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State and Fate of Glaciers in the Val Veny (Mont-Blanc Range, Italy): Contribution of Optical Satellite Products

Antoine Rabatel, Etienne Ducasse, Victor Ramseyer et Romain Millan
Cet article est une traduction de :
Évolution récente et à venir des glaciers du Val Veny (massif du Mont-Blanc, Italie) : apports de la télédétection satellite optique [fr]

Résumé

The glaciers of the Val Veny (Italian side of the Mont-Blanc Massif) have been the site of numerous field observations during the last decades, in particular for the study of glacial fluctuations or surface processes related to the debris cover. Here, we propose to examine how satellite observations can complement field measurements on the state and fate of the Val Veny glaciers. Indeed, satellite products obtained in a quasi-systematic way allow to account not only for the loss of surface and volume, but also for the changes in their flow velocities. The overall pattern we document is a glacier thinning and slowdown of the ice flow, with an estimated shrinkage of 25% by 2050 and a volume loss ranging between 30 and 43% depending on the data source used for the estimation of the initial volume. In such a context, a portion of the upper reaches of Brenva Glacier shows an unexpected pattern of thickening and increase in ice flow that rises questions on its origin. Finally, the uncertainties in the estimation of ice thicknesses remain important and have repercussions on the future evolution of the glaciers and their contribution from a hydrological point of view. By 2050, we estimate that the water contribution due to the volume loss of Val Veny glaciers could decrease by 40%.

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Texte intégral

The glacier surface flow velocity data presented in this work have been generated within the framework of “Glacier Science in the Alps” project (contract no. 4000133436/20/I-NB) coordinated by Frank Paul (University of Zurich) and funded by the European Space Agency (ESA). This work has also been supported by the project SatIceFY funded by the LabEx OSUG@2020 (Investissements d’Avenir—ANR10 LABX56). We thank the GLIMS initiative (https://www.glims.org/) and the “CES Glaciers” of the French Pôle National de Données THEIA (https://www.theia-land.fr/ceslist/ces-glaciers/) for the support regarding the distribution of the satellite products used in this work, particularly R. Hugonnet and E. Berthier for the Dh/Dt maps. Finally, we would like to thank the editors and reviewers for their careful proofreading and comments on the manuscript.

Introduction

1Likely related to the diversity of the glaciers that can be found in the Val Veny (Italian side of the Mont Blanc massif) and also to its accessibility, the Val Veny has been at the centre of an important number of glaciological studies in the last decades. For instance, attention has been focused on the fluctuations of glaciers during the Holocene, in particular for the Brenva Glacier (Orombelli & Porter, 1982) and thanks to the morainic amphitheatre of the Miage Glacier (Deline, 1999; Deline & Orombelli, 2005). Indeed, important moraine ridges can be found as a consequence of the large amount of debris transported by the glaciers. In addition, the low elevation of Miage Glacier’s terminus has favoured the presence of vegetation, making it one of the only sites in the Alps where living trees can be found at the surface. The use of dendrological analyses allowed to reconstruct the glacier variations and surface instabilities (Pelfini et al., 2007; Leonelli & Pelfini, 2013).

2In relationship with the important debris-covered ablation area, the Miage and Brenva glaciers have concentrated many pioneering works focusing on surface processes like the temporal evolution of the debris coverage (D’Agata & Zanutta, 2007); the surface energy fluxes and mass balance over a debris-covered glacier tongue (Brock et al., 2010; Stefaniak et al., 2021); the contribution of ice cliffs to the ablation of a debris-covered glacier tongue (Reid & Brock, 2014); the application of satellite remote-sensing data for the monitoring of surface temperature and debris-covers thickness (Mihalcea et al., 2008).

3As the debris cover on the Val Veny glaciers is the result of an important production of debris along the steep south exposed headwalls, several studies focused on the history of the slope instabilities, along with their climatic and structural controls (Giardino et al., 2013; Deline et al., 2015), as well as on the formation of supraglacial debris cover (Kirkbride & Deline, 2013; Deline & Kirkbride, 2017).

