1 Introduction
Enhancing global flood resilience is essential for mitigating the increasing impacts of extreme weather events and safeguarding vulnerable regions. Over the past few decades, rising rainfall and temperature extremes, combined with an increase in urban population and growing development and redevelopment in flood-prone urban areas, has significantly diminished human capacity to manage floods (
Liu et al., 2022;
Mijic et al., 2022). Urban rainwater management has emerged as a critical challenge for numerous cities, particularly in sprawling urban centers (
Pappalardo et al., 2017;
Butler, 2019). Moreover, conventional urban drainage systems frequently prove inadequate in handling stormwater runoff, particularly during escalating extreme weather events (
Chen et al., 2016;
Alamdari, 2018). More than 1500 documented catastrophic flood events occurred worldwide from 2010 to 2020, resulting in overall damages costing USD 363 billion (
IFRC, 2018;
Hamers et al., 2023). Floods stand out as one of the most economically burdensome natural disasters, and multi-hazard events (e.g., flooding, landslides, and impacts to agriculture, water supply, and human health) are common, inducing greater losses than just a single disaster. As with other multi-hazard events, dry-wet scenarios pose greater threats to environmental and human systems compared to single extreme events. The sustainability and resilience of floodplains depend on many factors, including natural balance, biodiversity conservation, agricultural productivity, and protection against desertification, all of which contribute to the overall sustainability and resilience of the region.
Challenges such as heat stress, food insecurity, energy instability, declining air quality, water scarcity and contamination, flooding, and sea level rise are affecting even the most remote regions (
Wuebbles et al., 2010,
2021). However, these issues are significantly exacerbated in urban areas, where dense populations often face compounded implications in health, economic opportunity, and political equity. Recent events have highlighted the vulnerability of the Midwest US region to flooding. The 2019 Midwest flooding had far-reaching effects on nine states: Illinois, Iowa, Kansas, Minnesota, Missouri, Nebraska, North Dakota, South Dakota, and Wisconsin (
Wuebbles et al., 2010). The impact included widespread utility outages, property damage, and residential evacuations. Iowa and Nebraska, in particular, faced significant challenges. Governor Reynolds of Iowa reported damages exceeding USD 1.6 billion (
Zaimes et al., 2021), while Nebraska experienced over USD 1.3 billion in infrastructure and property damage (
Kraft et al., 2023), comparable to the damages incurred during the 2008 and 1993 Midwest floods. The overall estimated damage reached approximately USD 10.7 billion (
Smith and Katz, 2013). While these figures provide rough estimates of damage to public property, there is limited information available regarding the direct economic impacts of the 2019 flood on households and individuals, suggesting additional losses occurred during this event. Urban flood risk is an increasing concern for cities worldwide as rainfall events intensify and urbanization continues to escalate. While Nature-based Solutions (NbS) have been identified as effective flood mitigation strategies, their implementation is often hindered by a lack of scientifically rigorous evaluation and clear guidelines for their application. The existing literature on NbS fails to provide comprehensive, context-specific frameworks for evaluating and selecting appropriate NbS in different urban settings. This study seeks to bridge this gap by applying a SWMM-HEC-based model to evaluate the effectiveness of NbS in flood mitigation for the Quad Cities Metro Area (QCMA), including Davenport, Bettendorf, Moline, and Rock Island. Despite the growing body of research, there remains insufficient detail in the scientific community on how to optimize NbS for urban areas prone to flooding.
