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The economic value of delaying adaptation to sea-level rise: An application to coastal properties in Connecticut

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Abstract

The magnitude and frequency of coastal storms are expected to increase with rising global sea levels, which necessitates evaluating coastal flood adaptation measures. This study examines an important issue in the context of coastal flood protection, namely, the decision when to adopt protection measures. For any given coastal region, our benefit-cost framework allows us to determine the optimal timing of initiating protection that maximizes expected net benefits. We present an application of this framework to a coastal area in Connecticut. Our results suggest that the optimal timing of adopting protection may vary across different census blocks within the study area. We find that using a relatively low discount rate in the benefit-cost analysis implies greater heterogeneity in the timing decisions and earlier overall adoption, whereas, with higher discount rates, the timing decisions are reduced to a choice between early protection and no protection at all. If possible negative environmental and aesthetic impacts of sea barriers are taken into account, delaying protection would become more desirable, with the extent of delay being sensitive to the relative magnitude of one-time costs (e.g., loss of ocean view and recreational opportunities) vs. continuous costs (e.g., shoreline erosion and loss of wetlands).

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Notes

  1. Although sea-level rise has been the prevalent trend globally, there are some regions of the world (e.g., Alaska) where sea level has been declining over time (see, for example, http://www.tidesandcurrents.noaa.gov/sltrends). Due to the specific focus of this study, we restrict attention to sea-level rise in our subsequent discussion.

  2. This can be partly attributed to the fact that insurance purchase is not always enforced beyond the initial year of the mortgage contract (Landry and Jahan-Parvar 2011).

  3. A feature of the CZMA is that state participation is voluntary. Nevertheless, all coastal states, except for Alaska, are currently enforcing the Act. See http://coastalmanagement.noaa.gov/mystate/welcome.html.

  4. See Section 2.2 for a more detailed discussion of social costs in the case of sea barriers.

  5. Note that the use of a finite time horizon makes our results sensitive to the length of the horizon. Nonetheless, for a large enough t T the approximation error would be of small magnitude.

  6. While in theory more than one flood event may occur at a given locality during the year, evidence of such multiple occurrences in the U.S. is rare. Thus, we make the simplifying assumption that only one random event takes place every year.

  7. This framework assumes that a one-year flood, which is equaled or exceeded with certainty every year, generates no damages, i.e., D(1) = 0.

  8. Note that the damage function D jt (R) depends on the characteristics of the flooded area j in the specific year t when the flood takes place. Hence, this function accounts for the condition of properties in j at the start of year t (e.g., whether they are already damaged by a flood that took place in an earlier year) when determining the damages by any flood event in year t and allows for the possibility that recurring floods lead to asset write-off.

  9. For example, a 100-year flood event has the same probability of being equaled or exceeded as a flood of the size that corresponds to a 100-year flood event.

  10. On the one hand, by slowing down the storm waters, a seawall/levee may reduce total damages from events greater than a 100-year flood, even if storm surge during these events exceeds the height of the structure resulting in overflow. On the other hand, if overflow leads to structural failure, debris from the structure could cause additional damage to the property behind it, while the costs of repairing the structure would also add to total damage costs. Although, in general, damages from structural breach are uncertain and region-specific (see, for example, Dawson and Hall 2006), we make the simplifying assumption that the above effects fully offset each other.

  11. If due to sea level rise a sea barrier can no longer grant protection against a 100-year flood, it fails to meet the Federal regulations. If the costs of removing the structure are relatively high, which one would anticipate given the substantial length and height of structures in our analysis, the assumption of regular maintenance and retrofitting to keep up with the sea level is quite sensible.

  12. Unlike the more general conceptual model in Section 2.2, the Flood Module has an inbuilt assumption that damaged buildings are repaired (or replaced, if damages exceed 50 %) following each flood event (Scawthorn et al. 2006b).

  13. When running the simulations over the entire 100-year period, we make the simplifying assumption that the real value of building contents remains unchanged over time. In reality, existing building and content values may depreciate due to aging.

  14. Federal Information Processing Standard (FIPS) codes are used to identify geographical entities, such as countries, states, counties, and county subdivisions. For more information, see http://quickfacts.census.gov/qfd/meta/long_fips.htm.

  15. HAZUS requires data only on 100-year flood stillwater elevation. The Flood Module then computes values for elevations for other flood events based on the 100-year value and default flood elevation ratios (FEMA 2009).

