Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes

Ioannis Kougkoulos (Lead / Corresponding author), Simon J. Cook (Lead / Corresponding author), Vincent Jomelli, Leon Clarke, Elias Symeonakis, Jason M. Dortch, Laura A. Edwards, Myriam Merad

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Abstract

Glacial Lake Outburst Floods (GLOFs) represent a significant threat in deglaciating environments, necessitating the development of GLOF hazard and risk assessment procedures. Here, we outline a Multi-Criteria Decision Analysis (MCDA) approach that can be used to rapidly identify potentially dangerous lakes in regions without existing tailored GLOF risk assessments, where a range of glacial lake types exist, and where field data are sparse or non-existent. Our MCDA model (1) is desk-based and uses freely and widely available data inputs and software, and (2) allows the relative risk posed by a range of glacial lake types to be assessed simultaneously within any region. A review of the factors that influence GLOF risk, combined with the strict rules of criteria selection inherent to MCDA, has allowed us to identify 13 exhaustive, non-redundant, and consistent risk criteria. We use our MCDA model to assess the risk of 16 extant glacial lakes and 6 lakes that have already generated GLOFs, and found that our results agree well with previous studies. For the first time in GLOF risk assessment, we employed sensitivity analyses to test the strength of our model results and assumptions, and to identify lakes that are sensitive to the criteria and risk thresholds used. A key benefit of the MCDA method is that sensitivity analyses are readily undertaken. Overall, these sensitivity analyses lend support to our model, although we suggest that further work is required to determine the relative importance of assessment criteria, and the thresholds that determine the level of risk for each criterion. As a case study, the tested method was then applied to 25 potentially dangerous lakes in the Bolivian Andes, where GLOF risk is poorly understood; 3 lakes are found to pose 'medium' or 'high' risk, and require further detailed investigation.

Original languageEnglish
Pages (from-to)1453-1466
Number of pages14
JournalScience of the Total Environment
Volume621
Early online date19 Oct 2017
DOIs
Publication statusPublished - 15 Apr 2018

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glacial lake
decision analysis
Decision theory
Lakes
outburst
lake
risk assessment
Risk assessment
hazard assessment
software

Keywords

  • Decision theory
  • Geohazards
  • Glacial lake outburst flood (GLOF)
  • Glacier shrinkage
  • Multi-criteria decision analysis (MCDA)
  • Risk assessment

Cite this

Kougkoulos, Ioannis ; Cook, Simon J. ; Jomelli, Vincent ; Clarke, Leon ; Symeonakis, Elias ; Dortch, Jason M. ; Edwards, Laura A. ; Merad, Myriam. / Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes. In: Science of the Total Environment. 2018 ; Vol. 621. pp. 1453-1466.
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abstract = "Glacial Lake Outburst Floods (GLOFs) represent a significant threat in deglaciating environments, necessitating the development of GLOF hazard and risk assessment procedures. Here, we outline a Multi-Criteria Decision Analysis (MCDA) approach that can be used to rapidly identify potentially dangerous lakes in regions without existing tailored GLOF risk assessments, where a range of glacial lake types exist, and where field data are sparse or non-existent. Our MCDA model (1) is desk-based and uses freely and widely available data inputs and software, and (2) allows the relative risk posed by a range of glacial lake types to be assessed simultaneously within any region. A review of the factors that influence GLOF risk, combined with the strict rules of criteria selection inherent to MCDA, has allowed us to identify 13 exhaustive, non-redundant, and consistent risk criteria. We use our MCDA model to assess the risk of 16 extant glacial lakes and 6 lakes that have already generated GLOFs, and found that our results agree well with previous studies. For the first time in GLOF risk assessment, we employed sensitivity analyses to test the strength of our model results and assumptions, and to identify lakes that are sensitive to the criteria and risk thresholds used. A key benefit of the MCDA method is that sensitivity analyses are readily undertaken. Overall, these sensitivity analyses lend support to our model, although we suggest that further work is required to determine the relative importance of assessment criteria, and the thresholds that determine the level of risk for each criterion. As a case study, the tested method was then applied to 25 potentially dangerous lakes in the Bolivian Andes, where GLOF risk is poorly understood; 3 lakes are found to pose 'medium' or 'high' risk, and require further detailed investigation.",
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Kougkoulos, I, Cook, SJ, Jomelli, V, Clarke, L, Symeonakis, E, Dortch, JM, Edwards, LA & Merad, M 2018, 'Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes', Science of the Total Environment, vol. 621, pp. 1453-1466. https://doi.org/10.1016/j.scitotenv.2017.10.083

Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes. / Kougkoulos, Ioannis (Lead / Corresponding author); Cook, Simon J. (Lead / Corresponding author); Jomelli, Vincent; Clarke, Leon; Symeonakis, Elias; Dortch, Jason M.; Edwards, Laura A.; Merad, Myriam.

In: Science of the Total Environment, Vol. 621, 15.04.2018, p. 1453-1466.

Research output: Contribution to journalArticle

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T1 - Use of multi-criteria decision analysis to identify potentially dangerous glacial lakes

AU - Kougkoulos, Ioannis

AU - Cook, Simon J.

AU - Jomelli, Vincent

AU - Clarke, Leon

AU - Symeonakis, Elias

AU - Dortch, Jason M.

AU - Edwards, Laura A.

AU - Merad, Myriam

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AB - Glacial Lake Outburst Floods (GLOFs) represent a significant threat in deglaciating environments, necessitating the development of GLOF hazard and risk assessment procedures. Here, we outline a Multi-Criteria Decision Analysis (MCDA) approach that can be used to rapidly identify potentially dangerous lakes in regions without existing tailored GLOF risk assessments, where a range of glacial lake types exist, and where field data are sparse or non-existent. Our MCDA model (1) is desk-based and uses freely and widely available data inputs and software, and (2) allows the relative risk posed by a range of glacial lake types to be assessed simultaneously within any region. A review of the factors that influence GLOF risk, combined with the strict rules of criteria selection inherent to MCDA, has allowed us to identify 13 exhaustive, non-redundant, and consistent risk criteria. We use our MCDA model to assess the risk of 16 extant glacial lakes and 6 lakes that have already generated GLOFs, and found that our results agree well with previous studies. For the first time in GLOF risk assessment, we employed sensitivity analyses to test the strength of our model results and assumptions, and to identify lakes that are sensitive to the criteria and risk thresholds used. A key benefit of the MCDA method is that sensitivity analyses are readily undertaken. Overall, these sensitivity analyses lend support to our model, although we suggest that further work is required to determine the relative importance of assessment criteria, and the thresholds that determine the level of risk for each criterion. As a case study, the tested method was then applied to 25 potentially dangerous lakes in the Bolivian Andes, where GLOF risk is poorly understood; 3 lakes are found to pose 'medium' or 'high' risk, and require further detailed investigation.

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