Abstract. Delineation of Glaciers is a challenging task in the Himalaya due to its complex topography, cloud cover, seasonal snow cover, hillshade, debris cover. Glacio-hydrological studies including mass balance, run-off, and dynamic modelling rely on the availability of consistent and reliable glacier inventory datasets. This article on data set presents a homogenous, multidecadal inventory of glaciers in the Chandra-Bhaga Basin (CB Basin), western Himalaya, for 1993, 2000, 2010, and 2019. Landsat Thematic Mapper (TM), Enhanced Thematic mapper (ETM+), and Operational Land Imager (OLI) imageries, with minimum snow and cloud cover have been used for enhanced accuracy and consistency. Uncertainty assessment for the generated glacier inventory was performed, following various approaches such as buffer method, standard error estimation, and manual digitisation error and the maximum uncertainty has been quantified. We have identified and manually mapped a total of 251 glaciers with an area > 0.5 km², and in order to minimise the uncertainty, field surveys were carried out on 6 glaciers in the basin. Out of these 251 glaciers, 217 are clean ice and 35 were debris-covered glaciers. The estimated total glacier area was 996 ± 62 km² in 1993 that decreased to 973 ± 70 km² in 2019. Apart from quantifying temporal changes in glacier area, this inventory further allows the estimation of supraglacial debris cover and glacier volume. The supraglacial debris cover area has increased by 14.1 ± 2.54 km² (15.2 %) during 1993–2019. Accuracy of the debris cover dataset estimated using ground surveys is 82 % with a kappa coefficient of 0.87. Moreover, a glacier ice volume dataset was also generated by incorporating the inventory into Glacier Bed Topography Version 2 (GlabTop2) model and shows a total of 112.5 ± 41 km³ of ice volume stored in the CB Basin glaciers. For accuracy assessment of the DEMs generated using ASTER Stereopairs images, DGPS surveys were carried out on (28 GCPs) and off (6 GCPs) the glaciers. Glacier volume uncertainty with respect to the generated DEMs and model bias is 5.3 km³ and 35.5 km³ respectively. Overestimation of glacier volume due to over deepening is estimated to be 1.2 km³. The impact of climate change on the Himalayan glaciers is a matter of serious concern and such holistic multitemporal inventory datasets can help quantify that impact with improved certainty.

中文翻译：

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印度西喜马拉雅 Chandra-Bhaga 盆地的综合多年代冰川清单数据集

摘要。由于其复杂的地形、云层、季节性积雪、山体阴影、碎屑覆盖，在喜马拉雅山脉划定冰川是一项具有挑战性的任务。包括质量平衡、径流和动态建模在内的冰川水文研究依赖于一致和可靠的冰川清单数据集的可用性。这篇关于数据集的文章介绍了 1993 年、2000 年、2010 年和 2019 年喜马拉雅西部 Chandra-Bhaga 盆地（CB 盆地）的同质、多年代冰川清单。Landsat Thematic Mapper (TM)，Enhanced Thematic Mapper (ETM+) , 和操作陆地成像仪 (OLI) 图像，具有最少的积雪和云量，已用于提高准确性和一致性。采用缓冲法、标准误差估计、和手动数字化误差和最大不确定性已被量化。我们已经识别并手动绘制了总共 251 条面积 > 0.5 公里的冰川²，为了尽量减少不确定性，对流域内的 6 个冰川进行了实地调查。在这 251 个冰川中，217 个是干净的冰，35 个是被碎片覆盖的冰川。估计的冰川总面积在 1993 年为 996 ± 62 km ² ，到 2019年减少到 973 ± 70 km ²。除了量化冰川面积的时间变化外，该清单还可以进一步估计冰上碎片覆盖和冰川体积。冰上碎片覆盖面积增加了 14.1 ± 2.54 km ²（15.2%）在 1993-2019 年期间。使用地面调查估计的碎片覆盖数据集的准确性为 82%，kappa 系数为 0.87。此外，通过将清单纳入冰川床地形第 2 版 (GlabTop2) 模型，还生成了冰川冰量数据集，显示CB 盆地冰川中储存的冰量总计为 112.5 ± 41 km ^{3 。}为了评估使用 ASTER Stereopairs 图像生成的 DEM 的准确性，在（28 个 GCP）和（6 个 GCP）冰川上进行了 DGPS 调查。关于生成的 DEM 和模型偏差的冰川体积不确定性分别为 5.3 km ³和 35.5 km ³。由于过度加深而高估的冰川体积估计为 1.2 km ³. 气候变化对喜马拉雅冰川的影响是一个值得严重关注的问题，这种整体的多时相清单数据集可以帮助更确定地量化这种影响。