Recent evolution and degradation of the bent Jatunraju glacier (Cordillera Blanca, Peru)

Emmer, Adam; Loarte, Edwin; Klimeš, Jan; Vilímek, Vít

doi:10.1016/j.geomorph.2014.09.018

Cited by 43 publications

(26 citation statements)

References 34 publications

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“…Secondly, it provides insights in to the processes that control glacier melt over a debris-covered tropical glacier. Our findings regarding the importance of ice cliffs and surface melt ponds in debris-covered glacier melt processes corroborate findings for debris-covered glaciers in the Cordillera Blanca (Emmer et al, 2015) and the Himalaya (Buri et al, 2016;Immerzeel et al, 2014). The high spatial resolution of UAV-derived datasets facilitates a much better understanding of surface heterogeneity and spatial variability in debris-covered glacier melt processes and changes in proglacial lake systems.…”

Section: Discussionsupporting

confidence: 84%

“…Emmer et al (2015) reported maximum values of 11.2 m yr −1 for a similar debriscovered section at the much steeper Jatunraju Glacier, which is less than half what is presented here. However, the relative size of the accumulation area at Llaca is much larger than for Jatunraju.…”

Section: Glacier and Proglacial Lake Dynamicscontrasting

confidence: 71%

“…Huh et al (2017) combined airborne lidar and photogrammetry to quantify changes in glacier volume for a handful of valleys within the Cordillera Blanca, but large errors exist for the earlier date photogrammetric DEMs. Most recently Emmer et al (2015) combined a single DEM with high-resolution satellite imagery and field investigations to understand the geomorphic evolution and measure surface velocities of the debris-covered Jatunraju Glacier. Most research in the Cordillera Blanca has addressed the entire range with a focus on glacier response to larger-scale climatic perturbations (Rabatel et al, 2013;Vuille et al, 2008) and their role in the hydrologic budget of the Rio Santa basin (Baraer et al, 2012;Juen et al, 2007;Kaser et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

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Monitoring tropical debris-covered glacier dynamics from high-resolution unmanned aerial vehicle photogrammetry, Cordillera Blanca, Peru

Wigmore

Mark

2017

The Cryosphere

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Abstract. The glaciers of the Cordillera Blanca, Peru, are rapidly retreating and thinning as a result of climate change, altering the timing, quantity and quality of water available to downstream users. Furthermore, increases in the number and size of proglacial lakes associated with these melting glaciers is increasing potential exposure to glacier lake outburst floods (GLOFs). Understanding how these glaciers are changing and their connection to proglacial lake systems is thus of critical importance. Most satellite data are too coarse for studying small mountain glaciers and are often affected by cloud cover, while traditional airborne photogrammetry and lidar are costly. Recent developments have made unmanned aerial vehicles (UAVs) a viable and potentially transformative method for studying glacier change at high spatial resolution, on demand and at relatively low cost.Using a custom designed hexacopter built for high-altitude (4000-6000 m a.s.l.) operation, we completed repeat aerial surveys (2014 and 2015) of the debris-covered Llaca Glacier tongue and proglacial lake system. High-resolution orthomosaics (5 cm) and digital elevation models (DEMs) (10 cm) were produced and their accuracy assessed. Analysis of these datasets reveals highly heterogeneous patterns of glacier change. The most rapid areas of ice loss were associated with exposed ice cliffs and meltwater ponds on the glacier surface. Considerable subsidence and low surface velocities were also measured on the sediments within the pro-glacial lake, indicating the presence of extensive regions of buried ice and continued connection to the glacier tongue. Only limited horizontal retreat of the glacier tongue was observed, indicating that measurements of changes in aerial extent alone are inadequate for monitoring changes in glacier ice quantity.

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Section: Discussionsupporting

confidence: 84%

Section: Glacier and Proglacial Lake Dynamicscontrasting

confidence: 71%

Section: Introductionmentioning

confidence: 99%

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Monitoring tropical debris-covered glacier dynamics from high-resolution unmanned aerial vehicle photogrammetry, Cordillera Blanca, Peru

Wigmore

Mark

2017

The Cryosphere

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“…To our knowledge, no modeling considers their evolution. Furthermore, recent contributions investigated the transition from very small debris-covered glaciers to rock glaciers at the site-specific scale (e.g., Bosson et al, 2015;Emmer et al, 2015;Monnier and Kinnard, 2015;Seppi et al, 2015), but quantitative data on internal structure and on the operating processes are still lacking. In particular, the definition of the distinct components of these systems, the understanding of their origin and the identification of their responses to climatic variations is needed.…”

Section: Introductionmentioning

confidence: 99%

Internal Structure and Current Evolution of Very Small Debris-Covered Glacier Systems Located in Alpine Permafrost Environments

Bosson

Lambiel

2016

Front. Earth Sci.

