Transboundary hazard and downstream impact of glacial lakes in Hindu-Kush Karakoram Himalayas.

Glacial Lake Outburst Floods (GLOFs) can generate catastrophic flash floods when the damming structure is breached or overtopped. Some of these glacial lakes are located in transboundary regions where floods originating from the lake in one country could inundate a neighboring country, devastating the population and infrastructure of both nations and influencing socio-political relationships. Therefore, assessing the lakes' hazard is crucial. This study investigates transboundary glacial lakes, considering their GLOF hazard, including potential mass movement intrusion, moraine's stability, upstream and downstream process cascades, downstream flood extents, and the exposure and vulnerability of the downstream infrastructure and affected population. GLOF exposure assessments were carried out to identify exposed buildings, bridges, and hydropower systems in transboundary regions. China currently has the highest number of transboundary lakes, with most of them potentially impacting India and Nepal. Most of the transboundary lakes in China, and many in India and Nepal, are susceptible to mass movements. Among the 230 transboundary glacial lakes in the Hindu Kush Karakoram Himalaya, 55 lakes can potentially impact other glacial lakes along their flow path, creating a cascade of events. Five transboundary lakes could potentially impact over 1000 buildings, and 16 lakes could impact over 500 buildings. A total of 35 lakes can impact at least one hydropower station along their flow path, and 4 lakes can impact two hydropower stations. This research emphasizes the critical importance of conducting comprehensive risk analyses of GLOFs in transboundary regions to inform policy-makers. It calls for investing in broad-scale assessments and data-driven decision-making for mitigating and adapting to GLOF risks effectively. Finally, by raising awareness among policy-makers, the study aims to drive actions that safeguard communities and infrastructure vulnerable to GLOF.

Long-term analysis of glaciers and glacier lakes in the Central and Eastern Himalaya.

Himalayan glaciers represent both an important source of water and a major suite of geohazards for inhabitants of their downstream regions. Recent climate change has intersected with local topographic, geomorphic, and glaciological factors to drive complex patterns of glacier thinning, retreat, velocity change, and lake development. In this study, we analyze the long-term variations in surface elevation change and velocity of the glaciers in the Central and Eastern Himalaya using existing and newly generated datasets spanning 1975 to 2018. We have used modelled (e.g., debris and ice thickness) and remote sensing datasets (e.g., Corona, Hexagon, and Landsat images) to investigate the impact of debris cover and the evolution of proglacial lakes on the glacier response in the region. We found that lake-terminating glaciers (lake TGs) have significantly higher thinning, velocity, and deceleration over time than land-terminating glaciers (land TGs). Lakes have shown an overall growth of 98 % in area and 40 % in number during 1975-2017. New proglacial lakes will likely continue to develop, and existing ones will keep expanding, influencing the frontal changes and dynamics of the lake-terminating glaciers. Debris-covered glaciers have undergone similar thinning compared to clean-ice glaciers, both for lake and land TGs; however, variations exist across the ablation zones between clean and debris-covered glaciers which this study further explores using a data-driven approach. Overall, the proglacial lakes development, changes in debris coverage, and topography significantly affect the glacier responses in the regions.

Machine learning based downscaling of GRACE-estimated groundwater in Central Valley, California.

California's Central Valley, one of the most agriculturally productive regions, is also one of the most stressed aquifers in the world due to anthropogenic groundwater over-extraction primarily for irrigation. Groundwater depletion is further exacerbated by climate-driven droughts. Gravity Recovery and Climate Experiment (GRACE) satellite gravimetry has demonstrated the feasibility of quantifying global groundwater storage changes at uniform monthly sampling, though at a coarse resolution and is thus impractical for effective water resources management. Here, we employ the Random Forest machine learning algorithm to establish empirical relationships between GRACE-derived groundwater storage and in situ groundwater level variations over the Central Valley during 2002-2016 and achieved spatial downscaling of GRACE-observed groundwater storage changes from a few hundred km to 5 km. Validations of our modeled groundwater level with in situ groundwater level indicate excellent Nash-Sutcliffe Efficiency coefficients ranging from 0.94 to 0.97. In addition, the secular components of modeled groundwater show good agreements with those of vertical displacements observed by GPS, and CryoSat-2 radar altimetry measurements and is perfectly consistent with findings from previous studies. Our estimated groundwater loss is about 30 km3 from 2002 to 2016, which also agrees well with previous studies in Central Valley. We find the maximum groundwater storage loss rates of -5.7 ± 1.2 km3 yr-1 and -9.8 ± 1.7 km3 yr-1 occurred during the extended drought periods of January 2007-December 2009, and October 2011-September 2015, respectively while Central Valley also experienced groundwater recharges during prolonged flood episodes. The 5-km resolution Central Valley-wide groundwater storage trends reveal that groundwater depletion occurs mostly in southern San Joaquin Valley collocated with severe land subsidence due to aquifer compaction from excessive groundwater over withdrawal.

Transition of a small Himalayan glacier lake outburst flood to a giant transborder flood and debris flow.