1.1 Motivation
The efficacy of NbS in urban areas has primarily been evaluated on smaller, localized scales, such as street blocks or small suburbs (
Kim and Park, 2016;
Wadhwa and Pavan Kumar, 2020;
Wadhwa and Kummamuru, 2021). Previous studies have concentrated primarily on detailed modeling of individual NbS schemes at specific locations, examining their effectiveness under various rainfall scenarios (
Ruangpan et al., 2020;
Hamers et al., 2023). However, the application of NbS at larger scales—combining different NbS (e.g., green roofs, swales, rain gardens, retention basins, wetlands) across an extended urban/suburban area or a flood plain has been largely unexplored. Despite the potential benefits in terms of increased adaptability, amenity, and decreased economic impacts, the role of NbS as alternative to conventional measures (so-called “gray infrastructure”) remains underexplored at larger spatial scales (
Fastenrath et al., 2020). In the US, the focus on utilizing ecosystem services for NbS is progressing, and funding agencies like FEMA have adopted formal policies that encourage incorporating NbS benefits into benefit-cost analysis (FEMA, Hazard Mitigation Assistance Division Fact Sheet, 2021).
To bridge these gaps, this study provides insights by identifying the most optimal NbS for the QCMA. We employed an integrated modeling framework to visualize flood inundation over the Quad Cities for past flood events. One potential approach to mitigating long-term losses from flood disasters involves mapping flood-prone areas to raise risk awareness and promote sustainable land-use planning, floodplain management, and urban development. In this context, fine-scale hydrological modeling is a valuable tool for assessing alterations in regional processes resulting from changes in land-use features within an urban catchment. Overall, we propose three tasks: a) extract rainfall data from the relevant sources for the QCMA; b) develop a baseline flood inundation map using coupled SWMM + HEC RAS for overland flooding; c) identify the most optimal combination of NbS to reduce spatial extent of floods over the QCMA. The effectiveness of the proposed approach is evaluated through the computation of surface runoff reduction and improvement in infiltration efficiency across the study domain.
1.2 Potential QCMA regions impacted due to flood events
Several natural features in the region offer significant opportunities to build urban resilience. Wetlands, floodplains, forests, rivers, creeks, and open green spaces provide essential protective services by slowing runoff, increasing floodplain water storage capacity, enhancing surface water infiltration, improving water quality, and reducing the urban heat island effect, all while sequestering carbon dioxide. Recent studies highlight the region’s diverse land cover, including croplands, grasslands, forests, and emergent wetlands surrounding water bodies. Beyond their hazard risk reduction benefits, these natural features improve the overall quality of life and human health (
Santiago Fink, 2016), promote biodiversity (
Xie and Bulkeley, 2020), offer recreational opportunities (
Kabisch et al., 2016), and connect people with nature (
Frantzeskaki, 2019), fostering environmental stewardship. Many of these features are preserved and managed through nature preserves, state parks, and local parks, such as Nahant Marsh, Illiniwek Forest Preserve, Rock Island Forest Preserve, Black Hawk State Park, Vander Veer Botanical Park, and Duck Creek Park. Nahant Marsh, for example, acts as a massive urban floodwater sponge, filtering up to 2 billion gallons of water during peak flows on the Mississippi River (Scientific American, 2019). Additionally, it serves as an educational center and recreational site, contributing to tourism and local revenue. In 2023, over 6 million visitors to the Quad Cities generated USD 1.3 billion in revenue and employed nearly 10000 residents, underscoring the economic benefits of preserving these natural features.
1.3 Existing flood mitigation initiatives in QCMA
Flooding and flood-related damage regularly affect Quad Cities communities in the Mississippi River watershed. While flood issues may be complex and seem difficult to resolve, there are technical resources and programs available to help solve and mitigate flood-related problems. FEMA, National Flood Insurance Program (NFIP), Homeland Security, the Insurance Service Office, Iowa or Illinois Emergency Management Agencies, and Iowa or Illinois Department of Natural Resources each have resources to help us deal with the post-flood challenges at hand and to help us prevent flood damages in the future. Existing efforts for flood protection and mitigation in the QCMA region include road raises, street repairs, traffic safety improvements, flood resiliency planning, installation and maintenance of permanent and/or temporary flood risk measures, creating awareness and educating the public, and many more. QCMA region is protected by levees, culverts, water-resistant HESCO barriers (boxes made of metal netting covered with fabric), 800-foot-long floodwall, wetlands, green spaces, and so on. The region also has a permanent floodwall (in Modern Woodmen Park tested for high crests), three flood protection reservoirs in Des Moines areas with two dry reservoirs in Peoria and a temporary flood control barrier system put in place with a vision to protect the region if the water is 5.64 m (18.5 ft) or below. A detailed flood resiliency alliance, Quad Cities Flood Resiliency Alliance (QCFRA), is formed in the QCMA region, which helps to bring local governments, emergency management, public works personnel, and other river stakeholders together as a single unit to prepare for and recover from floods, and take actions to reduce flood insurance costs for residential and commercial property owners. Davenport was also awarded a USD 13.1 million Federal Highway Administration (FHWA) grant in April 2024 to perform street repairs, road raises, and traffic safety improvements. Aforementioned measures are converted into raster format and are ingested in HEC-RAS model as a base terrain layer and the model is further validated with the FEMA flood maps and crowdsourcing data.
