Year: 2026
Type: article
Abstract: Compound flooding threatens communities along the coastline of the Laurentian Great Lakes, where intense rainfall and high lake levels can occur simultaneously, creating large flood impacts. Understanding the extent and impact of these floods is important for planning and assessing risk in areas with vulnerable populations and infrastructure. To increase knowledge of Great Lakes compound flooding, this study develops and tests a coupled hydrodynamic-wave model for the Great Lakes, using Berrien County, Michigan and Milwaukee, Wisconsin as test cases. The model simulates a set of historical compound flood events that occurred during a period of high Lake Michigan levels. While hydrodynamic models offer important insights into flood risk, evaluating their performance is often challenging due to a lack of in situ data of flooding events. To overcome this challenge, this study incorporates location-specific feedback from local experts to guide model development and validate the modeled inundation. Data shared by these experts includes geolocated images taken during a flood event as well as feedback provided through public participatory GIS (PPGIS) that are used to qualitatively and quantitatively validate the compound flood model’s performance. This showcases useful techniques for flood model validation that can be applied to other data-scarce areas and events.
Source: Natural Hazards
Language: English
Subfield: Global and Planetary Change
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,990
OpenAlex ID: W7225622922