The Economic Value of Water: Providing Confidence and Context to FEMA’s Methodology

Craig P. Aubuchon; Kevin M. Morley

doi:10.1515/jhsem-2012-0081

Article

The Economic Value of Water: Providing Confidence and Context to FEMA’s Methodology

Craig P. Aubuchon and Kevin M. Morley

Published/Copyright: April 13, 2013

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From the journal Journal of Homeland Security and Emergency Management Volume 10 Issue 1

Abstract

As municipalities, utilities and communities place more emphasis on security, resilience and disaster planning, it is increasingly more important to have an accurate dollar value to assess the economic importance of water for a community. This allows community level decision makers to accurately plan and implement pre-disaster mitigation strategies and effectively allocate resources post-disaster. This decision-making is based in part on a benefit cost analysis framework established by FEMA that establishes several per capita, per day (pcpd) dollar values that capture the total economic impact of the loss of potable water service. A primary motivation of this work is to acknowledge some of the uncertainties and data parameters in the FEMA model so that water utilities can downscale loss projections to the appropriate level of analysis. This study recommends using population weighted state level data and finds an estimated range of economic losses per capita per day between $67 and $457. This research allows utilities to better understand and estimate supply disruption valuations for their own service areas and choose the appropriate risk level for their benefit-cost decisions with regards to security preparedness infrastructure improvements.

Keywords: benefit cost analysis (BCA); drinking water; economic loss; mitigation; resilience

Corresponding author: Craig P. Aubuchon, Analysis Group, Inc., 111 Huntington Avenue, Boston, MA 02199, USA, e-mail: CAubuchon@analysisgroup.com

¹
Hazard mitigation is defined as “any sustained action taken to reduce or eliminate long-term risk to people and property from natural hazards and their effects.” The Hazard Mitigation Assistance program includes five programs: Hazard Mitigation Grant Program, Flood Mitigation Assistance Grant Program, Pre-Disaster Mitigation Program, Repetitive Flood Claims Program and Severe Repetitive Loss Program. The Hazard Mitigation Grant Program (HMGP) provides assistance ex post and accounts for the majority of historic hazard mitigation assistance. In FY09, HMGP spent $359m (out of a total $574m); in FY08, HMGP accounted for $1.2b out of $1.48b. For more detail, see http://www.fema.gov/government/grant/bca.shtm#1.
²
A number of popular media articles detailed the budget resolution. For example, see Hook and Johnson (2011): http://online.wsj.com/article/SB10001424052970204831304576594872744108788.html
³
The original FEMA study is calculated as $93 in 2008 dollars. The current paper presents values as 2011 dollars, adjusted by the Bureau of Labor Statistics all-item Consumer Price Index.
⁴
Throughout the text, we use the term “business” and “industry” loss interchangeably.
⁵
The term lifeline sector is used here as applied by the State, Local, Tribal, and Territorial Government Coordinating Council (SLTTGCC or Council) report Landscape of State and Local Government Critical Infrastructure Resilience Activities & Recommendations, May 2011, to convey the importance of sectors that if compromised and left un-restored would present a risk to human health and safety.
⁶
Brozovic et al. (2007) also account for the extent and severity of a disruption. In contrast, FEMA assumes a full disruption. The estimated economic loss, calculated as the area under a consumer’s demand curve, depends significantly on the amount of water provided. Because of the constant elasticity assumption, any supply of water above a total disruption results in a sharp decrease in the total economic loss. This was modeled with a Monte Carlo simulation, with extent and severity drawn from a uniform distribution (0,1) and elasticity from a normal distribution with mean (–0.41) and standard deviation (0.11). Results are available from the authors upon request.
⁷
See the Office of Management and Budget (OMB) Circular A-94 for a detailed prescription of sensitivity analysis in BCA.
⁸
The Environmental Protection Agency’s (EPA) 2006 Inventory of Community Water Systems (CWS) (2009) has approximately 50,000 CWSs with an estimated 26,000 serving <500 people.
⁹
Rose (2009) provides a comprehensive definition and review of economic resilience and points out that resilience occurs at the individual, economic and macroeconomic scale. Resilience is also comprised of direct impacts and indirect impacts, which can happen in either the positive or negative direction. This analysis works entirely within the current FEMA hazard mitigation methodology, which only considers direct impacts.
¹⁰
Chang et al. (2002) use the raw data from the Disaster Research Center at the University of Delaware, including ex post surveys of 1110 Los Angeles business following the Northridge 1994, and 737 ex ante surveys of Memphis area businesses (Tierney 1997; Tierney and Dahlhamer 1998a,b). They model the probability of business closure as a function of severity and time duration with a Monte Carlo analysis framework.
¹¹
Formally, price elasticity is: . Values between 0 and –1 are termed ‘inelastic’ since a one percent price increase results in less than one percent reduction in demand; a value of –1 is perfectly elastic and magnitudes >–1 are considered elastic.
¹²
For example, the concept of consumer’s demand elasticity is central to designing and implementing water conservation rates. Utilities that face high levels of population growth, large peaking factors (maximum production to average production) or water scarcity may implement conservation rate structures that charge higher prices at higher levels of water consumption. A number of Journal AWWA articles explore conservation rate structures in detail, including Chesnutt and Beecher (1998), Mayer et al. (2008) and Aubuchon and Roberson (2012).
¹³
The authors were unable to verify the source cited by FEMA because the full reference was not included in the BCA report. The primary purpose of this paper is a sensitivity analysis on how state level data, resilience factors, and elasticity parameters influence the FEMA value, thus a sensitivity analysis on price inputs is not necessary and detracts from the broader goal. However, by sharing the FEMA methodology, this paper provides an individual utility with the option to easily include its own price data in calculating loss. It should be noted that the 2010 AWWA/RFC rate survey found a mean price per 1000 gallons of $3.40 in 2008 dollars.