2 Study area
Quad Cities Metro Area (QCMA), as shown in Fig.1, is already contending with extreme weather phenomena, notably a rise in heatwaves, as evidenced by a 37% increase in extreme heat episodes since the 1950s. Additionally, the region has experienced significant alterations in winter conditions and precipitation patterns, with historic flood occurrences recorded in 1993, 2008, 2014, 2019, and 2023. These manifestations are poised to exacerbate in tandem with escalating global temperatures. Rigorous scientific evaluations underscore a series of imminent risks, such as a projected 50% escalation in heavy precipitation events and a heightened susceptibility to riverine flood damages across the Midwest (
Wilson et al., 2023). The climate of QCMA is seasonally variable, with significant rainfall occurring during the summer, making the area prone to floods due to its landscape characteristics and summer precipitation. Analyses indicate a consistent uptick in spring precipitation levels since 1990, which has improved soil moisture levels but also led to temporal delays in spring planting schedules, with projections indicating further amplifications. Moreover, the region anticipates a surge in both the frequency and intensity of extreme weather events, including a forecasted 40% increase in heavy downpour episodes, exacerbating the dual threats of flooding and drought occurrences. Despite these vulnerabilities, QCMA boasts natural assets, including various water retaining measures comprising creeks, forests, wetlands, and prairies. These features harbor immense potential for enhancing regional resilience, providing habitats for wildlife, catalyzing tourism activities, and serving as invaluable educational resources.
2.1 Data sets used in the study
2.1.1 Rainfall data sets
Daily rainfall data sets for the study period (1983−2023) are obtained from the NOAA Climate Data Online (CDO) repository, EXNET (available at ExNET website), HADS (available at NOAA website), IFC (available at IFC website), and WeatherSpark (available at WeatherSpark website) data portal for QCMA. These data sets are used to identify the maximum rainfall depth observed during flood events in QCMA. The maximum for each event and the flood depth observed during these events from both observed and model outputs are extracted for demonstration and are discussed later in detail. A total of 12 rain gauges are used in the study, and the Thiessen polygon method is employed to assess the impact of these rain gauges across the region
2.1.2 Discharge data sets
Daily discharge and water depth values from stream gage stations 05448000, 05420500, 05422470, 05446500, and 05447500 are extracted from the USGS data repository for model calibration (1983−2004) and validation (2005−2020). For the flood events listed in Tab.1, maximum water depth values from the USGS data repository and model outputs are extracted and analyzed against the corresponding rainfall depths during those periods. This provides an overview of the variation in flood levels relative to rainfall in the region. Additionally, stream sensor data from the Iowa Flood Information System Center (IFIS) portal is used to generate flow data for the streams.
2.1.3 Geomorphological and topographical data sets
Topographical and geomorphological data sets used for model development, along with their sources and resolutions, are detailed in Tab.2. All data sets are first converted into raster format. The NLCD land cover data sets (as shown in Fig.2), GLOBUS building data sets, and WSIO indicator data are overlaid with a 1 m DEM to form a single raster. These overlaid products are further validated using the Google Earth database by selecting a few training data sets and performing visual interpretation. This combined raster is then used as an input to the flood model for 1D-2D routing.
