Estimating Global Damages from Sea Level Rise with the Coastal Impact and Adaptation Model (CIAM)

Estimating Global Damages from Sea Level Rise with the Coastal Impact and Adaptation Model (CIAM) Delavane B. Diazy FEEM Note di Lavoro/Working Paper Series originally presented at European Summer School in Resource and Environmental Economics San Servolo, Venice, Italy July 12, 2014 Abstract The costs of coastal sector impacts from sea level rise (SLR) are an important component of the total projected economic damages of climate change, a major input to decision-making and design of climate policy. Moreover, the ultimate costs to coastal resources will depend strongly on adaptation, society's response to cope with the impacts. This paper presents a new model to assess coastal impacts from SLR, combining global scope with high spatial resolution to fill a gap between very detailed local studies and aggregate global estimates. The Coastal Impact and Adaptation Model (CIAM) determines the optimal strategy for adaptation at the local level, evaluating over 12,000 coastal segments, as described in the DIVA database (Vafeidis et al, 2006), based on their socioeconomic characteristics and the potential impacts of relative sea level rise and uncertain storm surge. An application of CIAM is then presented to demonstrate the model's ability to assess local impacts and direct costs, choose the least-cost adaptation, and estimate global net damages for several probabilistic SLR scenarios (Kopp et al, 2014). CIAM finds that there is large potential for coastal adaptation to reduce the expected impacts of SLR compared to the alternative of no adaptation, lowering global net present costs by a factor of 10 to less than $1.5 trillion over the next two centuries, although this does not include initial transition costs to overcome an under-adapted current state. In addition to producing aggregate estimates, CIAM results can also be interpreted at the local level, where we find that retreat (e.g., relocate inland) is often a more cost-effective adaptation strategy than protect (e.g., construct physical defenses). Keywords: Adaptation, coastal impacts, climate change, sea level rise, storm surge, flooding JEL: C61, Q25, Q51, Q54 yDepartment of Management Science and Engineering, Stanford University, Stanford, CA 94305; Phone: 650-646- 5448; Email: [email protected]; Web: profiles.stanford.edu/delavane-diaz. 1 1 Introduction Coastal zones are one of several key impact sectors that are threatened by potential impacts to the earth system from climate change. Rising sea levels will affect tens of millions of people who live in low-lying coastal areas, as well as infrastructure and capital assets, vulnerable ecosystems, cultural heritage, major port cities, and island nations (IPCC, 2014; Melillo et al, 2014). The potential damages to coasts from sea level rise (SLR) and storm surge include accelerated erosion of beaches and cliffs, permanent inundation of low-lying zones, increased flooding, saltwater intrusion into aquifers and surface water resources, and degradation of coastal wetlands that are rich in habitat and biological diversity and provide important services such as flood protection (Dasgupta et al, 2007; Nicholls et al, 2007; Nicholls, 2011; Hinkel et al, 2013b). The ultimate economic cost of climate change on coastal resources will depend closely on adaptation to cope with the impacts of SLR. Coastal adaptation serves to reduce vulnerability through various strategies that are broadly characterized as protect, accommodate, and retreat (Dronkers et al, 1990; Nicholls, 2011).1 Protection prevents inundation of low-lying, high economic value areas through physical armoring measures like seawalls, dikes, and bulkheads. Accommodation allows rising waters to encroach, but minimizes damages by flood-proofing or raising structures. Retreat moves humans and capital assets out of harm's way. Regardless of the adaptation strategy pursued, certain regions are likely to suffer disproportionately from SLR, such as small island nations and delta areas like Bangladesh, which have particularly vulnerable populations. Adaptation decisions must consider the long-term nature of the threat as well as the potential for extreme events. Regarding the former, global mean thermosteric SLR will unfold gradually over several centuries due to thermal inertia in oceanic processes such as mixing and circulation (Church and Clark, 2013).2 Global mean SLR is also driven by loss of land ice from glaciers as well as the polar ice sheets of Greenland and Antarctica, which store approximately 65m of SLR combined; despite incomplete understanding of the links between atmospheric and ocean warming and the rate of loss, the time frame for ice sheet disintegration is believed to be on the order of multiple centuries to millennia (National Research Council, 2013; Applegate et al, 2014). While this is fast on a geological timescale, the incremental signal of global SLR is manageable for human response, offering time to prepare. In contrast to gradual rise, storm surge extremes will continue to happen without warning 1Nicholls(2011) further differentiates three modes of adaptation: autonomous, which occurs automatically with negligible net cost (e.g., property appreciation or wetland migration); reactive, which responds to realized impacts (e.g., relocation or beach nourishment); and anticipatory, which occurs with foresight (e.g., seawall construction or storm sewer upgrades). 2The very same inertia that moderates the rate of SLR also ensures that SLR will not be easily reversed even with aggressive greenhouse gas mitigation, a feature known as commitment to SLR (Meehl et al, 2007). The limited efficacy of mitigation to avoid coastal impacts means that adaptation planning will be an essential part of society's response to SLR. 2 and cause local flooding. SLR has an additive effect on the current frequency of extreme water heights, shifting the probability distribution by the amount of rise, which will shorten return periods and expand current floodplain boundaries (Tebaldi et al, 2012).3 Finally, relative SLR includes local change in the sea surface height relative to the land, due to factors such as daily tides, seasonal weather patterns, mass redistribution effects, subsidence, isostacy, and tectonics (Church and White, 2011; Kopp et al, 2014). Effective coastal adaptation planning is an exercise in managing all of these risks: global incremental rise, storm surge extremes (and potential nonstationarity), and other local change. 1.1 Literature on global coastal impact estimates Because coastal zones are some of the most densely populated and economically productive in the world, the threat of rising seas from climate change has been studied for several decades. Most coastal impact studies fit into two categories: (1) aggregate global exposure surveys that quantify the land, people, and capital at risk of inundation, often ignoring adaptation or applying generalized rules that overlook its local determinants; and (2) high-resolution local studies that evaluate targeted adaptation projects, which are critical for local planning but are site-specific so cannot be extrapolated or applied more broadly to inform global estimates of coastal impacts. Before presenting the current model, designed to bridge the gap between these two extremes, we first review prominent global direct cost estimates of coastal impacts along key dimensions (summarized in Figure1) and then describe how these studies relate to the present work. Dimensions) increasing)complexity)or)coverage) Present)study) Scope) local& na.onal& regional& global& global& Resolu8on) region& na.on& county& city& property& segment*& Temporal) sta.c& dynamic& dynamic& Other)factors:) Adapta8on) none&(exposure)& fixed&rule& cost<benefit&rule& op.mal& op.mal& SLR)impact) global&mean&SLR& local&SLR& local&SLR& Flood)impact) none& average&surge& surge&PDF& surge&PDF& Figure 1: Characteristics of coastal impact studies for key dimensions or factors, increasing in complexity from left to right. Most aggregate global studies have limited complexity in dimensions other than scope. The present study seeks to improve coverage along many dimensions, as described in the far right column of the diagram. *segment refers to a variable spatial unit between county and property, depending on the extent of roughly homogenous divisions. 3It is not fully understood whether the tail of the surge distribution will be further influenced by climate change (Grinsted et al, 2013) or other factors such as SLR, bathymetry, water depth, or wetland effects (Menéndezand Woodworth, 2010; Cayan et al, 2008; Smith et al, 2010). 3 The first rigorous assessment of SLR was a static vulnerability study of the continental US that quantified the land, population, income, and capital that would be exposed for 4.6 m and 7.6 m SLR scenario (Schneider and Chen, 1980). Such vulnerability assessments have been updated over time with advances in the underlying geophysical and socioeconomic data (see Yohe, 1990; Hoozemans et al, 1993). The next generation of direct cost studies accounted for likely adaptation measures by using a ‘fixed rule' (e.g., protect all coastal zones above a threshold population density) to estimate the total costs of protection measures, coastal retreat, and land inundation. A national study of the US estimated total cost would be between $270 and $475 billion ($1985) for 1 m of SLR in 2100 (Titus et al, 1991), while a similar global assessment estimated $488 billion to protect the world's developed coastlines (Dronkers et al, 1990). A more sophisticated fixed rule approach

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