The Yellow River basin (YRB) has played an important role in the forming of Chinese civilization. Located in the upper reaches of the YRB and the southeastern edge of the Qinghai–Tibet Plateau (QTP), the Gannan Plateau (GP), which consists of mainly alpine and mountain ecosystems, is one of the most important water conservation areas for the Yellow River and recharges 6.59 billion cubic meters of water to the Yellow River each year, accounting for 11.4% of the total runoff of the Yellow River. In the past 30 years, due to climate change and intense human activities, the GP is facing increasing challenges in maintaining its ecosystem integrity and security. Vegetation is a central component of the terrestrial ecosystem and is also key to maintaining ecosystem functioning and services. To form sound ecological restoration projects for the GP and the upper reaches of the YRB in general, this study assesses the trend in FVC (Fractional Vegetation Cover) and its drivers across the GP by integrating high-resolution satellite remote sensing images and meteorological data from 2000 to 2020. Results showed that the mean value of FVC for the entire GP between 2000 and 2020 was 89.26%. Aridity was found to be the main factor that determined the spatial distribution of FVC, while ecosystem type exhibited the secondary effect with forests having the highest FVC within each aridity class. From 2000 to 2020, the FVC in 84.11% of the study area did not exhibit significant change, though 10.32% of the study area still experienced a significant increase in FVC. A multi-factor analysis revealed that precipitation surpassed temperature as the main driver for the FVC trend in semi-arid and semi-humid areas, while this pattern was reversed in humid areas. A further residual analysis indicated that human activities only played a minor role in determining the FVC trend in most naturally vegetated areas of the study area, except for semi-arid crops where a significant positive role of human influences on the FVC trend was observed. The findings highlight the fact that aridity and vegetation types interact to explain the relative sensitivity of alpine and mountain ecosystems to climate trends and human influences. Results from this study provide an observational basis for better understanding and pattern prediction of ecosystem functioning and services in the GP under future climate change, which is key to the success of the national strategy that aims to preserve ecosystem integrity and promote high-quality development over the entire YRB.

River and lake health assessment (RLHA) is an important approach to alleviating the conflict between protecting river and lake ecosystems and fostering socioeconomic development, aiming for comprehensive protection, governance, and management. Vegetation, a key component of the riparian zone, supports and maintains river and lake health (RLH) by providing a range of ecological functions. While research on riparian zone vegetation is ongoing, these studies have not yet been synthesized from the perspective of integrating RLHA with the ecological functions of riparian zone vegetation. In this paper, based on the bibliometric method, the relevant literature studies on the topics of RLHA and unmanned aerial vehicle (UAV) remote sensing of vegetation were screened and counted, and the keywords were highlighted, respectively. Based on the connotation of RLH, this paper categorizes the indicators of RLHA into five aspects: water space: the critical area from the river and lake water body to the land in the riparian zone; water resources: the amount of water in the river and lake; water environment: the quality of water in the river and lake; water ecology:aquatic organisms in the river and lake; and water services:the function of ecosystem services in the river and lake. Based on these five aspects, this paper analyzes the key role of riparian zone vegetation in RLHA. In this paper, the key roles of riparian zone vegetation in RLHA are summarized as follows: stabilizing riverbanks, purifying water quality, regulating water temperature, providing food, replenishing groundwater, providing biological habitats, and beautifying human habitats. This paper analyzes the application of riparian zone vegetation ecological functions in RLH, summarizing the correlation between RLHA indicators and these ecological functions. Moreover, this paper analyzes the advantages of UAV remote sensing technology in the quantitative monitoring of riparian zone vegetation. This analysis is based on the high spatial and temporal resolution characteristics of UAV remote sensing technology and focuses on monitoring the ecological functions of riparian zone vegetation. On this basis, this paper summarizes the content and indicators of UAV quantitative remote sensing monitoring of riparian zone vegetation for RLHA. It covers several aspects: delineation of riparian zone extent, identification of vegetation types and distribution, the influence of vegetation on changes in the river floodplain, vegetation cover, plant diversity, and the impact of vegetation distribution on biological habitat. This paper summarizes the monitoring objects involved in monitoring riparian zones, riparian zone vegetation, river floodplains, and biological habitats, and summarizes the monitoring indicators for each category. Finally, this paper analyzes the challenges of UAV quantitative remote sensing for riparian zone vegetation at the current stage, including the limitations of UAV platforms and sensors, and the complexity of UAV remote sensing data information. This paper envisages the future application prospects of UAV quantitative remote sensing for riparian zone vegetation, including the development of hardware and software such as UAV platforms, sensors, and data technologies, as well as the development of integrated air-to-ground monitoring systems and the construction of UAV quantitative remote sensing platforms tailored to actual management applications.

