70 years of lake evolution and glacial lake outburst floods in the Cordillera Blanca (Peru) and implications for the future

Emmer, Adam; Harrison, Stephan; Mergili, Martin; Allen, Simon; Frey, Holger; Huggel, Christian

doi:10.1016/j.geomorph.2020.107178

Cited by 68 publications

(82 citation statements)

References 52 publications

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“…Five lakes were found to have medium GLOF susceptibility for Scenario 1 and four other lakes for Scenario 2. Dam failures (Scenarios 3, 4 and 5) appear unlikely in the Cordillera Huayhuash, considering the fact that the majority of steep-sloped moraine dams that retain large lakes have already failed (see The limited information about GLOF timing in the Cordillera Huayhuash (Table 4) shows that major and extreme moraine dam failure-induced GLOFs (Solteracocha, Sarapococha, Rurigallay) occurred in the first half of the 20th Century, which is in line with the observations from the Cordillera Blanca where the peak frequency of GLOFs from moraine-dammed lakes was observed from late 1930s to early 1950s [44]. Increased occurrence of GLOFs during the wet season (see Table Figure 6.…”

Section: Glof Susceptibility Assessmentsupporting

confidence: 80%

“…The limited information about GLOF timing in the Cordillera Huayhuash (Table 4) shows that major and extreme moraine dam failure-induced GLOFs (Solteracocha, Sarapococha, Rurigallay) occurred in the first half of the 20th Century, which is in line with the observations from the Cordillera Blanca where the peak frequency of GLOFs from moraine-dammed lakes was observed from late 1930s to early 1950s [44]. Increased occurrence of GLOFs during the wet season (see Table 4) explains why many of these events remained unnoticed, because mountain pastures are only used during the dry season (which is true also of tourism).…”

Section: Timing Of Glof Occurrence and Glof Hazard Implicationssupporting

confidence: 78%

“…All mapped GLOF-producing lakes are the first or second generation of lakes in terms of distance from glacier termini, suggesting that: (i) these lakes are most likely not older than a few hundred years (for dating of moraines see [26]); (ii) GLOF response time (i.e., a period between the lake formation and a GLOF) likely did not exceed several tens of years (for more details on this concept see [7]), which is in line with recent findings from the Cordillera Blanca [44]. Approximating the timing of past GLOFs is complicated because of a lack of data before the advent of satellite remote sensing.…”

Section: Timing Of Glof Occurrence and Glof Hazard Implicationssupporting

confidence: 77%

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Glacial Lake Outburst Floods (GLOFs) in the Cordillera Huayhuash, Peru: Historic Events and Current Susceptibility

Baťka

Vilímek

Štefanová

et al. 2020

Water

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The aim of this paper is to create a glacial lake inventory for the Cordillera Huayhuash in Peru and to evaluate the susceptibility of lakes to the generation of glacial lake outburst floods (GLOFs). Using high-resolution satellite images, we undertook qualitative and quantitative analysis of lake type, characteristics and distribution, and placed our findings within the context of existing Peru-wide lake inventories. We also mapped and analyzed past GLOFs, revealing a total of 10 GLOFs and 4 ambiguous events, most of which have not been reported before. We found that past GLOFs usually occurred as a result of moraine dam breach during the proglacial stage of lake evolution. Further, we used our lake inventory to evaluate GLOF susceptibility of all lakes larger than 20,000 m2. Of 46 evaluated lakes, only two lakes (Lake Tsacra and Lake W014) are currently susceptible to generating a GLOF, which would most likely be through dam overtopping resulting from a flood originating in smaller lakes located upstream. The future perspectives of lake evolution and implications for GLOF hazard management are discussed in light of the post-Little Ice Age glacier ice loss as well as in the context of extensive related research undertaken in the nearby Cordillera Blanca.

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Section: Glof Susceptibility Assessmentsupporting

confidence: 80%

Section: Timing Of Glof Occurrence and Glof Hazard Implicationssupporting

confidence: 78%

Section: Timing Of Glof Occurrence and Glof Hazard Implicationssupporting

confidence: 77%

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Glacial Lake Outburst Floods (GLOFs) in the Cordillera Huayhuash, Peru: Historic Events and Current Susceptibility

Baťka

Vilímek

Štefanová

et al. 2020

Water

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“…Here, we map the glacial lakes in the Peruvian Andes using the PlanetScope imagery and the trained U-Net model as shown in Figure 17. For a comparison, the glacial lake outlines of Cordillera Blanca (Peru) [65], which have been derived from visual interpretation of satellite imagery are also shown as a reference. A visual analysis of the results shows that the trained U-Net model generalizes well to the other areas.…”

Section: Discussionmentioning

confidence: 99%

“…Mapping of the glacial lakes in the Peruvian Andes using PlanetScope imagery and the U-Net model, which was trained on the data from the Hindu Kush, Karakoram and Himalaya (HKKH) region. For a comparison, lake outlines from Emmer et al [65] are also shown.…”

Section: Discussionmentioning

confidence: 99%

Glacial Lakes Mapping Using Multi Satellite PlanetScope Imagery and Deep Learning

