Wang Yao, Feng Lei, Shao Jingan, Gan Menglan, Liu Meiling, Wu Ling, Zhou Botian
School of Geography and Tourism, Chongqing Normal University, Chongqing 401331, China.
Chongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.
Sensors (Basel). 2024 Nov 22;24(23):7449. doi: 10.3390/s24237449.
Water color is an essential indicator of water quality assessment, and thus water color remote sensing has become a common method in large-scale water quality monitoring. The satellite-derived Forel-Ule index (FUI) can actually reflect the comprehensive water color characterization on a large scale; however, the spatial distribution and temporal trends in water color and their drivers remain prevalently elusive. Using the Google Earth Engine platform, this study conducts the Landsat-derived FUI to track the complicated water color dynamics in a large reservoir, i.e., the Three Gorges Reservoir (TGR), in China over the past decade. The results show that the distinct patterns of latitudinal FUI distribution are found in the four typical TGR tributaries on the yearly and monthly scales, and the causal relationship between heterogeneous FUI trends and natural/anthropogenic drivers on different temporal scales is highlighted. In addition, the coexistence of phytoplankton bloom and summer flood in the TGR tributaries has been revealed through the hybrid representation of greenish and yellowish schemes. This study is an important step forward in understanding the water quality change in a river-reservoir ecosystem affected by complex coupling drivers on a large spatiotemporal scale.
水色是水质评估的重要指标，因此水色遥感已成为大规模水质监测的常用方法。卫星衍生的福尔-乌勒指数（FUI）实际上可以在大尺度上反映综合水色特征；然而，水色的空间分布和时间趋势及其驱动因素仍然普遍难以捉摸。本研究利用谷歌地球引擎平台，采用陆地卫星衍生的FUI来追踪中国一个大型水库——三峡水库（TGR）在过去十年中复杂的水色动态。结果表明，在三峡水库四条典型支流的年尺度和月尺度上发现了明显的纬度FUI分布模式，并突出了不同时间尺度上异质FUI趋势与自然/人为驱动因素之间的因果关系。此外，通过绿色和黄色方案的混合表示，揭示了三峡水库支流中浮游植物水华和夏季洪水的共存情况。本研究是在大时空尺度上理解受复杂耦合驱动因素影响的河流水库生态系统水质变化方面向前迈出的重要一步。
