Abstract
The quantification of snow cover changes and of the related water resources in mountain areas has a key role for understanding the impact on several sectors such as ecosystem services, tourism and energy production. By using NASA-Moderate Resolution Imaging Spectroradiometer (MODIS) images from 2000 to 2018, this study analyzes changes in snow cover in the High Mountain Asia region and compares them with global mountain areas. Globally, snow cover extent and duration are declining with significant trends in around 78% of mountain areas, and the High Mountain Asia region follows similar trends in around 86% of the areas. As an example, Shaluli Shan area in China shows significant negative trends for both snow cover extent and duration, with −11.4% (confidence interval: −17.7%, −5.5%) and −47.3 days (confidence interval: −70.4 days, −24.4 days) at elevations >5500 m a.s.l. respectively. In spring, an earlier snowmelt of −13.5 days (confidence interval: −24.3 days, −2.0 days) in 4000–5500 m a.s.l. is detected. On the other side, Tien Shan area shows an earlier snow onset of −28.8 days (confidence interval: −44.3 days, −8.2 days) between 2500 and 4000 m a.s.l., governed by decreasing temperature and increasing snowfall. In the current analysis, the Tibetan Plateau shows no significant changes. Regarding water resources, by using Gravity Recovery and Climate Experiment (GRACE) data it was found that around 50% of areas in the High Mountain Asia region and 30% at global level are suffering from significant negative temporal trends of total water storage (including groundwater, soil moisture, surface water, snow, and ice) in the period 2002–2015. In the High Mountain Asia region, this negative trend involves around 54% of the areas during spring period, while at a global level this percentage lies between 25% and 30% for all seasons. Positive trends for water storage are detected in a maximum 10% of the areas in High Mountain Asia region and in around 20% of the areas at global level. Overall snow mass changes determine a significant contribution to the total water storage changes up to 30% of the areas in winter and spring time over 2002–2015.
Highlights
Mountains cover 22% of the earth surface, they are home to around 13% of global population, and provide between 60% and 80% of the global fresh water including drinking, domestic use, irrigation, industry and hydropower [1,2]
This study focused on mountain areas in the High Mountain Asia (HMA), that stretch from the Pamir and the Hindu Kush in the west to the Mishmi Hills and Shaluli Shan mountains in the southeast, from Kunlun and Qilian mountains in the north to the Himalayas in the south
The presented analyses highlight a high variability of snow cover in the HMA region, where three main subregions can be identified
Summary
Mountains cover 22% of the earth surface, they are home to around 13% of global population, and provide between 60% and 80% of the global fresh water including drinking, domestic use, irrigation, industry and hydropower [1,2]. Mountain areas are considered sentinels as most phenomena can be amplified in this environment [3,4]. The changes related to snow and glacier mass for both the Northern and Southern Hemispheres are a clear sign of the climate change impact in mountain areas [5,6,7]. Notarnicola, (2020) [9] analyzed the snow parameter trends in the last two decades by using NASA-Moderate Resolution Imaging Spectroradiometer (MODIS) products and reported that, at a global level, around 78% of the areas with significant changes are suffering from snow cover and duration negative trends. Considering different elevation belts, at a medium elevation between 1000 and 4000 m a.s.l., positive and negative changes are intermixed, while at an elevation higher than 4000 m a.s.l., only negative changes are found in the different snow parameters. Areas located in western USA, South America and Australia are suffering from extensive decline in many parameters, while areas in Northeastern Russia, Northern Europe and in some parts of central Asia show positive trends [5,10,11,12]
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