PhD Position in Groundwater Hydrology and Machine Learning
Explore how to improve groundwater flow predictions in snow-affected watersheds with innovative machine learning and physics-based models. Develop computational skills while addressing critical water resource challenges.
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Project Description
Project Overview
This PhD project focuses on predicting baseflow in snow-dominated watersheds using a combination of physics-based hydrologic modeling and machine learning techniques. The research will be conducted within the Shuai Computational and Integrated Hydrology Group at Utah State University.
What You Will Do
You will develop and integrate computational models that predict groundwater baseflow by leveraging strengths of both physics-based simulations and advanced machine learning methods. The work involves programming, data analysis, and model validation using hydrologic data from snow-influenced environments.
Expected Outcomes
The project aims to create robust predictive models that improve understanding of groundwater and surface water interactions during snowmelt periods. Anticipated results include novel hybrid modeling frameworks and enhanced predictive accuracy for hydrologic processes that support better water resource management.
Why This Matters
Accurate prediction of baseflow in snow-dominated watersheds is critical for managing water resources, especially in regions dependent on snowmelt for freshwater supplies. Integrating machine learning with physics-based models offers an opportunity to overcome limitations of traditional approaches and address challenges posed by climate variability.
Entry Requirements
How to Apply
Eligibility
Supervisor Profile
Dr. Pin Shuai specializes in investigating groundwater and surface water interactions, flow, and reactive transport in hydrologic systems. His research focuses on biogeochemical processes and hydrogeologic dynamics, using advanced computational methods to understand complex environmental systems. He leads the Shuai Computational and Integrated Hydrology Group at Utah State University and is recognized for his contributions to hydrology and environmental engineering.