An integrated modelling approach to evaluate the impacts of nature-based solutions of flood mitigation across a small watershed in the southeast United States

Abstract

Abstract. Floods are among the most destructive natural hazards in the world, posing numerous risks to societies and economies globally. Accurately understanding and modeling floods driven by extreme rainfall events has long been a challenging task in the domains of hydrologic science and engineering. Unusual catchment responses to flooding cause great difficulty in predicting the variability and magnitude of floods, as well as proposing solutions to manage large volumes of overland flow. The usage of Nature-Based Solutions (NBS) has proved to be effective in the mitigation of flood peak rate and volume in urban or coastal areas, yet it is still not widely implemented due to limited knowledge and testing compared to traditional engineering solutions. This research examined an integrated hydrological and hydraulic modeling system to understand the response of an at-risk watershed system to flooding and evaluate the efficacy of NBS measures. Using the Hydrologic Engineering Center Hydrologic Modeling System and River Analysis System (HEC-HMS and HEC-RAS) software, an integrated hydrologic-hydraulic model was developed for Hurricanes Matthew (2016) and Florence (2018) driven floods across the Little Pee Dee-Lumber Rivers watershed, North and South Carolina (the Carolinas), USA. The focus was on Nichols town, a small town that has been disproportionately impacted by flooding during these two hurricane events. Different NBS measures including flood storage ponds, riparian reforestation, and afforestation in croplands were designed, modeled, and evaluated. Hurricane Matthew's flooding event was used for evaluating the NBS scenarios given its high simulation accuracy in flood inundation compared to the less accurate results obtained for Hurricane Florence. The scenario comparison evidenced that large-scale natural interventions, such as afforestation in croplands, can reduce the inundated area in Nichols town by 8 % to 18 %. On the contrary, the smaller-scale interventions such as riparian reforestation and flood storage ponds showed a negligible effect of only 1 % on flood mitigation.

Quantitative Assessment of Future Land Use Changes' Impact on Flood Risk Components: Integration of Remote Sensing, Machine Learning, and Hydraulic Modeling

“…Adnan et al, 2020 assessed flood damages through the analysis of diverse flood recurrence intervals and LULC change scenarios; an increase in flood damages corresponding to shifts in both recurrence intervals and LULC scenarios was revealed. Guido et al, 2023 analyzed the potential impacts of flood events and identified vulnerable areas by considering the influence of LULC changes through hydraulic modeling (HEC-RAS) and geospatial analysis in a small watershed in the southeast United States. Previous studies have made valuable contributions to assessing hazards, vulnerabilities, and flood consequences under LULC changes (Mind'je et al, 2019).…”