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Media Matters in Landscape Architecture, a new book edited by Professor of Landscape Architecture Karen M'Closkey and Senior Lecturer in Landscape Architecture Keith VanDerSys, critically examines the ways in which various tools, methods, and images shape our conceptions of landscapes and environments. In an excerpt from their chapter, “Additional Complications Have Emerged,” the two give an overview of how hydrologists' research led to the creation of floodplains as risk objects, and how the effects of climate change have led to uncertainties in mapping such phenomena.
On Thursday, March 19, the McHarg Center for Urbanism and Ecology will host a public talk by M'Closkey and VanDerSys. They will be joined by Jeffrey Moro of the University of Maryland and Brian Harris of the US Army Engineer Research and Development Center.
On July 4, 2023, as Americans celebrated Independence Day with barbecues and fireworks, the Earth recorded its hottest day in over 120,000 years, a figure that will likely be surpassed by the time of this publication.1 While this fact confirms the alarming trends projected by climate models, global averages cannot capture how the increasingly severe and unpredictable weather caused by a rapidly heating planet will affect specific places. In The Great Displacement: Climate Change and the Next American Migration, journalist Jack Bittle paints a vivid portrait of domestic climate migrants whose intimate stories portend what many millions more Americans will face in the not-too-distant future. Bittle’s stories include people ranging from low-wage workers to the ultra-rich; those displaced by headline-grabbing “event” disasters such as hurricanes, floods, and wildfires; and those experiencing slow-moving, or less visible, disasters caused by drought, the creep of high tides, or heat.2
Although development in coastal areas and deserts is unfortunately still increasing, this trend will likely reverse as land subsidence and sea-level rise push people away from coasts, and lack of water and extreme heat drive them away from deserts. As Bittle makes clear, this displacement will be “unpredictable, chaotic, and life-changing.”3 Not only is the United States, as a nation, ill-equipped to deal with the increasing numbers of people who will need assistance after experiencing loss from a disaster, but it is also woefully unprepared to prevent the same calamities from occurring in areas that are being developed in response to climate-induced migration.4 This is especially true in the case of floods.
This chapter considers environmental media in relation to the concept of floods as “risk objects” and the creation of floodplains as a spatial result of this concept.5 These media include hydrologic and hydraulic models that incorporate rainfall, water flow rate, and topographic data; flood maps that delineate the location and extent of floodplains based on the outputs of those models; and the physical and statistical apparatus that underlies the measurement of dynamic media—rain, wind, and tides—that the models and maps seek to represent. We use the word “creation” rather than “mapping” because, as discussed below, flood maps are not simply the media through which a hazard is documented. Rather, flood maps yield specific material and social conditions around which a particular understanding of “floodplain” emerges. This understanding conditions how and where we build and thus shapes the practice of landscape architecture. This phenomenon is not unique to the United States; however, we focus our attention on the United States because of the differences in floodplain definitions and regulations between countries.6
Extent of flood probabilities of combined fluvial and pluvial events with a projected rainfall increase if approximately 22% (a near-future increase estimated by the US Army Corps of Engineers, Philadelphia District, and New Jersey Dept of Environmental Protection). The 1979 floodplain more closely matches the projected flood extent compared to the 2015 map.
