Surface-water flow and early-warning models

Last updated: August 2026

About

Surface-water flow links rainfall, topography, river networks, floods, and water availability. Early-warning systems often need to make predictions with incomplete observations and limited computational time. A physically based model can help interpret measurements, assess uncertainty, and anticipate the evolution of hazards.

This project will develop thin-shell approximations for surface-water flow and use observations to calibrate and evaluate early-warning models. It can address catchment-scale floods, inundation, water movement across complex terrain, or the connection between surface water and groundwater.

Research questions

• When do thin-shell flow models provide a useful approximation for catchment-scale water movement?
• Which observations improve model calibration and early warning most effectively?
• How can uncertainty in rainfall, topography, and model parameters be communicated in a prediction?

Methods and data

Projects can use topography, rainfall products, stream gauges, satellite observations, numerical flow models, data assimilation, and uncertainty quantification.

Possible projects

Possible directions include deriving and testing a thin-shell model, evaluating an early-warning workflow for a selected catchment, or coupling surface-water and groundwater models.

Essential background

Useful preparation includes hydrology, fluid mechanics, Earth science, engineering, mathematics, programming, or data analysis.