2.2 Proposed framework for flood model development
To develop an integrated model for the QCMA, first a watershed delineation using a Digital Terrain Model (DTM) that includes a 1 m DEM overlaid with building heights from GLObal Building heights for Urban Studies (GLOBUS) and National Land Cover Data set (NLCD) percentage imperviousness data sets were developed. Most of the outlets were considered to be stream gage stations in and around the region. The stream order of three and one outlet per sub-catchment was broadly assumed for modeling.
Using inp.PINS, 328 delineated sub-catchments in QCMA, including neighborhoods, inlets, outlets, and conduits, were exported in a format readable by the Storm Water Management Model (SWMM). NLCD land use data overlaid with GLOBUS data, wetlands data from the US Fish and Wildlife Service (USFWS), hydraulic structures from the National Hydrography Data set, groundwater data from the National Water Portal, and other hydrological data sets (with spatial and temporal resolutions mentioned in Tab.2) were used to generate sub-catchment properties, storage-discharge curves for storage nodes, and hydraulic properties of the drainage network. Daily rainfall data from 12 rain gages were assigned to each sub-catchment in SWMM based on the area covered by Thiessen polygons. The duration of the rain gages used in the model was 24 h, and the model was set to run for a period of 40 years (1983−2023).
The infiltration method used in the model was the SCS Curve Number (CN) method, and the routing method used was kinematic wave routing. Ponding was allowed while running the SWMM model. Input parameters such as area, width, percentage slope, length of conduits, latitude and longitude of all elements, and outlets were directly added to the model using INPPINS. Other parameters like Manning’s coefficient for pervious and impervious regions, percentage imperviousness, storage curves for different hydraulic elements, and curve numbers were obtained from the overlaid raster file. Default values were used for the depth of depression storage, conductivity, and drying time of sub-catchments. NbS (also known as LID controls in SWMM) are identified using land distribution, and the input parameters mentioned in Tab.3 for NbS are further ingested in SWMM. With a daily time step and ponding allowed, the model was simulated to generate flow curves for all elements. These flow curves at the USGS stream gauge locations were compared with the daily observed discharge data from 1983 to 2023. The model showed a fair comparison, and with the statistical performance indicators shown in Tab.4, the model was classified as demonstrating “acceptable levels of performance” and as a “well-interpreted model.”
The flow curves were further ingested into the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) model as unsteady boundary conditions at each junction. The DTM was used as a base layer in the HEC-RAS model, with the locations of junctions/outlets specified as boundary conditions. The study area was converted into computational cells with a 1 m cell size around the region and 10 m inside the open spaces and river profile. Break lines were added at the boundary of the study area with a depth-to-discharge relation set to zero. This was done to avoid congestion of flow at the boundaries and to allow the free flow of water outside the region. HEC-RAS was then used to route the flow for the same period as the boundary conditions.
In summary, the framework of workflow of integrating a 1D hydrological model (SWMM) and a hydrodynamic model (HEC-RAS) along with associated data sets is shown in Fig.3. The SWMM model was developed over urban regions to generate runoff from impervious surfaces in response to environmental variables, and the HEC-RAS model was used to route unsteady flow and generate flood inundation maps. The junction/outlet locations in SWMM were replicated in HEC-RAS as boundary condition locations. Further, flow hydrographs, stage hydrographs, normal depth, and rating curves were extracted from SWMM for the boundary condition locations. Flow hydrographs and lateral inflows to the junctions/outlets were provided as unsteady flow inputs to HEC-RAS at the respective locations.
To reduce complexity and make the model globally replicable, several assumptions were made in the proposed framework.
a) Runoff generated from the entire catchment is conveyed through the outlet junction of each catchment to the adjacent drainage system. If the drainage capacity is exceeded, the water starts overflowing, resulting in inundation.
b) A grid size of 1 m was used for urban regions and 10 m for large green/open spaces and the Mississippi River cross-section. The grid size was manually adjusted for excess regions to solve grid size errors.
c) A free flow normal depth condition is assigned as the outer boundary condition for the study area to allow unimpeded water flow toward downstream sections.
