Search Results (10)

Cropland is crucial for food production, food security, and economic stability, especially in high-altitude Tibetan regions where it is limited. This study investigates the spatiotemporal changes and driving factors of cropland in the Yarlung Zangbo River Basin (YZRB) from 2000 to 2020. Using land use transfer matrices, center of gravity models, standard deviation ellipses, the Patch-generating Land Use Simulation (PLUS) model, and Partial Least Squares Structural Equation Modeling (PLS-SEM), it explores cropland dynamics and predicts land use for 2030. Results show the following: (1) Between 2000 and 2020, the area of cropland entering the basin exceeded that leaving, mainly concentrated in the middle and lower reaches, with a dynamic degree of 0.97%. The proportion of cropland increased from 1.28% in 2000 to 1.52% in 2020. (2) The center of gravity shifted northwest (2000–2005), southeast (2005–2015), and northwest again (2015–2020). (3) Factors like elevation, temperature, precipitation, population density, and GDP correlated with cropland changes. Natural factors positively affected cropland expansion, while socioeconomic and proximity factors indirectly inhibited it. (4) The 2030 cropland conservation scenario in the PLUS model ensures cropland security, ecological protection, and controlled construction land expansion, aligning with the Sustainable Development Goals. Targeted cropland conservation measures can effectively promote sustainable land use and ecological security in the Yarlung Zangbo River Basin. Full article

Vegetation, as a fundamental component of terrestrial ecosystems, plays a pivotal role in the flux of water, heat, and nutrients between the lithosphere, biosphere, and atmosphere. Assessing the impacts of climate change and human activities on vegetation dynamics is essential for maintaining the health and stability of fragile ecosystems, such as the Yarlung Zangbo River (YZR) basin of the Tibetan Plateau, the highest-elevation river basin in the world. Vegetation responses to climate change are inherently asymmetric, characterized by distinct temporal effects. However, these temporal effects remain poorly understood, particularly in high-altitude ecosystems. Here, we examine the spatiotemporal changes in leaf area index (LAI) and four climatic factors—air temperature, precipitation, potential evapotranspiration, and solar radiation—in the YZR basin over the period 2000–2019. We further explore the time-lag and time-accumulation impacts of these climatic factors on LAI dynamics and apply an enhanced residual trend analysis to disentangle the relative contributions of climate change and human activities. Results indicated that (1) a modest increase in annual LAI at a rate of 0.02 m² m⁻² dec⁻¹ was detected across the YZR basin. Spatially, LAI increased in 66% of vegetated areas, with significant increases (p < 0.05) in 10% of the basin. (2) Temperature, precipitation, and potential evapotranspiration exhibited minimal time-lag (<0.5 months) but pronounced notable time-accumulation effects on LAI variations, with accumulation periods ranging from 1 to 2 months. In contrast, solar radiation demonstrated significant time-lag impacts, with an average lag period of 2.4 months, while its accumulation effects were relatively weaker. (3) Climate change and human activities contributed 0.023 ± 0.092 and –0.005 ± 0.109 m² m⁻² dec⁻¹ to LAI changes, respectively, accounting for 60% and 40% on the observed variability. Spatially, climate change accounted for 85% of the changes in LAI in the upper YZR basin, while vegetation dynamics in the lower basin was primarily driven by human activities, contributing 63%. In the middle basin, vegetation dynamics were influenced by the combined effects of climate change and human activities. Our findings deepen insights into the drivers of vegetation dynamics and provide critical guidance for formulating adaptive management strategies in alpine ecosystems. Full article