Qayyum

Ghuffar

Ahmad

et al. 2020

IJGI

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Glacial lakes mapping using satellite remote sensing data are important for studying the effects of climate change as well as for the mitigation and risk assessment of a Glacial Lake Outburst Flood (GLOF). The 3U cubesat constellation of Planet Labs offers the capability of imaging the whole Earth landmass everyday at 3–4 m spatial resolution. The higher spatial, as well as temporal resolution of PlanetScope imagery in comparison with Landsat-8 and Sentinel-2, makes it a valuable data source for monitoring the glacial lakes. Therefore, this paper explores the potential of the PlanetScope imagery for glacial lakes mapping with a focus on the Hindu Kush, Karakoram and Himalaya (HKKH) region. Though the revisit time of the PlanetScope imagery is short, courtesy of 130+ small satellites, this imagery contains only four bands and the imaging sensors in these small satellites exhibit varying spectral responses as well as lower dynamic range. Furthermore, the presence of cast shadows in the mountainous regions and varying spectral signature of the water pixels due to differences in composition, turbidity and depth makes it challenging to automatically and reliably extract surface water in PlanetScope imagery. Keeping in view these challenges, this work uses state of the art deep learning models for pixel-wise classification of PlanetScope imagery into the water and background pixels and compares the results with Random Forest and Support Vector Machine classifiers. The deep learning model is based on the popular U-Net architecture. We evaluate U-Net architecture similar to the original U-Net as well as a U-Net with a pre-trained EfficientNet backbone. In order to train the deep neural network, ground truth data are generated by manual digitization of the surface water in PlanetScope imagery with the aid of Very High Resolution Satellite (VHRS) imagery. The created dataset consists of more than 5000 water bodies having an area of approx. 71km2 in eight different sites in the HKKH region. The evaluation of the test data show that the U-Net with EfficientNet backbone achieved the highest F1 Score of 0.936. A visual comparison with the existing glacial lake inventories is then performed over the Baltoro glacier in the Karakoram range. The results show that the deep learning model detected significantly more lakes than the existing inventories, which have been derived from Landsat OLI imagery. The trained model is further evaluated on the time series PlanetScope imagery of two glacial lakes, which have resulted in an outburst flood. The output of the U-Net is also compared with the GLakeMap data. The results show that the higher spatial and temporal resolution of PlanetScope imagery is a significant advantage in the context of glacial lakes mapping and monitoring.

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Inventory and evolution of glacial lakes since the Little Ice Age: Lessons from the case of Switzerland

Mölg

Huggel

Herold

et al. 2021

Earth Surf Processes Landf

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Retreating glaciers give way to new landscapes with lakes as an important element.In this study, we combined available data on lake outlines with historical orthoimagery and glacier outlines for six time periods since the end of the Little Ice Age (LIA; $1850). We generated a glacial lake inventory for modern times (2016) and traced the evolution of glacial lakes that formed in the deglaciated area since the LIA. In this deglaciated area, a total of 1192 lakes formed over the period of almost 170 years, 987 of them still in existence in 2016. Their total water surface in 2016 was 6.22 AE 0.25 km 2 . The largest lakes are > 0.4 km 2 (40 ha) in size, while the majority (> 90%) are smaller than 0.01 km 2 . Annual increase rates in area and number peaked in 1946-1973, decreased towards the end of the 20th century, and reached a new high in the latest period 2006-2016. For a period of 43 years , we compared modelled overdeepenings from previous studies to actual lake genesis.For a better prioritization of formation probability, we included glacier-morphological criteria such as glacier width and visible crevassing. About 40% of the modelled overdeepened area actually got covered by lakes. The inclusion of morphological aspects clearly aided in defining a lake formation probability to be linked to each modelled overdeepening. Additional morphological variables, namely dam material and type, surface runoff, and freeboard, were compiled for a subset of larger and ice-contact lakes in 2016, constituting a basis for future hazard assessment.

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70 years of lake evolution and glacial lake outburst floods in the Cordillera Blanca (Peru) and implications for the future

Cited by 68 publications

References 52 publications

Glacial Lake Outburst Floods (GLOFs) in the Cordillera Huayhuash, Peru: Historic Events and Current Susceptibility

Glacial Lake Outburst Floods (GLOFs) in the Cordillera Huayhuash, Peru: Historic Events and Current Susceptibility

Glacial Lakes Mapping Using Multi Satellite PlanetScope Imagery and Deep Learning

Inventory and evolution of glacial lakes since the Little Ice Age: Lessons from the case of Switzerland

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70 years of lake evolution and glacial lake outburst floods in the Cordillera Blanca (Peru) and implications for the future

Cited by 68 publications

References 52 publications

Glacial Lake Outburst Floods (GLOFs) in the Cordillera Huayhuash, Peru: Historic Events and Current Susceptibility

Glacial Lake Outburst Floods (GLOFs) in the Cordillera Huayhuash, Peru: Historic Events and Current Susceptibility

Glacial Lakes Mapping Using Multi Satellite PlanetScope Imagery and Deep Learning

Inventory and evolution of glacial lakes since the Little Ice Age: Lessons from the case of Switzerland

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70 years of lake evolution and glacial lake outburst floods in the Cordillera Blanca (Peru) and implications for the future