Flood risk analysis is the instrument for local officials to create a sound strategy and adaptation plans for the impacts of inundation due to heavy rains, climate change and sea level rise. Hence, cities with aging infrastructure are retrofitting their stormwater management systems to mitigate the impacts. However determining the most at risk areas and the options for corrections is more challenging. As a result, there is an urgent need to develop a screening tool to analyze watersheds and identify the most at-risk areas. High-quality, open source data and sophisticated spatial analysis techniques allow engineers to create innovative ways to conduct watershed wide inundation analysis. In th is study, the investigators developed a screening tool to identify at-ri sk properties by combining readily available data on topography, groundwater, surface water, tidal information for coastal communities, soils, open space, and rainfall data. Once the screening tool is developed, the means to identify and prioritize improvements to be funded with scarce capital funds is the next step. A tool box of solutions was developed to address flood risk and vulnerability. Testing of the screening tool was conducted in Broward County, Florida and shows encouraging results. Comparison with FEMA Flood maps and repetitive loss mapping indicates that the process works in a coastal community. The framework appears to be viable across cities that may be inundated with water due to sea-level rise, rainfall, runoff upstream, and other natural events.
According to the Federal Emergency Management Agency (FEMA), over 98% of counties in the United States have experienced a previous flooding event, and just one inch of water can cause up to $25,000 in damage (FEMA, 2017). To meet the longer-term goal of protecting life and property, FEMA created the National Flood Insurance Program’s (NFIP) Community Rating System (CRS) in 1990, to encourage community floodplain management activities. As of 2017, nearly 3.6 million policyholders in 1444 communities participate in the CRS program, but this is only 5% of the over 22,000 communities participating in the NFIP (FEMA, 2017). Florida has nearly one-half of those flood risk policies.
Under the CRS program, flood insurance premiums are discounted to reward community actions that meet the three goals of the CRS, which are to 1) reduce flood damage to insurable property, 2) strengthen and support the insurance aspects of the NFIP, and 3) encourage a comprehensive approach to floodplain management. The Florida Division of Emergency Management (FDEM) and FEMA funded development of template and prototype watershed master plans (WMPs) to improve the safety of the public, reduce property losses, and limit economic disruption while providing an annual savings of $60 million in discounted premiums for communities where the watershed plans could improve the community rating from a class 5 to a class 4. The grant funded development of a consistent framework to create WMPs across the state.
Defining flood risk due to compounding hydrographic influences and developing a roadmap to mitigating this risk are the central concerns of a WMP exercise. This requires a spatial model for risk considerations, which is distinctly different from developing a model of predicted averages of groundwater/surface water values. Instead, the model should be conceptualized as an average of the in situ observed extremes that considers a high groundwater table, soil conditions, land development, surface water elevations, rainfall events, and if applicable king tides, climate change (sea level rise particularly), and storm surge. These conditions include LiDAR-based topography, groundwater levels, tidal and surface water levels, soil storage, land cover/imperviousness, precipitation, sea level rise, storm surge, and existing stormwater infrastructure. With these inputs, a screening tool can be used to create flood risk contours that are useful for predicting areas flooded after specific rain events.
To be useful long-term, it is critical to developing an effective screening tool that can extend beyond nuisance flooding events to those long-range events that call for structural changes to protect economic and social institutions along with critical infrastructure and property assets. In addition, a reading of the FEMA, NFIP and CRS guidelines indicates that these assessments should be at the HUC 12 level (~50 sq mi or less) as opposed to the water management district and TMDL basins typically used for state planning purposes in Florida. Therefore, scalability is an important consideration as the screening tool must be able to provide information at the watershed level, and also be able to drill down to the subwatershed level to identify flood-prone areas that might not have flooded recently but have are at risk to do so under certain conditions.
For the case of south Florida, there is little soil storage capacity due to the combination of very flat topography and high water table elevations that provide a direct relationship between ground and surface waters (Bloetscher & Wood, 2016; Bloetscher & Romah, 2015; Wood, 2016; E Sciences, 2014; Romah, 2011). Wood (2016) used LiDAR and groundwater measurements on a given day, with the requisite high tides on that day, to create a GIS surface layer to predict flood risk. As a part of the process, Romah (2011) found a 1:1 relationship between tidal rise and groundwater elevations using the method discussed in Chang et al. (2011). This behavior was later confirmed for barrier islands, when E Sciences (2014) similarly evaluated flood risk for Miami Beach, FL using the 99th percentile tide event associated with king tide in Fall.
