A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa, Peru

Frey, Holger; Huggel, Christian; Bühler, Yves; Buis, Daniel; Burga, María Dulce; Choquevilca, Walter; Fernández, Fidel Fernández; Hernández, Javier García; Giráldez, Claudia; Loarte, Edwin; Masias, Paul; Portocarrero, César; Vicuña, Luis; Walser, Marco

doi:10.1007/s10346-015-0669-z

Cited by 31 publications

(25 citation statements)

References 41 publications

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“…Unfortunately, cost constraints and a lack of field data on channel and moraines sediments did not permit the use of models such as RAMMS, which have been used in previous studies to model GLOFs and debris flows originating from such events (e.g. Frey et al 2016). Other options that have been used to model GLOFs include FLO-2D (e.g.…”

Section: Modelling Approachmentioning

confidence: 99%

Modelling glacial lake outburst flood impacts in the Bolivian Andes

et al. 2018

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The Bolivian Andes have experienced sustained and widespread glacier mass loss in recent decades. Glacier recession has been accompanied by the development of proglacial lakes, which pose a glacial lake outburst flood (GLOF) risk to downstream communities and infrastructure. Previous research has identified three potentially dangerous glacial lakes in the Bolivian Andes, but no attempt has yet been made to model GLOF inundation downstream from these lakes. We generated 2-m resolution DEMs from stereo and tri-stereo SPOT 6/7 satellite images to drive a hydrodynamic model of GLOF flow (HEC-RAS 5.0.3). The model was tested against field observations of a 2009 GLOF from Keara, in the Cordillera Apolobamba, and was shown to reproduce realistic flood depths and inundation. The model was then used to model GLOFs from Pelechuco lake (Cordillera Apolobamba) and Laguna Arkhata and Laguna Glaciar (Cordillera Real). In total, six villages could be affected by GLOFs if all three lakes burst. For sensitivity analysis, we ran the model for three scenarios (pessimistic, intermediate, optimistic), which give a range of ~ 1100 to ~ 2200 people affected by flooding; between ~ 800 and ~ 2100 people could be exposed to floods with a flow depth ≥ 2 m, which could be life threatening and cause a significant damage to infrastructure. We suggest that Laguna Arkhata and Pelechuco lake represent the greatest risk due to the higher numbers of people who live in the potential flow paths, and hence, these two glacial lakes should be a priority for risk managers.

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Section: Modelling Approachmentioning

confidence: 99%

Modelling glacial lake outburst flood impacts in the Bolivian Andes

et al. 2018

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“…Haeberli, 1983;Huggel et al, 2004;Haeberli et al, 2001), the Andes (e.g. Schneider et al, 2014;Schaub et al, 2015;Frey et al, 2016) and the Himalayas (e.g. Budhathoki et al, 2010;Haemmig et al, 2014) in the last years.…”

Section: Introductionmentioning

confidence: 99%

Glacial lake outburst flood hazard assessment by satellite Earth observation in the Himalayas (Chomolhari area, Bhutan)

et al. 2019

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Abstract. A case study of glacial lakes outburst flood (GLOF) hazard assessment by satellite Earth observation (EO) and numerical modelling is presented for the supraglacial and ice-contact lakes on Thangothang Chhu glacier, Chomolhari area (Bhutan). Detailed geomorphological mapping, including landslide and rock glacier inventories, as well as surface displacement determination using an interferometric SAR (InSAR) satellite, allowed a GLOF hazard assessment for lake Wa-007 to be performed. Outburst scenario modelling was achieved by combining both empirical and numerical modelling approaches, revealing that only a flood wave can have an impact on the two human settlements located downslope of Wa-007 lake. The worst-case scenario, modelled thanks to r.damflood, allowed the wave-front arrival time, the maximum water depth and the arrival time of maximum water height for the two human settlements to be quantified. A long-term monitoring strategy based entirely on EO data, with an update cycle of 5 years, is proposed to assess the future evolution of the area.

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“…Thousands of people have lost their lives to such events in the last few decades, mostly during the 1941 GLOF at Huaraz, Peru, and the 2013 Kedernath event, India (Richardson and Reynolds, 2000;Allen et al, 2015;Carrivick and Tweed, 2016). Given the risk posed to downstream communities, industry and infrastructure in deglaciating mountain ranges worldwide, there has been an intensification of research interest in GLOFs , with many such studies seeking to estimate GLOF hazard or risk for individual lakes or in specific regions including North America (Clague and Evans 2000;O'Connor et al, 2001;McKillop and Clague, 2007a,b), South America Anacona et al, 2015;Cook et al, 2016;Emmer et al, 2016a;Frey et al, 2016), the European Alps (Huggel et al, 2004;Frey et al, 2010), central Asia (Bolch et al, 2008;Mergili and Schneider, 2011;Petrov et al, 2017), and the Himalayas (Wang et al, 2008;Ives et al, 2010;ICIMOD, 2011;Ashraf et al, 2012;Worni et al, 2013;Watson et al, 2015;Aggarwal et al, 2016;Rounce et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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

Kougkoulos

Cook

Jomelli

et al. 2018

Science of The Total Environment

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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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A robust debris-flow and GLOF risk management strategy for a data-scarce catchment in Santa Teresa, Peru

Cited by 31 publications

References 41 publications

Modelling glacial lake outburst flood impacts in the Bolivian Andes

Modelling glacial lake outburst flood impacts in the Bolivian Andes

Glacial lake outburst flood hazard assessment by satellite Earth observation in the Himalayas (Chomolhari area, Bhutan)

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

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