Tariq Abdullah, Shakil Ahmad Romshoo, Mustafa Hameed Bhat
{"title":"Comparative analysis of glacier inventories and vicennial glacier changes (2000–2020) in the Northwestern Himalaya","authors":"Tariq Abdullah, Shakil Ahmad Romshoo, Mustafa Hameed Bhat","doi":"10.1007/s10661-025-13682-7","DOIUrl":null,"url":null,"abstract":"<div><p>This study evaluates global and regional glacier inventories (RGI, GAMDAM, ICIMOD) against the newly generated Kashmir University Glacier Inventory (KUGI) for the Jhelum, Suru, and Chenab basins in the northwestern Himalaya. The KUGI, comprising 2096 glaciers with an area of ~ 3300.0 ± 117.8 km<sup>2</sup>, was created by manually delineating glacier boundaries from Landsat satellite data, supplemented by a Digital Elevation Model (DEM), Google Earth images, and limited field surveys. The inventory includes 154 glaciers in the Jhelum basin (85.9 ± 11.4 km<sup>2</sup>), 328 in the Suru basin (487 ± 16.2 km<sup>2</sup>), and 1614 in the Chenab basin (2727 ± 90.2 km<sup>2</sup>). While estimates of glacier area, altitude, slope, and aspect of the individual glaciers varied significantly among the four inventories, a broad similarity was found among the evaluated inventories in terms of distribution of the most common glacier size, elevation, and slope classes. Majority of the of glaciers were smaller than 1 km<sup>2</sup>, while the 1–5 km<sup>2</sup> size class accounted for the largest share of the total glacier area. The GAMDAM (<span>\\({R}_{A}^{B}\\)</span>=0.75) and RGI (<span>\\({R}_{A}^{B}\\)</span>=0.73) inventories were relatively consistent with the KUGI; however, significant discrepancies were noted in the debris-covered and shadowed glaciers, particularly in the ICIMOD inventory. Furthermore, the study revealed differential glacier area changes across the three basins from 2000 to 2020. The Jhelum basin experienced the largest area loss (8%), followed by the Suru (4%) and Chenab basins (3%). These area losses are largely explained by the prevailing topographic and morphological settings of the glaciers. The development of a multi-date KUGI with improved attributes and enhanced accuracy in the data-scarce Himalaya offers a reliable database, fostering research in hydrology, glaciology, climate change, glacial hazards, glacier evolution and water resource management.</p></div>","PeriodicalId":544,"journal":{"name":"Environmental Monitoring and Assessment","volume":"197 3","pages":""},"PeriodicalIF":3.0000,"publicationDate":"2025-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Monitoring and Assessment","FirstCategoryId":"93","ListUrlMain":"https://link.springer.com/article/10.1007/s10661-025-13682-7","RegionNum":4,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
This study evaluates global and regional glacier inventories (RGI, GAMDAM, ICIMOD) against the newly generated Kashmir University Glacier Inventory (KUGI) for the Jhelum, Suru, and Chenab basins in the northwestern Himalaya. The KUGI, comprising 2096 glaciers with an area of ~ 3300.0 ± 117.8 km2, was created by manually delineating glacier boundaries from Landsat satellite data, supplemented by a Digital Elevation Model (DEM), Google Earth images, and limited field surveys. The inventory includes 154 glaciers in the Jhelum basin (85.9 ± 11.4 km2), 328 in the Suru basin (487 ± 16.2 km2), and 1614 in the Chenab basin (2727 ± 90.2 km2). While estimates of glacier area, altitude, slope, and aspect of the individual glaciers varied significantly among the four inventories, a broad similarity was found among the evaluated inventories in terms of distribution of the most common glacier size, elevation, and slope classes. Majority of the of glaciers were smaller than 1 km2, while the 1–5 km2 size class accounted for the largest share of the total glacier area. The GAMDAM (\({R}_{A}^{B}\)=0.75) and RGI (\({R}_{A}^{B}\)=0.73) inventories were relatively consistent with the KUGI; however, significant discrepancies were noted in the debris-covered and shadowed glaciers, particularly in the ICIMOD inventory. Furthermore, the study revealed differential glacier area changes across the three basins from 2000 to 2020. The Jhelum basin experienced the largest area loss (8%), followed by the Suru (4%) and Chenab basins (3%). These area losses are largely explained by the prevailing topographic and morphological settings of the glaciers. The development of a multi-date KUGI with improved attributes and enhanced accuracy in the data-scarce Himalaya offers a reliable database, fostering research in hydrology, glaciology, climate change, glacial hazards, glacier evolution and water resource management.
本研究对喜马拉雅西北部Jhelum, Suru和Chenab盆地的全球和区域冰川清单(RGI, GAMDAM, ICIMOD)与新生成的克什米尔大学冰川清单(KUGI)进行了评估。KUGI由2096个冰川组成,面积为3300.0±117.8 km2,由Landsat卫星数据手动划定冰川边界,辅以数字高程模型(DEM)、谷歌地球图像和有限的实地调查。其中Jhelum流域154座冰川(85.9±11.4 km2), Suru流域328座冰川(487±16.2 km2), Chenab流域1614座冰川(2727±90.2 km2)。虽然对冰川面积、海拔高度、坡度和单个冰川坡向的估计在四个清单之间存在显著差异,但在最常见的冰川大小、海拔高度和坡度类别的分布方面,被评估的清单之间存在广泛的相似性。大部分冰川面积小于1 km2,而1 ~ 5 km2的冰川面积占冰川总面积的比例最大。GAMDAM (\({R}_{A}^{B}\) =0.75)和RGI (\({R}_{A}^{B}\) =0.73)量表与KUGI相对一致;然而,在碎片覆盖的冰川和阴影的冰川中,特别是在ICIMOD的清单中,发现了显著的差异。此外,研究还揭示了2000年至2020年三个流域冰川面积的差异变化。Jhelum盆地的面积损失最大(8.8%)%), followed by the Suru (4%) and Chenab basins (3%). These area losses are largely explained by the prevailing topographic and morphological settings of the glaciers. The development of a multi-date KUGI with improved attributes and enhanced accuracy in the data-scarce Himalaya offers a reliable database, fostering research in hydrology, glaciology, climate change, glacial hazards, glacier evolution and water resource management.
期刊介绍:
Environmental Monitoring and Assessment emphasizes technical developments and data arising from environmental monitoring and assessment, the use of scientific principles in the design of monitoring systems at the local, regional and global scales, and the use of monitoring data in assessing the consequences of natural resource management actions and pollution risks to man and the environment.