by Kathleen Schaefer and Brett F. Sanders
Why Dialogue Matters
For fifty years, Flood Insurance Rate Maps (FIRMs) have unintentionally stifled conversations of flood risk. They have encouraged property-owners and governments at all levels to dwell on map details for one static event, rather than flood risks for a range of events under changing conditions (Soden et al. 2017). Now, First Street Foundation has released a new tool that can change how these conversations develop: Flood Factor, a publicly available online resource to help people understand flood risk for an individual property, area, or region.
For each property parcel, several indicators about flooding are provided by Flood Factor including information about past floods, past flood claims, present-day flood risk, and future risks. This makes it possible to learn if a home has flooded from major recent events, is currently at risk, and how that risk changes over time. This follows previous efforts to bring detailed information on sea level rise into coastal community planning (e.g., Fu et al. 2017). Importantly, the tool presents an opportunity for fresh dialogue about flooding, including what’s at risk and ways to manage it. There is growing interest in having these types of conversations across the U.S. (National Academies 2019, Sanders et al. 2020).
To frame the timeliness of new flood risk information for dialogue, we can go back to 1968 when Congress passed the National Flood Insurance Act. Community participation in the National Flood Insurance Program (NFIP) and homeowner purchase of a flood policy were initially voluntary (Burby 2001; Horn and Brown, 2017), and the NFIP gave homeowners a more affordable option for insurance than what was available from the private sector (Burby 2001). To determine who would quality, a 1% annual chance risk (or 100-year return period) was selected as the standard, and Flood Insurance Rate Maps (FIRMs) were created to delineate flood hazard zones where properties met the standard. Moreover, community-level dialogue about flooding, and how to manage risks, was part of the plan. As a partnership between federal, state and local government, the NFIP required that communities take responsibility for managing floodplains to reduce the damages of floods and taxpayer liabilities.
But in the ensuing years, major disasters prompted Congress to change the NFIP to a mandatory program. This unintentionally derailed productive conversations about flooding. FIRMs, with the single “in-out” 100-year flood zone boundary, became a battle map. If FEMA announced that it was going to initiate a new study, community leaders would vow to fight the new maps. The contentious nature of the maps made flood risk something no one wanted talk about or pay for. Interest and funding for updating the maps also declined. Today, engineering studies of flood hazards for almost half of California’s communities are over 20 years old. FEMA has designated less than 23% of California’s mapped river miles as ‘valid.’ And, less than 30,000 miles of the State’s estimated 180,000 stream miles have been mapped.
FEMA has worked to develop a more community-friendly mapping process called Risk MAP, and it has shown promise for improving dialogue and deliberations about flooding. However, nationwide implementation of Risk MAP appears cost prohibitive. A study by the California Department of Water Resources (DWR), funded by FEMA, found that implementing the Risk MAP process in California alone would cost $445 million and concluded that much of California would never again see a new FIRM (CA DWR 2013). Indeed, what California and all of the U.S. now have is Flood Factor.
A sample set of depth maps from Flood Factor is shown below in Fig. 1, including a depiction of a past flood, the present-day 500-year return period event, and a future 500-year return period event. Multiple depictions about flooding are important for meeting needs of different end-users of hazard maps (Sanders et al. 2020), and for encouraging end-users of flood hazard information to “wrestle with uncertainty” about flooding (Soden et al. 2017). Whether the resulting dialogue will be productive is unclear.
Fig 1. Sample of past, current and future flood risk for Toledo, Ohio
FloodRISE reveals keys to productive dialogue
Fostering productive dialogue about a societal problem like flooding is challenging. Researchers at UC Irvine tested the value of more detailed flood data, and more intuitive visualizations, in the context of a community-based approach to flood resilience through a program called FloodRISE funded by the National Science Foundation. Working in three coastal sites with different flood hazards (coastal, fluvial and pluvial) and contrasting socio-economic conditions, research showed the importance of fine-resolution data (resolving individual streets and land parcels) for increasing awareness about flooding and building a shared awareness of flooding across subgroups in the community (Cheung et al. 2016, Houston et al. 2019). Research also showed the importance of inclusive and iterative community engagement, which promoted trust, heightened interests, and improved flood model accuracy through input of local knowledge (Luke et al. 2017, Sanders et al. 2020, Goodrich et al. 2020). Iterative community engagement allowed researchers to tailor flooding scenarios, mapped variables and contextual information to the needs and preferences of local end-users including planners, residents, public works managers, developers, natural resource managers, emergency managers, and non-governmental organizations. Hence, a participatory research approach was critical to building trust (Goodrich et al. 2020) and making flood maps that end-users found useful (Luke et al. 2017, Sanders et al. 2020). Examples are shown in Fig.2.
