Enhanced glacial lake activity threatens numerous communities and infrastructure in the Third Pole.

Glacial lake outburst floods (GLOFs) are among the most severe cryospheric hazards in the Third Pole, encompassing the Tibetan Plateau and surrounding Himalayas, Hindu Kush, and Tianshan Mountains. Recent studies on glacial lake changes and GLOF characteristics and risks in this region have shown scattered and insufficiently detailed features. Here, we conduct an appraisal of the GLOF risks by combining high-resolution satellite images, case-by-case high-precision GLOF modeling, and detailed downstream exposure data. The glacial lake changes from 2018 to 2022 in the region were primarily driven by the accelerated expansion of proglacial lakes. The GLOF frequency has exhibited a significant increasing trend since 1980, with intensified activity in Southeastern Tibet and the China-Nepal border area over the past decade. Approximately 6,353 km2 of land could be at risk from potential GLOFs, posing threats to 55,808 buildings, 105 hydropower projects, 194 km2 of farmland, 5,005 km of roads, and 4,038 bridges. This study directly responds to the need for local disaster prevention and mitigation strategies, highlighting the urgent requirement of reducing GLOF threats in the Third Pole and the importance of regional cooperation.

Automatic Monitoring Alarm Method of Dammed Lake Based on Hybrid Segmentation Algorithm.

Mountainous regions are prone to dammed lake disasters due to their rough topography, scant vegetation, and high summer rainfall. By measuring water level variation, monitoring systems can detect dammed lake events when mudslides block rivers or boost water level. Therefore, an automatic monitoring alarm method based on a hybrid segmentation algorithm is proposed. The algorithm uses the k-means clustering algorithm to segment the picture scene in the RGB color space and the region growing algorithm on the image green channel to select the river target from the segmented scene. The pixel water level variation is used to trigger an alarm for the dammed lake event after the water level has been retrieved. In the Yarlung Tsangpo River basin of the Tibet Autonomous Region of China, the proposed automatic lake monitoring system was installed. We pick up data from April to November 2021, during which the river experienced low, high, and low water levels. Unlike conventional region growing algorithms, the algorithm does not rely on engineering knowledge to pick seed point parameters. Using our method, the accuracy rate is 89.29% and the miss rate is 11.76%, which is 29.12% higher and 17.65% lower than the traditional region growing algorithm, respectively. The monitoring results indicate that the proposed method is a highly adaptable and accurate unmanned dammed lake monitoring system.

Elemental composition of the topsoil fine fraction at and around the Tibetan plateau.

The <20 µm fractions of crusted topsoils on and around the Tibetan Plateau (TP) were analyzed to take a broad view of the composition of major elements (MEs, Al, Fe, and Mn) and twelve trace elements (TEs, As, Ba, Cd, Co, Cr, Cu, Ni, Pb, Sr, U, V, and Zn) and provide a crustal reference for environmental quality evaluation. The concentrations of most elements were generally higher in the Yarlung Zangbo River watershed (YZRW) and Pamirs but lower in the central Tibetan Plateau (CTP), Qaidam Basin (QB), and Tarim Basin (TB) due to the natural geochemical process. The concentrations of most elements in the five regions were higher than those of the upper continental crust (UCC), which was mainly affected by two natural factors. One was that the wide distribution of shale, schist, and phyllite on the TP led to the high concentrations of As and Cr. The other was that the concentrations of most elements in the <20 µm fractions of crusted topsoils were affected by particle sorting. Cu, Cd, As, and Pb in a few sites of the YZRW were influenced by local traffic emissions, mining operations, and increasing fossil fuel combustion over the past three decades (i.e., the 1980s-2010s). Furthermore, the values of crust‒referenced enrichment factor (EFucc) of most TEs (except Ba and Sr) in different environmental media with a high proportion of fine particles, such as aerosols, snow and ice cores, and river and lake sediments were generally 1.2-24.2 times greater than the values of fine fraction (<20 µm)‒referenced enrichment factor (EF < 20 µm), suggesting that the degree of anthropogenic effects on the TP environment should be overestimated in previous assessments using the UCC as the reference.

Satellite-Enabled Internet of Remote Things Network Transmits Field Data from the Most Remote Areas of the Tibetan Plateau.