A floodplain depicted on a map does not represent a physical entity; it depicts a probability. It represents the likelihood that a certain amount of rainfall (depth) will occur over a certain period of time (duration) at a certain frequency (the recurrence interval), expected to submerge the land to a certain level (the base flood elevation). In other words, little is natural about these floodplains. They result from an agreed-upon set of practices and standards designed to signal risk and are used to set infrastructure design guidelines and insurance premiums. The inadequacy of the United States’ approach to mapping flood hazards is becoming increasingly apparent as the Earth continues to heat up and the impacts of this rapid transformation become more unpredictable. Some have even argued that “rational planning in conditions of uncertainty is, by definition, impossible,” which poses a challenge to designers and planners.7
When it comes to modeling floods, topography is the only variable that can be made more accurate than previous maps and models because, although its accuracy depends on spatial resolution, its existence is not predictive or based on a probability of occurrence. [T]his is why the National Research Council (NRC), in its 2007 recommendation to Congress for funding of FEMA’s ongoing map upgrades, suggested focusing primarily on improving topographic accuracy through the use of lidar.8 It argued that increased accuracy would enable better decision-making about floodplain development, stating that accurate topographic data is the most important factor in determining base flood elevations, which “overturns the conventional view that map accuracy is affected at least as much by the accuracy of the hydraulic model and hydraulic parameters as by the accuracy of the topographic data.”9 The NRC made its recommendation based on several case study areas where the use of more accurate topography expanded the number of structures included within the base flood elevation zone. However, in our comparison of six cities, where we overlaid older FEMA maps with those that had been updated with more accurate topographic data from lidar, we found that the floodplains shrank while the population increased in five of the six locations.10
Although FEMA’s updated flood zones are based on more accurate topography, the presumption of stationarity—that variation occurs within known boundaries—is assumed for all other model inputs, from rainfall to stream flow to the landscape itself.11 This is why so many flood losses—between 25% and 40%—occur outside officially designated floodplains, even in areas where maps have been recently updated.12
As of 2023, FEMA has implemented a method to address the inequities baked into the way flood insurance is priced by providing a risk rating based on the specifics of individual structures, such as how high above the base flood elevation a home sits.13 The further granularization of our maps may help individuals pay a rate that more accurately reflects their insurance risk but it sends the wrong message about floodplains. Even maps produced with gradients based on different storm intensities and rainfall amounts will have uncertainties that cannot be accounted for, and these will only be exacerbated by changing precipitation due to climate change.
Rather than treating uncertainty as something to be tamed, as continues to be the trend, landscape architects can treat it as something generative, bringing the assumptions behind best-laid plans to the forefront.
Given the variables and uncertainties involved in producing flood maps, it is not possible to provide the kind of assurance that people want. Even within the scientific and modeling communities, there is no consensus on how to account for climate change in understanding the effects of riverine or pluvial flooding, and little consensus on how to account for pluvial flooding even under stationary conditions.14 As one hydrologist puts it, a “suitable successor” to stationarity has yet to be found.15 The “great displacement” from the coasts will lead people to areas that do not have development restrictions to account for rain, and there is no easy way to define them, especially for the longer term. Even TMAC [Technical Mapping Advisory Council}, which insists that the theory behind risk-based flood management is “well established and sound,” acknowledges that with climate change, “additional complications have emerged.”16
Landscape architects work between public and private interests, as well as local, state, and federal regulations. Rather than treating uncertainty as something to be tamed, as continues to be the trend, landscape architects can treat it as something generative, bringing the assumptions behind best-laid plans to the forefront. There is no ideal way to do this; much depends on the participants or recipients of these media. Some have argued that creating ambiguity in maps—gradients, blurred boundaries, tones, and transparencies—rather than clear lines of distinction is the way forward for any kind of spatial information with a high degree of uncertainty.17 However, FEMA plans to use gradients to represent more accuracy (for insurance assessments), not more ambiguity. Another study that conducted interviews and workshopping to understand flood maps with residents who had experienced a significant flood supported ambiguity by depicting multiple floodplains on maps.18 In other cases, however, maps without clear distinctions have been shown to induce what is known as ambiguity aversion, leading participants to underestimate their risk.19 Perhaps we should heed the advice of geographers Magali Reghezza-Zitt and Samuel Rufat, who argue that uncertainty is irreducible to risk and acknowledge the unprecedented nature of this challenge.20
1) Damien Gayle, “Tuesday Was World’s Hottest Day on Record – Breaking Monday’s Record,” The Guardian (July 5, 2023), https://www.theguardian.com/environment/2023/jul/05/tuesday-was-worlds-hottest-day-on-record-breaking-mondays-record.