The FloodRISE project also showed that is possible to change power structures that develop around control over the flood mapping process. Dialogue between researchers and diverse groups of end-users triggered “what if” scenarios related to the management and operation of watersheds and flood infrastructure, which were then modeled and mapped (Luke et al. 2017, Goodrich et al. 2020). Historically, such analyses have only been accessible to those with financial resources to hire technical consultants, which excludes many from processes to plan for and respond to flooding.
Fig. 2 Examples of flood hazard maps for Newport Bay including: (left) flood depth for a historical event including photos of flooding; (middle) year 2015 chance of flooding; and (right) year 2035 flood depth corresponding to the 1% annual chance event. The flood depth scale, dimensioned by the average human body size, is an example of co-production by researchers and end-users.
A contrasting experience with detailed flood maps was reported in Florida, where researchers sought to better understand how information on flooding affected attitudes and opinions about climate change and sea level rise (Palm and Bolsen, 2020). Here, researchers reported that those who viewed detailed flood maps showing future flooding from sea level rise were less likely to believe that climate change was occurring and responsible for increasing coastal flooding—a response linked to political party affiliation. This aligns with a general U.S. trend of polarized views on climate issues and mistrust of scientists around party affiliation (Pew Research Center, 2016).
First Street Foundation Brings Detailed Data to the U.S.
The contrasting California and Florida experiences using detailed flood maps to engage communities in conversations about flooding point to both dangers and opportunities on the horizon for flood management. One danger is that people will not be familiar with the First Street Foundation, and there will be insufficient trust for productive dialogue. Furthermore, mapping errors could undermine trust and perceptions of risk (Cheung et al. 2016, Houston et al. 2019). Just as FEMA flood maps are prone to errors due to various reasons including data quality, rules about what gets mapped (Wing et al. 2018) and the impacts of political influence (Burby 2006), there will be errors in Flood Factor maps based on limited local knowledge and uncertain models and data. For example, a comparison of FloodRISE and Flood Factor depictions of the 1% annual chance flood zone for Newport Beach, California, where FloodRISE benefitted from extensive local data and knowledge, showed significant differences. Furthermore, most communities do not have a mechanism to dialogue with experts about flood risk, which is critical for building actionable knowledge (Lemos et al. 2018, Goodrich et al. 2020).
On the other hand, major opportunities stem from the potential to engage many more people across the U.S. in contemplating the possibility of flooding, and wresting with uncertainty about what might happen. Furthermore, Flood Factor can not only support national conversations about flooding by policy makers, but serve as a shared reference point for community- and regional-level discussions nationwide. Finally, the form of Flood Factor data, intuitive maps of flood depth for different events, is a much-needed departure from FEMA’s cryptic flood hazard mapping conventions (e.g., Zones AR, X and VE) and terminology (e.g., “floodway”, “special flood hazard area”). These changes are desperately needed so community conversations about flooding focus less on mapping conventions and more about the consequences of flooding and what can be done about it (Sanders et al. 2020).
Kathleen Schaefer is a Ph.D. candidate in Civil and Environmental Engineering at the University of California, Davis. Kathleen’s research is focused on examining community-based alternatives to the NFIP. Brett Sanders, Ph.D. is a Professor of Civil and Environmental Engineering at University of California, Irvine. Dr. Sanders served as Principal Investigator of the the FloodRISE Project, promoting resilience to coastal flooding in Southern California, and leads the Flooding and Poverty Division of the UCI Blum Center for Poverty Alleviation.
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 The data was produced by researchers and hydrologists from First Street Foundation; Columbia University; Fathom; George Mason University; Massachusetts Institute of Technology; Rhodium Group; Rutgers University; University of California, Berkeley; and University of Bristol.