基于XGBoost的内陆河湖浊度反演与长时序分析  

Inversion and long-term series analysis of turbidity in inland rivers and lakes based on XGBoost

作　　者：李媛媛[1] 沈芳[1] 陈嵩钰 魏小岛 LI Yuanyuan;SHEN Fang;CHEN Songyu;WEI Xiaodao(State Key Laboratory of Estuarine and Coastal Research,East China Normal University,Shanghai 200241,China;Shanghai Investigation,Design&Research Institute Co.,Ltd,Shanghai 200050,China;YANGTZE Eco-Environment Engineering Research Center(shanghai),China Three Gorges Corporation,Shanghai 200050,China)

机构地区：[1]华东师范大学河口海岸学国家重点实验室,上海200241 [2]上海勘测设计研究院有限公司,上海200050 [3]中国长江三峡集团有限公司长江生态环境工程研究中心(上海),上海200050

出　　处：《环境工程学报》2024年第2期398-408,共11页Chinese Journal of Environmental Engineering

基　　金：上海市科委重点项目(20dz1204700);中国长江三峡集团有限公司科研项目资助(202103552)。

摘　　要：浊度是影响水下光场及营养盐循环的关键要素之一,浊度监测可以为河湖水质的污染防控和预警提供科学依据。以长三角示范区的典型河湖为研究区,使用实测数据构建浊度反演模型,并利用1984—2022年Landsat卫星数据分析了研究区河湖浊度的长时序动态变化。对比传统经验模型、半经验模型和机器学习模型,XGBoost机器学习模型精度最高(R^(2)为0.68,RMSE为4.78 NTU)。浊度反演结果表明,近40年河流航道和淀山湖北部非渔场区域浊度上升了10%和12%,而元荡湖和大莲湖浊度下降了19%和27%,并且浊度随着建设用地面积的增加而增大;研究区浊度季节性变化显著,秋冬季平均浊度比春夏季高6 NTU,月平均浊度与月平均降水量负相关,相关系数为-0.61(p<0.05),但与月平均风速没有显著的相关性。基于XGBoost的Landsat长时序浊度反演能够把握研究区浊度的时空变化趋势,明确水污染管理与治理方向,最终助力长三角一体化发展。Turbidity is one of the key elements affecting the underwater light field and nutrient cycling.Turbidity monitoring can provide a scientific basis for pollution prevention,control,and early warning of river and lake water quality.The typical rivers and lakes in the demonstration zone of the Yangtze River Delta were taken as the study area.The turbidity inversion model was constructed using in-situ data,based on which the long-term dynamic changes of turbidity in the rivers and lakes of the study area were analyzed using a total of 323 Landsat TM/ETM+/OLI images from 1984 to 2022.Through the comparison between the traditional empirical model,semi-empirical model,and machine learning model,the machine learning model named XGBoost demonstrated the highest accuracy(R^(2) and RMSE were 0.68 and 4.78 NTU,respectively).The results of turbidity inversion showed that,in the last 40 years,turbidity in the river channel and the northern non-fishing area of Dianshan Lake increased by 10% and 12%,respectively,while turbidity in Yuandang Lake and Dalian Lake decreased by 19% and 27%,respectively.Moreover,it was found that turbidity increased with the expansion of the built-up land area.The seasonal variation of turbidity in the study area was significant and the average turbidity in autumn and winter was 6 NTU higher than that in spring and summer.The monthly average turbidity was negatively correlated with the monthly average precipitation(r=-0.61,p<0.05),but its correlation with the monthly average wind speed was found to be insignificant.The XGBoost-based long-term inversion of turbidity from Landsat images can not only capture the spatiotemporal trend of turbidity in the study area,but also reveal the direction of water pollution management and control,eventually contributing to the integrated development of the Yangtze River Delta.

关 键 词：浊度 XGBoost LANDSAT 长时序 长三角示范区 

分 类 号：X832[环境科学与工程—环境工程]