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.

冰川湖爆发洪水（GLOF）在冰川环境中构成了重大威胁，因此有必要制定GLOF危害和风险评估程序。在这里，我们概述了一种多标准决策分析（MCDA）方法，该方法可用于在没有现有量身定制的GLOF风险评估，存在各种冰川湖类型，且野外数据稀疏或非实地数据不存在的情况下，快速识别区域中的潜在危险湖泊-存在。我们的MCDA模型（1）是基于桌面的，并使用免费且广泛使用的数据输入和软件，并且（2）允许在任何区域内同时评估各种冰川湖类型带来的相对风险。对影响GLOF风险的因素进行了回顾，再加上MCDA固有的严格的标准选择规则，使我们能够确定13种详尽，无冗余，和一致的风险标准。我们使用MCDA模型评估了16个现存的冰川湖泊和6个已经产生GLOF的湖泊的风险，并发现我们的结果与以前的研究非常吻合。在GLOF风险评估中，我们首次使用敏感性分析来测试模型结果和假设的强度，并确定对所使用的标准和风险阈值敏感的湖泊。MCDA方法的主要好处是可以轻松进行灵敏度分析。总体而言，这些敏感性分析为我们的模型提供了支持，尽管我们建议需要进一步的工作来确定评估标准的相对重要性，以及确定每个标准的风险水平的阈值。作为案例研究 然后将测试方法应用于玻利维亚安第斯山脉的25个潜在危险湖泊，那里对GLOF的风险了解甚少；发现3个湖泊构成“中”或“高”风险，需要进一步详细调查。