Search Results (7)

This study examines runoff variations and their drivers in the Buha and Shaliu Rivers of the Qinghai Lake Basin (1960–2016), a key ecological area in China. Abrupt changes were detected using the Mann–Kendall and cumulative anomaly methods, while the Budyko framework attributed runoff variations to dominant factors. Correlation and grey relational analyses assessed multicollinearity, and a lake water balance model with climate elasticity theory quantified the effects of climate and land surface changes on runoff components and lake levels. Results indicate that the Buha River experienced an abrupt runoff change in 2004, while the Shaliu River exhibited a change beginning in 2003. Based on the trends and abrupt change points of each factor, the study period was divided into four segments: 1960–1993, 1994–2016, 1960–2003, and 2004–2016. The correlation coefficients are significantly different in different periods. The climate elasticity coefficients were as follows: P (precipitation), 1.98; ET₀ (potential evapotranspiration), −0.98; Rn (net radiation), 0.66; T (average temperature), 0.02; U₂ (wind speed at 2 m height), 0.16; RHU (relative umidity), −0.56. The elasticity coefficient of runoff with respect to precipitation is significantly higher than that for other climate variables. Net radiation and relative humidity contribute equally to runoff, while wind speed and temperature have relatively smaller effects. In the Qinghai Lake Basin, runoff is sensitive to precipitation (0.38), potential evapotranspiration (−0.07), and the underlying surface parameter ω (−98.32). Specifically, a 1 mm increase in precipitation raises runoff by 0.38 mm, while a 1 mm rise in potential evapotranspiration reduces it by 0.07 mm. A one-unit increase in ω leads to a significant runoff decrease of 98.32 mm. According to the lake water balance model, climate contributes 88.43% to groundwater runoff, while land surface changes contribute −11.57%. Climate change and land surface changes contribute 93.02% and 6.98%, respectively, to lake water levels. This study quantitatively evaluates the impacts of climate and land surface changes on runoff, providing insights for sustainable hydrological and ecological management in the Qinghai Lake Basin. Full article

This study, based on hydrological station data and wavelet analysis, explores the periodic variation characteristics and trends of the two main tributaries (Buha River and Shaliu River) in the Qinghai Lake Basin from 1960 to 2016. Wavelet transform is used to analyze the runoff data, revealing long-term periodic fluctuations and their correlation with precipitation changes. The study finds that, from 2003 to 2016, the daily peak flow and daily minimum flow of the two rivers increase compared to the period from 1960 to 2003, though the magnitude and trends of the increase differ. At the monthly scale, runoff patterns show that June to October is the main period for concentrated runoff in the basin, with July and August being the peak months. Additionally, interannual runoff changes for both rivers show a gradually increasing trend amid fluctuations, with varying fluctuation intensities observed in different years. Wavelet analysis results indicate that the main periodicity of runoff is 23 years, closely linked to changes in precipitation. This study reveals the periodic variation patterns of runoff in the Qinghai Lake Basin, providing valuable insights for watershed water resource management and hydrometeorological forecasting. Full article

Alluvial parent material soil is an important soil type found on the Qinghai–Tibet Plateau (QTP) in China. However, due to the limited age data for alluvial soils, the relationship between alluvial geomorphological processes and soil pedogenic processes remains unclear. In this study, three representative alluvial parent material profiles on the Buha River alluvial plain in the Qinghai Lake Basin, northeast QTP, were analyzed using the optical luminescence (OSL) dating method. Combined with physical and chemical analyses of the soil, we further analyzed the pedogenic process of alluvial soil. The alluvial parent material of the Buha alluvial plain predominately yielded ages between 11.9 and 9.1 ka, indicating that the alluvial soil began to form during the early Holocene. The development of the alluvial soil on the first-order terrace presents characteristics of entisol with multiple burial episodes, mainly between 8.5 and 4.0 ka, responding to the warm and humid middle Holocene and high lake levels. Full article

This study utilizes the Simulator of Hydrologic Unstructured Domains (SHUD) model and the China Meteorological Forces Dataset (CMFD) to investigate the hydrological dynamics of the Buha River watershed, a critical tributary of Qinghai Lake, from 1979 to 2018. By integrating high-resolution terrestrial and meteorological data, the SHUD model simulates streamflow variations and other hydrological characteristics, providing valuable insights into the region’s water balance and runoff processes. Key findings reveal a consistent upward trend in precipitation and temperature over the past four decades, despite minor deviations in daily precipitation intensity and relative humidity data. The SHUD model demonstrates high accuracy on a monthly scale, with Nash–Sutcliffe Efficiency (NSE) values of 0.72 for the calibration phase and 0.61 for the validation phase. The corresponding Kling–Gupta Efficiency (KGE) values are 0.73 and 0.49, respectively, underscoring the model’s applicability for hydrological forecasting and water resource management. Notably, the annual runoff ratios for the Buha River fluctuate annually between 0.11 and 0.21, with significant changes around 2007 correlating with a shift in Qinghai Lake’s water levels. The analysis of water balance indicates a net leakage over long-term periods, with spatial alterations in leakage and replenishment along the river. Furthermore, snow accumulation, which increases with altitude, significantly contributes to streamflow during the melting season. Despite the Buha River basin’s importance, research on its hydrology remains limited due to data scarcity and minimal human activity. This study enhances the understanding of the Buha River’s hydrological processes and highlights the necessity for improved dataset accuracy and model parameter optimization in future research. Full article