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This contribution explores the internal structure of very small debris-covered glacier systems located in permafrost environments and their current dynamical responses to short-term climatic variations. Three systems were investigated with electrical resistivity tomography and dGPS monitoring over a 3-year period. Five distinct sectors are highlighted in each system: firn and bare-ice glacier, debris-covered glacier, heavily debris-covered glacier of low activity, rock glacier and ice-free debris. Decimetric to metric movements, related to ice ablation, internal deformation and basal sliding affect the glacial zones, which are mainly active in summer. Conversely, surface lowering is close to zero (−0.04 m yr −1 ) in the rock glaciers. Here, a constant and slow internal deformation was observed (c. 0.2 m yr −1 ). Thus, these systems are affected by both direct and high magnitude responses and delayed and attenuated responses to climatic variations. This differential evolution appears mainly controlled by (1) the proportion of ice, debris and the presence of water in the ground, and (2) the thickness of the superficial debris layer.

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“…The first is that the thickness of the debris layer on DCGs in the Cordillera Blanca exceeds the 40cm-50cm depth of debris, above which the cooling effect of underlying ice is not manifest on the debris surface Ranzi 2002, Ranzi et al 2004). While there were no data available that comprehensively quantify debris depths in this region, a recent survey of the well-documented Jatunraju glacier found debris depths of several meters in the thickest parts, and over one meter in thinner portions (Emmer et al 2015). It seems plausible that the debris layers of DCGs in the Cordillera Blanca are simply too thick for any thermal effect from underlying ice to be detectable on the surface.…”

Section: Characteristics Of Dcgs In the Cordillera Blancamentioning

confidence: 99%

Mapping debris-covered glaciers in the Cordillera Blanca, Peru : an object-based image analysis approach.

Biddle¹

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Biddle,, Donald J. 1982-, "Mapping debris-covered glaciers in the Cordillera Blanca, Peru : an object-based image analysis approach." (2015). ACKNOWLEDGEMENTSThere are so many people without whose guidance and support this thesis would not have come to fruition. To thank them all by name would be major work in its own right! If I must pare the list for this limited space it should begin with my advisors, Dr. Keith Mountain and Dr. Andrea Gaughan. They challenged me to be the best version of myself, even -nay -especially when it was not the easiest way forward. Thank you also to Dr.Michael Croasdaile for putting his geographer's hat back on to see me through this process, and providing an invaluable outside perspective. A very special thank you to Dr.Carol Hanchette, for her patient encouragement over the (many) years it has taken to reach this point. She reminded me that yes, I can do this. Thanks to Forrest Stevens for the crash course in R coding and machine learning that led to a major breakthrough that helped push me over the hump with this project. My brain still hurts. To my lovely wife Nicole, thank you for putting up with me through the deepest moments of frustration, and being a constant companion, confidante, and comedy sidekick…not just now, but always. Accurate remote-sensing based inventories of glacial ice are often hindered by the presence of supraglacial debris cover. Attempts at automated mapping of debris-covered glacier areas from remotely-sensed multispectral data have met with limited success due to the spectral similarity of supraglacial debris to nearby bedrock, moraines, and fluvial deposition features. Data-fusion approaches leveraging terrain and/or thermal data with multispectral data have yielded improved results in certain geographic regions, but remain unproven in others. This research builds on the data-fusion approaches from the literature and explores the efficacy of object-based image analysis (OBIA) and tree-based machine learning classifiers using Landsat OLI imagery and SRTM elevation data, in effort to map debris-covered glaciers in the Cordillera Blanca range of Peru. Results suggest that the OBIA and machine learning methods render advantages over traditional methods given the unique morphological settings associated with debris-covered glaciers.

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Recent evolution and degradation of the bent Jatunraju glacier (Cordillera Blanca, Peru)

Cited by 43 publications

References 34 publications

Monitoring tropical debris-covered glacier dynamics from high-resolution unmanned aerial vehicle photogrammetry, Cordillera Blanca, Peru

Monitoring tropical debris-covered glacier dynamics from high-resolution unmanned aerial vehicle photogrammetry, Cordillera Blanca, Peru

Internal Structure and Current Evolution of Very Small Debris-Covered Glacier Systems Located in Alpine Permafrost Environments

Mapping debris-covered glaciers in the Cordillera Blanca, Peru : an object-based image analysis approach.

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