Outside southeast Florida, coastal flooding events are influenced by other dynamic processes (Sweet et al., 2017), such as from waves, storm surge, and their effects (Stockdon et al., 2006; Serafin & Ruggiero, 2014; Sweet et al., 2017), local rainfall (Wahl et al., 2015), elevated groundwater (Romah, 2011, Rotzoll et al., 2013; Wood, 2016; Sukop et al., 2018), or river runoff (Moftakhari et al., 2017). In studying the potential impacts of flooding in a watershed, a certain set of ongoing strategies would appear to be useful for ultimately protecting the economic and social viability of communities, minimizing risks to residents, identifying vulnerable assets, and providing insurance and banking entities with a degree of confidence in local community protection efforts. These strategies are not the same for any two communities, and the outcomes vary.
The key for local officials is to be able to identify flood-prone areas quickly—including those that might not have flooded recently but may pose a significant risk for flooding under certain conditions. The existing literature on developing screening tools for conditions similar to south Florida have not previously taken into consideration soil storage capacity based on rainfall and groundwater level. As a result, the goal of this paper is to refine screening tool methods further by incorporating the surface waters that influence groundwater in southeast Florida, adjust for true soil storage, and model a series of design storms as a means to better predict flood risk for events not related to sea level rise. Independently generated FEMA flood maps will be used to compare the results of the model in Broward County, FL. This screening tool could then be used to better identify zones at the subwatershed-level to target for mitigation strategies within a watershed master planning framework.
The screening tool conceptually depicted in
To be useful, the screening tool must be able to drill down from a regional watershed or subwatershed scale down to smaller community-level scales for sufficient detail required for development of a watershed master plan. The plans themselves require the following basic steps:
1) Identify the subwatershed boundaries using the USGS subbasin hydrologic unit code (HUC) definitions. For a subwatershed to be creditable in the CRS program, it should generally not exceed 50 square miles, but should be sizable enough to address the water quantity in the basin (Carlton, 2021).
2) Identify key stakeholders (governments, community organizations, etc.) and existing planning supports or regulations that will impact the subwatershed.
3) Acquire comprehensive planning, zoning, land use, flood control and other policy frameworks for future land use that contribute to flood risk.
4) Identify an appropriate planning level of service and obtain the following design storms: a) 1-day, 10-year, b) 3-day, 25-year, and c) 1-day, 100-year storm events to determine extent and severity of flooding. Where applicable, sea level rise, king tides, etc. should also be modeled with each precipitation event.
5) Acquire recent aerial photographs of the basin (note historical aerial photos may be helpful in developing projections for development).
6) Acquire FEMA flood insurance rate maps and repetitive loss data.
7) Acquire GIS data for roads, property, topography, waterways (streams, lakes, canals and rivers), groundwater levels, sea levels and tidal data (as applicable), land use, future land use, open space, impervious areas, structures (where available) and storm surge (coastal communities).
8) Acquire information of local stormwater infrastructure and input to the GIS maps.
9) Identify applicable standards for stormwater design—for example, permits or requirements in place requiring communities to meet a given flood protection event (3-day, 25-year storm, for South Florida). Note detailed routing software may be required to accomplish this task with accompanying costs.
10) Identify water that flows from another community and outlets of water that receive the overflow.
11) Identify drainage issues within the jurisdiction caused by current and future development.
12) Identify properties at risk of flooding (county property appraiser maps—note specific property identification must be avoided in publicly available maps).
13) Identify solutions that may be applicable for implementation in a given basin.
14) Prioritize properties based on critical infrastructure consequences of flooding and probability of flooding.
15) Identify funding sources for these solutions and establish a schedule for implementation.
16) Develop a capital improvement program for infrastructure.
17) Compile comments from stakeholder groups.
18) Develop a maintenance plan for infrastructure and monitoring results (MS4 permits are an example that could be used).