4The large majority of previous works on the Val Veny glaciers have relied on in situ measurements. In the current study, we propose to concentrate on satellite remote sensing data as a complementary source of information. Indeed, satellite data show promise in terms of spatial coverage, temporal revisit and possibilities to document the Earth surface state and its spatial and temporal evolution. Therefore, we analyse the contribution of satellite remote sensing on the quantification of the recent evolution of the glaciers in terms of surface-area variations, volume changes, surface flow velocity and thickness estimates. In the last two decades, the number of satellite observations has continuously increased, allowing to systematically and almost automatically realise products that are largely freely distributed to the community (Rabatel et al., 2017; Hugonnet et al., 2023). Combining these products allows better characterisation of the state of the glaciers and also enables projections of their evolution in the next decades. We first briefly present the study area, and describe the datasets and methods that have been used. We then present an analysis of the state and fate of the glaciers in the Val Veny. Finally, we provide conclusions and recommendations regarding the limits of existing datasets, the approach used and potential future work.

Study Area

5Our study focuses on the glaciers of the Val Veny, in the upper reaches of the Val d’Aosta on the Italian side of the Mont Blanc range, to the west of the city of Courmayeur (Fig. 1).

Figure 1. Glaciers of the Val Veny catchment in the upper Aoste Valley, Italy

Figure 1. Glaciers of the Val Veny catchment in the upper Aoste Valley, Italy

Glacier outlines are taken from the GLIMS database.

6The Val Veny extends from the summit of the Mont Blanc at 4808 m a.s.l. to about 1450 m a.s.l. at the front of the Brenva Glacier. The Val Veny had a glacierized area of 23.7 km² in 2015 (Paul et al., 2020) distributed between 18 ice bodies. Morphology of the glaciers is highly diverse, ranging from very small ice bodies of about 0.01 km² to the almost 11 km² Miage valley glacier that presents a 6 km long debris-covered tongue. Some of the steepest glaciers of the Mont Blanc massif can be found in the Val Veny (e.g., Freney Glacier, Brouillard Glacier) with some of them having an average slope higher than 35%.

Data and Methods

7In this study, we used glaciological products freely available at regional-to-global scales:

  • Glacier outlines were taken from the Global Land Ice Measurements from Space initiative (https://www.glims.org/​), which includes the Randolph Glacier Inventory v6.0 (RGI-Consortium, 2017). These data have been derived from satellite remote sensing data and are available in polygon format (i.e. vectorial shapefile). For Val Veny glaciers, the available outlines date from 2000, 2003, 2011 and 2015.

  • Rates of glacier surface elevation changes between 2000 and 2019 were taken from Hugonnet et al. (2021). In their study, the surface elevation changes are estimated from fitting Gaussian Process regressions to time series of elevation observations from multiple digital elevation models (DEMs). DEMs are primarily generated and corrected from stereo images acquired by the ASTER instrument (NASA, METI) aboard the Terra satellite. These data are distributed at a horizontal resolution of 100 m x 100 m. We considered the 10-year periods of 2000–2009 and 2010–2019 and the full 20-year period of 2000–2019. These rates of glacier surface elevation changes (i.e., glacier thinning or thickening rates) take into account both the surface mass balance due to climate conditions and the mass transfer due to the ice flow. As such, the ice dynamics are implicitly considered.

  • Glacier surface flow velocity is extracted from Rabatel et al. (2023). These data are annual glacier surface flow velocity maps at the European Alps scale, covering the period 2015–2021 at a 50 m × 50 m resolution. Such data are quantified applying the normalised cross-correlation approach on Sentinel-2 optical satellite data (ESA, Copernicus). The satellite image-processing chain is presented in Millan et al. (2019). A post-processing chain to filter and aggregate ice flow velocities on the 2015–2021 period is applied using the method described in Mouginot et al. (2023).

  • Glacier ice thickness distributions were taken from Farinotti et al. (2019) and Millan et al. (2022). Both products, available at global scale, have been estimated considering the mass conservation and using inversion of glacier surface variables: mass balance and slopes in the case of Farinotti et al. (2019), and also considering glacier surface flow velocity in the case of Millan et al. (2022). Uncertainties on such estimates have been largely discussed in Farinotti et al. (2017, 2019, 2021) and Millan et al. (2022). Locally, the uncertainty can reach up to 50% of the estimated value when thickness is below 100 m of ice. Thickness data are mapped considering the RGI-v6.0 glacier extent dated to 2003 in the multi-temporal inventory data available through GLIMS. Glacier ice thickness distribution data are accessible in a raster format at different spatial resolutions. Both products were resampled at a horizontal resolution of 50 m.

8All these data are used to describe and analyse the current state of glaciers in the Val Veny catchment, as well as to simulate their evolution in the coming decades (up to 2050). For that, we followed a rather simplistic approach in which the glacier volume changes through time are quantified starting from the glacier outline and glacier thickness map representative of the glacier state in the early 2000s, and by applying the corresponding rates of glacier surface elevation changes at each site (three rates available from Hugonnet et al., 2021) in an iterative procedure by temporal steps of 10 years from 2000 to 2050.

