Recent water-level fluctuations, future trends and their eco-environmental impacts on Lake Qinghai

Study on Characteristics of Water Level Variations and Water Balance of the Largest Lake in the Qinghai-Tibet Plateau

“…The Mann-Kendall (M-K) test method was used to determine whether the time series has a monotonic increased or decreased trend. The details calculated equation can be found in the reference [19]. This method is a non-parametric test closely related to the concept of Kendall's correlation coefficient.…”

“…The difference in the water level of Qinghai Lake is primarily influenced by the combined effects of inflow runoff (R s ), lake surface precipitation (P) and lake surface evaporation (E) [45]. Among these, R s constitutes the main input to the lake water and accounts for approximately 43.5% of the lake's water supply, significantly impacting the water level variations [2,19]. According to the findings of Li et al ( 2005), the R s from the previous year has a greater influence on the current year's lake water level than the R s of the current year [46].…”

“…Hao et al indicates that there has been no significant change in the water quality of Qinghai Lake in recent years, but the increase in water level may be an important reason for the expansion of the coverage area of flagella in Qinghai Lake [18]. Hou et al found that the continuous rise in the water level of Qinghai Lake may result in erosion of shallow lake areas and the suspension of sediment, leading to a decline in water quality [19]. Therefore, it is of great significance to study the evolution law of Qinghai Lake water level under climate change and its mechanism analysis for the understanding of the plateau water cycle and the protection of plateau ecology.…”

“…The main factors affecting the changes in water quantity in Qinghai Lake are precipitation (P), evaporation (E) and runoff into the lake (R s ) [24]. Most previous studies qualitatively revealed that the increase in P and R s was significantly positively correlated with the lake water level, while the increase in E inhibited the increase in the lake water level [19,[25][26][27][28][29][30][31]. Li et al (2020) concluded that the influence of last year's factors (R s , P and E) on the water level was more significant than that of the current year, and further quantitatively evaluated the contribution rate of the three variables to the water level fluctuation of Qinghai Lake from 1961 to 2015 by using the principle of water balance and correlation coefficients as R s > P > E. For the same research period, Wang and Gao (2021) conducted work based on the study of Li (2020) and further demonstrated through the quantitative analysis of ridge regression that the contribution rate of the three variables to the water level fluctuation of Qinghai Lake was R s (38.2%) > E (31.4%) > P (30.4%).…”

Estimation of Phytoplankton Primary Productivity in Qinghai Lake Using Ocean Color Satellite Data: Seasonal and Interannual Variations

“…are mainly based on a small number of field samples from cruise surveys. These methods are time-consuming and labor-intensive, and are also unable to enable spatial distribution estimation over a long time sequence [6][7][8]. Remote sensing monitoring technology, with its advantages of wide spatial coverage and high temporal continuity, is a powerful tool for monitoring lake environments at large spatial scales [9].…”