Author Type

Graduate Student

Date of Award

Summer 7-29-2026

Document Type

Thesis

Publication Status

Version of Record

Submission Date

August 2026

Department

Civil, Environmental and Geomatics Engineering

College Granting Degree

College of Engineering and Computer Science

Department Granting Degree

Civil, Environmental and Geomatics Engineering

Degree Name

Master of Science (MS)

Thesis/Dissertation Advisor [Chair]

Frederick Bloetscher

Abstract

This study evaluates PyWMP (Python-based Watershed Modeling and Planning), which is a flood modeling framework developed by the Center for Water Resiliency and Risk Reduction (CWR3) at Florida Atlantic University (FAU). The framework includes a 2D Rain-on-Mesh (ROM) solver, which is an explicit finite-volume shallow-water equation model. PyWMP is compared against HEC-RAS 2D and Flood Modeller for their rain-on-grid capabilities for watershed-scale flood inundation mapping under three design storm scenarios. The performance of PyWMP was evaluated using both quantitative and spatial metrics. Mean absolute error values showed that the average depth difference between each model is under 1 foot. Percent bias results indicate that both models consistently predicted higher flood depths than PyWMP. Spatial agreement improved for higher-magnitude storm events, with F1 scores showing greater than 80 percent overlap, indicating good agreement between models. This study shows that PyWMP provides a reliable and computationally efficient alternative for watershed-scale flood modeling.

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