9With such an approach, the changes in glaciers are calculated independently from any climate data. Doing so, we assume that the thinning rates observed in the former decades (i.e., for the period 2000–2009, 2010–2019 and 2000–2019) can be linearly extrapolated for the next three decades. This assumption can be supported by the limited differences between the climate scenarios in the coming decades (IPCC, 2021). Indeed, differences emerge at the turn of the mid-century and accentuate in the second half of the 21st century. In addition, the three used thinning rates can be seen as different trajectories based on the so-called committed loss; i.e., the volume loss occurring as a result of the glacier-climate imbalance (Zekollari et al., 2020). Finally, because the ice dynamics are implicitly considered in the rates of glacier surface elevation changes our approach seems reasonable for small-sized mountain glaciers where the role of ice dynamics and the potential changes in ice dynamics associated with glacier shrinkage are limited.

Results and Interpretations

Changes in Glacier Surface Area

10Figure 1 illustrates the multi-temporal inventory available through the GLIMS interface for the glaciers in the Val Veny. Four dates are available: 2000, 2003, 2011 and 2015. According to these data, the glacierized area decreased over the entire time period from close to 30 km² in 2000 to close to 24 km² in 2015 which corresponds to a shrinkage of 20%. However, one can note some inconsistencies between the inventories, particularly in the upper reaches of the Brenva and Miage glaciers, close to the summit of Mont Blanc, where the outlines are not consistent with one another. Indeed, close to Mont Blanc summit several glaciers are contiguous and a mismatch between the political border between France and Italy and the geographical limit of the catchments leads to inconsistency in the allocation of the accumulation area into one national inventory or another. In addition, classical sources of inconsistencies in inventory works can also contribute to the differences between the inventories, such as the different spatial resolution of the data sources (i.e., pixel size of the used satellite images that can vary between 30 m in the case of Landsat to a few tens of cm when aerial pictures are used); the debris-cover or snow-cover that can prevent an accurate identification of the glacier outline; the method used, i.e., automatic or supervised work.

11Therefore, an overall shrinkage of 20% between 2000 and 2015 appears to be overestimated.

12On the other hand, focusing on the lower reaches of the glaciers the outlines show a clear signal of shrinkage in glacierized area, more easily evidenced on the clean-ice tongue than on the debris-covered areas. It is noteworthy that the debris-covered part of Brenva Glacier is now completely disconnected from the upper part of the glacier.

Changes in Glacier Surface Elevation

13Figure 2 displays the glacier surface elevation change rates (Dh/Dt) extracted from Hugonnet et al. (2021) dataset for the period 2000–2019 and the two sub-periods 2000–2009 and 2010–2019.

14Unsurprisingly, glacier thinning (i.e., negative Dh/Dt) largely dominates with average annual surface elevation lowering rates that reach more than 4 m/yr over the 20-yr time period. The spatial pattern is consistent between the different periods. However, an increase in the thinning rates between the two sub-periods can be noticed on the debris-covered tongues of Miage and Brenva glaciers. Such an increase can likely be attributed to lower mass fluxes from the upper reaches which is consistent with the lowering trend in the glacier surface flow velocity (see below, section “Glacier Surface Flow Velocity”).

15On the other hand, a slight thickening can be seen for the upper part of the Brenva Glacier. During the sub-period 2000–2009, this thickening is located at the foot of the Grand Pilier d’Angle and Aiguille Blanche de Peuterey (green arrow on Fig. 2 low left). Then, during the sub-period 2010–2019, it propagates downward and is also visible at the foot of the Aiguille Noire de Peuterey (green arrow on Fig. 2 low right). If this thickening could be attributed to increased accumulation in the upper sector, its propagation downward is likely to be related to an increase in the mass transfer which is in agreement with the increasing surface flow velocities in this portion of the glacier that can be seen in the most recent years (see below, section 4.3). Although increasing precipitation at high elevation has not been evidenced so far, it must be reminded that in situ measurements are very spare at high elevation, and therefore limited to document very localised patterns.

Figure 2. Surface elevation change rates quantified from optical satellite derived digital elevation models for the periods: 2000–2019, 2000–2009 and 2010–2019

Figure 2. Surface elevation change rates quantified from optical satellite derived digital elevation models for the periods: 2000–2019, 2000–2009 and 2010–2019

Glacier Surface Flow Velocity

16Figure 3 shows the averaged glacier surface flow velocity (Fig. 3A) for the period 2015–2021 (Rabatel et al., 2023), and the trend in glacier surface flow velocity that has been quantified over the period 2015–2021 (Fig. 3B).

Figure 3. Glacier surface flow velocity derived from optical satellite data. (A) Annually averaged surface flow velocity; (B) Trend of the period 2015–2021

Figure 3. Glacier surface flow velocity derived from optical satellite data. (A) Annually averaged surface flow velocity; (B) Trend of the period 2015–2021

17The range of glacier surfaces flow velocities is large, from almost stagnant ice in the lower reaches of the heavily debris-covered terminus of the Miage Glacier, to more than 500 m/yr in the accumulation zone of the Brenva Glacier. The steep tributaries of the Miage Glacier: i.e., Italian Bionnassay Glacier, du Dôme Glacier and Mont Blanc Glacier, flowing from the uppermost elevation of the study area (the Dôme du Goûter at 4304 m a.s.l. and the Mont Blanc at 4808 m a.s.l.), together with the Brouillard and Frêney glaciers show surface flow velocities between 100 and 250 m/yr on a large portion of their surface area. On the other hand, glaciers with more gentle slopes like Lée Blanche and Estelette glaciers show surface flow velocities around 50 m/yr over most of their area.

18Although the time period covered by the dataset presented by Rabatel et al. (2023) is rather short (i.e., 6 years), several portions of the glaciers show trends in glacier surface flow velocity that are statistically significant (Fig. 3B where only glacierized pixels with significant trend values are displayed). Decreasing trends largely dominate (yellow to red colours) with the highest rates exceeding -5 m/yr² that are mostly seen on the lower parts of the glacier tongues. On the other hand, a large portion of the Brenva Glacier, on the right-hand side of its accumulation zone present an accelerating trend that reaches more than 5 m/yr² over a large area. A similar trend, although less pronounced can be noticed on a small tributary located on the right-hand side of the Miage Glacier.

19In the overall context of glacier volume loss, such increases in glacier surface flow velocity raise questions. Some hypothesis can be mentioned: (1) a thickening of the glacier as noted in section “Changes in Glacier Surface Elevation” with the positive Dh/Dt in this sector of the Brenva Glacier; (2) a change in the thermal regime of the ice with an influence on the ice flow, as documented on the Taconnaz Glacier on the northern side of the Mont Blanc (Gilbert et al., 2014); (3) a change in the subglacial hydrology, that could be related to an increased ablation at the glacier surface in the upper reaches of the glacier, leading more water percolation into the firn and fracturing into the ice.

Ice Thickness Distribution and Glacier Change Between 2000 and 2050

20Figure 4 shows the ice thickness distribution of the glaciers of the Val Veny estimated by Farinotti et al. (2019) and by Millan et al. (2022) as representative of the early 2000s (Fig. 4A & 4C) and as simulated for 2050 (Fig. 4B & 4D) by linearly interpolating the 2000–2019 glacier surface elevation changes quantified by Hugonnet et al. (2021).

21Regarding the initial ice thickness distribution in the early 2000s, if the overall pattern agrees between the two sources of data, the absolute ice thickness values strongly differ with thickness estimates by Millan et al. (2022) being largely higher than the ones estimated by Farinotti et al. (2019). For instance, the ice thickness on the debris-covered tongue of the Miage Glacier largely exceeds 250 m (up to 350 m) in the Millan et al. (2022) estimates (Fig. 4C) while it is closer to 150 m (up to 180 m) in the Farinotti et al. (2019) estimates (Fig. 4A). In the same way, estimates from Farinotti et al. (2019) for the upper reaches of Brenva Glacier are within the range of 60 to 90 m while Millan et al. (2022) show thicknesses within the range of 150–200 m in the same area.

Figure 4. Distribution of ice thickness in 2000 (A and C) and projected for 2050 (B and D) considering the surface elevation change rates for the period 2000–2019 and the initial ice thickness distribution from Farinotti et al., 2019 (A and B) and from Millan et al., 2022 (C and D)

Figure 4. Distribution of ice thickness in 2000 (A and C) and projected for 2050 (B and D) considering the surface elevation change rates for the period 2000–2019 and the initial ice thickness distribution from Farinotti et al., 2019 (A and B) and from Millan et al., 2022 (C and D)

22Figure 5 shows the evolution of the surface area, volume and water contribution of the Val Veny glaciers for the period 2000–2050 considering the three trajectories of glacier surface elevation changes quantified over the periods 2000–2009, 2010–2019 and 2000–2019.

23Initial surface area slightly differs from the one found in the inventory (-6% for Farinotti et al., 2019; and -10% for Millan et al., 2022) because small glaciers are discarded in the ice thickness estimates due to their small size or location in steep terrains were the global DEM used in the ice thickness estimates is subject to high uncertainties. The surface area at the beginning of the simulation is even smaller in Millan et al. (2022). This is due to the fact that the glacier surface flow velocities data are also used as input of the ice thickness estimate, and because such data cannot be retrieved on small glaciers due to their size, more small ice bodies are discarded. Overall, the differences in surface area between Farinotti et al. (2019) and Millan et al. (2022) at the beginning of the simulation is 4.4%, and 4% at the end. The overall glacier shrinkage illustrated by Figure 5 between 2000 and (2020) 2050 is of (-5±0.5%) -25±1% vs. (-9±0.5%) -24.5±0.5% when using Farinotti et al. (2019) vs. Millan et al. (2022) ice thickness distribution data as input, respectively.

Figure 5. Evolution of the surface area (to the left), volume (in the middle) and water contribution (to the right) of the Val Veny glaciers for the period 2000–2050 considering the three trajectories of glacier surface elevation changes quantified over the periods 2000–2009, 2010–2019 and 2000–2019

Figure 5. Evolution of the surface area (to the left), volume (in the middle) and water contribution (to the right) of the Val Veny glaciers for the period 2000–2050 considering the three trajectories of glacier surface elevation changes quantified over the periods 2000–2009, 2010–2019 and 2000–2019

24Differences in volume between Farinotti et al. (2019) and Millan et al. (2022) at the beginning of the simulation is 38%, and 74% at the end. The volume estimate by Millan et al. (2022) being largely higher. Such difference at the beginning of the study period is a direct consequence of the inversion method used to estimate the glacier thickness distribution. However, without in situ measurements of ice thickness, it is impossible to say which estimate is better. The difference in volume is much higher at the end of the study period (i.e., in 2050). This has to be related to the pattern of ice thickness distribution. For instance, the thickest area on Brenva Glacier is located at low elevation in Farinotti et al. (2019) estimate. These lower areas are thinning, and in some case disappearing, faster (highest Dh/Dt, see Fig. 2) thus increasing the difference in volume at the end of the study period. Overall, Figure 5 shows that the glacier volume loss between 2000 and (2020) 2050 is of (-20±1%) -43±2% vs. (-13±1%) -29±1% when using Farinotti et al. (2019) vs. Millan et al. (2022) ice thickness distribution data as input, respectively.

25The difference in water contribution from the glacier volume loss between the estimates of glacier evolutions when using Farinotti et al. (2019) or Millan et al. (2022) ice thickness distribution data as input data is 7% at the beginning of the simulation, and 6% at the end. Although the glacier volume is different, the volume loss rate is close. Figure 5 shows that the water contributions due to glacier volume loss are 380 L/s vs. and 350 L/s at the beginning of the period (i.e., for the decade 2000–2010) and 230 L/s vs. 220 L/s at the end of the period (i.e., for the decade 2040–2050), when using Farinotti et al. (2019) vs. Millan et al. (2022) ice thickness distribution data as input, respectively. This represents a decrease by 40% in both cases over the 50-yr period.

Conclusions

26In this study, we analysed the contribution of satellite-based glacier products for the quantification of the current glacier evolution in the Val Veny (southern side of the Mont Blanc massif, Italy). Such products allow documenting changes over the last two decades in terms of glacier surface area (i.e. multi-temporal inventories), volume and surface flow velocity, as well as estimating the ice thickness distribution. Combining these products allows characterising the state of the glaciers and also to propose projections of their evolution in the coming decades. Our main results are:

  • A clear shrinkage in glacier surface area observed from the multi-temporal inventories. However, we note some inconsistencies with the inventories made by different groups, within different initiatives. A homogenisation work could be encouraged and, in view of the important melting experienced by the glaciers in recent years, an update would deserve to be made.

  • The surface elevation changes maps derived from satellite stereo-images constitute a highly relevant product to both documents the current state of glaciers and to calibrate models for projecting their future evolution. To realise such maps, the ASTER sensor onboard of Terra satellite has proven its relevance. Unfortunately, the lifetime of this platform is almost over (end of 2023—early 2024) and no equivalent satellite mission is currently planned by the space agencies. This is highly regrettable as no continuity is insured for such maps to be realised in the coming years.

  • Regarding the glacier surface flow velocities. The satellite product derived from Sentinel-2 data is highly relevant. Although an overall trend of decrease in glacier surface flow velocities has been documented on the Val Veny glaciers, consistent with the overall glacier shrinkage and thinning, a significant increase in surface flow velocities is documented in the upper part of Brenva Glacier. Such trend raises questions on its origin, either due to a local thickening or a possible change in the thermal regime of the glacier or subglacial hydrology.

  • Regarding the glacier ice thickness distribution, important differences between the available products can be seen. Overall, Millan et al. (2022) show thicker ice masses than Farinotti et al. (2019). In situ measurements would be valuable to qualify which of the products is the most accurate. On the other hand, such in situ data would help to better constrain future inversion models.

  • Regarding the future evolution of the Val Veny glaciers up to 2050. Our simple approach based on interpolating the thinning rates determined over the past two decades shows that the water contribution originating from glacier volume loss will decrease by close to 40%. Such decrease is more pronounced between 2020 and 2050 when using Farinotti et al. (2019) ice thickness distribution data as input of the modelling. Our results would deserve to be confirmed by other approaches explicitly considering the glacier dynamics, mostly for the two largest glaciers (Brenva and Miage) for which the hypothesis we made that neglects the role of ice dynamics is the most questionable.

27Future works could rely on the changes we documented for Brenva Glacier to confirm the thickening and acceleration of the flow in its upper part: to see if it comes from the thermal regime (drilling a hole with temperature measurements could help to confirm the thermal state of the glacier), or if it comes from the subglacial hydrology or if it can simply be linked to a more important accumulation in the recent years at high elevation.

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Table des illustrations

Titre Figure 1. Glaciers of the Val Veny catchment in the upper Aoste Valley, Italy
Légende Glacier outlines are taken from the GLIMS database.
URL http://journals.openedition.org/rga/docannexe/image/11619/img-1.png
Fichier image/png, 1,0M
Titre Figure 2. Surface elevation change rates quantified from optical satellite derived digital elevation models for the periods: 2000–2019, 2000–2009 and 2010–2019
URL http://journals.openedition.org/rga/docannexe/image/11619/img-2.png
Fichier image/png, 1,8M
Titre Figure 3. Glacier surface flow velocity derived from optical satellite data. (A) Annually averaged surface flow velocity; (B) Trend of the period 2015–2021
URL http://journals.openedition.org/rga/docannexe/image/11619/img-3.png
Fichier image/png, 1,5M
Titre Figure 4. Distribution of ice thickness in 2000 (A and C) and projected for 2050 (B and D) considering the surface elevation change rates for the period 2000–2019 and the initial ice thickness distribution from Farinotti et al., 2019 (A and B) and from Millan et al., 2022 (C and D)
URL http://journals.openedition.org/rga/docannexe/image/11619/img-4.png
Fichier image/png, 1,1M
Titre Figure 5. Evolution of the surface area (to the left), volume (in the middle) and water contribution (to the right) of the Val Veny glaciers for the period 2000–2050 considering the three trajectories of glacier surface elevation changes quantified over the periods 2000–2009, 2010–2019 and 2000–2019
URL http://journals.openedition.org/rga/docannexe/image/11619/img-5.png
Fichier image/png, 84k
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Référence électronique

Antoine Rabatel, Etienne Ducasse, Victor Ramseyer et Romain Millan, « State and Fate of Glaciers in the Val Veny (Mont-Blanc Range, Italy): Contribution of Optical Satellite Products »Journal of Alpine Research | Revue de géographie alpine [En ligne], 111-2 | 2023, mis en ligne le 02 novembre 2023, consulté le 10 décembre 2023. URL : http://journals.openedition.org/rga/11619

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Auteurs

Antoine Rabatel

Université Grenoble Alpes, CNRS, IRD, INRAE, Grenoble-INP, Institut des Géosciences de l’Environnement (IGE, UMR 5001)

Etienne Ducasse

Université Grenoble Alpes, CNRS, IRD, INRAE, Grenoble-INP, Institut des Géosciences de l’Environnement (IGE, UMR 5001)

Victor Ramseyer

Université Grenoble Alpes, CNRS, IRD, INRAE, Grenoble-INP, Institut des Géosciences de l’Environnement (IGE, UMR 5001)

Romain Millan

Université Grenoble Alpes, CNRS, IRD, INRAE, Grenoble-INP, Institut des Géosciences de l’Environnement (IGE, UMR 5001)

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