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.

Information about end‐of‐winter spatial distribution of snow depth is important for seasonal forecasts of spring/summer streamflow in high‐mountain regions. Nevertheless, such information typically relies upon extrapolation from a sparse network of observations at low elevations. Here, we test the potential of high‐resolution snow depth data derived from optical stereophotogrammetry of Pléiades satellites for improving the representation of snow depth initial conditions (SDICs) in a glacio‐hydrological model and assess potential improvements in the skill of snowmelt and streamflow simulations in a high‐elevation Andean catchment. We calibrate model parameters controlling glacier mass balance and snow cover evolution using ground‐based and satellite observations, and consider the relative importance of accurate estimates of SDICs compared to model parameters and forcings. We find that Pléiades SDICs improve the simulation of snow‐covered area, glacier mass balance, and monthly streamflow compared to alternative SDICs based upon extrapolation of meteorological variables or statistical methods to estimate SDICs based upon topography. Model simulations are found to be sensitive to SDICs in the early spring (up to 48% variability in modeled streamflow compared to the best estimate model), and to temperature gradients in all months that control albedo and melt rates over a large elevation range (>2,400 m). As such, appropriately characterizing the distribution of total snow volume with elevation is important for reproducing total streamflow and the proportions of snowmelt. Therefore, optical stereo‐photogrammetry offers an advantage for obtaining SDICs that aid both the timing and magnitude of streamflow simulations, process representation (e.g., snow cover evolution) and has the potential for large spatial domains.

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<p>This study presents a glacier clustering for the Chilean Andes (17.6-55.4°S) realized with the Partitioning Around Medoids (PAM) algorithm and using topographic and climatic variables over the 1980-2019 period. We classified ~24,000 glaciers inside thirteen different clusters (C1 to C13). These clusters show specific conditions in terms of annual and monthly amounts of precipitation, temperature, and solar radiation. In the Northern part of Chile, the Dry Andes (17-36°S) gather five clusters (C1-C5) that display mean annual precipitation and temperature differences up to 400 mm/yr and 8°C, respectively, and a mean elevation difference reaching 1800 m between glaciers in C1 and C5 clusters. In the Wet Andes (36-56°S) the highest differences were observed at the Southern Patagonia Icefield (50°S), with mean annual values for precipitation above 3700 mm/yr (C12, maritime conditions) and below 1000 mm/yr in the east of Southern Patagonia Icefield (C10), and with a difference in mean annual temperature near 4°C and mean elevation contrast of 500 m.</p><p>This classification confirms that Chilean glaciers cannot be grouped only latitudinally as it has been commonly considered, hence contributing to a better understanding of recent glacier volume changes at regional and watershed scales. An example of this was observed in the Maipo watershed (33°S), where the Echaurren Norte glacier is located, which is the reference glacier for Chile and WGMS because it has the oldest time series of mass balance monitoring in the Andes, followed by the Piloto Este glacier, since the 70's. Indeed, we identified that Echaurren Norte glacier only has similarities with 5% of the glacierized surface area of the Maipo watershed. Echaurren Norte glacier is within a glacier cluster that presents warmer and wetter climate conditions (3.1°C, 574 mm/yr) than the average of the watershed, a cluster that contains also 68% of the glacierized surface composed of rock glaciers.</p>

Over the last decades, glaciers across the Andes have been strongly affected by a loss of mass and surface areas. This increases risks of water scarcity for the Andean population and ecosystems. However, the factors controlling glacier changes in terms of surface area and mass loss remain poorly documented at watershed scale across the Andes. Using machine learning methods (Least Absolute Shrinkage and Selection Operator, known as LASSO), we explored climatic and morphometric variables that explain the spatial variance of glacier surface area variations in 35 watersheds (1980–2019), and of glacier mass balances in 110 watersheds (2000–2018), with data from 2,500 to 21,000 glaciers, respectively, distributed between 8 and 55°S in the Andes. Based on these results and by applying the Partitioning Around Medoids (PAM) algorithm we identified new glacier clusters. Overall, spatial variability of climatic variables presents a higher explanatory power than morphometric variables with regards to spatial variance of glacier changes. Specifically, the spatial variability of precipitation dominates spatial variance of glacier changes from the Outer Tropics to the Dry Andes (8–37°S) explaining between 49 and 93% of variances, whereas across the Wet Andes (40–55°S) the spatial variability of temperature is the most important climatic variable and explains between 29 and 73% of glacier changes spatial variance. However, morphometric variables such as glacier surface area show a high explanatory power for spatial variance of glacier mass loss in some watersheds (e.g., Achacachi with r2 = 0.6 in the Outer Tropics, Río del Carmen with r2 = 0.7 in the Dry Andes). Then, we identified a new spatial framework for hydro-glaciological analysis composed of 12 glaciological zones, derived from a clustering analysis, which includes 274 watersheds containing 32,000 glaciers. These new zones better take into account different seasonal climate and morphometric characteristics of glacier diversity. Our study shows that the exploration of variables that control glacier changes, as well as the new glaciological zones calculated based on these variables, would be very useful for analyzing hydro-glaciological modelling results across the Andes (8–55°S).

Utilizando variables topográficas y climáticas, presentamos clústeres glaciares en los Andes chilenos (17.6-55.4°S), donde se ejecutó el algoritmo de aprendizaje automático no supervisado Partitioning Around Medoids (PAM). Los resultados clasificaron 23,974 glaciares dentro de trece clústeres, que muestran condiciones específicas en términos de cantidades anuales y mensuales de precipitación, temperatura y radiación solar. En los Andes secos, los valores medios anuales de cinco clústeres glaciares (C1-C5) muestran una diferencia de precipitación y temperatura de hasta 400 mm (29 y 33°S) y 8°C (33°S), con una resta de elevación promedio de 1800 m entre glaciares clústeres C1 y C5 (18 a 34°S). Mientras que en los Andes húmedos las mayores diferencias se observaron en la latitud del Campo de Hielo Patagónico Sur (50°S), donde los valores medios anuales de precipitación y temperatura muestran una precipitación marítima por encima de 3700 mm/año (C12), donde el aire húmedo occidental juega un papel importante, y por debajo de 1000 mm/año al este del Campo de Hielo Patagónico Sur (C10), con diferencias de temperatura cercanas a 4°C y una resta de elevación promedio de 500 m. Esta clasificación confirma que los glaciares chilenos no pueden agruparse solo latitudinalmente, contribuyendo a una mejor comprensión de los cambios recientes en el volumen de los glaciares a escala regional.