IDEAS home Printed from https://ideas.repec.org/a/spr/waterr/v37y2023i6d10.1007_s11269-022-03376-x.html
   My bibliography  Save this article

The Great Salt Lake Water Level is Becoming Less Resilient to Climate Change

Author

Listed:
  • Daniyal Hassan

    (University of Utah)

  • Steven J. Burian

    (University of Alabama
    University of Alabama)

  • Ryan C. Johnson

    (University of Alabama)

  • Sangmin Shin

    (Southern Illinois University)

  • Michael E. Barber

    (University of Utah)

Abstract

Climate change and water diversions are putting the Great Salt Lake (GSL) at risk. Projections indicate a continued decrease in the GSL water surface elevation (WSE) would lead to several catastrophic consequences. An aspect of the GSL dynamics gaining importance, and not addressed in past studies, is how resilient the lake WSE will be to increasing diversions from contributing rivers, intensifying drought conditions, and more frequent hydrologic deficits caused by climate change. The objectives of the present study were to: (1) examine the impacts of historical drought and development on the GSL resilience and (2) determine future WSE resilience under a range of hydroclimate and development scenarios. The historical resilience was analyzed considering three periods with different development conditions: (1) less developed (1901–1950); (2) moderately developed (1951–2000); (3) highly developed (2001–2020). Furthermore, a range of hydroclimate and development conditions were introduced into a system dynamics-based water management model to simulate the future GSL WSE and corresponding resilience. The historical analysis showed a significant decline in resilience (45.4%) during the highly developed period compared with the moderately developed period. Future scenarios of climate change and development revealed that the mean GSL WSE for the 2021–2050 period may drop by 0.93 m, while the resilience reduces by 30%, and 38% using RCP4.5 and RCP8.5 scenarios when compared to the less and medium developed historical periods respectively. This research provides insight for the State of Utah Department of Natural Resources and stakeholders to inform water management policies and GSL adaptive management strategies.

