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Water quality indices and benefit-cost analysis

Published online by Cambridge University Press:  19 January 2015

Patrick J. Walsh  and
William J. Wheeler
Patrick J. Walsh*
Affiliation:
US EPA, National Center for Environmental Economics, 1200 Pennsylvania Avenue, Ariel Rios Bldg, MC1809T DC Washington 20460, USA
William J. Wheeler
Affiliation:
US EPA, National Center for Environmental Economics, 1200 Pennsylvania Avenue, Ariel Rios Bldg, MC1809T DC Washington 20460, USA
*
Patrick J. Walsh, US EPA, National Center for Environmental Economics, 1200 Pennsylvania Avenue, Ariel Rios Bldg, MC1809T DC Washington 20460, USA, walsh.patrick@epa.gov
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Abstract

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The water quality index (WQI) has emerged as a central way to convey water quality information to policy makers and the general public and is regularly used in US EPA regulatory impact analysis. It is a compound indicator that aggregates information from several water quality parameters. Several recent studies have criticized the aggregation function of the EPA WQI, arguing that it suffers from “eclipsing” and other problems. Although past papers have compared various aggregation functions in the WQI (usually looking at correlation), this is the first paper to examine these functions in the context of benefit-cost analysis. Using data from the 2003 EPA CAFO rule, the present paper examines four aggregation functions and their impact on estimated benefits. Results indicate that the aggregation method can have a profound effect on benefits, with total benefit estimates varying from $82 million to $504 million dollars. The net benefits of the rule vary from negative to positive over this range of estimates. Furthermore, a sensitivity analysis does not find convincing evidence to substitute the current aggregation function, although several changes to the underlying WQI methodology may be warranted.

Keywords

cost benefit analysisvaluationwater qualitywater quality index
Type
Article
Information
Journal of Benefit-Cost Analysis , Volume 4 , Issue 1 , 28 March 2013 , pp. 81 - 105
Copyright
Copyright © Society for Benefit-Cost Analysis 2013

