The 2015 Chileno Valley glacial lake outburst flood, Patagonia

Wilson, Ryan; Harrison, Stephan; Reynolds, John M.; Hubbard, Alun; Glasser, Neil F.; Wündrich, Olaf; Anacona, Pablo Iribarren; Mao, Luca; Shannon, Sarah

doi:10.1016/j.geomorph.2019.01.015

Cited by 39 publications

(26 citation statements)

References 56 publications

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“…In order to extract DEMs from the HYCON (1955), Chile-80 (1983) and GEOTEC (1996) aerial imagery, Structure from Motion (SfM) techniques were applied. The SfM photogrammetric approach has become a common technique to derive 3D topographic data from overlapping image sequences (Westoby and others, 2012; Smith and others, 2016) and has reliably produced DEMs for the quantification of river-floodplain morphological changes (Bakker and Lane, 2016; Wilson and others, 2019), the estimation of glacier mass balance (Mölg and Bolch, 2017), and the monitoring of rock glaciers (Vivero and Lambiel, 2019). In this case, the 1955, 1983 and 1996 digital aerial photography was processed using SfM algorithms embedded in the PIX4dmapper Pro software package (version 4.1).…”

Section: Methodsmentioning

confidence: 99%

“…The control system for the sounder module included an ATMega 328 microcontroller, an uBlox NEO-6 GPS unit and an RFM69HW radio transceiver that was used during debugging. The boat itself was controlled manually using a standard 2.4 GHz radio system and water depth measurements were acquired every 3 s. Further specifications for the bathymetry boat are available in Wilson and others (2019). Using the lake depth data acquired in the field, a 2 m grid bathymetry DEM was interpolated using the kriging method.…”

Section: Methodsmentioning

confidence: 99%

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A near 90-year record of the evolution of El Morado Glacier and its proglacial lake, Central Chilean Andes

et al. 2020

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Using an ensemble of close- and long-range remote sensing, lake bathymetry and regional meteorological data, we present a detailed assessment of the geometric changes of El Morado Glacier in the Central Andes of Chile and its adjacent proglacial lake between 1932 and 2019. Overall, the results revealed a period of marked glacier down wasting, with a mean geodetic glacier mass balance of −0.39 ± 0.15 m w.e.a−1 observed for the entire glacier between 1955 and 2015 with an area loss of 40% between 1955 and 2019. We estimate an ice elevation change of −1.00 ± 0.17 m a−1 for the glacier tongue between 1932 and 2019. The increase in the ice thinning rates and area loss during the last decade is coincident with the severe drought in this region (2010–present), which our minimal surface mass-balance model is able to reproduce. As a result of the glacier changes observed, the proglacial lake increased in area substantially between 1955 and 2019, with bathymetry data suggesting a water volume of 3.6 million m3 in 2017. This study highlights the need for further monitoring of glacierised areas in the Central Andes. Such efforts would facilitate a better understanding of the downstream impacts of glacier downwasting.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

A near 90-year record of the evolution of El Morado Glacier and its proglacial lake, Central Chilean Andes

et al. 2020

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“…Observations of modern catastrophic floods provide another constraint on the total erosion we would expect from these floods. Wilson et al (2019) looked at a 2015 glacial lake outburst flood (GLOF) in Chile with peak discharge of 5 * 10 −3 Sv and resulted in a maximum of 38 meters of erosion in a sediment-laden alluvial plain. Cook et al (2018) examined GLOFs in the Himalaya with a peak discharge of 2.3 * 10 −3 Sv which caused 1-10 meters of erosion into sediment.…”

Section: Calculation Of Erosion Ratesmentioning

confidence: 99%

Supplemental Material: Pliocene–Pleistocene megafloods as a mechanism for Greenlandic megacanyon formation

Keisling¹

2020

Preprint

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“…The findings on the land cover transformation in the oceanic glacial region by multiple classification algorithms can provide both long-term evidence and methodological indications to understand the recent environmental change in the "third pole".Remote Sens. 2020, 12, 999 2 of 20 have greatly increased and directly threatened human activities in glacier regions [7,8]. Therefore, the accurate monitoring of environmental changes in glacier regions is necessary for climate change research, natural disaster prediction, and preserving human life.The oceanic glaciers, also called monsoonal temperate glaciers, make up approximately 22% of the total glaciated area in China, with an area of approximately 1.32 × 10 4 km 2 and are mainly located in the southeast Tibetan Plateau [9].…”

mentioning

confidence: 99%

“…Remote Sens. 2020, 12, 999 2 of 20 have greatly increased and directly threatened human activities in glacier regions [7,8]. Therefore, the accurate monitoring of environmental changes in glacier regions is necessary for climate change research, natural disaster prediction, and preserving human life.…”

mentioning

confidence: 99%

Vegetation-Ice-Bare Land Cover Conversion in the Oceanic Glacial Region of Tibet Based on Multiple Machine Learning Classifications

Yang

Liu

et al. 2020

Remote Sensing

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Oceanic glaciers are one of the most sensitive indicators of climate change. However, remotely sensed evidence of land cover change in the oceanic glacial region is still limited due to the cloudy weather during the growing season. In addition, the performance of common machine learning classification algorithms is also worth testing in this cloudy, frigid and mountainous region. In this study, three algorithms, namely, the random forest, back-propagation neural network (BPNN) and convolutional neural network algorithms, were compared in their interpretation of the land cover change in south-eastern Tibet and resulted in three findings. (1) The BPNN achieves the highest overall accuracy and Kappa coefficient compared with the other two algorithms. The overall accuracy was 97.82%, 98.07%, 98.92%, and 94.63% in 1990, 2000, 2007, and 2016, and the Kappa coefficient was 0.958, 0.959, 0.980, and 0.918 in these four years, respectively. (2) From 1990 to 2000, the dominant land cover was ice at the landscape level. The landscape fragmentation decreased and the landscape aggregation increased. From 2000 to 2016, the dominant land cover transformed from ice to vegetation. The vegetation aggregation increased, while the ice aggregation decreased. (3) When the elevation was less than 4 km, the vegetation was usually transformed into bare land; otherwise, the probability of direct transformation between vegetation and ice increased. The findings on the land cover transformation in the oceanic glacial region by multiple classification algorithms can provide both long-term evidence and methodological indications to understand the recent environmental change in the “third pole”.

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The 2015 Chileno Valley glacial lake outburst flood, Patagonia

Cited by 39 publications

References 56 publications

A near 90-year record of the evolution of El Morado Glacier and its proglacial lake, Central Chilean Andes

A near 90-year record of the evolution of El Morado Glacier and its proglacial lake, Central Chilean Andes

Supplemental Material: Pliocene–Pleistocene megafloods as a mechanism for Greenlandic megacanyon formation

Vegetation-Ice-Bare Land Cover Conversion in the Oceanic Glacial Region of Tibet Based on Multiple Machine Learning Classifications

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