Incorporating Potential Severity into Vulnerability Assessment of Water Supply Systems under Climate Change Conditions
Publication: Journal of Water Resources Planning and Management
Volume 142, Issue 2
Abstract
In response to climate change, vulnerability assessment of water resources systems is typically performed based on quantifying the severity of the failure. This paper introduces an approach to assess vulnerability that incorporates a set of new factors. The method is demonstrated with a case study of a reservoir system in Salt Lake City using an integrated modeling framework composed of a hydrologic model and a systems model driven by temperature and precipitation data for a 30-year historical (1981–2010) period. The climate of the selected future (2036–2065) simulation periods were represented by five combinations of warm or hot, wet or dry, and central tendency projections derived from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project Phase 5. The results of the analysis illustrate that basing vulnerability on severity alone may lead to an incorrect quantification of the system vulnerability. In this study, a typical vulnerability metric (severity) incorrectly provides low magnitudes under the projected future warm-wet climate condition. The proposed new metric correctly indicates the vulnerability to be high because it accounts for additional factors. To further explore the new factors, a sensitivity analysis (SA) was performed to show the impact and importance of the factors on the vulnerability of the system under different climate conditions. The new metric provides a comprehensive representation of system vulnerability under climate change scenarios, which can help decision makers and stakeholders evaluate system operation and infrastructure changes for climate adaptation.
Get full access to this article
View all available purchase options and get full access to this article.
Acknowledgments
The support and cooperation of the Salt Lake City Department of Public Utilities, specifically Jeff Niermeyer, Laura Briefer, and Tracie Kirkham are gratefully acknowledged. In addition, the authors acknowledge the support of Western Water Assessment to permit Tim Bardsley to contribute as a coauthor, and the National Oceanic and Atmospheric Association (NOAA) Colorado River Basin Forecast Center supporting the hydrologic modeling. The authors also acknowledge Mike Hobbins, NOAA Physical Science Division, for his contribution to generate temperature driven dynamic PET inputs for the CBRFC model. This research was primarily funded through National Science Foundation awards EPS—1135482 and EPS—1135483. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. The authors acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and the authors thank the climate modeling groups (listed in Table 9 of this paper) for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals.
References
Acosta, I., and Martínez, M. (2014). “Assessment of surface runoff vulnerability to climate change in the Lerma-Chapala basin, Mexico.” J. Water Resour. Plann. Manage., 04014042.
Anderson, E. A. (1973). “National Weather Service river forecast system: snow accumulation and ablation model.”, U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Weather Service, Washington, DC.
Asefa, T., Clayton, J., Adams, A., and Anderson, D. (2014). “Performance evaluation of a water resources system under varying climatic conditions: Reliability, resilience, vulnerability and beyond.” J. Hydrol., 508, 53–65.
Ashofteh, P., Haddad, O., and Mariño, M. A. (2012). “Climate change impact on reservoir performance indexes in agricultural water supply.” J. Irrig. Drain. Eng., 85–97.
Ault, T. R., Cole, J. E., and St. George, S. (2012). “The amplitude of decadal to multidecadal variability in precipitation simulated by state-of-the-art climate models.” Geophys. Res. Lett., 39(21), L21705.
Bergström, S., Carlsson, B., Gardelin, M., Lindström, G., Pettersson, A., and Rummukainen, M. (2001). “Climate change impacts on runoff in Sweden-assessments by global climate models, dynamical downscaling and hydrological modelling.” Clim. Res., 16(2), 101–112.
Bureau of Reclamation. (2008). “Sensitivity of future CVP/SWP operations to potential climate change and associated sea level rise.” Bureau of Reclamation, U.S. Dept. of the Interior, Sacramento, CA, 134.
Burnash, R. J. C. (1995). “The NWS river forecast system: catchment modeling.” Computer models of watershed hydrology, V. P. Singh, ed., Water Resources, 311–366.