  16. Local flood insurance studies can be found at http://store.msc.fema.gov.

  17. It should be noted that linear addition of sea-level rise and storm surge levels may result in omitting additional changes (positive or negative) in surge levels due to dynamic interactions within the storm system driven by sea-level rise (Hagen and Bacopoulos 2012). While modeling these processes requires introducing additional non-linearity in the framework (e.g., Mousavi et al. 2011; Lin et al. 2012), our study settles for a more pragmatic approximation approach, in line with recent practical guidelines for risk analysis (e.g., DEFRA and Environment Agency 2011).

  18. Other functional forms (linear, log-linear, and polynomial) were also fitted through the data, but showed worse fits relative to the log-log form.

  19. A list of all α jt . and β jt . values obtained from the interpolation is available in Online Resource 1.

  20. Note that the function exp(α)R β yields D(1) > 0, while in reality damages become negligible for small flood events. Hence, we assume that D(R) = 0 for R < 2.

  21. Although in practice floods greater than a 500-year event exist, HAZUS does not include simulations for these events. Since the relevant range for determining the optimal timing of protection in our analysis is R ∈ [1,100], lack of data on more extreme events would not affect our results significantly, as long as the interpolated damage function D(R) is relatively robust to the exclusion of these events. Unfortunately, data limitation prevents us from testing the latter assumption.

  22. Other functional forms (linear, log-linear, and log-log) were also fitted through the report’s estimates. The polynomial form gave the best fit (R 2 = 0.994) and is therefore the one we use in our final analysis.

  23. To the extent that raising an existing sea barrier involves not only expanding its width and height, but also replacing parts of the initial structure, this method can lead to underestimation of retrofit costs. However, within our relatively simple framework, it offers a reasonable approximation, as it preserves the sensible notion that constructing a barrier of a given height involves lower total costs when done all at once rather than piecewise over time.

  24. See http://seamless.usgs.gov.

  25. See Online Resource 2 for more details.

  26. One-percent wave refers to the wave height at the shore that could be either reached or exceeded with 1 % probability during a 100-year flood event. See Online Resource 2 for details.

  27. Other papers studying the impacts of gradual sea-level rise over the course of the next century (e.g., Yohe et al. 1995; Pendleton et al. 2011; Kirshen et al. 2012; Pendleton et al. 2012) have also conducted their analyses on a decadal (or longer-period) basis.

  28. Our choice of 3 % follows the general recommendations of the U.S. Environmental Protection Agency with regards to discounting benefits and costs over the longer time horizon relevant for climate change policies (EPA 2008, p. 9). A 3 % rate has also been adopted by other recent climate-related studies conducting assessments over a 100-year horizon (Dorbian et al. 2011; Neumann et al. 2011; Azar and Johansson 2012). It should be noted, however, that a wider range of discount rates have been used in the literature and the choice of appropriate discount rate for evaluating environmental projects is still subject to debate (e.g., Carson and Tran 2009).

  29. Complete output (optimal height and length of the protective structure, HAZUS-generated flood damage data for five return periods, costs and benefits of protection, and timing of protection) for each census block at various discount rates and costs is presented in Online Resource 3.

  30. See, for example, costs and damages for census blocks #111-4000, #111-4005, and #111-4016 in Online Resource 3, which appear relatively stable at different sea levels.

  31. See, for example, damages at different sea levels for census blocks #111-3004, #112-1041, and #112-1045 in Online Resource 3.

  32. E.g., census blocks #108-1006, #108-3009, and #112-1032.

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Acknowledgements

Research for this paper was supported by the Center for Environmental Sciences and Engineering (CESE) at the University of Connecticut and by the U.S. Department of Agriculture. The views expressed in this paper are solely ours and are not to be attributed to any of the sponsors. We extend our gratitude to Kathleen Segerson, Stephen Ross, Michael Willig, and Glenn Warner, along with the journal editors and three anonymous reviewers, for their helpful comments and suggestions. Any remaining errors are our own.

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  1. Department of Agricultural and Resource Economics, University of Connecticut, 3107 Horsebarn Hill Rd, Unit 4021, Storrs, CT, 06269, USA

    Tsvetan G. Tsvetanov

  2. Department of Agricultural and Resource Economics, University of Connecticut, 3107 Horsebarn Hill Rd, Unit 4021, Storrs, CT, 06269, USA

    Farhed A. Shah

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Correspondence to Tsvetan G. Tsvetanov.

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Tsvetanov, T.G., Shah, F.A. The economic value of delaying adaptation to sea-level rise: An application to coastal properties in Connecticut. Climatic Change 121, 177–193 (2013). https://doi.org/10.1007/s10584-013-0848-7

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