Baosheng An

The Qinghai-Xizang Plateau is among the most ecologically vulnerable and responsive areas worldwide. Studying the characteristics of soil microbial communities along altitudinal gradients on plateaus and revealing the response mechanisms and vertical distribution patterns of microbial communities in alpine ecosystems is of significant academic value for assessing the ecological stability of the Qinghai-Xizang Plateau. This research examines the Lhasa River Basin by employing Illumina NovaSeq high-throughput sequencing to investigate how soil bacterial and fungal communities shift across elevation gradients in the Duilong Qu subbasin. This study also explored the key environmental drivers behind these microbial distribution patterns. The results indicate the following: (1) Key bacterial groups in the Duilong Qu Basin soil include Proteobacteria, Acidobacteria, and Actinobacteria, with Ascomycota, Mortierellomycota, and Basidiomycota as the prevalent fungal phyla. (2) Soil bacterial richness fluctuates with increasing elevation, and diversity exhibits a V-shaped distribution; fungal richness increases monotonically with elevation, whereas diversity shows no altitudinal dependence. (3) Principal coordinate analysis (PCoA) revealed that bacterial community structures exhibit separation trends across different elevations, with high intragroup consistency; fungal community structures at mid-elevations (4000–5000 m) show clustering similarity, whereas those at 3650–5000 m and 5500 m remain highly distinct from those at other elevations. (4) RDA reveals that factors such as accessible phosphorus, potassium, and organic content have a major effect on how bacterial communities are arranged. On the other hand, soil conductivity, along with available and total phosphorus levels, as well as pH, plays a key role in shaping fungal communities. (5) Functional prediction analysis suggests that soil bacteria shift from aerobic and biofilm-forming to facultatively anaerobic, stress-tolerant, and pathogenic traits with increasing elevation. Fungi are predominantly undefined saprotrophs, transitioning from ectomycorrhizal and pathogenic functions to saprotrophic functions at relatively high elevations.

The Tibetan Plateau and its surroundings have recently experienced several catastrophic glacier-related disasters. It is of great scientific and practical significance to establish ground-based early warning systems (EWSs) to understand the processes and mechanisms of glacial disasters and warn against potential threats to downstream settlements and infrastructure. However, there are few sophisticated EWSs on the Tibetan Plateau. With the support of the Second Tibetan Plateau Scientific Expedition and Research Program (STPSER), an EWS was developed and implemented in the Sedongpu Valley, southeastern Tibetan Plateau, where repeated river blockages have occurred due to ice/rock collapse debris flow. The EWS collected datasets of optical/thermal videos/photos, geophone waveforms, water levels, and meteorological variables in this sparsely populated zone. It has successfully warned against three ice-rock collapse–debris flow–river blockage chain events, and seven small-scale ice-rock collapse–debris flow events. Meanwhile, it was found that the low-cost geophone can effectively indicate the occurrence and magnitude of ice/rock collapses by local thresholds, and water level observation is an efficient way to warn of river blockages. Our observations showed that there were no immediate meteorological triggers for the ice-rock collapses and associated debris flows. Several factors, such as the volume and location of the collapses and the percentage of ice content involved, influence the velocities of debris flows and the magnitude of river blockages. There are still two possible glaciers in the study area that are at risk of ice collapse. It is worth monitoring their dynamic changes using high-resolution satellite data and the ground-based EWS to safeguard the surrounding hydrological projects and infrastructure in this transboundary region.

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.

The Tibetan Plateau and its surroundings have recently experienced several catastrophic glacier-related disasters. It is of great scientific and practical significance to establish ground-based early warning systems (EWS) to understand the processes and mechanisms of glacial disasters and warn against potential threats to downstream settlements and infrastructure. However, there are few sophisticated EWSs on the Tibetan Plateau. With the support of the Second Tibetan Plateau Scientific Expedition and Research Program, an EWS was developed and implemented in the Sedongpu Valley, southeastern Tibetan Plateau, where repeated river blockages have occurred due to ice/rock collapse debris flow. The EWS collected datasets of optical/thermal videos/photos, geophone waveforms, water levels, and meteorological variables in this sparsely populated zone. It has successfully warned against three ice-rock collapse-debris flow - river blockage chain events and seven small-scale ice-rock collapse-debris flow events. Meanwhile, it was found that the low-cost geophone can effectively indicate the occurrence and magnitude of ice/rock collapses by local thresholds, and water level observation is an efficient way to warn of river blockages. Our observations showed that several factors, such as the volume and location of the collapses and the percentage of ice content involved, influence the velocities of debris flows and the magnitude of river blockages. There are still two possible glaciers in the study area that are at risk of ice collapse. It is worth monitoring their dynamic changes using high-resolution satellite data and the ground-based EWS to safeguard the surrounding hydrological projects and infrastructure in this transboundary region.

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.