References

Bhargava, D. S. (1983). Use of water quality index for river classification and Zoning of Ganga river. Environmental Pollution Series B, Chemical and Physical, 6(1), 51–67.CrossRefGoogle Scholar
Binkley, C. S., & Hanemann, W. M. (1978). The recreation benefits of water quality improvement: analysis of day trips in an urban setting. Report No. EPA-600/5-78-010. Washington, DC: U.S. Environmental Protection Agency.Google Scholar
Brown, R. M., McClelland, N. I., Deininger, R. A., & Tozer, R. G. (1970). A water quality index – do we dare? Water and Sewage Works, 11, 339–343.Google Scholar
Carruthers, T., & Wazniak, C. (2004). Development of a water quality index for the Maryland Coastal Bays. In: Wazniak, C. E. & Hall, M. R. (Eds.), Maryland’s Coastal Bays: Ecosystem Health Assessment 2004. DNR-12-1202-0009. Annapolis, MD: Maryland Department of Natural Resources Tidewater Ecosystem Assessment.Google Scholar
Carson, R. T., & Mitchell, R. C. (1993). The value of clean water: the public’s willingness to pay for boatable, fishable, and swimmable quality water. Water Resources Research, 29(7), 2445–2454.CrossRefGoogle Scholar
Chang, N. -B., Chen, H. W., & Ning, S. K. (2001). Identification of river water quality using the fuzzy synthetic evaluation approach. Journal of Environmental Management, 63(3), 293–305.CrossRefGoogle ScholarPubMed
Cude, C. G. (2001). Oregon water quality index: a tool for evaluating water quality management effectiveness. JAWRA Journal of the American Water Resources Association, 37(1), 125–137.CrossRefGoogle Scholar
Dalkey, N. C. (1968). The Delphi method: an experimental survey of group opinion. RAND Corporation Paper Series RM-5888-PR. Available at: http://www.rand.org/pubs/research_memoranda/RM5888.html.Google Scholar
Diewert, W. E. (1993). Symmetric means and choice under uncertainty. Essays in Index Number Theory (Vol. 1), North Holland, London.Google Scholar
Dojlido, J., Raniszewski, J., & Woyciechowska, J. (1994). Water quality index applied to rivers in the vistula river basin in Poland. Environmental Monitoring and Assessment, 33(1), 33–42.CrossRefGoogle ScholarPubMed
Dunnette, D. A. (1979). A geographically variable water quality index used in Oregon. Journal of the Water Pollution Control Federation, 51(1), 53–61.Google Scholar
Eom, Y. S., & Larson, D. M. (2006). Improving environmental valuation estimates through consistent use of revealed and stated preference information. Journal of Environmental Economics and Management, 52, 501–516.CrossRefGoogle Scholar
Flores, J. C. (2002). Comments to the use of water quality indices to verify the impact of Cordoba City (Argentina) on Suquia river. Water Research, 36(18), 4664–4666.CrossRefGoogle Scholar
Griffiths, C., Klemick, H., Massey, D. M., Moore, C., Newbold, S., Simpson, R. D., ..... Wheeler, W. (2012). EPA valuation of surface water quality improvements. Review of Environmental Economics and Policy, 6(1), 130–146.CrossRefGoogle Scholar
Gupta, A. K., Gupta, S. K., & Patil, R. S. (2003). A Comparison of Water quality indices for coastal water. Journal of Environmental Science and Health, Part A, 38(11), 2711–2725.CrossRefGoogle ScholarPubMed
Horton, R. K. (1965). An index-number system for rating water quality. Journal of the Water Pollution Control Federation, 37(3), 300–305.Google Scholar
Hoyer, M. V., Brown, C. D., & Canfield, D. E. Jr., (2004). Relation between water chemistry and water quality as defined by lake users in Florida. Lake and Reservoir Management, 20, 240–248.CrossRefGoogle Scholar
Jeon, Y., Herriges, J. A., Kling, C. L., & Downing, J. (2005). The role of water quality perceptions in modeling lake recreation demand. Iowa State University, Department of Economics Working Paper #05032.Google Scholar
Johnston, R. J., Besedin, E. Y., Iovanna, R., Miller, C. J., Wardwell, R. F., & Ranson, M. H. (2005). Systematic variation in willingness to pay for aquatic resource improvements and implications for benefit transfer: a meta-analysis. Canadian Journal of Agricultural Economics/Revue canadienne d’agroeconomie, 53(2–3), 221–248.CrossRefGoogle Scholar
Johnston, R. J., Besedin, E. Y., & Wardwell, R. F. (2003). Modeling relationships between use and nonuse values for surface water quality: a meta-analysis. Water Resources Research, 39(12), 1363.CrossRefGoogle Scholar
Johnston, R. J., Schultz, E. T., Segerson, K., Besedin, E. Y., & Ramachandran, M. (2012). Enhancing the content validity of stated preference valuation: the structure and function of ecological indicators. Land Economics, 88, 102–120.CrossRefGoogle Scholar
Khan, F., Husain, T., & Lumb, A. (2003). Water quality evaluation and trend analysis in selected watersheds of the atlantic region of Canada. Environmental Monitoring and Assessment, 88(1), 221–248.CrossRefGoogle ScholarPubMed
Kung, H., Ying, L., & Liu, Y. (1992). A complementary tool to water quality index: fuzzy clustering analysis. JAWRA Journal of the American Water Resources Association 28(3), 525–533.CrossRefGoogle Scholar
Landwehr, J. M., & Deininger, R. A. (1976). A comparison of several water quality indices. Journal of the Water Pollution Control Federation, 48(5), 954–958.Google Scholar
Liou, S. M., Lo, S. L., & Wang, S. H. (2004). A generalized water quality index for Taiwan. Environmental Monitoring and Assessment, 96(1), 35–52.CrossRefGoogle ScholarPubMed
McClelland, N. I. (1974). Water quality index application in the Kansas river basin. EPA-907/9-74-001. Kansas City, MO: US EPA Region VII.Google Scholar
Mercer, P. (2003). Refined arithmetic, geometric, and harmonic mean inequalities. Rocky Mountain Journal of Mathematics, 33(4), 1459–1464.CrossRefGoogle Scholar
