevin Anchukaitis

Professor

University of Arizona

UNITED STATES

View details

Bart Nijssen

Professor

University of Washington

UNITED STATES

View details

Alain Pietroniro

Professor and Chair

University of Calgary

CANADA

View details

Yifan Cheng

Assistant Professor

University at Albany, State University of New York

UNITED STATES

View details

Raymond Spiteri

Professor

University of Saskatchewan

CANADA

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Andrew Bennett

Research Interests

Explore related searches

Contact this professor

About

Articles (10)

A HydroLSTM‐Based Machine‐Learning Approach to Discovering Regionalized Representations of Catchment Dynamics

A Deep‐Learning Based Parameter Inversion Framework for Large‐Scale Groundwater Models

Coupled High‐Resolution Land‐Atmosphere Modeling for Hydroclimate and Terrestrial Hydrology in Alaska and the Yukon River Basin (1990–2021)

Sensitivity to Data Choice for Index‐Based Flood Insurance

Spatio‐Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology

Simulation-based inference for parameter estimation of complex watershed simulators

Community Workflows to Advance Reproducibility in Hydrologic Modeling: Separating Model-Agnostic and Model-Specific Configuration Steps in Applications of Large-Domain Hydrologic Models

When and Where Are Multiple Snow Layers Important for Simulations of Snow Accumulation and Melt?

Evaluating Multiple Canopy‐Snow Unloading Parameterizations in SUMMA With Time‐Lapse Photography Characterized by Citizen Scientists

Deep Learned Process Parameterizations Provide Better Representations of Turbulent Heat Fluxes in Hydrologic Models

Collaborators (7)

Peter Melchior

Laura Condon

Kevin Anchukaitis

Bart Nijssen

Alain Pietroniro

Yifan Cheng

Raymond Spiteri

Make your next move.