Snow is involved in and influences water–energy processes at multiple scales. Studies on land surface snow phenology are an important part of cryosphere science and are a hot spot in the hydrological community. In this study, we improved a statistical downscaling method by introducing a spatial probability distribution function to obtain regional snow depth data with higher spatial resolution. Based on this, the southern Gansu Plateau (SGP), an important water source region in the upper reaches of the Yellow River, was taken as a study area to quantify regional land surface snow phenology variation, together with a discussion of their responses to land surface terrain and local climate, during the period from 2003 to 2018. The results revealed that the improved downscaling method was satisfactory for snow depth data reprocessing according to comparisons with gauge-based data. The downscaled snow depth data were used to conduct spatial analysis and it was found that snow depth was on average larger and maintained longer in areas with higher altitudes, varying and decreasing with a shortened persistence time. Snow was also found more on steeper terrain, although it was indistinguishable among various aspects. The former is mostly located at high altitudes in the SGP, where lower temperatures and higher precipitation provide favorable conditions for snow accumulation. Climatically, factors such as precipitation, solar radiation, and air temperature had significantly singular effectiveness on land surface snow phenology. Precipitation was positively correlated with snow accumulation and maintenance, while solar radiation and air temperature functioned negatively. Comparatively, the quantity of snow was more sensitive to solar radiation, while its persistence was more sensitive to air temperature, especially extremely low temperatures. This study presents an example of data and methods to analyze regional land surface snow phenology dynamics, and the results may provide references for better understanding water formation, distribution, and evolution in alpine water source areas.

The study of climate element distribution models under complex terrain conditions is a popular topic in the field of GIS application in climatology, especially in plateau areas with a complex topography and scarce meteorological station information. In this paper, the spatial and temporal heterogeneity of temperature and precipitation at the northeastern edge of the Tibetan Plateau was analyzed by taking the northeastern edge of the plateau as the study area and constructing a topographic spatial statistical model using 47 meteorological stations and digital elevation models from 1981 to 2010. The following conclusions were drawn from the study: (1) The ME of the temperature distribution model for each month is below 0.9 °C; the maximum ME of the precipitation distribution model for each month is −5.808 mm in July, and the precipitation distribution model has similar error characteristics with the temperature distribution model, which can reflect the horizontal zone distribution pattern of meteorological data and can clearly show the changes of temperature and precipitation as the altitude increases. (2) The spatial distribution pattern of temperature is as follows: the temperature in the study area gradually increases from the southwest to the northeast, with Zhouqu County in Linxia Prefecture and Gannan Prefecture as the main high-temperature areas; the spatial distribution of precipitation is as follows: the precipitation in the southwest of the study area is significantly higher than that in the north, and the precipitation in Linxia Prefecture is significantly lower than that in Gannan Prefecture. (3) The temporal distribution pattern of the temperature distribution model is as follows: the overall temperature in the study area is at its lowest level in January, and the maximum temperature is only 2.6 °C, until July, when the maximum temperature rises to 24.2 °C and then gradually starts to decline; the spatial distribution of precipitation is as follows: the precipitation in the study area gradually rises from January, and the maximum precipitation rises to July and then starts to decline, and in December the precipitation falls to the lowest level. The temporal distribution characteristics of the precipitation distribution model are similar to those of the air temperature model, with obvious hydrothermal synchronization characteristics.

1. Global warming has become an indisputable fact, with its impact on the high-altitude cryosphere being particularly pronounced (Wang et al. 2020). As one of the core elements of the cryosphere, m...