Due to the fencing of the Przewalski’s gazelle (Procapra przewalskii), the microcytic anemia incidence rate continues to increase. The primary pathological symptoms include emaciation, anemia, pica, inappetence, and dyskinesia. To investigate the cause of microcytic anemia ailment in the Przewalski’s gazelle, the Upper Buha River Area with an excessive incidence was chosen as the experimental pasture, and the Bird Island Area without microcytic anemia disease was chosen as the control field. Then, the mineral contents in the soil, forage, blood, and liver, as well as the blood routine parameters and biochemical indexes were measured. The findings showed that the experimental pasture had much lower Se content in the soil and forage than the control field (p < 0.01), while the impacted pasture had significantly higher S content in the forage. The damaged gazelles had considerably lower Se and Cu contents and higher S content in the blood and liver than the healthy gazelles (p < 0.01). The presences of Hb, HCT, MCV, and MCH were significantly decreased compared to those in healthy gazelles (p < 0.01). The experimental group had a significantly lower level of GSH-Px activity in their serums compared to the control group (p < 0.01). In the treatment experiment, ten gazelles from the affected pasture were orally administered CuSO₄, 6 g/animal once every 10 days for two consecutive times, and all gazelles were successfully cured. Therefore, it is possible that low Se content in the soil induced an increase in the absorption of S content by forage, leading to the deficiency of secondary Cu in the Przewalski’s gazelles, resulting in microcytic anemia. Full article

Qinghai Lake is the largest lake in Qinghai-Tibet Plateau and China, it is also an important part of the national ecological security strategy. Since 1950s, the water level of Qinghai Lake has been changing rapidly, which induces great effects on the surrounding traffic facilities, residents’ safety and the development of animal husbandry, etc. Therefore, it is necessary to study the water level evolution and water balance of Qinghai Lake under the main impact of climate change. Based on meteorological and hydrological data from Buha River Hydrological Station, Xiashe Hydrological Station, and Gangcha Meteorological Station, CMFD, and water balance equation, this article first analyzes the interannual and intra-year water level evolution characteristics of Qinghai Lake from 1956 to 2020, including lake surface precipitation (P), runoff into the lake (${\mathrm{R}}_{\mathrm{s}}$) and evaporation (E). Secondly, we conducted a study on the water level change characteristics calculated for fixed months. Finally, the contribution rate of each factor to the fluctuation of Qinghai Lake water level was quantitatively calculated using the ridge regression method. Results show that the annual average water level declined at a rate of 0.8 m decade⁻¹ from 1956 to 2004, primarily due to E exceeding the sum of P and ${\mathrm{R}}_{\mathrm{s}}$. However, from 2004 to 2020, the water level increased at a rate of 1.7 m decade⁻¹, mainly attributed to the increase in P and ${\mathrm{R}}_{\mathrm{s}}$. Qinghai Lake exhibits evident intra-year variations, with the water level starting to rise in May and reaching its peak in September, which aligns with the monthly variations of ${\mathrm{R}}_{\mathrm{s}}$, P, and E. Furthermore, the impacts of the current year’s P, ${\mathrm{R}}_{\mathrm{s}}$, and E on the annual water level fluctuations for fixed months of September to December is greater than that of the previous year. Specifically, the contributions of the current year’s P, ${\mathrm{R}}_{\mathrm{s}}$ and E to the water level fluctuations calculated based on December data are 10%, 70%, and 20%, respectively. The contribution rate of meteorological factors to the rise and fall of water level was wind speed (33%), downward short-wave radiation (27%), precipitation (27%), downward long-wave radiation (11%) and specific humidity (2%). Full article

With climate warming and intensification of human activities, the eco-environmental problems of lakes in middle and high latitudes become increasingly prominent. Qinghai Lake, located in the northeastern of the Tibetan Plateau, is the largest inland saltwater lake in China. Recently, the problem of Cladophora blooms has been widely concerning. In this study, the area of floating Cladophora blooms (hereafter FCBs) in Qinghai Lake from 1986 to 2021 was extracted using Floating Algal Index (FAI) method based on Landsat TM/ETM+/OLI and Sentinel-2 MSI images, and then the intra- and inter-annual variation characteristics and spatial patterns of FCBs were analyzed. The results show that the general change trend of FCBs in Qinghai Lake featured starting in May, expanding rapidly from June to August, and increasing steadily from September to October. From 1986 to 2021, the area of FCBs in Qinghai Lake showed an overall increasing trend in all months, with the largest increase in July at 0.1 km²/a, followed by October at 0.096 km²/a. Spatially speaking, the FCBs area showed a significant increasing trend in the northern Buha River estuary (BRN) and southern Buha River estuary (BRS) regions, a slight increase in the Shaliu River estuary (SR) region, and a decreasing trend in the Quanji River estuary (QR) region and the Heima River estuary (HR) region. The correlation between the meteorological factors and the changes in FCBs was weak, but the increase in flooded pastures in the BRN region (Bird Island) due to rising water levels was definitely responsible for the large-scale increase in FCBs in this region. However, the QB, northeastern bay of Shaliu River estuary (SRB) and HR regions, which also have extensive inundated grassland, did not have the same increase in FCBs area, suggesting that the growth of Cladophora is caused by multiple factors. The complex relationships need to be verified by further research. The current control measures have a certain inhibitory effect on the Cladophora bloom in Qinghai Lake because the FCBs area was significantly smaller in 2017–2020 (5.22 km², 3.32 km², 4.55 km² and 2.49 km²), when salvage work was performed, than in 2016 and 2021 (8.67 km² and 9.14 km²), when no salvage work was performed. Full article