Yao Hu
Assistant Professor
Placeholder bio — to be replaced with Dr. Hu's own first-person research statement.
Dr. Yao Hu leads the Water Intelligence Lab at the University of Delaware. His work develops physics-based and machine-learning models of water systems, decision-making frameworks such as agent-based modeling, and the cyber-infrastructure needed to study the co-evolution of coupled human and water systems.
Research interests
Socio-hydrology · Agent-based modeling · Food–Energy–Water Nexus · Model coupling and integration · Water system modeling, analysis, and optimization · Causal inference · HPC and cloud computing · Data science and cyber-infrastructure.
Appointments
- Department of Geography and Spatial Sciences, College of Earth, Ocean & Environment
- Department of Civil, Construction and Environmental Engineering
- Engineering and Public Policy Program
Education
- Ph.D., Civil Engineering — University of Illinois at Urbana-Champaign, 2016
- M.S., Environmental Engineering — Hamburg University of Technology, Germany, 2010
- B.Eng., Civil Engineering & Computer Science — Huazhong University of Science and Technology, China, 2006
Office
217A Pearson Hall, 125 Academy Street, Newark, DE 19716
Currently working on
- Hybrid Modeling for Fine-Scale Runoff Prediction
Combining physically-based hydrology with machine learning to improve edge-of-field and watershed-scale runoff and risk prediction.
- Agent-Based Modeling of Groundwater Irrigation
Coupling agent-based models of farmer decision-making with groundwater systems to study irrigation behavior and water security.
Publications (15)
- Street-to-pipe diagnosis of compound rain–tailwater flooding
S. Xi, Y. Hu · Earth's Future, 14(4), e2026EF008402 · 2026
- Evaluating the Impact of Non-Stationary Groundwater Irrigation Behavior
Y. Hu · Authorea Preprints · 2025
- Assessing Hybrid Modeling for Fine-Scale Runoff Prediction
J. P. De Leon, Y. Hu, A. Meydani, D. N. Yates, L. M. Fry · AGU Fall Meeting Abstracts · 2024
- Hydrological extremes heighten vulnerability to schistosomiasis
D. F. Levia, R. Bergquist, A. Meydani, Y. Hu, D. M. Hannah · Earth's Future, 12(6), e2024EF004659 · 2024
- A methodological framework for improving the performance of data-driven models
Y. Hu, C. Ghosh, S. Malakpour-Estalaki · Geoscientific Model Development, 16(7), 1925–1936 · 2023
- Coastal Flooding: Modeling, Monitoring, and Protection Systems
V. Prigiobbe, C. Dawson, Y. Hu, H. O. Sharif, N. Tahvildari · Frontiers in Climate, 3, 830946 · 2022
- Generalization of Runoff Risk Prediction
C. M. Ford, Y. Hu, C. Ghosh, L. M. Fry, S. Malakpour-Estalaki, L. Mason · Geophysical Research Letters, e2022GL100667 · 2022
- Edge-of-field runoff prediction by a hybrid modeling approach
Y. Hu, L. Fitzpatrick, L. M. Fry, L. Mason, L. K. Read, D. C. Goering · Environmental Research Communications, 3(7), 075003 · 2021
- Detroit River Phosphorus Loads: Anatomy of a Binational Watershed
D. Scavia, S. A. Bocaniov, A. Dagnew, Y. Hu, B. Kerkez, C. M. Long · Journal of Great Lakes Research, 45(6), 1150–1161 · 2019
- Role of Heterogeneous Behavioral Factors in an Agent-Based Model of Crop Choice and Groundwater Irrigation
Y. Hu, S. Beattie · Journal of Water Resources Planning and Management, 145(2), 04018100 · 2019
- Urban Total Phosphorus Loads to the St. Clair–Detroit River System
Y. Hu, C. M. Long, Y. C. Wang, B. Kerkez, D. Scavia · Journal of Great Lakes Research, 45(6), 1142–1149 · 2019
- Are all data useful? Inferring causality to predict flows across sewer and drainage systems using directed information and boosted regression trees
Y. Hu, D. Scavia, B. Kerkez · Water Research, 145, 697–706 · 2018
- Combining human and machine intelligence to derive agents' behavioral rules for groundwater irrigation
Y. Hu, C. J. Quinn, X. Cai, N. W. Garfinkle · Advances in Water Resources, 109, 29–40 · 2017
- Design of a web-based application of the coupled multi-agent system model and environmental model for watershed management analysis using Hadoop
Y. Hu, X. Cai, B. DuPont · Environmental Modelling & Software, 70, 149–162 · 2015
- Global sensitivity analysis for large-scale socio-hydrological models
Y. Hu, O. Garcia-Cabrejo, X. Cai, A. J. Valocchi, B. DuPont · Environmental Modelling & Software, 73, 231–243 · 2015