Department of Civil Engineering, Indian Institute of Technology, Delhi, New Delhi, 110016, India.
Sci Rep. 2020 Jul 22;10(1):12211. doi: 10.1038/s41598-020-69203-8.
Accurate assessment of glacier mass loss is essential for understanding the glacier sensitivity to climate change and the ramifications of glacier retreat or surge. The glacier melt affects the runoff and water availability, on which the drinking and irrigation water supplies and generation of hydroelectric energy depend upon. The excessive glacial retreat may cause flood, glacial lake outburst flood, avalanches and sea level rise which are likely to affect the lives and livelihood of the people and damage the infrastructure. Here, we present a remote sensing based modeling framework to improve the understanding of accumulation and ablation processes and to quantify the glacier mass balance using multispectral satellite imageries, as several glacierized regions of the world are still poorly monitored because the field measurements for continuous monitoring on a large scale or in a complex harsh terrain are costly, time consuming and difficult. The developed modeling framework has been applied to the Parvati glacier in the western Himalaya to investigate glaciological processes and estimate the surface mass loss using 19 years of satellite images from 1998 to 2016. It spreads over 425.318 km and more than 50% of the area is accumulation area. The study shows that the Parvati glacier is not in equilibrium and its behavioural response changes year to year characterized with high rate of mass loss. The value of accumulation area ratio varies between 0.33 and 0.70 with an average value of 0.55, indicating a negative mass loss. The mean specific mass loss is - 0.49 ± 0.11 m w.e. and the total mass loss is 3.95 Gt., indicating strong influence of climate change and effect on river flows and water availability.
准确评估冰川质量损失对于理解冰川对气候变化的敏感性以及冰川退缩或涌动的后果至关重要。冰川融化会影响径流量和水资源可用性，而饮用水和灌溉用水供应以及水力发电的产生都依赖于这些水资源。冰川过度退缩可能导致洪水、冰川湖溃决洪水、雪崩和海平面上升，这些都可能影响人们的生活和生计，并破坏基础设施。在这里，我们提出了一个基于遥感的建模框架，以提高对积累和消融过程的理解，并利用多光谱卫星图像量化冰川质量平衡，因为世界上几个冰川覆盖的地区仍然监测不足，因为在大规模或在复杂恶劣的地形上进行连续监测的实地测量既昂贵、耗时又困难。所开发的建模框架已应用于西喜马拉雅山的帕瓦蒂冰川，以研究冰川学过程并使用 1998 年至 2016 年的 19 年卫星图像估算表面质量损失。它覆盖了 425.318 公里，超过 50%的面积是积累区。研究表明，帕瓦蒂冰川不平衡，其行为反应逐年变化，表现出高质量损失率。积累区比例值在 0.33 到 0.70 之间变化，平均值为 0.55，表明存在负质量损失。平均特定质量损失为-0.49±0.11 m w.e.，总质量损失为 3.95 Gt.，表明气候变化的强烈影响以及对河流流量和水资源可用性的影响。