Glacial lake outburst floods (GLOFs) are a great concern for the Himalaya, as they can severely damage downstream populations and infrastructures. These floods originate at high altitudes and can flow down with enormous energy and change the terrain's existing morphology. One such devastating event occurred on the night of 5 July 2016, from the inconspicuous Gongbatongsha Lake, located in the Poiqu basin, Eastern Himalaya. The Poiqu basin in the Tibetan Autonomous Region currently contains numerous big glacial lakes; however, this event originated from a small lake. The GLOF was triggered following heavy precipitation that led to a slope failure above the lake and deposition of debris into the lake, which breached the moraine dam and rapidly drained the entire lake. The flood damaged several downstream infrastructures, including the Arniko highway, the Upper Bhotekoshi hydropower plant, and several buildings as it made its way into the Bhotekoshi basin in Nepal. This study adopts a multi-model approach to reconstruct the GLOF trigger and the flood's transformation into a severe debris flow. Proxies including flow discharge, flow velocity, runout distances were used to calibrate the model and validate the results. Results reveal that a debris flow of volume ranging between 3000 and 6000 m3 from the headwall must have led to lake overfill, eventually leading to the GLOF event. The GLOF showed a significant increase in peak discharge from 618 to 4123 m3 s-1 at the Zhangzangbo-Bhotekoshi confluence. The average velocity of the flow is calculated to be ~ 5.5 m s-1. Reconstruction of the erosion and deposition dynamics show that maximum erosion occurred in the first 6.5 km, with maximum deposition occurring near the Upper Bhotekoshi hydropower station. The modeling indicates that the availability of the entrainable debris along the channel, likely from the previous landslides, amplified the event by three orders of magnitude-additional water ingested from the river. Overall, we demonstrate how the small-scale Gongbatongsha GLOF amplified downstream by incorporating pre-existing sediment in the valley and triggered damaging secondary landslides leading to an economic loss of > 70 million USD.

Glaciohydrology of the Himalaya-Karakoram.

Understanding the response of Himalayan-Karakoram (HK) rivers to climate change is crucial for ~1 billion people who partly depend on these water resources. Policy-makers tasked with sustainable water resources management require an assessment of the rivers' current status and potential future changes. We show that glacier and snow melt are important components of HK rivers, with greater hydrological importance for the Indus basin than for the Ganges and Brahmaputra basins. Total river runoff, glacier melt, and seasonality of flow are projected to increase until the 2050s, with some exceptions and large uncertainties. Critical knowledge gaps severely affect modeled contributions of different runoff components, future runoff volumes, and seasonality. Therefore, comprehensive field observation-based and remote sensing-based methods and models are needed.

The hazardous 2017-2019 surge and river damming by Shispare Glacier, Karakoram.

In 2017-2019 a surge of Shispare Glacier, a former tributary of the once larger Hasanabad Glacier (Hunza region), dammed the proglacial river of Muchuhar Glacier, which formed an ice-dammed lake and generated a small Glacial Lake Outburst Flood (GLOF). Surge movement produced the highest recorded Karakoram glacier surface flow rate using feature tracking (~18 ± 0.5 m d-1) and resulted in a glacier frontal advance of 1495 ± 47 m. The surge speed was less than reports of earlier Hasanabad advances during 1892/93 (9.3 km) and 1903 (9.7 km). Surges also occurred in 1973 and 2000-2001. Recent surges and lake evolution are examined using feature tracking in satellite images (1990-2019), DEM differencing (1973-2019), and thermal satellite data (2000-2019). The recent active phase of Shispare surge began in April 2018, showed two surface flow maxima in June 2018 and May 2019, and terminated following a GLOF on 22-23 June 2019. The surge likely had hydrological controls influenced in winter by compromised subglacial flow and low meltwater production. It terminated during summer probably because increased meltwater restored efficient channelized flow. We also identify considerable heterogeneity of movement, including spring/summer accelerations.

The State of Remote Sensing Capabilities of Cascading Hazards over High Mountain Asia.

Cascading hazard processes refer to a primary trigger such as heavy rainfall, seismic activity, or snow melt, followed by a chain or web of consequences that can cause subsequent hazards influenced by a complex array of preconditions and vulnerabilities. These interact in multiple ways and can have tremendous impacts on populations proximate to or downstream of these initial triggers. High Mountain Asia (HMA) is extremely vulnerable to cascading hazard processes given the tectonic, geomorphologic, and climatic setting of the region, particularly as it relates to glacial lakes. Given the limitations of in situ surveys in steep and often inaccessible terrain, remote sensing data are a valuable resource for better understanding and quantifying these processes. The present work provides a survey of cascading hazard processes impacting HMA and how these can be characterized using remote sensing sources. We discuss how remote sensing products can be used to address these process chains, citing several examples of cascading hazard scenarios across HMA. This work also provides a perspective on the current gaps and challenges, community needs, and view forward towards improved characterization of evolving hazards and risk across HMA.