The proposed model was validated for flood events, with the depth comparison shown in Fig.4 and visual validation from the Iowa Flood Information System (IFIS) model in Fig.5. The model outcomes were also compared with IFIS flood risk maps for a 1% annual chance (100-year) rainfall event. Performance statistics are shown in Tab.4, and a visual comparison is shown in Fig.5.
2.3 Identification of historical flood events in Quad Cities
The flood database developed by
Li et al. (2021), which includes flood events across the US from 1985 to 2020, along with information from crowdsourced data, was used to extract reliable flood information for the study area. The corresponding list of flood events, maximum rainfall depths, and information about the major regions affected during each flood event are detailed in Tab.2. These flood events were simulated using the proposed modeling framework, and the generated flood maps were validated with crowdsourced information (
Helmrich et al., 2021).
2.4 Identification of potential areas to implement NbS
Choosing the most suitable NbS for a specific location depends on its morpho-structural characteristics and land use. Therefore, assessing the technical feasibility constraints for NbS implementation is a crucial stage of this study. We reclassified the land use maps from NLCD overlaid with GLOBUS building height data sets, considering a range of criteria including terrain slope, groundwater level, soil hydrological type, infiltration rate, distance from existing foundations, and other specific requirements such as width, length, and area needed for NbS implementation (
Alves et al., 2024). The constraints and design dimensions outlined by (
Xie and Bulkeley, 2020;
Alves et al., 2024) were used in this study to identify the layer-wise dimensions of NbS and the total area required for their implementation. Details are provided in Tab.3, and the potential locations for NbS are shown in Fig.6.
2.4.1 Choice of hybrid NbS for evaluation in the study
To assess the feasibility of implementing a range of NbS, the proposed flood model framework was used to virtually implement NbS and observe changes in flow dynamics in the QCMA region. The NbS chosen for this study, each offering unique ecosystem services, and include green roofs, rain gardens, infiltration trenches, permeable pavements, vegetative swales, dry detention basins, retention ponds, and rain barrels and cisterns.
The SWMM user interface characterizes the connections between sub-catchments, hydraulic nodes and conduits, NbS, and other conveyance systems in a simplified view, aiding in parameterization and reducing the risk of mismanaging runoff flow (
Wadhwa and Pavan Kumar, 2020). The SWMM LID-control option was used to simulate different combinations of NbS in the QCMA region. The input parameters for the NbS were collected based on previous studies in regions with similar topography (
Santiago Fink, 2016;
Xie and Bulkeley, 2020;
Kumar et al., 2021). The design dimensions of the NbS were further determined based on area availability (obtained from overlaid maps discussed earlier), soil properties (obtained from the Soil Survey Geographic Database (SSURGO) database), and their performance for a 5-year design return period. The performance of the NbS was evaluated using five efficiency measures (
Marchi et al., 2016;
Sørup et al., 2016;
Wadhwa and Pavan Kumar, 2020;
Wadhwa et al., 2023): volumetric efficiency (
Efp) and runoff reduction efficiency (
Er). These efficiency metrics relate the individual volumes to key aggregated annual water flows.
3 Results and discussion
3.1 Proposed flood model outcomes
Discharge data sets from the SWMM model are extracted at the locations of USGS stream gauge stations and calibrated against observed data for the period 1983−2005 by adjusting sub-catchment properties. The statistical performance of the model at each station is detailed in Tab.4. Calibration results indicate a Nash-Sutcliffe Efficiency (NSE) score of ~0.68, which meets the threshold for acceptable model performance (
Moriasi et al., 2007). Validation results further support the model’s robustness, showing an RMSE of 0.043 m (0.14 ft) and a correlation coefficient of 0.84 between simulated and observed discharge values.