References

Applied Technology Council (ATC) (1985) Earthquake Damage Evaluation Data for California. United States: Federal Emergency Management Agency. p. 492.Search in Google Scholar

Applied Technology Council (ATC) (1991) Seismic Vulnerability and Impact of Disruption of Lifelines in the Counterminous United States. Federal Emergency Management Agency Report, 224.Search in Google Scholar

Aubuchon, C. P. and J. A. Roberson (2012) “Price Perception and Non-price Controls under Conservation Rate Structures,” Journal of American Water Works, 104(8):E446–E456.10.5942/jawwa.2012.104.0101Search in Google Scholar

Brozovic, N., D. L. Sunding and D. Zilberman (2007) “Estimating Business and Residential Water Supply Interruption Losses from Catastrophic Events,” Water Resources Research, 43:1–14.10.1029/2005WR004782Search in Google Scholar

Barakat and Chamberlin Inc., (1994) The Value of Water Supply Reliability: Results of a Contingent Valuation Survey of Residential Customers. Prepared for the California Urban Water Agencies, Oakland, CA.Search in Google Scholar

Chang, S. E., W. D. Svekla and M. Shinozuka (2002) “Linking Infrastructure and Urban Economy: Simulation of Water-Disruption Impacts in Earthquakes,” Environment and Planning B: Planning and Design 29:281–301.10.1068/b2789Search in Google Scholar

Chesnutt T. W. and J. A. Beecher (1998) “Conservation Rates in the Real World,” Journal of American Water Works Association, 90(2):60–70.10.1002/j.1551-8833.1998.tb08378.xSearch in Google Scholar

Dalhuisen, J. M., R. Florax, H. de Groot and P. Nijkamp (2003) “Price and Income Elasticities of Residential Water Demand: A meta-analysis,” Land Economics, 79(2):292–308.10.2307/3146872Search in Google Scholar

Environmental Protection Agency (2009) 2006 Community Water System Survey: Volume I Overview. Avilable at: http://water.epa.gov/aboutow/ogwdw/cwssvr.cfm. (accessed October 10, 2011).Search in Google Scholar

Federal Emergency Management Agency (2010) Hazard Mitigation Assistance Unified Guidance.Search in Google Scholar

Federal Emergency Management Agency (2009) BCA Reference Guide: Final. Prepared by URS group.Search in Google Scholar

Hook, J. and K. Johnson (2011) “Stopgap Fix Ends Budget Impasse: Senate Approves Short-Term Funding Measure After Sticking Point is Resolved,” Wall Street Journal, September 27. Avilable at: http://online.wsj.com/article/SB10001424052970204831304576594872744108788.html.Search in Google Scholar

Jenkins, M. W., J. R. Lund, and R. E. Howitt (2003) “Using Economic Loss Functions to Value Urban Water Scarcity in California,” Journal American Water Works Association 95(2): 58–70.10.1002/j.1551-8833.2003.tb10292.xSearch in Google Scholar

Kajitani, Y. and H. Tatano (2009) “Estimation of Lifeline Resilience Factors based on Surveys of Japanese Industries,” Earthquake Spectra, 25(4):755–776.10.1193/1.3240354Search in Google Scholar

