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利用陆地卫星 8 衍生的福雷尔-乌勒指数评估中国长江流域季节性城市湖泊的富营养化:六年(2013-2018 年)观测。

Eutrophication assessment of seasonal urban lakes in China Yangtze River Basin using Landsat 8-derived Forel-Ule index: A six-year (2013-2018) observation.

机构信息

College of Hydropower and Information Engineering, Huazhong University of Science and Technology, NO. 1037, Luoyu Road, Wuhan 430074, China.

College of Hydropower and Information Engineering, Huazhong University of Science and Technology, NO. 1037, Luoyu Road, Wuhan 430074, China.

出版信息

Sci Total Environ. 2020 Nov 25;745:135392. doi: 10.1016/j.scitotenv.2019.135392. Epub 2019 Nov 23.

Abstract

Lakes eutrophication have been a complex and serious problem for China's Yangtze River Basin. A series of algorithms based on different remote sensing dataset have been proposed to simulate the lakes trophic state. However, these algorithms are often targeted at a particular lake and cannot be applied to a watershed management. In this study, a Forel-Ule index (FUI) method based on Landsat 8 OLI image is proposed to simulate trophic state index (TSI) in three typical urban lakes (Dianchi, Donghu, and Chaohu) from 2013 to 2018. The results show that the Landsat 8 derived FUI can well represent the lake TSI with an accuracy of R = 0.6464 for the in situ experimental TSI dataset (N = 115) and R = 0.8065 for the lake average TSI dataset (N = 315). In the study period 2013-2018, the order of the simulated TSI is Dianchi > Chaohu > Donghu. Seasonal dynamics show differences where the percentage of eutrophic area in summer is significantly lower than the other seasons for Lake Dianchi and Chaohu. However, the percentage of eutrophic area for Lake Donghu is highest in summer and lowest in winter. To further detect the driving factors of eutrophication in study lakes, the Pearson correlation and multiple linear regression analyses were conducted. The results show that sunshine and temperature are, respectively, the most and the second most significant factors for Lake Dianchi with explanations of 14.8% and 22.0%; temperature and pollution are the main influencing factors for Lake Donghu (39.2% and 10.9% explanation, respectively) and Chaohu (57.2% and 60.7% explanations, respectively). In addition, the wind is another negatively significant factor for Lake Chaohu with an explanation of 31.3%. Our results serve as an example for other lakes in the Yangtze River Basin and support the formulation of effective strategies to reduce seasonal eutrophication.

摘要

湖泊富营养化一直是中国长江流域面临的一个复杂而严重的问题。已经提出了一系列基于不同遥感数据集的算法来模拟湖泊营养状态。然而,这些算法通常针对特定的湖泊,无法应用于流域管理。本研究提出了一种基于 Landsat 8 OLI 图像的 Forel-Ule 指数(FUI)方法,用于模拟 2013 年至 2018 年三个典型城市湖泊(滇池、东湖和巢湖)的营养状态指数(TSI)。结果表明,Landsat 8 衍生的 FUI 可以很好地代表湖泊 TSI,对于现场实验 TSI 数据集(N=115)的精度为 R=0.6464,对于湖泊平均 TSI 数据集(N=315)的精度为 R=0.8065。在 2013-2018 年期间,模拟 TSI 的顺序为滇池>巢湖>东湖。季节性动态显示出差异,滇池和巢湖夏季富营养化区域的比例明显低于其他季节。然而,东湖夏季富营养化区域的比例最高,冬季最低。为了进一步检测研究湖泊富营养化的驱动因素,进行了 Pearson 相关和多元线性回归分析。结果表明,对于滇池,阳光和温度分别是最重要和第二重要的因素,解释率分别为 14.8%和 22.0%;对于东湖和巢湖,温度和污染是主要影响因素(东湖分别为 39.2%和 10.9%,巢湖分别为 57.2%和 60.7%)。此外,风也是巢湖的另一个负显著因素,解释率为 31.3%。我们的结果为长江流域的其他湖泊提供了一个范例,并支持制定减少季节性富营养化的有效策略。

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