Community-informed flood risk modeling for climate adaptation in Waihe'e - Waiehu, Maui

Abstract

Flash flooding over the decades has repeatedly affected the community of Waiheʻe–Waiehu, Maui, damaging homes, farms, and periodically closing the area’s only access road. To improve community resilience amid increasing flood risks, this study developed high-resolution (10 m) flood maps for Waiheʻe–Waiehu by integrating local knowledge with physics-based modeling techniques. To accomplish this, Gridded Surface Subsurface Hydrological Analysis (GSSHA) models were developed in the Kalepa Gulch and Waiehu stream watersheds. Publicly available data, including a digital elevation model, a land use map, Manning's roughness coefficients, and precipitation data, were used to produce 2D flood models for a hypothetical 100-year precipitation event and a 2018 flood event. High-resolution physics-based GSSHA flood models show greater inundation under a hypothetical 100-year rainfall event than a 1 in 5-year storm that occurred on February 18, 2018. Results help identify flood-prone areas that are not fully represented in FEMA hazard maps, and demonstrate that community input improves the interpretation and evaluation of modeled flood patterns in Waiheʻe–Waiehu. Conversations with community members also helped identify areas of model overprediction and underprediction, resulting in a modeling project rooted in community-informed practices, strengthening the accuracy of the model itself and bridging gaps between science and the local community directly impacted.