Burnash, R. J. C., Ferral, R. L., and McGuire, R. A. (1973). “A generalized streamflow simulation system: conceptual modeling for digital computers.”, U.S. Dept. of Commerce, National Weather Service, and State of California, Dept. of Water Resources.
Chen, H., Guo, S., Xu, C.-Y., and Singh, V. P. (2007). “Historical temporal trends of hydro-climatic variables and runoff response to climate variability and their relevance in water resource management in the Hanjiang basin.” J. Hydrol., 344(3–4), 171–184.
Christensen, N., Wood, A., Voisin, N., Lettenmaier, D., and Palmer, R. (2004). “The effects of climate change on the hydrology and water resources of the Colorado River basin.” Clim. Change, 62(1–3), 337–363.
Daniel, C. (1973). “One-at-a-time-plans.” J. Am. Stat. Assoc., 68(342), 353–360.
Fischer, E. M., Beyerle, U., and Knutti, R. (2013). “Robust spatially aggregated projections of climate extremes.” Nat. Clim. Change, 3(12), 1033–1038.
Fowler, H. J., Kilsby, C. G., and O’Connell, P. E. (2003). “Modeling the impacts of climatic change and variability on the reliability, resilience, and vulnerability of a water resource system.” Water Resour. Res., 39(8), 1222.
Frederick, K. D., and Gleick, P. H. (1999). “Water and global climate change: Potential impacts on U.S. water resources.” Pew Center on Global Climate Change, Arlington, VA.
Füssel, H.-M. (2010). “Review and quantitative analysis of indices of climate change exposure, adaptive capacity, sensitivity, and impacts.” 〈https://openknowledge.worldbank.org/handle/10986/9193〉 (Jul. 20, 2015).
Goharian, E., Burian, S., Bardsley, T., and Kirkham, T. (2013). “Evaluating the reliability of a water supply system based on system dynamics modeling: A case study of Salt Lake City, Utah.” 2013 World Environmental and Water Resources Congress, ASCE, Reston, VA.
GoldSim Technology Group. (2013). GoldSim user’s manual, Issaquah, WA.
Guo, S., Wang, J., Xiong, L., Ying, A., and Li, D. (2002). “A macro-scale and semi-distributed monthly water balance model to predict climate change impacts in China.” J. Hydrol., 268(1–4), 1–15.
Gyawali, R., and Watkins, D. (2013). “Continuous hydrologic modeling of snow-affected watersheds in the great lakes basin using HEC-HMS.” J. Hydrol. Eng., 29–39.
Hashimoto, T., Stedinger, J. R., and Loucks, D. P. (1982). “Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation.” Water Resour. Res., 18(1), 14–20.
Hobbins, M. T., Wood, A., Streubel, D., and Werner, K. (2012). “What drives the variability of evaporative demand across the conterminous United States?” J. Hydrometeorol., 13(4), 1195–1214.
IPCC (Intergovernmental Panel on Climate Change). (2007). “The physical science basis.” Contribution of Working Group I to the Fourth Assessment Rep. of the Intergovernmental Panel on Climate Change, S. Solomon, et al., eds., Cambridge University Press, Cambridge, U.K.
IPCC (Intergovernmental Panel on Climate Change). (2013). “The physical science basis.” Contribution of Working Group I to the Fifth Assessment Rep. of the Intergovernmental Panel on Climate Change.” T. F. Stocker, et al., eds., Cambridge University Press, Cambridge, U.K., 1535.
Jenks, G. F. (1967). “The data model concept in statistical mapping.” Int. Yearbook Cartography, 7, 186–190.
Kanta, L., and Brumbelow, K. (2013). “Vulnerability, risk, and mitigation assessment of water distribution systems for insufficient fire flows.” J. Water Resour. Plann. Manage., 593–603.
Karamouz, M., Goharian, E., and Nazif, S. (2013). “Reliability assessment of the water supply systems under uncertain future extreme climate conditions.” Earth Interact., 17(20), 1–27.