19) Seek approval of plans from stakeholder governments and NFIP.
Localized infrastructure improvements in small subwatersheds will have more impact on the results than in larger watersheds, meaning the ability to scale up or down, while incorporating associated infrastructure, is required. At the same time at the neighborhood level, under-designed piping, which will not impact the regional flood models, will be identified as failing to meet the level of service standard for the subwatershed and cause major flood concerns.
Surface Topography Development
Topography is a key parameter that influences many of the processes involved in flood risk assessment, and thus, up-to-date, high-resolution, and high-accuracy elevation data are required. As specified by the FEMA Risk Mapping, Assessment, and Planning (RiskMAP) protocols, 1-meter (2015 to present) and 1/9 arc-second (~3-meter) (2010-2015) LiDAR DEMs were acquired from the USGS 3D Elevation Program (3DEP) using the National MapViewer (https://viewer.nationalmap.gov/basic/). FEMA has adopted the Quality Level 2 (QL2) data as a standard as defined in the USGS LiDAR Base Specification v1.2 (Heidemann 2014), which is provided through the USGS 3DEP (FEMA, 2016). QL2 from the National Enhanced Elevation Assessment (NEEA), which serves as the basis for the USGS 3DEP, was developed using airborne LiDAR point density of 2 points per square meter allowing for a high accuracy and enhanced resolution of derivatives. The 1-meter Digital Elevation Model (DEM) has a target non-vegetated vertical accuracy of 19.6 cm at the 95% confidence level, which is consistent with the 3DEP QL2 vertical accuracy threshold of plus or minus (±) 10 cm RMSEz (Arundel et al., 2015). The 3-meter DEM products have a vertical accuracy between 22 cm and 30 cm that meets the specifications of FEMA Elevation Guidance (Document 47) for flood risk analysis and mapping (FEMA, 2016). The source data included NOAA flights in 2018, plus local data of various dates. Where the maps overlapped, they were stitched together using GIS smoothing.
Groundwater
For situations in which groundwater is under the influence of surface water, it is necessary to collect groundwater table elevation data to calculate soil storage capacity. Since well density varies considerably, interpolation of data was required to create a groundwater surface developed using groundwater data from 2005 to 2018. To establish a common date for modeling purposes, the recorded groundwater table elevations were sorted in ascending order to determine the 98th-100th percentile date of occurrence in Excel®, following the manual procedure detailed in Romah (2011). In this study, the manual procedure was automated using a python code to process the groundwater data more efficiently. Outliers and anomalous groundwater levels in the database are initially identified (e.g. catastrophic storm events) and replaced by region-specific mean values based on observations available from the nearest wells. Missing date-specific data are estimated using simple temporal interpolation based on observations available in time. If a station (or monitoring well) data contains missing data, it is not used in the generation of the groundwater surface. The full process is outlined in Zhang et al. (2020).
Surface Waters/Tides
Because the water table is so shallow (<4ft bls) in the southeast Florida study area, surface waters tend to directly influence groundwater (Romah, 2011; Chang et al., 2011). E Sciences (2014) and Bloetscher (2012) found that the groundwater elevation is also consistent with high tides as opposed to average tides for a boundary condition. As a result, projecting groundwater levels will indicate infrastructure with a greater vulnerability for flooding where water, sewer, stormwater and transportation infrastructure in low-lying inland areas may be compromised faster due to the loss of soil storage capacity. Therefore, once the common date for the groundwater surface is determined, surface water levels and tidal data can be obtained for that same date (±3 days, in the event the water elevation in the canals was deliberately lowered by the water management district authorities). Surface water stage heights for canals and other important water bodies were obtained from DBHYDRO, which is a database system used by SFWMD to record water quantity and water quality data. The canals form boundary conditions for the screening tool on the edges of the basin and affect localized groundwater. Besides groundwater and surface water levels, to set a boundary for the coastal areas, the high tide on the common date should be chosen. The tidal data for the common date is obtained from NOAA tide data (https://tidesandcurrents.noaa.gov/).