Accurate cropland distribution data are essential for efficiently planning production layouts, optimizing farmland use, and improving crop planting efficiency and yield. Although reliable cropland data are crucial for supporting modern regional agricultural monitoring and management, cropland data extracted directly from existing global land use/cover products present uncertainties in local regions. This study evaluated the area consistency, spatial pattern overlap, and positional accuracy of cropland distribution data from six high-resolution land use/cover products from approximately 2020 in the alpine agricultural regions of the Hehuang Valley and middle basin of the Yarlung Zangbo River (YZR) and its tributaries (Lhasa and Nianchu Rivers) area on the Qinghai-Tibet Plateau. The results indicated that (1) in terms of area consistency analysis, European Space Agency (ESA) WorldCover cropland distribution data exhibited the best performance among the 10 m resolution products, while GlobeLand30 cropland distribution data performed the best among the 30 m resolution products, despite a significant overestimation of the cropland area. (2) In terms of spatial pattern overlap analysis, AI Earth 10-Meter Land Cover Classification Dataset (AIEC) cropland distribution data performed the best among the 10 m resolution products, followed closely by ESA WorldCover, while the China Land Cover Dataset (CLCD) performed the best for the Hehuang Valley and GlobeLand30 performed the best for the YZR area among the 30 m resolution products. (3) In terms of positional accuracy analysis, the ESA WorldCover cropland distribution data performed the best among the 10 m resolution products, while GlobeLand30 data performed the best among the 30 m resolution products. Considering the area consistency, spatial pattern overlap, and positional accuracy, GlobeLand30 and ESA WorldCover cropland distribution data performed best at 30 m and 10 m resolutions, respectively. These findings provide a valuable reference for selecting cropland products and can promote refined cropland mapping of the Hehuang Valley and YZR area. Full article

Vegetation is a key indicator of the health of most terrestrial ecosystems and different types of vegetation exhibit different sensitivity to climate change. The Yarlung Zangbo River Basin (YZRB) is one of the highest basins in the world and has a wide variety of vegetation types because of its complex topographic and climatic conditions. In this paper, the sensitivity to climate change for different vegetation types, as reflected by the Normalized Difference Vegetation Index (NDVI), was assessed in the YZRB. Three machine learning models, including multiple linear regression, support vector machine, and random forest, were adopted to simulate the response of each vegetation type to climatic variables. We selected random forest, which showed the highest performance in both the calibration and validation periods, to assess the sensitivity of the NDVI to temperature and precipitation changes on an annual and monthly scale using hypothetical climatic scenarios. The results indicated there were positive responses of the NDVI to temperature and precipitation changes, and the NDVI was more sensitive to temperature than to precipitation on an annual scale. The NDVI was predicted to increase by 1.60%–4.68% when the temperature increased by 1.5 °C, while it only changed by 0.06%–0.24% when the precipitation increased by 10% in the YZRB. Monthly, the vegetation was more sensitive to temperature changes in spring and summer. Spatially, the vegetation was more sensitive to temperature increases in the upper and middle reaches, where the existing temperatures were cooler. The time-lag effects of climate were also analyzed in detail. For both temperature and precipitation, Needleleaf Forest and Broadleaf Forest had longer time lags than those of other vegetation types. These findings are useful for understanding the eco-hydrological processes of the Tibetan Plateau. Full article

The number of precipitation products at the global scale has increased rapidly, and the accuracy of these products directly affects the accuracy of hydro-meteorological simulation and forecast. Therefore, the applicability of these precipitation products should be comprehensively evaluated to improve their application in hydrometeorology. This paper evaluated the performances of six widely used precipitation products in southwest China by quantitative assessment and contingency assessment. The precipitation products were Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis 3B42 version 7 (TRMM 3B42 V7), Global Satellite Mapping of Precipitation (GSMaP MVK), Integrated Multi-satellitE Retrievals for GPM final run (GPM IMERG Final), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network—Climate Data Record (PERSIANN-CDR), Climate Hazards Infrared Precipitation with Stations version 2.0 (CHIRPS V2.0), and the Global Land Data Assimilation System version 2.0 (GLDAS V2.0). From the above six products, the daily-scale precipitation data from 2001 to 2019 were chosen to compare with the measured data of the rain gauge, and the data from the gauges were classified by river basin and elevation. All precipitation products and measured data were evaluated by statistical indicators. Results showed that (1) GPM IMERG Final and CHIRPS V2.0 performed well in the Yarlung Zangbo River (YZ) basin, while GPM IMERG Final and GLDAS V2.0 performed well in the Lantsang River (LS), Nujiang River (NJ), Yangtze River (YT), and Yellow River (YL) basins; (2) in the upper and middle reaches of the YZ basin, GPM IMERG Final and CHIRPS V2.0 were outstanding in all evaluated products; downstream of the YZ basin, all six products performed well; and upstream of the LS and NJ, GPM IMERG Final, TRMM 3B42 V7, CHIRPS V2.0, and GLDAS V2.0 can be recommended as a substitute for measured data; and (3) GPM IMERG Final and GLDAS V2.0 can be seen as substitutes for measured data when elevation is below 4000 m. GPM IMERG Final and CHIRPS V2.0 were recommended when elevation is above 4000 m. This study provides a reference for data selection of hydro-meteorological simulation and forecast in southwest China and also provides a basis for multi-source data assimilation and fusion. Full article

