Research Insights

Compound floods (CFs), a combination of hydrologic and coastal flood processes, are a worldwide phenomenon that affects coastal communities within a tropical cyclone’s (TC) path and low-lying urbanized landscapes prone to high tides and extreme rainfall events. CF assessments and their modeling tools have become widely available in recent years (mid-2010s) but have failed to understand the physical interaction between flood drivers, which can lead to better coupling techniques and modeling outputs, such as flood mitigation solutions (FMS). Furthermore, local knowledge (LK) and citizen science have been traditionally overlooked as only inputs in the FMS planning phase and not throughout the entire design process, resulting in a less salient solution for the community. Thus, there is a clear disconnection between CF modeling approaches, LK, and FMS. The overall objective of this project is to integrate and improve current flood modeling techniques with LK concepts to improve the interaction of flood drivers during CF events and include LK as an input variable. At the completion of the proposed research, we will develop a one-of-a-kind modeling framework capable of assessing CF holistically. Moreover, we will produce an adaptable methods handbook to guide future endeavors to include LK and citizen science in any flood modeling framework and co-develop FMS with stakeholders and community members. These outcomes are expected to have an important positive impact on the general flood science community and provide direct and immediate support to the impacted communities in an equitable manner.

Funder: NSF

Amount: $999,732

PI: Felix Santiago Collazo, College of Engineering