Once the common date is found, the water levels in all wells from the modified database and the surface water stations, canals, lakes, and ocean are used to create the groundwater surface in GIS. Spatial interpolation using a stochastic variance-dependent interpolation is used to estimate groundwater levels at points of interest or for the generation of the surface (Romah, 2011
Sea level rise also must be included for coastal ares. The NFIP program looks for a model of the NOAA mean medium high 2100 value. For southeast Florida, this value is 5 ft based on
Soils
Soils can store additional water before becoming saturated if there is sufficient distance between the ground surface and the water table and if the soils are capable of infiltrating the water. Soil data is obtained from the USDA gSSURGO database and is interpreted to determine whether water can be absorbed or will run off. This is a critical issue for precipitation modeling. The soil maps are incorporated as a GIS layer in the overall mapping effort. The USDA gSSURGO database contains all the original soil attribute tables from the USDA National Cooperative Soil Survey (NCSS) (Soil Survey Staff, 2020) in the Environmental Systems Research Institute, Inc. (ESRI®) file geodatabase format. This allows for
statewide or even Conterminous United States (CONUS) tiling of data. An important addition to this format is a 10-meter raster (MapunitRaster_10m) of the map unit soil polygon feature class, which provides statewide coverage in a single GIS layer.
To find the unsaturated zone, the groundwater layer, as influenced by the surficial canals, is subtracted from the topographic layer to show the apparent unsaturated zone. In Broward County much of the area is expected to show minimal differences between the ground surface and the water table elevations in the fall, except along the coastal ridge. The void space comes from a statewide GIS file of soil void capacity. The unsaturated zone layer is multiplied by void space to create the soil storage capacity layer.
Land Cover
The National Land Cover Database (NLCD) provides nationwide data on changes in land cover at a 30-m resolution with a 16-class legend based on a modified Anderson Level II classification system (Jin et al., 2019). The database is designed to provide cyclical updates of United States land cover and associated changes. The latest release of NLCD products named NLCD 2016 is used. For the conterminous United States, NLCD 2016 contains 28 different land cover products characterizing land cover and land cover change across 7 epochs from 2001-2016, urban imperviousness and urban imperviousness change across 4 epochs from 2001-2016, tree canopy and tree canopy change across 2 epochs from 2011-2016 and western U.S. shrub and grassland areas for 2016. Large water bodies such as the Intracoastal Waterway and canals are delineated by NLCD dataset, but it does not have sufficient resolution of smaller waterbodies and impervious surfaces. Therefore, a statewide land use land cover dataset (FLUCCS-FSWMD, 2012) compiled by the Florida Department of Environmental Protection (FDEP) was also collected. This dataset integrates land use land cover data products provided by the regional water management districts in Florida based on manually interpreted fine resolution aerial photography. Compared to the NLCD dataset, the FDEP land use land cover product has a finer delineation of land cover types. This dataset was used to refine water bodies and impervious surfaces, where soil water holding capacity is considered as zero in the screening tool. The impervious areas, the water mask layer, the soil water holding capacity ratio layer, and the soil storage capacity layer allow calibration of the model to account for the actual amount of water that can enter the soil before filling it; these layers represent the real characteristics of the area (refer to
Precipitation
Precipitation is available from NOAA and as apart of many software packages for the State of Florida. For the purposes of thisproject, NFIP desires a comparison on the 1-hr, 100-year, or 3-day, 25-year and 1:10 year events. The SFWMD includes theser values in their Environmental Resources permitting manual (https://www.sfwmd.gov/document/environmental-resource-permit-information-manual). Rainfall records were derived from NOAA records available from FAU’s cwr3 website.