Following calibration, the SWMM model is validated using daily discharge values compared against USGS stream gauge stations. The discharge or lateral flow values from SWMM at each junction are inputted into the HEC-RAS model as unsteady boundary conditions covering the period from 1983 to 2023. The HEC-RAS model is then run daily to generate depth and velocity profiles for the QCMA region. Flood extents produced by the integrated model were visually validated against existing FEMA flood maps for a 100-year return period event. A strong spatial correlation between the FEMA flood maps and the model results underscores its reliability.
A total of 180 sampling points were randomly selected from flood maps provided by FEMA and from the integrated model proposed in this study. Statistical comparisons between the data sets (RMSE: 0.0426 m (0.14 ft), NSE: ~0.68) confirm the reliability of the model for flood depth estimation and propagation analysis. The comparison demonstrates a strong correlation (correlation coefficient of 0.84) with daily discharge values compared to the USGS station data set. The flood inundation maps for major flood events in the QCMA region are depicted in Fig.7. These maps illustrate widespread flooding due to heavy rainfall events during major flood events. Time-series flood depths from these inundation maps at stream gauge locations are extracted and compared with observed stage values. The comparison of maximum water depths observed in the QCMA region is summarized in Tab.5.
3.2 Feedback from the flood inundation maps for different regions
Flood model simulation results show that the regions near the Mississippi River are highly susceptible to flooding, exacerbated by impervious runoff from urban areas. The model outputs reveal that urban areas adjacent to the Mississippi River could experience runoff depths of up to 3.35 m (11 ft). Significant impacts are observed downstream, particularly near landmarks such as the Centennial Bridge, Modern Woodmen Park, Credit Island, and Sunset Park. Hydrological model findings indicate that this area faces variable and frequent discharge events, worsened by urbanization and changes in land use that reduce infiltration capacity.
QCMA region is predominantly affected by discharge from upstream and the discharge generated within its own urban catchment. Historical data shows that downstream sections of the QCMA experience high discharge peaks roughly every decade. Recent Flood Risk Profiles (FRPs) from NOAA, Illinoisfloodmaps.org, FEMA, and other agencies indicate a 26% likelihood of severe flooding events in the QCMA region, warranting urgent attention. The flood model predicts that peak runoff in the QCMA can be significantly mitigated by implementing vegetative swales, infiltration trenches, and green roofs/rooftops.
The QCMA consists of medium to low-intensity built-up areas interspersed with patches of woody wetlands across the river basin. Local authorities advise residents to stay informed through local news, radio, and television for flood warnings, and prepare with basic measures such as sandbags to protect their homes and businesses. Observations from the flood model underscore the area’s vulnerability to upstream discharges and periodic rainfall, exacerbated by population growth and land use changes that diminish infiltration space.
To provide robust flood mitigation solutions, the next section discusses the implementation of NbS across various regions of the QCMA (refer to Fig.6). These NbS are carefully designed and analyzed for their effectiveness in mitigating flood events, considering specific efficiencies tailored to each flood scenario.
3.3 Feedback from the flood inundation maps for different regions
Flood model simulation results show that the regions near the Mississippi River are highly susceptible to flooding, exacerbated by impervious runoff from urban areas. The model outputs indicate significant vulnerability to urban runoff depths of up to 3.35 m (11 ft) in areas adjacent to the river, such as Centennial Bridge, Modern Woodmen Park, Credit Island, and Sunset Park. Historical flood peaks in the QCMA confirm a recurring pattern of high discharge every decade, further validated by NOAA and FEMA flood risk profiles.
QCMA is predominantly affected by upstream discharges and urban catchment-generated runoff. Historical data shows that downstream sections of the QCMA experience high discharge peaks roughly every decade. Recent Flood Risk Profiles (FRPs) from NOAA, Illinoisfloodmaps.org, FEMA, and other agencies indicate a 26% likelihood of severe flooding events in the QCMA region, warranting urgent attention. The proposed flood model identifies the critical impact of urbanization and land-use changes on flood risks, reducing infiltration capacity and amplifying runoff during extreme events.
