Application of 1D HEC-RAS to Investigate Nature-Based Infrastructures (NBI) for Flood Mitigation along the Neosho River near Miami, Oklahoma

Abstract

Riverine flooding has been shown to cause damage to civil infrastructure, disrupt business operations and public services within cities, which can result in substantial economic losses. Cities that are located near larger rivers, such as the City of Miami along the Neosho River – the study area for this work, can be impacted significantly by flooding events. Nature-Based Infrastructure (NBI) can be utilized as a method for reducing flooding extents from rivers; however, many previous studies have focused on small watersheds. The Neosho River resides in a larger watershed and captures a different magnitude and volume of streamflow than the smaller watersheds, thus they pose different challenges in using NBI. Research done in this thesis will explore different NBI options via a calibrated hydraulic model within the Neosho River watershed with a focus on the effects in the City of Miami. To evaluate different NBIs for this larger watershed, a one-dimensional HEC-RAS model was developed for the study area within Oklahoma. The model was calibrated and validated across the different seasonal variations with events that spanned the years of 2009 to 2024. Once the model was calibrated and validated, three NBI implementations were then tested to evaluate whether nature-based measures such as vegetation enhancements and managed wetland storage could meaningfully reduce the peak water surface elevations (WSE) in the City of Miami and the flooding extents along the river. Examination of the NBIs occurred using three scenarios: moderate (2009), high (2017) and extreme (2019) storm events. For the vegetation enhancements, NBIs such as Targeted Afforestation (TA) and Floodplain Afforestation Enhancements (FAE) were examined. The TA method targets changing the agricultural-based areas to forested or shrub-dominated areas along the river, while the FAE method changes all the overbank areas of the river to either the forested or shrub-dominated areas or a forested and woody wetland landscape. Results from these NBI enhancements showed that even under the most intensive afforestation case the maximum WSE reductions were only seen with the high storm event (e.g.,0.16 ft for the 2017 event). An additional NBI was examined to determine if managed wetland storage ponds could provide a reduction in inundation extents and peak WSE in Miami. These managed wetland storage ponds were examined across various volumes , which spanned 5,000 -100,000 acre-ft across four different representative locations along the river. Significant changes can be seen with the largest managed wetland storage pond scenario with reductions in the peak WSE in Miami for the different storm events (e.g., 0.7 ft below, 1.36 ft above, and 7.19 ft above the peak WSE in Miami for the 2009, 2017, and 2019 events, respectively). Because these NBI mechanisms alone did not consistently reduce the flooding within the Neosho River, a Magnitude-Adaptive Design Flood Hydrograph framework spanning different return periods was developed and incorporated into the HEC-RAS 1D model. This was done to estimate the upstream inflow reduction needed to decrease the peak WSE and flooding inundations within the Miami area. Results show that this reduction is roughly 20% for the 5-year event, 40% for the 10-year event, 65% for the 50-year event, and at least 70% for the 100-year event. Overall, the vegetation-based NBI alone produced negligible reductions, while the managed wetland storage required extremely large volumes to bring the peak WSE in Miami for both moderate and extreme storm events, so meaningful reduction at Miami will ultimately depend on pairing NBI with other mitigation techniques at the watershed scale. Since most of the Grand Lake watershed lies in Kansas, achieving this level of reduction would require trans-boundary coordination of NBIs, such as wetlands, vegetation restoration, floodplain lowering, and natural flood diversion measures.