Kunkel, K. E., et al. (2013). “Probable maximum precipitation and climate change.” Geophys. Res. Lett., 40(7), 1402–1408.
Lanini, J., Dozier, A., Furey, P., and Kampf, S. (2014). “Stochastic method for examining vulnerability of hydropower generation and reservoir operations to climate change: Case study of the Dworshak Reservoir in Idaho.” J. Water Resour. Plann. Manage., 05014004.
Loucks, D. P. (1997). “Quantifying trends in system sustainability.” Hydrol. Sci. J., 42(4), 513–530.
Maurer, E. P., Brekke, L., Pruitt, T., and Duffy, P. B. (2007). “Fine-resolution climate projections enhance regional climate change impact studies.” Eos. Trans. AGU, 88(47), 504.
Miller, W. P., Piechota, T. C., Gangopadhyay, S., and Pruitt, T. (2011). “Development of streamflow projections under changing climate conditions over Colorado River basin headwaters.” Hydrol. Earth Syst. Sci., 15(7), 2145–2164.
Nadal, N., Zapata, R., Pagán, I., López, R., and Agudelo, J. (2010). “Building damage due to riverine and coastal floods.” J. Water Resour. Plann. Manage., 327–336.
Scoccimarro, E., Gualdi, S., Bellucci, A., Zampieri, M., and Navarra, A. (2013). “Heavy precipitation events in a warmer climate: Results from CMIP5 models.” J. Clim., 26(20), 7902–7911.
Seager, R., et al. (2007). “Model projections of an imminent transition to a more arid climate in southwestern North America.” Science, 316(5828), 1181–1184.
Sedláček, J., and Knutti, R. (2012). “Evidence for external forcing on 20th-century climate from combined ocean-atmosphere warming patterns.” Geophys. Res. Lett., 39(20), L20708.
Simonovic, S., and Li, L. (2003). “Methodology for assessment of climate change impacts on large-scale flood protection system.” J. Water Resour. Plann. Manage., 361–371.
Stewart, I. T., Cayan, D. R., and Dettinger, M. D. (2005). “Changes toward earlier streamflow timing across western North America.” J. Clim., 18(8), 1136–1155.
Tabor, K., and Williams, J. W. (2010). “Globally downscaled climate projections for assessing the conservation impacts of climate change.” Ecol. Appl., 20(2), 554–565.
Utah Division of Water Resources. (2009). “Residential water use: Survey results and analysis of residential water use for seventeenth communities in Utah.” Salt Lake City.
Vicuña, S., McPhee, J., and Garreaud, R. (2012). “Agriculture vulnerability to climate change in a snowmelt-driven basin in semiarid Chile.” J. Water Resour. Plann. Manage., 431–441.
Vogel, R., Lane, M., Ravindiran, R., and Kirshen, P. (1999). “Storage reservoir behavior in the United States.” J. Water Resour. Plann. Manage., 245–254.
Wilby, R. L., Charles, S. P., Zorita, E., Timbal, B., Whetton, P., and Mearns, L. O. (2004). “Guidelines for use of climate scenarios developed from statistical downscaling methods.” 〈http://www.ipcc-data.org/guidelines/dgm_no2_v1_09_2004.pdf〉 (Jul. 20, 2015).
Wood, A. W., Leung, L. R., Sridhar, V., and Lettenmaier, D. P. (2004). “Hydrologic implications of dynamical and statistical approaches to downscaling climate model outputs.” Clim. Change, 62(1–3), 189–216.
Zahmatkesh, Z., Karamouz, M., Goharian, E., and Burian, S. (2015). “Analysis of the effects of climate change on urban storm water runoff using statistically downscaled precipitation data and a change factor approach.” J. Hydrol. Eng., 05014022.
Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 142 • Issue 2 • February 2016
Copyright
© 2015 American Society of Civil Engineers.
History
Received: Jul 14, 2014
Accepted: Jun 25, 2015
Published online: Aug 26, 2015
Discussion open until: Jan 26, 2016
Published in print: Feb 1, 2016
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.