Existing Infrastructure
For flood modeling to provide useful results, modeling must include relevant infrastructure. As
| Level of Modeling | HUC | Examples of Infrastructure of Concern |
|---|---|---|
| TMDL Region/USGS Watershed | 8 digit | Major canals, dams, large rivers, lakes, and ocean |
| Subwaterhed | 12 digit | Primary and secondary canals, dams, large rivers, lakes, ocean, streams, smaller lakes, large bridge/culvert structures, draiange operations/staging |
| Community | n/a | Rivers/streams/canals, interceptors/large ditchs, neighborhood lakes/large retention/detention areas, major roadway conveyances |
| Neighborhood | n/a | Catch basins, swales, 15" piping, crowns of road, culverts under driveways, local retention/detentaion areas |
Flood Mapping
A basin is defined as an area where all the water that falls via rainfall stays in an area and travels to an outlet. The areas of the basin and the longest time it takes the runoff to travel to the most distant point of discharge must be estimated. Putting the prior datasets together, is a software package (CASCADE 2001) developed by SFWMD (2001) to predict flooding. CASCADE 2001 is a GIS-based multi-basin hydrologic/hydraulic routing model that permits investigators to analyze different storm events to determine potential flooding. The boundaries are critical for basin studies and must be chosen carefully. The model requires the following input:
• Topography
• Groundwater elevations
• Surface water/Outlet locations
• Soils
• Development intensity/land cover
The screening tool predicts how areas with low elevations may be affected by a selected rainfall event (1-hr, 100-year, or 3-day, 25-year, or other event), inundation from the ocean directly, rising groundwater levels, and the inability of inland areas to drain. Romah (2011) defined vulnerability maps using the definitions of the U.S. Army Corps of Engineers (USACE) that are “Vulnerable,” “Potentially Vulnerable,” or “Less Vulnerable”. However for this application, a modified approach was used that defines flood risk as the probability of inundation based on ground elevation data. A major advantage of this approach compared to inappropriate bathtub mapping performed by others is that it takes into consideration the vertical accuracy error in the elevation datasets, which may vary depending on the available data spatial resolution. Errors in elevation data are typically reported as either the RMSE or Accuracy (FEMA, 2003). In addition, RMSE approximates the population standard deviation (SD) when the data are not biased (i.e. the mean error is zero). The uncertainties associated with the DEM vertical accuracy, estimated depths to groundwater table, and the modeling approach itself are incorporated in the RMSE computation. A z-score surface can be used to derive the probability of inundation under an assumption of a normal distribution for the measurement and modeling errors (Schmid, Hadley, & Waters, 2014). The z-score surface from which to derive probabilities of inundation is defined as follows:
Z-Score = [(highest headwater height) – (Ground Elevation from LiDAR DEM)]/(RMSE_LidaDEM2 + RMSE_CRT2001Model2)0.5
= (Headwater Height – LiDAR DEM Elevation)/0.46 (1)
The value of one standard deviation in the inundation modeling suggested by NOAA for the coastal vulnerability assessments is 0.46 ft (NOAA, 2010), which is the value adopted in this work. The relationship of the inundation probability and the predicted water surface elevations is calculated as follows:
Probability of Inundation = CDFnormal(Z-Score) (2)
Finally, review the veracity of the model, the the flood risk probabilyt maps for the area ferived formteh Cascade model were compared to the FEMA flood maps to compare the percentage of the area that was predicted to the flooded by both methods. The subject area was Broward County, Florida (see
The drainage canals installed between 1930 and 1960 control groundwater levels throughout the subwatershed.
There are over 50 groundwater wells located in and around the subwatershed were used to develop
The unsaturated zone depth is the difference between the ground surface elevation and the groundwater table elevation layer (
to nearby unsaturated areas. Impervious areas also include water bodies (
Vulnerability to Flooding
• Area
• Portion of area above a given elevation
• Initial ground water stage
• Longest travel time for the runoff to reach the most distance point of discharge
• Ground storage as estimated from the USDA gridded National Soil Survey Geographic Database (gNATSGO)
Ground storage ≈ (Water holding capacity) × (Surface elevation – GW elevation) = 2 × (AWS for a soil layer of 0 - 150 cm)/150 cm × (Surface elevation – GW elevation)
• Available water storage (AWS) for a soil layer of 0 - 150 cm
• Average amount of precipitation that can be stored in the soil layer
NFIP guidelines).
Options for Correction
Once the probability of flooding is determined, the next step is identify critical assets. To help with prioritization, the following is suggested:
• Tier 1—Critical facility protection (water/sewer utilities, public safety, hospitals, schools, power).
• Tier 2—Essential facilities (groceries, pharmacies, roadways)
• Tier 3—Economic centers (protecting jobs)
• Tier 4—At risk communities
• Tier 5—Other urban/suburban property
• Tier 6—Agriculture/public property/vacant/undeveloped
| Description | Total Area (mi^2) |
|---|---|
| FEMA’s high-risk region based on the 100-year flood event (1%-annual-chance Flood Hazard Areas) | 174.00 |
| FAU’s high-risk region based on the 1-day 100-year storm event (Above 90% probability of inundation) | 116.16 |
| Overlap between the high-risk regions designated by FAU and FEMA | 88.38 (50%) |
The process of identifying potential mitigation measures to implement begins with narrowing down the feasible engineering alternatives using threshold criteria and quantifiable selection criteria that include measures of effectiveness, cost, and added benefit to the community. The toolbox describes a variety of strategies that could be used to improve potential flood management conditions. They are community-specific and most require significant engineering and planning to determine the most efficient configuration to achieve the community’s goals. Hard infrastructure systems are usually the first systems to be impacted because they are built at lower elevations than the finished floor of structures. In addition, many infrastructure systems are located within the roadways (water, sewer, stormwater, power, phone, cable tv, internet, etc.). At present, most roadway base courses are installed above the water table. If the base stays dry, the roadway surface will remain stable. As soon as the base is saturated, the roadway can deteriorate.
To help develop solutions for the identified priority areas, a toolbox was developed that describes a variety of strategies (n = 36) to improve potential flood management conditions.
| Strategy Class | Implementation Strategy | Applications | Benefits | Cost | Barriers to Implementation |
|---|---|---|---|---|---|
| Green | Bioretention planter | Local, small scale, easily implemented in developed areas | Protects property, treats runoff | $2500 ea | Limited volume disposed of, so many are needed, maintenance |
| Green | Tree box filter | Local, small scale, easily implemented in developed areas | Protects property, treats runoff | $2500 ea | Limited volume disposed of, so many are needed, maintenance |
| Green | Rainwater harvesting | Local, small scale, easily implemented in developed areas | Protects property, treats runoff | Under $5000 | Limited volume disposed of, so many are needed, maintenance |
| Green | Vegetated roof | Specific to a building, absorbs water, reduces runoff | Protects property, treats runoff | $100/sf | Requires irrigation if insufficient rainfall occurs Requires runoff control if too much rainfall occurs |
| Green | Bioswale | Parking lots, runoff from development—primarily treatment for discharge to another system | Protects property, treats runoff | $20 K/ac | Maintenance, limited volume disposed of, used mostly for treatment |
| Gray | Pervious paving | Parking lots, patios, driveways, anything except paved roads due to traffic loading | Reduces roadway and parking lot flooding | $10 - 20/sf, requires bumpers and sub-base to maintain paver integrity | Must be maintained via vacuuming or the perviousness fades after 2 - 3 years |
| Green | Detention | Common for new development, but difficult to retrofit; limited to open areas | Removes water from streets, reduces flooding | $200 K/ac | Land availability, maintenance of pond, discharge location Uses up land that could otherwise be developed |
| Green | Vegetated wall | Used on walls of buildings and retaining walls | Protects property, treats runoff | $30/sf | Requires irrigation if insufficient rainfall occurs Requires runoff control if too much rainfall occurs |
| Gray | Exfiltration Trench | Any low-lying area where stormwater collects and the water table is more than 3 ft below the surface; densely developed areas where retention is not available, roadways | Excess water drains to aquifer, some treatment provided | $250/ft | Significant damage to roadways for installation, maintenance needed, clogging issues reduce benefits |
| Green | Dry Swale | Parking lots, runoff from development—primarily treatment for discharge to another system | Protects Property, treats runoff | $200 K/mi | Maintenance, limited volume disposed of, mostly for treatment |
| Green | Retention Ponds | Common for new development, but difficult to retrofit; limited to open areas | Removes water from streets, reduces flooding | $200 K/ac | Land availability, maintenance of pond, discharge location Uses up land that could otherwise be developed |
| Green | Rain Gardens | Local, small scale, easily implemented in developed areas | Protects property, treats runoff | $20 K/ac | Limited volume disposed of, so many are needed, maintenance |
| Gray | Infiltration Trench | Low lying areas that collect stormwater, but the water table is just below the surface meaning that retention and exfiltration trenches will not work properly | Excess water is drained to pump stations, creating soil storage capacity to store runoff, soil treatment | $250/ft plus pump station | Significant damage to roadways for installation, maintenance needed, clogging issues—must discharge somewhere (pump station, detention pond) |
| Green | Oversized pipes | Local solution—not watershed level, holds water to reduce flooding | Protects property and roadways | $350/ft of more | Sediments, maintenance needs, lack of means to flush, cost |
