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In High Mountain Asia (HMA), rising temperatures and retreating glaciers are leading to the formation of new glacial lakes and the expansion of existing ones. The sudden release of water from such lakes can lead to devastating glacial lake outburst floods (GLOF) threatening people and infrastructure for many kilometers downstream. Therefore, information on future glacial lakes, e.g., their location, area and volume as well as the timing of their development, is vital for sustainable development of settlements and infrastructures. In this study, we present comprehensive estimates for future glacial lake development in HMA with unprecedented temporal resolution. We rely on an ensemble of fifteen global climate models using the newest CMIP6 data and employ a set of four Shared Socioeconomic Pathway (SSP) scenarios. With the Open Global Glacier Model (OGGM), we use a modeling framework that explicitly simulates glacier dynamics in order to model glacier change until 2100 and estimate the formation period for each of the 2,700 largest future glacial lakes (>0.1 km2) in HMA. We estimate the glacial lake area in the entire region to grow by 474 ± 121 km2 for SSP126 and 833 ± 148 km2 for SSP585. Following recent estimates of currently existing glacial lakes (>0.1 km2), this would constitute an increase in lake area of ∼120–∼210% in 2100 compared to 2018. The lake volume is expected to increase by 22.8 ± 6.7 km3 for SSP126 and 39.7 ± 7.7 km3 for SSP585. This range includes a drastic tenfold increase in lake volume, from estimated 3.9 km3 in 2018 to 43.6 ± 7.7 km3 in 2100. However, there is a considerable spread between total and relative increase in glacial lake area and volume for different sub-regions of High Mountain Asia. As both, lake area and lake volume, could to lead to an increase in GLOF risk, the results emphasize the urgent need for more localized, in-depth studies at especially vulnerable locations in order to enable local communities to adapt to emerging challenges, to implement risk minimization measures, and to improve sustainable development in High Mountain Asia.

Climate-influenced changes in hydrology affect water-food-energy security that may impact up to two billion people downstream of the High Mountain Asia (HMA) region. Changes in water supply affect energy, industry, transportation, and ecosystems (agriculture, fisheries) and as a result, also affect the region's social, environmental, and economic fabrics. Sustaining the highly interconnected food-energy-water nexus (FEWN) will be a fundamental and increasing challenge under a changing climate regime. High variability in topography and distribution of glaciated and snow-covered areas in the HMA region, and scarcity of high resolution (in-situ) data make it difficult to model and project climate change impacts on individual watersheds. We lack basic understanding of the spatial and temporal variations in climate, surface impurities in snow and ice such as black carbon and dust that alter surface albedo, and glacier mass balance and dynamics. These knowledge gaps create challenges in predicting where and when the impact of changes in river flow will be the most significant economically and ecologically. In response to these challenges, the United States National Aeronautics and Space Administration (NASA) established the High Mountain Asia Team (HiMAT) in 2016 to conduct research to address knowledge gaps. This paper summarizes some of the advances HiMAT made over the past 5 years, highlights the scientific challenges in improving our understanding of the hydrology of the HMA region, and introduces an integrated assessment framework to assess the impacts of climate changes on the FEWN for the HMA region. The framework, developed under a NASA HMA project, links climate models, hydrology, hydropower, fish biology, and economic analysis. The framework could be applied to develop scientific understanding of spatio-temporal variability in water availability and the resultant downstream impacts on the FEWN to support water resource management under a changing climate regime.

High Mountain Asia (HMA) has the largest expanse of snow outside of the polar regions and it plays a critical role in climate and hydrology. In situ monitoring is rare due to terrain complexity and inaccessibility, making remote sensing the most practical way to understand snow patterns in HMA despite relatively short periods of record. Here, trends in snow cover duration were assessed using MODIS between 2002 and 2017 across the headwaters of the region’s primary river basins (Amu Darya, Brahmaputra, Ganges, Indus, and Syr Darya). Data limitations, associated with traditional binary mapping and data gaps due to clouds, were addressed with a daily, spatially and temporally complete, snow cover product that maps the fraction of snow in each pixel using spectral mixture analysis. Trends in fractional snow cover duration (fSCD) were calculated at the annual and monthly scale, and across 1,000 m elevation bands, and compared to trends in binary snow cover duration (SCD). Snow cover is present, on average, for 102 days across all basin headwaters, with the longest duration in western basins and shortest in eastern basins. Broadly, snow cover is in decline, which is most pronounced in elevation bands where snow is most likely to be present and most needed to sustain glaciers. Some of the strongest negative trends in fSCD were in the Syr Darya, which has 13 fewer days between 4,000–5,000 m, and Brahmaputra, which has 31 fewer days between 5,000–6,000 m. The only increasing tendency was found in the Indus between 2,000 and 5,000 m. There were differences between fSCD and SCD trends, due to SCD overestimating snow cover area relative to fSCD.