The flood model predicts that peak runoff in the QCMA can be significantly mitigated by implementing vegetative swales, infiltration trenches, and green roofs/rooftops. Observations from the flood model underscore the area’s vulnerability to upstream discharges and periodic rainfall, exacerbated by population growth and land-use changes that diminish infiltration space. These findings align with studies in urban settings, such as the Netherlands (
van der Nat et al., 2016) and Melbourne, Australia (
Rahman et al., 2012), where NbS have demonstrated similar flood attenuation efficiencies.
3.4 Flood propagation after implementation of NbS
The rising levels of the Mississippi River in the QCMA region (
Pinter et al., 2008;
Tao et al., 2014;
Criss and Luo, 2017;
Hiatt et al., 2019) make it susceptible to periodic flooding. To address these challenges, this study explores NbS as effective mitigation strategies. These are categorized into structural solutions—such as enhancing creeks, headwater streams, flood walls, and wooded trails—and non-structural solutions, including preserving areas like Maquoketa Caves (state parks) and Nahant Marsh (urban wetlands), creating prairies, green parks, and equitable urban spaces. The results demonstrate that integrating structural and non-structural NbS can significantly mitigate flood risks, emphasizing the importance of combining natural and engineered approaches to enhance flood resilience in urban areas.
For example, in Davenport, combinational strategies such as vegetative swales and green roofs have proven effective for flood attenuation. This combination demonstrates significant average performance efficiencies, with runoff reduction efficiency (Er) at 14% and volumetric efficiency (Efp) at 16% for daily rainfall during each flood event. Note, the efficiencies for each flood event are shown in Tab.5. Flood inundation maps show that flood levels in urban areas of Davenport decreased from 6.4 m (21 ft) to 3.96 m (13 ft) after implementing the proposed NbS (see Fig.7 and Fig.8 inundation maps with and without implementation of NbS). Consequently, Davenport would benefit from being bounded by flood walls for extreme cases, along with adopting a combination of NbS such as marshes, green spaces, open parks, and gardens to benefit both authorities and the general public.
In Bettendorf, vegetative swales (e.g., green spaces, nahant marsh (urban wetland), open fields) proved effective in reducing peak runoff and improving infiltration potential. Bioretention basins or infiltration trenches, combined with vegetative swales and permeable pavement, achieved efficiencies of Er at 19% (for instance, flood event of 1965 showed that the peak runoff is decreased from 6.27 m (20.57 ft) to 5.08 m (16.66 ft), Tab.5) and Efp at 14% (for peak flood event of 1965, the infiltration depth is increased by ~1.22 m (4 ft)). Flood maps indicate that the flood levels in Bettendorf are decreasing, and certain areas might avoid flooding if the proposed NbS are implemented. Similarly, in Rock Island, vegetative swales, green roofs, and infiltration trenches demonstrated high effectiveness, with efficiencies of Er at 38% and Efp at 19%. Implementing NbS in upstream regions and in Rock Island significantly reduced flood levels from 3.66 m (12 ft) to 2.74 m (9 ft) (see Fig.7 and Fig.8 inundation maps of with and without implementation of NbS). In East Moline, measures such as vegetative swales and green roofs were found to be the most effective. The efficacy of these measures was further enhanced through combination strategies to reduce flood extents, achieving an Efp of 16% and an Er of 30%. Significant reductions in flood depths were observed in urban areas of Moline after implementing the proposed NbS measures.
These findings align with global studies on the effectiveness of NbS. For instance, in the Netherlands, van der Nat et al. (2016) demonstrated that constructed wetlands and floodplain restorations reduced peak flood depths by up to 30% during extreme rainfall events, comparable to reductions of 37% in Davenport and 30% in East Moline in this study. In Australia,
Rahman et al. (2012) found that green roofs and permeable pavements in Melbourne attenuated peak runoff by 20%−25% during a 50-year return period, whereas the QCMA region achieved greater reductions, up to 37% during a 100-year return period, due to combined NbS measures like vegetative swales and green roofs. Similarly,
Everard and Moggridge (2012) reported a 28% runoff reduction in Birmingham, England, through floodplain reconnection and riparian buffer zones, consistent with the QCMA reductions of 19%−37%. Within the United States,
Grove et al. (2015) observed a 15% reduction in peak flow in Baltimore, though the QCMA outperformed this due to the larger scale and integration of multiple NbS, including green roofs and infiltration trenches.
