Implications of Accuracy of Global Glacier Inventories in Hydrological Modeling: A Case Study of the Western Himalayan Mountain Range

被引:1
|
作者
Attaullah, Haleema [1 ]
Khan, Asif [2 ]
Khan, Mujahid [1 ]
Atta, Hadia [3 ]
Iqbal, Muhammad Shahid [4 ]
机构
[1] Univ Engn & Technol, Dept Civil Engn, Peshawar 25000, Pakistan
[2] Univ Engn & Technol, Dept Civil Engn, Jalozai Campus, Peshawar 24210, Pakistan
[3] Islamia Coll, Dept Math, Peshawar 25000, Pakistan
[4] Int Water Management Inst IWMI, Lahore 54800, Pakistan
关键词
Hindukush Karakoram Himalaya (HKH); glacier inventory; GLIMS; RGI; debris-covered glacier outlines; glacier-melt contribution; Upper Indus Basin; UPPER INDUS BASIN; CLIMATE-CHANGE; RIVER FLOWS; KARAKORAM; SNOW; RUNOFF; PREDICTION; CATCHMENT; HINDUKUSH; REGIMES;
D O I
10.3390/w15223887
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Alpine glaciers are a fundamental component of the cryosphere and are significantly sensitive to climate change. One such region is the Hindukush Karakoram Himalaya (HKH) and Tibetan Plateau (TP) region, which contains more than 40,000 glaciers. There are more than 12 glacier inventories available covering parts of (or the entire) HKH region, but these show significant uncertainties regarding the extent of glaciers. Researchers have used different glacier inventories without assessing their accuracy. This study, therefore, assessed the implications of the accuracy of global glacier inventories in hydrological modeling and future water resource planning. The accuracy assessment of most commonly used two global glacier inventories (Global Land Ice Monitoring from Space-GLIMS v 2.0 and Randolph Glacier Inventory-RGI v 6.0) has been carried out for three sub-basins of the Upper Indus Basin-the Swat, the Chitral, and the Kabul River basins (combined, this is referred to as the Great Kabul River Basin)-with a total basin area of 94,552.86 km2. Glacier outlines have been compared with various Landsat 7 ETM+, Landsat 8, high-resolution Google Earth images, and manually digitized debris-covered glacier outlines during different years. The total glacier area for the Great Kabul River Basin derived from RGI and GLIMS is estimated to be 2120.35 km2 and 1789.94 km2, respectively, which was a difference of 16.9%. Despite being sub-basins of the Great Kabul River Basin, the Swat, and the Chitral River basins were different by 54.74% and 19.71%, respectively, between the two inventories, with a greater glacierized area provided by RGI, whereas the Kabul River basin was different by 54.72%, with greater glacierized area provided by GLIMS. The results and analysis show that GLIMS underestimates glacier outlines in the Swat and the Chitral basins and overestimates glacier extents in the Kabul River basin. The underestimation is mainly due to the non-representation of debris-covered glaciers. The overestimation in GLIMS data is due to the digitization of seasonal snow as part of the glaciers. The use of underestimated GLIMS outlines may result in 5-10% underestimation of glacier-melt contribution to flows in the Swat River basin, while an underestimation of 7% to 15% is expected in the Chitral River Basin, all compared to RGI v 6.0 outlines. The overestimation of glacier-melt contribution to flows in the Kabul River basin is insignificant (1% to 2%) using GLIMS data. In summary, the use of the GLIMS inventory will lead to underestimated flows and show that the Great Kabul River Basin (particularly the Chitral River Basin) is less sensitive to climate change effects. Thus, the current study recommends the use of RGI v 6.0 (best glacier inventory) to revisit the existing biased hydro-climate studies and to improve future hydro-climate studies with the concomitant rectification of the MODIS snow coverage data. The use of the best glacier inventory will provide the best estimates of flow sensitivity to climate change and will result in well-informed decision-making, precise and accurate policies, and sustainable water resource management in the study area. The methodology adopted in the current study may also be used in nearby areas with similar hydro-climate conditions, as well as for the most recently released RGI v 7.0 data.
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