Climatic Change

, Volume 133, Issue 4, pp 665–679

Vulnerability assessment for loss of access to drinking water due to extreme weather events

  • Jeanne Luh
  • Elizabeth C. Christenson
  • Aizhan Toregozhina
  • David A. Holcomb
  • Tucker Witsil
  • Laura R. Hamrick
  • Edema Ojomo
  • Jamie Bartram
Article

DOI: 10.1007/s10584-015-1493-0

Cite this article as:
Luh, J., Christenson, E.C., Toregozhina, A. et al. Climatic Change (2015) 133: 665. doi:10.1007/s10584-015-1493-0

Abstract

Climate-related extreme weather events can result in the loss of drinking water access. We assessed the relative vulnerability of 3143 United States (U.S.) counties to loss of drinking water access due to droughts, floods, and cyclones. Five vulnerability assessment models from the literature were compared, each differing in the aggregation method used to combine the three determinants of vulnerability (V) – exposure (E), sensitivity (S), and adaptive capacity (AC). Exposure scores were calculated using historical occurrence data, sensitivity scores were determined from the intrinsic resilience of the drinking water technologies, and adaptive capacity scores were calculated from nine socioeconomic indicators. Our results showed that models V = E + S + AC and V = E + SAC were the same, as were models V = E × S × AC and V = E × S ÷ AC. Between these two model forms (form 1: V = E + S + AC and V = E + SAC; form 2: V = E × S × AC and V = E × S ÷ AC), scores from one model form could be used to predict scores from the second model form, with R-squared values ranging from 0.61 to 0.82 depending on the extreme weather event type. A fifth model, V = (EAC) × S was not found to correlate with any of the other four models. We used V = E + S + AC as our reference model as this resulted in a more uniform distribution of counties in each of the five intervals of vulnerability. Comparing the vulnerability scores identified the counties with greatest vulnerability to losing access to drinking water due to floods, droughts, and cyclones. Our results can be used to inform evidence-based decisions such as allocation of resources and implementation of adaptation strategies.

Supplementary material

10584_2015_1493_MOESM1_ESM.pdf (3.5 mb)
ESM 1(PDF 3556 kb)

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Jeanne Luh
    • 1
  • Elizabeth C. Christenson
    • 1
  • Aizhan Toregozhina
    • 1
  • David A. Holcomb
    • 1
  • Tucker Witsil
    • 1
  • Laura R. Hamrick
    • 1
  • Edema Ojomo
    • 1
  • Jamie Bartram
    • 1
  1. 1.The Water Institute, Department of Environmental Sciences and Engineering, Gillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillUSA