The impact of climate change and glacier mass loss on the hydrology in the Mont-Blanc massif

Abstract

The Mont-Blanc massif, being iconic with its large glaciers and peaks of over 4,000 m, will experience a sharp increase in summer temperatures during the twenty-first century. By 2100, the impact of climate change on the cryosphere and hydrosphere in the Alps is expected to lead to a decrease in annual river discharge. In this work, we modelled the twenty-first century evolution of runoff in the Arve river, downstream of Mont-Blanc's French side. For the first time for this region, we have forced a hydrological model with output from an ice-dynamical glacier model and 16 downscaled climate projections, under RCP4.5 and RCP8.5 scenarios. By 2100, under RCP8.5 (high-emission scenario), the winter discharge of the Arve river remains low but is expected to increase by 80% when compared to the beginning of the century. By contrast, the summer season, currently the most important discharge period, will be marked by a runoff decrease of approximately 40%. These changes are almost similar according to a scenario with a lower warming (RCP4.5) and are mostly driven by glacier retreat. These shifts will have significant downstream impacts on water quantity and quality, affecting hydroelectric generation, agriculture, forestry, tourism and aquatic ecosystems. Global change and temperature increase are projected to lead to major environmental changes in mountainous regions 1 , including major changes in glacier extent 2,3 , permafrost 4 , ice and snow cover 5-7 , and vegetation 8,9. In the Alps, the cryosphere is crucial for water storage and for contributing to the total discharge of the main major European rivers 10. In this context, major changes are likely to occur in water discharge 11 in and near these vulnerable regions, mostly decreasing runoff in summer and modifying water resources 12. These changes could either be driven by (i) changes in precipitation 13,14 , especially in the proportion of liquid and solid water 15,16 , depending on the altitude of the 0 °C isotherm 17 ; (ii) a general warming trend, increasing snow and ice melt, hereby contributing to glacier mass loss 18 , but also increasing evapotranspiration from the surface; (iii) glacier retreat in response to such warming, ultimately leading to changes in water discharge as the available ice reserves gradually decrease 11. Of particular importance are the relative weight of each of these forcings over the coming years and decades, and their dependency on the greenhouse gas emission scenarios. These changes will have major effects on river discharges and water quality 19 , impacting hydropower generation, agriculture, forestry, tourism and aquatic ecosystems 8,20. Many studies have explored the impact of global warming and glacier retreat on glacier runoff, at global 21 and regional scales (e.g., High Mountain Asia 22,23 , the Andes 24,25 and the USA 26). In the European Alps, glacier runoff evolution under climate change has already been investigated in Switzerland 27,28 and Austria 29 for example. In the French Alps, assessments of future changes are sca...

Pay Attention to Evolution: Time Series Forecasting With Deep Graph-Evolution Learning

“…Due to the fact that not all the algorithms perform evenly across them, we display the 34 most prominent ones out of the 49 tested algorithms; for the extended results, please refer to the Supplementary Material. We also discuss the ablation experiments, which were carried out with REGENN's hyperparameters; in the Supplementary Material, we provide two other rounds of this same experiment using as hyperparameters PYTORCH's defaults 4…”

“…Time series refers to the persistent recording of a phenomenon along time, a continuous and intermittent unfolding of chronological events subdivided into past, present, and future. In the last decades, time series analysis has been vital to predict dynamic phenomena on a wide range of applications, such as climate change [1]- [4], financial market [5]- [7], land-use monitoring [8]- [10], anomaly detection [11]- [13], energy consumption, and price forecasting [14]- [16], apart from epidemiology and healthcarerelated studies [17]- [22]. On such applications, an effective data-driven decision requires precise forecasting based on time series [23].…”

Comment on hess-2021-92

“…The higher importance of melt contribution for summer runoff in high-elevation catchments compared to the low-elevation catchments can also explain the larger decrease in summer runoff of ∆Q = -14 to -24 mm month -1 compared to ∆Q = -6 to 13 mm month -1 in the low-elevation catchments. Furthermore, a decrease in melt contribution from glaciated areas could potentially be of importance for the decrease in summer runoff in the Pitztal (Hanzer et al, 2018;Laurent et al, 2020). Overall, the decrease in melt contribution and increase in potential evaporation influence the change in monthly runoff more than the changing precipitation patterns, as the maximum decrease in monthly runoff occurs earlier than for monthly precipitation.…”

“…As a result, summer low flows are expected to decrease in catchments in Switzerland (Jenicek et al, 2018;Muelchi et al, 2021). However, annual low flows are projected to increase in the Alps as winter low flows increase due to changes in snow dynamics related to increased temperatures (Laaha et al, 2016;Parajka et al, 2016;Marx et al, 2018;Laurent et al, 2020;Muelchi et al, 2021). With respect to annual floods in high alpine catchments, studies disagree on the sign of change, suggesting future increases (Köplin et al, 2014) or decreases (Muelchi et al, 2021) in magnitude.…”

Future changes in annual, seasonal and monthly runoff signatures in contrasting Alpine catchments in Austria

“…For example, the choice of estimation method for potential evaporation influences the results and, thus, introduces uncertainty (Seiller and Anctil, 2016). Similarly, snow processes are simplified by using a degree day method and, in the absence of more detailed data, not considering snow redistribution and sublimation, although it can have a significant effect in high-elevation areas (MacDonald et al, 2010). In general, different models with different structures are often not consistent in the results (e.g., Knoben et al, 2020) or their internal dynamics (Bouaziz et al, 2021).…”