Mitchell, R. C., & Carson, R. T.. (1981). An experiment in determining willingness to pay for national water quality improvements, report to the US Environmental Protection Agency. Washington, D.C: Resources for the Future.Google Scholar
Mitchell, R. C., & Carson, R. T. (1989). Using surveys to value public goods: the contingent valuation method. Washington, D.C.: Resources for the Future.Google Scholar
Morgan, M. G., & Henrion, M. (1990). Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Michael, H. J., Boyle, K. J., & Bouchard, R. (2000). Does the measurement of environmental quality affect implicit prices estimated from hedonic models? Land Economics, 76(2), 283–298.CrossRefGoogle Scholar
Nagels, J. W., Davies-Colley, R. J., & Smith, D. G. (2001). A water quality index for contact recreation in New Zealand. Water Science and Technology, 43(5), 285–292.CrossRefGoogle ScholarPubMed
Ott, W. R. (1978). Water quality indices: a survey of indices used in the United States (pp. 1–138). Washington DC: US Environmental Protection Agency. EPA-600/4-78-005.Google Scholar
Parparov, A., Hambright, K., Hakanson, L., & Ostapenia, A. (2006). Water quality quantification: basics and implementation. Hydrobiologia, 560(1), 227–237.CrossRefGoogle Scholar
Pendleton, L., Martin, N., & Webster, D. G. (2001). Public perceptions of environmental quality: a survey study of beach use and perceptions in Los Angeles county. Marine Pollution Bulletin, 42, 1155–1160.CrossRefGoogle ScholarPubMed
Pesce, S. F., & Wunderlin, D. A. (2000). Use of water quality indices to verify the impact of Córdoba City (Argentina) on Suquía River. Water Research, 34(11), 2915–2926.CrossRefGoogle Scholar
Prakirake, C., Chaiprasert, P., & Tripetchkul, S. (2009). Development of specific water quality index for water quality supply in Thailand. Songklanakarian Journal of Science and Technology, 31(1), 91–104.Google Scholar
Sarkar, C., & Abbasi, S. A. (2006). Qualidex – a new software for generating water quality indice. Environmental Monitoring and Assessment, 119(1), 201–231 CrossRefGoogle Scholar
Simões, F. S., Moreira, A. B., Bisinoti, M. C., Gimenez, S. M. N., & Yabe, M. J. S. (2008). Water quality index as a simple indicator of aquaculture effects on aquatic bodies. Ecological Indicators, 8(5), 476–484.CrossRefGoogle Scholar
Smith, D. G. (1990). A better water quality indexing system for rivers and streams. Water Research 24(10), 1237–1244.CrossRefGoogle Scholar
Smith, V. K., & Desvousges, W. H. (1986). Measuring water quality benefits. Boston: Kluwer Nijhoff.CrossRefGoogle Scholar
Swamee, P. K., & Tyagi, A. (2000). Describing water quality with aggregate index. Journal of Environmental Engineering, 126(5), 451–455.CrossRefGoogle Scholar
Taner, M. Ü., Üstün, B., & Erdinçler, A. (2011). A simple tool for the assessment of water quality in polluted lagoon systems: a case study for Küçükçekmece Lagoon, Turkey. Ecological Indicators, 11(2), 749–756.CrossRefGoogle Scholar
U.S. EPA. (2000). A benefits assessment of water pollution control programs since 1972: Part 1, the benefits of point source controls for conventional pollutants in rivers and streams., Washington, DC: Final report to the U.S. EPA, Office of Water. EPA-68-C6-0021.Google Scholar
U.S. EPA. (2003a). Environmental and economic benefit analysis of the final revisions to the national pollutant discharge elimination system regulation and the effluent guidelines for concentrated animal feeding operations. Washington, DC: Office of Water. EPA-821-R-03-003.Google Scholar
U.S. EPA. (2003b). Estimation of national economic benefits using the national water pollution control assessment model to evaluate regulatory options for Concentrated Animal Feeding Operations (CAFOs). Washington, DC: Office of Water. EPA-821-R-03-009.Google Scholar
U.S. EPA. (2004a). Economic and environmental benefits analysis of the final effluent limitations guidelines and new source performance standards for the concentrated aquatic animal production IndU.S.try point source category. Washington, DC: Office of Water. EPA-821-R-04-013.Google Scholar
U.S. EPA. (2004b). Economic and environmental benefits analysis of the final meat and poultry products rule. Washington, DC: Office of Water. EPA-821-R-04-010.Google Scholar
U.S. EPA. (2009). Environmental impact and benefits assessment for final effluent guidelines and standards for the construction and development category. Washington, DC: EPA Office of Water. EPA-821-R-09-012.Google Scholar
U.S. EPA. (2010). Economic analysis of final water quality standards for nutrients for lakes and flowing waters in Florida. Washington, DC: Office of Water.Google Scholar
Van Houtven, G., Powers, J., & Pattanayak, S. K. (2007). Valuing water quality improvements in the united states using meta-analysis: is the glass half-full or half-empty for national policy analysis? Resource and Energy Economics, 29(3), 206–228.CrossRefGoogle Scholar
Van Houtven, G., Pattanayak, S. K., Patil, S., & Depro, B. (2011). Benefits transfer of a third kind: an examination of structural benefits transfer. In: Whitehead, J., Haab, T., & Huang, J.-C. (Eds.), Preference data for environmental valuation: combining revealed and stated approaches (pp. 303–321). New York: Routledge.Google Scholar
Vaughan, W. J. (1981). The water quality ladder. In: Mitchell, R. C., & Carson, R. T. (Appendix II), An experiment in determining willingness to pay for national water quality improvement, draft report. (Available at: http://yosemite.epa.gov/ee/epa/eerm.nsf/vwAN/EE-0011-04.pdf/$file/EE-0011-04.pdf).Google Scholar
Walski, T. M., & Parker, F. L. (1974). Consumers water quality index. Journal of the Environmental Engineering Division, 100(3), 593–611.CrossRefGoogle Scholar