This study contributes to existing literature by demonstrating the synergistic effects of multiple NbS interventions in urban areas. Unlike previous studies that often focus on single interventions, the findings emphasize the scalability and effectiveness of integrated NbS in flood-prone, highly urbanized settings like QCMA. Furthermore, the study highlights the limitations of NbS in areas with high imperviousness, contributing to ongoing discussions on urban flood resilience. With Mississippi River levels reaching historic lows (
CNN, 2023) due to reduced rainfall and increased urbanization, these NbS provide dual benefits by mitigating flood risks during extreme rainfall events and improving water availability during drought conditions. The implementation of these solutions across QCMA is therefore strongly recommended to address both present and future water management challenges.
4 Conclusions
The increased occurrences of urban flooding due to extreme precipitation events are becoming more common. Many cities face challenges as their current urban drainage systems prove inadequate in addressing pluvial floods caused by expanding impervious areas. To tackle this issue, NbS has gained popularity in recent years. These solutions, when combined with traditional gray infrastructure, effectively manage urban flooding. However, challenges persist in mitigating extreme rainfall events. The flood model developed in this study, simulated with daily rainfall data from 1983 to 2022, showed an RMSE of 0.043 m (0.14 ft) and an NSE of ~0.68. The model was further simulated to generate the discharge at stream gage stations. The validated flood model was then used to create flood inundation maps with daily precipitation values. Eight types of NbS were considered: bio-retention tanks, rain gardens, green roofs, infiltration trenches, permeable pavement, rain barrels, rooftop disconnection, and vegetative swales. The hydrological mechanisms of these NbS were analyzed for their effectiveness in reducing runoff volumes, attenuating flood peaks, and improving infiltration capacity. The flood model outputs recommend that authorities implement measures such as Nahant Marsh, equitable and accessible green spaces and recreation areas (parks, sports fields, playgrounds), Milan Bottoms, and open parks. In line with Rock Island County guidelines (available at Rock Island County website), additional green spaces and open parks should be increased, and prior evacuation strategies need to be prepared. Existing flood protection measures, such as buffer zones and flood walls, should be enhanced with NbS, like wetlands, grassed swales, and vegetative filter strips, to effectively reduce flooding in the region. The results also emphasize that NbS alone may not offer a panacea for flood risk reduction in the QCMA. A hybrid approach combining NbS with traditional structural measures (e.g., levees, detention basins, and reinforced drainage systems) is likely necessary to achieve the desired flood risk reduction in the region. With the proposed NbS combinations, the study demonstrated the following average reductions in peak flood levels for flood events between 1983 and 2023: 1.68 m (5.52 ft) (25%) in Rock Island, 1.24 m (4.07 ft) (18%) in Davenport, 1.19 m (3.91 ft) (19%) in Bettendorf, and 1.42 m (4.65 ft) (21%) in Moline and East Moline. Similarly, increases in infiltration capacity were observed as follows: 1.10 m (3.62 ft) (19%) in Rock Island, 1.05 m (3.43 ft) (17%) in Davenport, 0.97 m (3.17 ft) (15%) in Bettendorf, and 1 m (3.28 ft) (16%) in Moline and East Moline. This indicates that the proposed combination will be capable of reducing flood inundation in the QCMA region. However, practical implementation and real-time performance assessment are crucial for validating this study.
In conclusion, this study contributes to the growing body of literature advocating for the integration of NbS into urban flood management strategies but also calls for a more nuanced understanding of their limitations and a comprehensive approach that considers both natural and engineered systems. Future research should focus on optimizing the design, scalability, and long-term performance of NbS in urban environments, particularly in flood-prone regions like QCMA. Additionally, real-time monitoring and adaptive management strategies are needed to ensure the sustainability of NbS solutions for evolving urban geographies.
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