Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; University of Chinese Academy of Sciences, Beijing 100049, China.
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China; Liaocheng University, Liaocheng 252000, China.
Sci Total Environ. 2022 Nov 10;846:157328. doi: 10.1016/j.scitotenv.2022.157328. Epub 2022 Jul 19.
Total suspended matter (TSM), as an indicator of the concentration of fine materials in the water column including particulate nutrients, pollutants, and heavy metals, is widely used to monitor aquatic ecosystems. However, the long-term spatiotemporal variations of TSM in lakes across the Tibetan Plateau (TP) and their response to environmental factors are rarely explored. Accordingly, taking advantage of the Landsat top-of-atmosphere reflectance and in-situ data, an empirical model (R = 0.83, RMSE = 1.08 mg/L, and MAPE = 19.49 %) was developed to estimate the average autumnal TSM in large TP lakes (≥50 km) during the 1990-2020 period. For analyzing the spatiotemporal variability in TP lakes TSM, the examined lakes were classified into four types (Type A-D) based on their water storage changing in different periods. The results showed that the lakes in the southern and some northeastern parts of the TP exhibited lower TSM values than those situated in other regions. The assessment of TSM in each of these four lake types showed that more than half of them had a TSM value of <20 mg/L. Apart from Type D, the lakes with the TSM showing significantly decreasing trends were dominantly Types A-C. A relative contribution analysis involving five driving factors indicated that they contributed by >50 % to lake TSM interannual variation in 73 out of 114 watersheds, and the lakes area change demonstrated the greatest contribution (82.2 %), followed by wind speed (11.0 %). Further comparison between the entire lake and the non-expansive regions suggested that the expansive region played an indispensable role in determining the TSM value of the whole lake. This study can help to better understand the water quality condition and provide valuable information for policy-makers to maintain sustainable development in the TP region.
总悬浮物质(TSM)作为水柱中细物质浓度的指标,包括颗粒营养物质、污染物和重金属,广泛用于监测水生态系统。然而,青藏高原(TP)湖泊 TSM 的长期时空变化及其对环境因素的响应很少被探索。因此,本研究利用 Landsat 大气顶部反射率和原位数据,建立了一个经验模型(R = 0.83,RMSE = 1.08 mg/L,MAPE = 19.49 %),以估计 1990-2020 年期间青藏高原大型湖泊(≥50 km)秋季平均 TSM。为了分析青藏高原湖泊 TSM 的时空变化,根据不同时期湖泊蓄水量的变化,将研究的湖泊分为四类(A-D 型)。结果表明,TP 南部和部分东北部的湖泊 TSM 值低于其他地区。对这四种类型湖泊 TSM 的评估表明,超过一半的湖泊 TSM 值<20 mg/L。除 D 型外,TSM 值呈显著下降趋势的湖泊主要是 A-C 型。涉及五个驱动因素的相对贡献分析表明,在 114 个流域中有 73 个流域的 50%以上的流域对湖泊 TSM 的年际变化做出了贡献,湖泊面积变化的贡献最大(82.2 %),其次是风速(11.0 %)。在整个湖泊和非扩张区域之间的进一步比较表明,扩张区域在确定整个湖泊的 TSM 值方面发挥了不可或缺的作用。本研究可以帮助更好地了解水质状况,并为决策者提供维持青藏高原地区可持续发展的有价值信息。