The Yarlung Zangbo River is the largest river on the Tibetan Plateau and a major international river in South Asia. Changes in the blue and green water resources in its basin are of great importance to the surrounding local and Asian regions in the context of global warming. This research used the Soil and Water Assessment Tool model to estimate blue and green flows (BWF and GWF) and analyze the spatial-temporal distribution characteristics under different hypothetical climate change scenarios. The results show that (1) the multi-year average BWF in the middle and upper reaches of the Yarlung Zangbo River Basin is 176.2 mm, the GWF is 213.1 mm, and the difference between precipitation and total water resources is only 5.4 mm; (2) both BWF and GWF in this basin showed a slightly increasing trend from 1980 to 2010, but the distribution of subbasins from upstream to downstream is decreasing; and (3) GWF has a positive correlation with both precipitation and temperature, but BWF only increases with precipitation and decreases with increasing temperature. Moreover, the change in blue and green water resources is more sensitive to the changes in precipitation than to changes in the temperature. Full article

As the “Water Tower of Asia” and “The Third Pole” of the world, the Qinghai–Tibet Plateau (QTP) shows great sensitivity to global climate change, and the change in its terrestrial water storage has become a focus of attention globally. Differences in multi-source data and different calculation methods have caused great uncertainty in the accurate estimation of terrestrial water storage. In this study, the Yarlung Zangbo River Basin (YZRB), located in the southeast of the QTP, was selected as the study area, with the aim of investigating the spatio-temporal variation characteristics of terrestrial water storage change (TWSC). Gravity Recovery and Climate Experiment (GRACE) data from 2003 to 2017, combined with the fifth-generation reanalysis product of the European Centre for Medium-Range Weather Forecasts (ERA5) data and Global Land Data Assimilation System (GLDAS) data, were adopted for the performance evaluation of TWSC estimation. Based on ERA5 and GLDAS, the terrestrial water balance method (PER) and the summation method (SS) were used to estimate terrestrial water storage, obtaining four sets of TWSC, which were compared with TWSC derived from GRACE. The results show that the TWSC estimated by the SS method based on GLDAS is most consistent with the results of GRACE. The time-lag effect was identified in the TWSC estimated by the PER method based on ERA5 and GLDAS, respectively, with 2-month and 3-month lags. Therefore, based on the GLDAS, the SS method was used to further explore the long-term temporal and spatial evolution of TWSC in the YZRB. During the period of 1948–2017, TWSC showed a significantly increasing trend; however, an abrupt change in TWSC was detected around 2002. That is, TWSC showed a significantly increasing trend before 2002 (slope = 0.0236 mm/month, p < 0.01) but a significantly decreasing trend (slope = −0.397 mm/month, p < 0.01) after 2002. Additional attribution analysis on the abrupt change in TWSC before and after 2002 was conducted, indicating that, compared with the snow water equivalent, the soil moisture dominated the long-term variation of TWSC. In terms of spatial distribution, TWSC showed a large spatial heterogeneity, mainly in the middle reaches with a high intensity of human activities and the Parlung Zangbo River Basin, distributed with great glaciers. The results obtained in this study can provide reliable data support and technical means for exploring the spatio-temporal evolution mechanism of terrestrial water storage in data-scarce alpine regions. Full article