2) The United States does not consider heat-related deaths as disasters, and thus federal funding through FEMA is not available. For the devasting effects of heat, see Jeff Goodell, The Heat Will Kill You First (Little, Brown & Co., 2023).
3) Jack Bittle, The Great Displacement: Climate Change and the Next American Migration (Simon & Schuster, 2023), xvi.
4) For example, after Hurricane Harvey flooded Houston, the homeowners who received federal buyouts could move anywhere, including into another flood zone, and thousands of the flooded homes were sold to large investment firms and hedge funds. See Bittle, The Great Displacement, 153, 168. Also see Jon Gorey, “What Will Make Home Buyers Consider Climate Risk? What Happens Once They Do?” Land Lines Magazine (Spring/Summer 2024), https://www.lincolninst.edu/publications/article/2023-11-homebuyers-climate-insurance-risk?.
5) The phrase “risk object” is from Rebecca Elliott, Underwater: Loss, Flood Insurance, and the Moral Economy of Climate Change in the United States (Columbia University Press, 2021), 110.
6) See, for example, Rachelle Alterman & Cygal Pellach (eds), Regulating Coastal Zones: International Perspective on Land Management Instruments (Routledge, 2021).
7) A. R. Siders & Andrea L. Pierce, “Deciding How to Make Climate Change Adaptation Decisions,” Current Opinion in Environmental Sustainability 52 (2021): 2.
8) FEMA began its Flood Map Modernization initiative in 2000 with the intent that flood maps would be updated every five years, which has not occurred.
9) National Research Council, Mapping the Zone: Improving Flood Map Accuracy (National Academies Press, 2009), 66.
10) The locations are Jacksonville, FL; Boston, MA; Charleston, NC; Philadelphia, PA; Virginia Beach, VA; and Trenton, NJ, the last of which did not significantly change.
11) Elliott describes this on p. 112. On stationarity, a foundational concept in water management, see P. C. D. Milly et al., who state that stationarity “assumes that natural systems fluctuate within an unchanging envelope of variability.” P. C. D. Milly et al., “Stationarity is Dead: Whither Water Management?” Science 319 (February 2008): 573.
12) Highfield et al., “Examining the 100‐Year Floodplain,” 189.
13) On the inequities embedded in floodplain regulations and insurance, see, for example, Elliott, Underwater; Gaul, The Geography of Risk; Koslov, “How Maps Make Time”; and Karen M’Closkey & Keith VanDerSys, “For Whom Do We Account in Climate Adaptation?” in Carolyn Kousky, Billy Fleming & Alan Berger (eds), A Blueprint for Coastal Adaptation: Uniting Design, Economics, and Policy (Island Press, 2021).
14) National Climate Task Force, Federal Flood Risk Management, 62.
15) Milly et al., “Stationarity is Dead.”
16) Technical Mapping Advisory Council, Future Conditions Risk Assessment and Modeling (December 2015), 5–2.
17) Alan M. MacEachren et al., “Visualizing Geospatial Information Uncertainty: What We Know and What We Need to Know,” Cartography and GIS 32, no. 3 (2005): 139–60.
18) Robert Soden, “Modes of Uncertainty: Rethinking Flood Risk in Colorado,” Items: Insights from the Social Sciences (July 30, 2019), https://items.ssrc.org/chancing-the-storm/modes-of-uncertainty-rethinki….
19) For example, see David P. Retchless, “Sea Level Rise Maps: How Individual Differences Complicate the Cartographic Communication of an Uncertain Climate Change Hazard,” Cartographic Perspectives 77 (2014); Sue Hope & Gary J. Hunter, “Testing the Effects of Thematic Uncertainty on Spatial Decision Making,” Cartography and GIS 34, no. 3 (2007): 199–214.
20) Magali Reghezza-Zitt & Samuel Rufat, “Disentangling the Range of Responses to Threats, Hazards and Disasters. Vulnerability, Resilience and Adaptation in Question,” Cybergeo: European Journal of Geography (2019): 11.