Suggested Citation

  • Daniyal Hassan & Steven J. Burian & Ryan C. Johnson & Sangmin Shin & Michael E. Barber, 2023. "The Great Salt Lake Water Level is Becoming Less Resilient to Climate Change," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(6), pages 2697-2720, May.
    • Handle: RePEc:spr:waterr:v:37:y:2023:i:6:d:10.1007_s11269-022-03376-x
    DOI: 10.1007/s11269-022-03376-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11269-022-03376-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11269-022-03376-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yusuf Alizade Govarchin Ghale & Abdusselam Altunkaynak & Alper Unal, 2018. "Investigation Anthropogenic Impacts and Climate Factors on Drying up of Urmia Lake using Water Budget and Drought Analysis," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(1), pages 325-337, January.
    2. Viorel Badescu & Roelof Schuiling, 2010. "Aral Sea; Irretrievable Loss or Irtysh Imports?," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(3), pages 597-616, February.
    3. Mehmet C. Demirel & Hamid Moradkhani, 2016. "Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation seasonality and timing," Climatic Change, Springer, vol. 135(2), pages 357-372, March.
    4. Elmira Hassanzadeh & Mahdi Zarghami & Yousef Hassanzadeh, 2012. "Determining the Main Factors in Declining the Urmia Lake Level by Using System Dynamics Modeling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(1), pages 129-145, January.
    5. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    6. Mehmet Demirel & Hamid Moradkhani, 2016. "Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation seasonality and timing," Climatic Change, Springer, vol. 135(2), pages 357-372, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mohamed Salem Nashwan & Shamsuddin Shahid & Eun-Sung Chung, 2020. "High-Resolution Climate Projections for a Densely Populated Mediterranean Region," Sustainability, MDPI, vol. 12(9), pages 1-22, May.
    2. Farhad Yazdandoost & Sogol Moradian & Ardalan Izadi, 2020. "Evaluation of Water Sustainability under a Changing Climate in Zarrineh River Basin, Iran," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 4831-4846, December.
    3. Alizade Govarchin Ghale, Yusuf & Baykara, Metin & Unal, Alper, 2019. "Investigating the interaction between agricultural lands and Urmia Lake ecosystem using remote sensing techniques and hydro-climatic data analysis," Agricultural Water Management, Elsevier, vol. 221(C), pages 566-579.
    4. Julie Shortridge, 2019. "Observed trends in daily rainfall variability result in more severe climate change impacts to agriculture," Climatic Change, Springer, vol. 157(3), pages 429-444, December.
    5. Trucco, Paolo & Petrenj, Boris, 2023. "Characterisation of resilience metrics in full-scale applications to interdependent infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    6. Fauzan Hanif Jufri & Jun-Sung Kim & Jaesung Jung, 2017. "Analysis of Determinants of the Impact and the Grid Capability to Evaluate and Improve Grid Resilience from Extreme Weather Event," Energies, MDPI, vol. 10(11), pages 1-17, November.
    7. Milan Janić, 2018. "Modelling the resilience of rail passenger transport networks affected by large-scale disruptive events: the case of HSR (high speed rail)," Transportation, Springer, vol. 45(4), pages 1101-1137, July.
    8. Yang, Bofan & Zhang, Lin & Zhang, Bo & Xiang, Yang & An, Lei & Wang, Wenfeng, 2022. "Complex equipment system resilience: Composition, measurement and element analysis," Reliability Engineering and System Safety, Elsevier, vol. 228(C).
    9. Zobel, Christopher W. & Baghersad, Milad, 2020. "Analytically comparing disaster resilience across multiple dimensions," Socio-Economic Planning Sciences, Elsevier, vol. 69(C).
    10. Zeng, Zhiguo & Fang, Yi-Ping & Zhai, Qingqing & Du, Shijia, 2021. "A Markov reward process-based framework for resilience analysis of multistate energy systems under the threat of extreme events," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    11. Francis, Royce & Bekera, Behailu, 2014. "A metric and frameworks for resilience analysis of engineered and infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 90-103.
    12. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    13. Milad Asadi & Amir Oshnooei-Nooshabadi & Samira-Sadat Saleh & Fattaneh Habibnezhad & Sonia Sarafraz-Asbagh & John Lodewijk Van Genderen, 2022. "Urban Sprawl Simulation Mapping of Urmia (Iran) by Comparison of Cellular Automata–Markov Chain and Artificial Neural Network (ANN) Modeling Approach," Sustainability, MDPI, vol. 14(23), pages 1-16, November.
    14. Baroud, Hiba & Barker, Kash & Ramirez-Marquez, Jose E. & Rocco S., Claudio M., 2014. "Importance measures for inland waterway network resilience," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 62(C), pages 55-67.
    15. Xiaoge Zhang & Sankaran Mahadevan & Kai Goebel, 2019. "Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 2054-2075, September.
    16. Ahmadi, Somayeh & Saboohi, Yadollah & Vakili, Ali, 2021. "Frameworks, quantitative indicators, characters, and modeling approaches to analysis of energy system resilience: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    17. Taheri, Mercedeh & Emadzadeh, Maryam & Gholizadeh, Mohsen & Tajrishi, Masoud & Ahmadi, Mehdi & Moradi, Melika, 2019. "Investigating the temporal and spatial variations of water consumption in Urmia Lake River Basin considering the climate and anthropogenic effects on the agriculture in the basin," Agricultural Water Management, Elsevier, vol. 213(C), pages 782-791.
    18. Ruiying Li & Qiang Dong & Chong Jin & Rui Kang, 2017. "A New Resilience Measure for Supply Chain Networks," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    19. Zio, E., 2018. "The future of risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 177(C), pages 176-190.
    20. Barabadi, A. & Ayele, Y.Z., 2018. "Post-disaster infrastructure recovery: Prediction of recovery rate using historical data," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 209-223.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:waterr:v:37:y:2023:i:6:d:10.1007_s11269-022-03376-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.