State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
State Key Laboratory of Lake Science and Environment, Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China; University of the Chinese Academy of Sciences, Beijing 100049, China; CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing 100101, China.
Sci Total Environ. 2021 Nov 20;796:148916. doi: 10.1016/j.scitotenv.2021.148916. Epub 2021 Jul 7.
Water clarity (generally quantified as the Secchi disk depth: SDD) is a key variable for assessing environmental changes in lakes. Using remote sensing we calculated and elucidated the SDD dynamics in lakes in the Inner Mongolia-Xinjiang Lake Zone (IMXL) from 1986 to 2018 in response to variations in temperature, rainfall, lake area, normalized difference vegetation index (NDVI) and Palmer's drought severity index (PDSI). The results showed that the lakes with high SDD values are primarily located in the Xinjiang region at longitudes of 75°-93° E. In contrast, the lakes in Inner Mongolia at longitudes of 93°-118° E generally have low SDD values. In total, 205 lakes show significant increasing SDD trends (P < 0.05), with a mean rate of 0.15 m per decade. In contrast, 75 lakes, most of which are located in Inner Mongolia, exhibited significant decreasing trends with a mean rate of 0.08 m per decade (P < 0.05). Pooled together, an overall increase is found with a mean rate of 0.14 m per decade. Multiple linear regression reveals that among the five variables selected to explain the variations in SDD, lake area accounts for the highest proportion of variance (25%), while temperature and rainfall account for 12% and 10%, respectively. In addition, rainfall accounts for 52% of the variation in humidity, 8% of the variation in lake area and 7% of the variation in NDVI. Temperature accounts for 27% of the variation in NDVI, 39% of the variation in lake area and 22% of the variation in PDSI. Warming and wetting conditions in IMXL thus promote the growth of vegetation and cause melting of glaciers and expansion of lake area, which eventually leads to improved water quality in the lakes in terms of higher SDD. In contrast, lakes facing more severe drought conditions, became more turbid.
水的清澈程度（通常以塞奇圆盘深度表示：SDD）是评估湖泊环境变化的关键变量。我们使用遥感技术，计算并阐明了 1986 年至 2018 年内蒙古-新疆湖区（IMXL）湖泊的 SDD 动态变化，以响应温度、降雨、湖泊面积、归一化差异植被指数（NDVI）和帕尔默干旱严重指数（PDSI）的变化。结果表明，高 SDD 值的湖泊主要位于新疆地区，经度在 75°-93°E 之间。相比之下，内蒙古经度在 93°-118°E 之间的湖泊通常 SDD 值较低。共有 205 个湖泊呈现出显著的 SDD 增加趋势（P<0.05），平均每十年增加 0.15 米。相比之下，75 个湖泊，其中大部分位于内蒙古，呈现出显著的 SDD 减少趋势，平均每十年减少 0.08 米（P<0.05）。综合来看，总体呈上升趋势，平均每十年增加 0.14 米。多元线性回归显示，在所选择的五个解释 SDD 变化的变量中，湖泊面积占方差的比例最高（25%），而温度和降雨分别占 12%和 10%。此外，降雨占湿度变化的 52%，占湖泊面积变化的 8%，占 NDVI 变化的 7%。温度占 NDVI 变化的 27%，占湖泊面积变化的 39%，占 PDSI 变化的 22%。因此，IMXL 的变暖增湿条件促进了植被的生长，导致冰川融化和湖泊面积扩大，最终导致湖泊水质提高，表现为 SDD 值升高。相反，面临更严重干旱条件的湖泊变得更加浑浊。