In this article, we employed a satellite-enabled Internet of Remote Things (IoRT) network as a promising solution to retrieve data in the most remote areas of interest, where public networks are absent. This article presents a system network based on the satellite-enabled IoRT, a new paradigm that defines a network where each environmental monitoring device can autonomously establish a network with a remote data center. The Xingyun satellite constellation was employed for data retrieval on the Tibetan Plateau (TP). The monitoring system was mainly composed of a ground Internet of Things (IoT) terminal that was built with satellite transceivers, environmental monitoring devices, and system software. We deployed five of these newly developed terminals in harsh areas to monitor environmental variables, and accordingly, air temperature and relative humidity, precipitation, snow depth, land surface temperature, tree stemflow rate, and photosynthetically active radiation were retrieved with the satellite-enabled IoRT network. Field experiments were conducted to evaluate the performance of the proposed system network, and the results indicated that the average time delay with and without the packet creation mode reached 32 and 32.7 s, respectively, and the average packet loss rate with and without the packet creation mode reached 5.63% and 4.48%, respectively. The successful implementation of the satellite-enabled IoRT network for the rapid retrieval of monitoring data in remote glacier, forestland, and canyon areas at very high altitudes on the TP provides an entirely new and revolutionary data retrieval means for backhauling data from remote areas of interest.

An integrative method for identifying potentially dangerous glacial lakes in the Himalayas.

Glacial lakes in the Himalayas are widely distributed. Since 1900, more than 100 glacial lake outburst floods (GLOFs) have originated in the region, causing approximately 7000 deaths and considerable economic losses. Identifying potentially dangerous glacial lakes (PDGLs) is considered the first step in assessing GLOF risks. In this study, a more thorough inventory of PDGLs was presented that included numerous small-sized glacial lakes (<0.1 km2) that were generally neglected in the Himalayas for decades. Moreover, the PDGL evaluation system was improved in response to several deficiencies, such as the selection of assessment factors, which are sometimes arbitrary without a solid scientific basis. We designed an optimality experiment to select the best combination of assessment factors from 57 factors to identify PDGLs. Based on the experiments on both drained and non-drained glacial lakes in the Sunkoshi Basin, eastern Himalayas, five assessment factors were determined to be the best combination: the mean slope of the parent glacier, the potential for mass movement into the lake, the mean slope of moraine dams, the watershed area, and the lake perimeter, corresponding to the GLOF triggers for ice avalanches, rockfalls and landslides, dam instability, heavy precipitation or other liquid inflows, and lake characteristics, respectively. We then applied the best combination of assessment factors to the 1650 glacial lakes with an area greater than 0.02 km2 in the Himalayas. We identified 207 glacial lakes as very high-hazard and 345 as high-hazard. It is noteworthy that in various GLOF susceptibility evaluation scenarios with different assessment factors, weighting schemes, and classification approaches, similar results for glacial lakes with high outburst potential have been obtained. The results provided here can be used as benchmark data to assess the GLOF risks for local communities.

Process, mechanisms, and early warning of glacier collapse-induced river blocking disasters in the Yarlung Tsangpo Grand Canyon, southeastern Tibetan Plateau.

Glacier collapse is a fairly new type of glacier-related disasters on the Asian Water Towers (AWTs) in the warming climate. On 16 October and 29 October 2018, two glacier collapses occurred in the Sedongpu Basin, 7 km downstream from Gyala Village, Paizhen Town, Miling County, on the Yarlung Tsangpo River (YTR). The ice and entrained debris flows caused by the glacier collapses blocked the YTR, resulting in a potential threat to residents and transport lines upstream and downstream. Through post-event field investigations with a helicopter and an unmanned aerial vehicle (UAV), remote sensing interpretation, and seismic, hydrological, and meteorological observations, the process and potential mechanisms of the glacier collapse-induced river blocking (GCRB) disasters were investigated. We confirmed that the first glacier collapse event occurred at 22:48 (Beijing time) on 16 October 2018 and the second began at 08:03 on 29 October 2018. Approximately 130 × 106 m3 of ice and debris detached from the glacier during the glacier collapse, and we calculated that the river blocking fans caused by the first and second glacier collapse event covered ~1.36 km2 and ~ 1.29 km2 on the main watercourse of the YTR, respectively. We determined that the GCRB incidents represent a disaster chain of glacier collapse → glacial debris flow → river blockage → dammed lake → outburst flood. These incidents arise due to a combination of factors, including glacier activity, climate warming, heavy precipitation, pre-seismic activity, and high topographic relief. In the context of climate warming on the Tibetan Plateau, such glacier collapse induced disaster chains will continue or even intensify in the future. To protect against glacier collapse disasters in the Grand Canyon on the YTR, we established a monitoring and early warning system (EWS), which has already successfully sounded alerts for GCRB incidents. As a major element of an integrated risk management strategy, the EWS represents a viable and promising tool for mitigating climate change-related risks.