DERIVATION OF SUPRAGLACIAL DEBRIS COVER BY MACHINE LEARNING ALGORITHMS ON THE GEE PLATFORM: A CASE STUDY OF GLACIERS IN THE HUNZA VALLEY

In this study, we presented a nearly complete inventory of glacier mass change dataset across the eastern Tibetan Plateau by using topographical maps, which will enhance the knowledge on the heterogeneity of glacier change before 2000. Our dataset, in combination with the published results, provide a nearly five decades mass balance to support hydrological simulation, and to evaluate the contribution of mountain glacier loss to sea level.

We propose a data fusion framework based on the random forest regression algorithm to derive a comprehensive snow depth product for the Northern Hemisphere from 1980 to 2019. This new fused snow depth dataset not only provides information about snow depth and its variation over the Northern Hemisphere but also presents potential value for hydrological and water cycle studies related to seasonal snowpacks.

Glacier centerlines are crucial input for many glaciological applications. We propose a new algorithm to derive glacier centerlines and implement the corresponding program in Python language. Application of this method to 48 571 glaciers in the second Chinese glacier inventory automatically yielded the corresponding glacier centerlines with an average computing time of 20.96 s, a success rate of 100 % and a comprehensive accuracy of 94.34 %.

The theoretical and methodological bases for all processing steps including glacial lake definition and classification and lake boundary delineation are discussed based on satellite remote sensing data and GIS techniques. The relative area errors of each lake in 2018 varied 1 %–79 % with average relative area errors of ±13.2 %. In high-mountain Asia, 30 121 glacial lakes with a total area of 2080.12 ± 2.28 km² were catalogued in 2018 with a 15.2 % average rate of increase in area in 1990–2018.

During the past three decades, Longbasaba Glacier has experienced a continuous and accelerating recession in glacier area and length but accompanied by the decelerating surface lowing and ice flow. The glacier surface lowering played a predominant role in the mass contribution of glacier shrinkage to the increase in lake water volume, while ice avalanches were the main potential trigger for failure of moraine dams and subsequent GLOF events.

We present an integrated view of the glacier area and its mass changes for Mt. Xinqingfeng and Mt. Malan of the inner Tibetan Plateau as derived from topographic maps, Landsat, ASTER, SRTM DEM, and TerraSAR-X/TanDEM-X for the period of 1970–2012 and 1970–2018, respectively. The glaciers experienced weak shrinkage and slight negative mass balance. The Monuomaha Glacier and Zu Glacier together with another 5 glaciers displayed the surging or advancing characteristics during the observation period.

This study presents diminishing ice cover in the central Nyainqentanglha Range by 0.68 % ± 0.05 % a⁻¹, and a mean mass deficit of 0.46 % ± 0.04 m w.e. a⁻¹ since 1968. Mass losses accelerating from 0.42 % ± 0.05 m w.e. a⁻¹ to 0.60 % ± 0.20 m w.e. a⁻¹ during 1968–2000 and 2000–~2013, with thinning noticeably greater on the debris-covered ice than the clean ice. Surface-elevation changes can be influenced by ice cliffs, as well as debris cover, and land- or lake-terminating glaciers and supraglacial lakes.

This study presents diminishing ice cover in the Kangri Karpo Mountains by 24.9 % ± 2.2 % or 0.71 % ± 0.06 % a⁻¹ from 1980 to 2015 but with nine glaciers advancing. By utilizing geodetic methods, glaciers have experienced a mean mass deficit of 0.46 ± 0.08 m w.e. a⁻¹ from 1980 to 2014. These glaciers showed slight accelerated shrinkage and significant accelerated mass loss during 2000–2015 compared to that during 1980–2000, which is consistent with the tendency of climate warming.