| Gray | Central sewer installation | All areas where there are septic tanks. Mostly a water quality issue | Public health benefit of reducing discharges to lawns, canals and groundwater from septic tanks | $15,000 per household | Cost, assessments against property owners, property rights issues |
| Green | Filter strips | Localized | Protects property, treats runoff | $50 K/mi | Does not address flooding, treatment/water quality measure |
| Green | Flood prone property acquisition | Regional agency—could be any low-lying areas | Removes flood prone areas from risk | $2 K - $100 K/ac depending on whether it is already developed | Difficult to implement if occupied, issues with willing sellers, cost, lack of funds for acquisition |
| Gray | Class I injection wells | Any low-lying area where stormwater collects, and there is sufficient land to permit, install and operate a Class I well-limited | Means to drain neighborhoods— potentially arge volumes | $3-6 million depending on size/depth | Needs baffle box, injection zone may not be available, requires a permit, may compete with water users |
| Green | Underground storage | Common for new developments, but difficult to retrofit | Storage of excess runoff from rainfall, can be used for irrigation, can sit under parking lots, unobtrusive | $2/gal | If the tank is full, there is no storage |
| Green | Constructed wetlands | Where there is low lying flood prone land that can be converted into wetlands | Reduces flooding by providing a low-lying area for water to go | $200 - $1 M/ac | Water quality, permitting, monitoring costs, maintenance |
| Gray | Pump stations | Any low-lying area where stormwater collects, and there is a place to pump the excess stormwater to such as a canal; common for developed areas | Removes water from streets, reduces flooding | Start at $1.5 to 5 million each, number unclear without more study | NPDES permits, maintenance cost, land acquisition, discharge quality |
| Gray | Armored sewer systems | Any area where gravity sanitary sewers are installed | Keeps stormwater out of sanitary sewer system and reduces potential for disease spread from sewage overflows | $500/manhole | Limited expense beyond capital cost |
| Gray | Raised roadways | Limited to areas where redevelopment is occurring areawide due to ancillary impacts on adjacent properties | Keeps traffic above floodwaters, access for emergency vehicles, commerce | $2 - 4 million/lane mile | Runoff, cost, utility relocation |
| Gray | Class V gravity wells | Any low-lying areas where stormwater collects and is located where saltwater has intruded the surficial aquifer beneath the site | Means to drain neighborhoods, limited volume | $250 K each | Needs baffle box, limited flow volume (1 MGD), zone for discharge may not be available, permits, water supply wells |
| Gray | Canals | Limited | Means to drain neighborhoods, provides treatment of water | $2 million/mile | Land area, flow volume, maintenance, ownership, capacity issues due to sea level rise pressure |
| Green | Aquatic zones | Any low-lying or flood-prone area that is undeveloped and can store large volumes of water | Place to store large volumes of water | $200 K/ac | Must be maintained, cost, impact on property owners |
| Gray | Levees | Regional issue—along rivers, lakes, impoundments | Protects widescale property | $ millions | Must be maintained, must be continuous, must be planned for extreme events (i.e. Hurricane Katrina showed that New Orleans planning horizon was not sufficient) |
| Gray | Lock structures | Regional (WMD) responsibility | Keeps seawater out, reduces saltwater intrusion | Up to $10 million, may require ancillary stormwater pumping stations at $2 - 5 million each | Permitting, private property rights arguments |
| Gray | Sea walls | Barrier islands and downtown coastal areas | Protects property | $1200/ft | Private property rights, neighbors |
| Green | Polders | Barrier islands and downtown coastal areas | Provides storage for coastal waters | $200 K/ac | Permitting, land acquisition |
| Gray | Surge barriers | Coastal communities—large footprint | Protects property | >$1 B | Cost, open ocean access challenges, property rights |
| Green | Enhanced wetlands | Where there is an existing wetlands area that can be augmented | Reduces flooding by providing a low-lying place for water to go | $200 - $1 M/ac | Water quality, permitting, monitoring costs, maintenance, ecosystem impacts |
| Green | Revetments | Retention, helps maintain the storage volume, in conjunction with other measures | Improves walls of retainage | Varies based on material, depth, wall height | Land area, maintenance |
| Policy | Changes in land use | Applicable universally | Achieves flood risk mitigation by djusting permitted land use | Low but may incur private property rights conflicts and litigation | Private property rights conflicts and litigation |
| Gray | Roadway base protection | Low-lying areas, coastal communities | Protects roads and access routes | $1 million per lane mile | Cost, adjacent properties become uninsurable |
| Policy | Enhanced elevation of buildings or land abandonment | Developers would implement this for new construction | Reduced flood risk | Varies | Potential issues with building structure or latticework, and existing homes that are not elevated |
from pluvial (rainfall and runoff mitigation in upland areas), fluvial (runoff, high ground water, and surface water management in low-lying flood prone areas), tidal (flooding associated with storm surge, high ground water, and tidally influenced), and all (applies across the spectrum). Each is site-specific, and most require significant engineering and planning to determine the most efficient configuration to achieve the community’s goals.