The current glacial lake datasets in the High Mountain Asia (HMA) region still need to be improved because their boundary divisions in the land–water transition zone are not precisely delineate, and also some very small glacial lakes have been lost due to their mixed reflectance with backgrounds. In addition, most studies have only focused on the changes in the area of a glacial lake as a whole, but do not involve the actual changes of per pixel on its boundary and the potential controlling factors. In this research, we produced more accurate and complete maps of glacial lake extent in the HMA in 2008, 2012, and 2016 with consistent time intervals using Landsat satellite images and the Google Earth Engine (GEE) cloud computing platform, and further studied the formation, distribution, and dynamics of the glacial lakes. In total, 17,016 and 21,249 glacial lakes were detected in 2008 and 2016, respectively, covering an area of 1420.15 ± 232.76 km2 and 1577.38 ± 288.82 km2; the lakes were mainly located at altitudes between 4400 m and 5600 m. The annual areal expansion rate was approximately 1.38% from 2008 to 2016. To explore the cause of the rapid expansion of individual glacial lakes, we investigated their long-term expansion rates by measuring changes in shoreline positions. The results show that glacial lakes are expanding rapidly in areas close to glaciers and had a high expansion rate of larger than 20 m/yr from 2008 to 2016. Glacial lakes in the Himalayas showed the highest expansion rate of more than 2 m/yr, followed by the Karakoram Mountains (1.61 m/yr) and the Tianshan Mountains (1.52 m/yr). The accelerating rate of glacier ice and snow melting caused by global warming is the primary contributor to glacial lake growth. These results may provide information that will help in the understanding of detailed lake dynamics and the mechanism, and also facilitate the scientific recognition of the potential hazards associated with glacial lakes in this region.

The Indus watershed is a highly populated region that contains parts of India, Pakistan, China, and Afghanistan. Changes in precipitation patterns and rates of glacial melt have significantly impacted the region in recent years, and climate change is projected to result in further serious human and environmental consequences. To understand the climate dynamics of the Indus watershed and surrounding regions, reanalysis and satellite data from products such as APHRODITE-2, TRMM, ERA5, and MERRA-2 are often used, yet these products are not always in agreement regarding critical variables such as precipitation. Here we objectively evaluate the level of agreement between precipitation from these four products. Because these data are on different spatial scales, we propose a low-rank spatio-temporal dynamic linear model for precipitation that integrates information from each of the above climate products. Specifically, we model each data source as the combination of a modified shared process, a discrepancy process, and Gaussian noise. We define the shared process at a high spatial resolution that can be upscaled according to the resolution of the observed data. Our proposed model's shared process provides a cohesive picture of monthly precipitation in the Indus watershed from 2000 to 2009, while the product-specific discrepancies provide insight into how and where the products differ from one another.

Glacier recession driven by climate change produces glacial lakes, some of which are hazardous. Our study assesses the evolution of three of the most hazardous moraine-dammed proglacial lakes in the Nepal Himalaya—Imja, Lower Barun, and Thulagi. Imja Lake (up to 150 m deep; 78.4 × 106 m3 volume; surveyed in October 2014) and Lower Barun Lake (205 m maximum observed depth; 112.3 × 106 m3 volume; surveyed in October 2015) are much deeper than previously measured, and their readily drainable volumes are slowly growing. Their surface areas have been increasing at an accelerating pace from a few small supraglacial lakes in the 1950s/1960s to 1.33 km2 and 1.79 km2 in 2017, respectively. In contrast, the surface area (0.89 km2) and volume of Thulagi lake (76 m maximum observed depth; 36.1 × 106 m3; surveyed in October 2017) has remained almost stable for about two decades. Analyses of changes in the moraine dams of the three lakes using digital elevation models (DEMs) quantifies the degradation of the dams due to the melting of their ice cores and hence their natural lowering rates as well as the potential for glacial lake outburst floods (GLOFs). We examined the likely future evolution of lake growth and hazard processes associated with lake instability, which suggests faster growth and increased hazard potential at Lower Barun lake.