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Assessing the Vulnerability of California Water Utilities to Wildfires

Author

Listed:
  • Juhee Lee

    (University of California, 900 University Ave. Riverside)

  • Mehdi Nemati

    (University of California, 900 University Ave. Riverside)

  • Jose J. Sanchez

    (USDA Forest Service Pacific Southwest Research Station)

Abstract

Wildfires are becoming more frequent and destructive in California, and it is essential to quantify their potential impacts on drinking water utilities. This study aims to measure the severity of wildfires in each California water utility based on the exposure frequency and the extent of area burned by wildfires in each service area. Our quantitative models show an association between water utility characteristics and their vulnerability to wildfires. Findings indicate that wildfire vulnerability is higher in government-owned utilities than private ones, utilities primarily relying on surface water than groundwater, and utilities using local-sourced water than purchased water. Also, we find a stronger association between wildfire vulnerability and large utilities in terms of population served than small or medium ones. Regarding geography, we find wildfire vulnerability is higher in southern and coastal California utilities than in Northern and inland California. These results help water utilities and land managers identify vulnerable locations and develop wildfire management and disaster preparedness strategies.

Suggested Citation

  • Juhee Lee & Mehdi Nemati & Jose J. Sanchez, 2022. "Assessing the Vulnerability of California Water Utilities to Wildfires," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(11), pages 4183-4199, September.
    • Handle: RePEc:spr:waterr:v:36:y:2022:i:11:d:10.1007_s11269-022-03247-5
    DOI: 10.1007/s11269-022-03247-5
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    References listed on IDEAS

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    1. James J. Heckman, 1976. "The Common Structure of Statistical Models of Truncation, Sample Selection and Limited Dependent Variables and a Simple Estimator for Such Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 5, number 4, pages 475-492, National Bureau of Economic Research, Inc.
    2. Amemiya, Yasuo, 1985. "Instrumental variable estimator for the nonlinear errors-in-variables model," Journal of Econometrics, Elsevier, vol. 28(3), pages 273-289, June.
    3. Jia Coco Liu & Loretta J. Mickley & Melissa P. Sulprizio & Francesca Dominici & Xu Yue & Keita Ebisu & Georgiana Brooke Anderson & Rafi F. A. Khan & Mercedes A. Bravo & Michelle L. Bell, 2016. "Particulate air pollution from wildfires in the Western US under climate change," Climatic Change, Springer, vol. 138(3), pages 655-666, October.
    4. MaCurdy, Thomas E & Pencavel, John H, 1986. "Testing between Competing Models of Wage and Employment Determination in Unionized Markets," Journal of Political Economy, University of Chicago Press, vol. 94(3), pages 3-39, June.
    5. Heckman, James J, 1974. "Shadow Prices, Market Wages, and Labor Supply," Econometrica, Econometric Society, vol. 42(4), pages 679-694, July.
    6. Francis Vella, 1998. "Estimating Models with Sample Selection Bias: A Survey," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 127-169.
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