The Yarlung Zangbo River basin ecosystem is fragile. The distribution and transportation of phosphorus is of great significance for aquatic environmental protection and ecological security. The sequential extraction method and molybdenum antimony anti-spectrophotometry were used to measure the concentrations of different forms of phosphorus in the surface sediments from 15 sampling sites along the middle reaches of the Yarlung Zangbo River and its tributaries. The results show that the total phosphorus concentration in the surface sediments is 194.0~540.7 mg/kg, which is mainly composed of inorganic phosphorus. The concentrations of various phosphorus forms ranked as calcium-bound phosphorus (355.6 ± 86.0 mg/kg) > soluble phosphorus (15.9 ± 10.0 mg/kg) > iron-bound phosphorus (12.4 ± 12.3 mg/kg) > organic phosphorus (9.6 ± 6.1 mg/kg) > occluded phosphorus (9.2 ± 3.8 mg/kg) > aluminum-bound phosphorus (5.4 ± 2.3 mg/kg). On the whole, phosphorus concentration is greater in wet season than dry season. Regarding the spatial distribution characteristics, there are great disparities in the different forms of phosphorus in the middle reaches of the Yarlung Zangbo River. Comprehensive analysis shows that phosphorus of this area is mainly self-generated, and concentration of bioavailable phosphorus is small, demonstrating there will not be a large release. We also drew a “specific triangle” of the different forms of phosphorus concentrations in the research area and defined the “α” angle to determine the nutrient status of the overlying water quickly and effectively. Finally, phosphorus flux of the mainstream was estimated. This research may provide information on the phosphorus of Plateau Rivers. Full article

The Yarlung Zangbo River Basin (YZRB) is an important transboundary river basin in Tibet, China with south Asian countries. Changes in precipitation are important driving factors of river flow changes. Extreme Precipitation Events (EPE), in particular, have serious impacts on human life and sustainable development. The objective of this study is to explore the temporal changes and the spatial distribution of EPE over the YZRB in recent decades using a precipitation product with a 5 km spatial resolution and the Mann–Kendall nonparametric statistical test method. A more thorough understanding of the spatial heterogeneity in precipitation was expected from using this high resolution dataset. At both basin and pixel scale, both annual precipitation amounts and number of rain days had significant upward trends, indicating that the increase in the number of rain days is one possible cause of the annual precipitation amounts increases. The annual precipitation and number of rain days increased significantly in 50.8% and 75.8% of the basin area, respectively. The areas showing upward trends for the two indexes mostly overlapped, supporting the hypothesis that the increasing number of rain days is one possible cause of the increases in annual precipitation in these areas. General precipitation intensity and EPE intensity increased in the Lhasa regions and in the southern part of the lower-reach region. However, the intensity of general precipitation and EPE decreased in the Nyangqu River Basin. A total of 43.0% of the area in the YZRB exhibits significant upward trends in EPE frequency. The contributions of EPE to total rainfall increase significantly in the Lhasa and Shannan regions. Overall, it was shown that the risk of disasters from EPE in the YZRB increases in the eastern middle-reach region and southern lower-reach region. Full article

Long-term hydro-climatic datasets and sophisticated change detection methods are essential for estimating hydro-climatic trends at regional and global scales. Here, we use the ensemble empirical mode decomposition method (EEMD) to investigate runoff oscillations at different time scales and its response to climatic fluctuations in the middle of the Yarlung Zangbo River Basin (MYZRB) over the period 1961–2009. In the study region, results revealed that the runoff presented an overall nonlinear and nonstationary decreasing-increasing alternative trend with weak quasi-three-year and unobvious quasi-five-year cycles at the inter-annual scale, while, significance was discovered with quasi-12-year and quasi-46-year cycles at the inter-decadal scale. Variance contribution rates of the hydrological components suggested that the inter-annual oscillations played an essential role in the runoff variations in the MYZRB. According to the reconstructed inter-decadal runoff series, the runoff may keep declining in future. For the response of runoff to climate change, overall, the runoff had a positive correlation with precipitation and a negative correlation with extreme temperature. But the runoff did not show obvious correlation with mean temperature. Furthermore, from a temporal scale point of view, the inter-annual runoff showed significant response to the inter-annual precipitation. The inter-decadal runoff strongly responded to the inter-annual extreme temperature. These findings will help us understand the hydro-climatic intrinsic mechanism in the MYZRB and develop better water resources management to account for climate change impact. Full article