Kenny, J. F., N. L. Barber, S. S. Hutson, K. S. Linsey, J. K. Lovelace, and M. A. Maupin (2009) Estimated use of water in the United States in 2005: U.S. Geological Survey Circular 1344, 52 p. Referenced as (USGS, 2009) in text.10.3133/cir1344Search in Google Scholar

Larsson, A., L. Ekenberg and M. Danielson (2010) “Decision Evaluation of Response Strategies in Emergency Management Using Imprecise Assessments,” Journal of Homeland Security and Emergency Management, 7(1):Article 53.10.2202/1547-7355.1646Search in Google Scholar

Mayer, P. W., W. B. DeOreo, E. M. Opitz, J. C. Kiefer, W. Y. Davis, B. Dziegielewski and J. O. Nelson (1999) Residential End Uses of Water. Denver: AwwaRF and AWWA.Search in Google Scholar

Mayer, P., W. DeOreo, T. Chesnutt and L. Summers (2008) “Water Budgets and Rate Structures: Innovative Management Tools,” Journal of American Water Works Association, 100(5): 117–131.10.1002/j.1551-8833.2008.tb09636.xSearch in Google Scholar

National Drinking Water Advisory Council (2010) Climate Ready Water Utilities Final Report. Avilable at: http://water.epa.gov/drink/ndwac/climatechange/upload/CRWU-NDWAC-Final-Report-12-09-10-2.pdf. (accessed October 10, 2011).Search in Google Scholar

Office of Management and Budget (1992) Circular A-94: Guidelines and Discount Rates for Benefit-Cost Analysis of Federal Programs.Search in Google Scholar

Raucher, B. (2005) “The Value of Water: What it Means, Why It’s Important and How Utility Managers Can Use It,” Journal American Water Works Association, 97(4):90–98.10.1002/j.1551-8833.2005.tb10867.xSearch in Google Scholar

Rockaway, T. D., P. C. Coomes, J. Rivard and B. Kornstein (2011) “Residential Water Use Trends in North America,” Journal of American Water Works Association, 103(2):76–89.10.1002/j.1551-8833.2011.tb11403.xSearch in Google Scholar

Rose, A. (2009) “A Framework for Analyzing the Total Economic Impacts of Terrorist Attacks and Natural Disasters,” Journal of Homeland Security and Emergency Management, 6(1): Article 9.10.2202/1547-7355.1399Search in Google Scholar

Rose, A., K. Porter, N. Dash, J. Bouabid, C. Huyck, J. Whitehead, D. Shaw, R. Eguchi, C. Taylor, T. McLane, T. Tobin, P. Ganderton, D. Godschalk, A. S. Kiremidjian, K. Tierney and C. T. West (2007) “Benefit-Cost Analysis of FEMA Hazard Mitigation Grants,” Natural Hazards Review, 8(4):97–111.10.1061/(ASCE)1527-6988(2007)8:4(97)Search in Google Scholar

Tierney, K. J. (1997) “Business Impacts of the Northridge Earthquake,” Journal of Contingencies and Crisis Management, 5:87–97.10.1111/1468-5973.00040Search in Google Scholar

Tierney, K. J. and J. M. Dahlhamer (1998a) Business Disruption, preparedness, and recovery: lessons from the Northridge Earthquake, in Proceedings of the NEHRP Conference and Workshop on Research on the Northridge, California Earthquake of January 17, 1994 volume IV, California Universities for Research in Earthquake Engineering, Richmond, California, pp. 87–97.Search in Google Scholar

Tierney K. J. and J. M. Dahlhamer (1998b) “Earthquake Vulnerability and Emergency Preparedness among Businesses.” Chapter 5 In: (M. Shinozuka, A. Rose, R. T. Eguchi, eds.) Engineering and Socioeconomic Impacts of Earthquakes. Monograph No 2, Multidisciplinary Center for Earthquake Engineering Research, Red Jacket Quadrangle, State University of New York at Buffalo, Buffalo, NY 14261, pp. 53–74.Search in Google Scholar

Water Utility Climate Alliance (2009) Options for Improving Climate Modeling to Assist Water Utility Planning for Climate Change. Avilable at: http://www.wucaonline.org/html. (accessed October 10, 2011).Search in Google Scholar

Published Online: 2013-04-13

Published in Print: 2013-01-01

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Articles in the same Issue

https://doi.org/10.1515/jhsem-2012-0081

Keywords for this article

benefit cost analysis (BCA); drinking water; economic loss; mitigation; resilience