Flood risk analysis is the instrument by which floodplain and stormwater utility managers create a sound strategy and adaptation plans to reduce flood potential in their communities. The goal of this study was to demonstrate a screening tool to identify areas at higher risk of flooding by implementing a water surface derived from groundwater levels, surface gage heights, and tidal influences to create a map of minimum soil storage capacity. The screening tool applies various rainfall events to this initial condition to determine the risk of flooding for each scenario. The study showed that the groundwater influence model, which is not contemplated under current modeling methods by government agencies or other parties, is capable of identifying higher risk areas on a subwatershed scale. This is important because communities creating watershed master plans will be empowered and find solutions to four of the seven CRS requirements, if the screening tool is implemented:
1) Evaluate the watershed’s runoff response from design storms of various magnitudes and durations under current and predicted future conditions.
2) Assess the impacts of sea-level rise and climate change.
3) Implement regulatory standards for new development such that peak flows and volumes are under control.
4) Include specific mitigation recommendations to ensure that communities are resilient in the future.
The objective of evaluating areas at the subwatershed scale was achieved, with overlap of over 50% when compared to FEMA FIRMs, realizing the FIRM maps and model do not scan for the same issues. As a result, the framework for the screening tool accurately identifies risk areas to assist decision-makers in developing appropriate mitigation strategies. Thus the screening tool will help officials create plans that are fundamental to providing necessary levels of drainage and flood protection under future climate conditions and development scenarios.
The strengths of this framework are the initial focus on location-specific science, enabling policy makers to develop long-term decisions with respect to infrastructure investments, because infrastructure and development are not temporal—they are expected to last 50 years or more. Hence it is in a community’s interest to develop a planning framework to adapt to flooding conditions to protect vulnerable infrastructure through a long-term plan. Because vulnerability can never be estimated with 100 percent accuracy, the conventional anticipation approach should be replaced or supplemented with one that recognizes the importance of building resiliency.
Further study should focus on four areas:
1) Application to a less flat, rocky terrain to determine if the protocols can be transferred outside Florida.
2) Rainfall was assumed to be consistent across the watershed. This rarely happens. A heuristic model of rainfall could better represent actual conditions.
3) A predictive model could be developed to evaluate prior events as a tool for predicting future results.
The authors declare no conflicts of interest regarding the publication of this paper.
Bloetscher, F., Rojas, G., Abbate, A., Hindle, T., Huber, J., Jones, R., Liu, W. B., Meeroff, D. E., Mitsova, D., Nagarajan, S., Oglesby, G., Polsky, C., Su, H., Suarez, E., Teegavarapu, R., Weaver, J., Xie, Z. X., Yong, Y., & Zhang, C. Y. (2021). A Framework for a Subwatershed-Scale Screening Tool to Support Development of Resiliency Solutions and Flood Protection Priority Areas in a Low-Lying Coastal Community. Journal of Geoscience and Environment Protection, 9, 180-205. https://doi.org/10.4236/gep.2021.910013