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基于Landsat卫星影像的草海水质遥感反演及营养状态评价
引用本文:陈艳,刘绥华,王堃,宋善海,梁萍萍,陈芳. 基于Landsat卫星影像的草海水质遥感反演及营养状态评价[J]. 水生态学杂志, 2020, 0(3): 24-31
作者姓名:陈艳  刘绥华  王堃  宋善海  梁萍萍  陈芳
作者单位:贵州师范大学地理与环境科学学院
基金项目:广西高校无人机重点实验室主任基金/开放项目:基于无人机遥感影像的SIFT匹配算法研究(WRJ2015KF03)。
摘    要:通过遥感手段对草海2000年、2005年、2010年及2015年的水质指标进行反演,并进行营养状态评价,获取草海水质数据,为草海湿地保护及污染治理提供依据。利用实测水质数据与遥感影像的关系建立反演模型,反演草海2000-2015年水质指标,包括Chl-a、TN、TP、CODMn、SD,并用综合营养状态指数(TLI)对草海水质情况进行评价。研究结果表明:(1)通过波段组合与实测数据建立水质参数反演模型能高效、大面积获得草海水质分布情况,草海整体水质2000-2005年为中营养、2010-2015年为轻度富营养,TLI表现为先升高后降低;(2)草海水质季节变化明显,4个季节的综合营养状态指数为春季>夏季>冬季>秋季,主要原因是草海春、夏季节农耕及旅游活动等人为活动较频繁;(3)空间上看,草海入水口及湖周围综合营养指数比湖中心及出水口高,其原因是入水口靠近城市,城市污水排入湖中,湖四周存在大量农业污染源。

关 键 词:草海  遥感  水质  营养评价  时空分布

Remote Sensing of Caohai Lake Water Quality Using Landsat Satellite Images
CHEN Yan,LIU Sui-hua,WANG Kun,SONG Shan-hai,LIANG Ping-ping,CHEN Fang. Remote Sensing of Caohai Lake Water Quality Using Landsat Satellite Images[J]. Journal of Hydroecology, 2020, 0(3): 24-31
Authors:CHEN Yan  LIU Sui-hua  WANG Kun  SONG Shan-hai  LIANG Ping-ping  CHEN Fang
Affiliation:(School of Geography and Environmental Science,Guizhou Normal University,Key Laboratory of Mountain Resources and Environmental Remote Sensing,Guiyang 550025,P.R.China)
Abstract:Water quality assessment is basic to water environment research and conservation.Water quality monitoring based on remote sensing is widely applied because it is efficient,economical and can be used to monitor large areas.In this study,we developed a regression model based on the relationship between measured water quality data and spectral data from Landsat satellite images.After verification,the model was used to estimate water quality parameters(WQPs)from the different spectral bands of satellite imagery.WQPs included chlorophyll a(chl-a),total nitrogen(TN),total phosphorous(TP),chemical oxygen demand(COD Mn)and transparency(SD).The water quality data for developing the model were measured at 33sampling sites in August of 2017and Landsat satellite imagery,providing spectral data for the model,were obtained in October of 2017.The regression model was then used to estimate WQPs from Landsat satellite images from the same months in 2000,2005,2010and 2015.The estimated WQPs were then used to calculate Caohai Lake water quality indices for 2000,2005,2010and 2015.The nutritional status of Caohai Lake was evaluated using the Trophic Level Index(TLI).The model successfully met the study objective of providing information on current water quality conditions in Caohai wetlands,derived from Landsat images,that is valuable for conserving Caohai wetland and controlling pollution.Results show that:(1)Water quality parameters estimated from the regression model,based on spectral bands from satellite imagery,can show the large-scale distribution of water in Caohai Lake.Overall water quality of Caohai Lake in 2000,2005was mesotrophic and was slightly eutrophic in 2010and 2015.The TLI increased and then decreased;(2)There is clearly seasonal variation of water quality in Caohai Lake.The TLI across four seasons was in the order:spring>summer>winter>autumn and attributed to intensive farming and tourism around Caohai Lake in spring and summer.(3)Spatially,the TLI of the inlet and surrounding area of Caohai Lake was higher than that at the lake center and outlet.The inlet is near Weining County,and the discharge of municipal sewage and nonpoint source agricultural pollution are serious.
Keywords:Caohai Lake:remote sensing  water quality  nutrient assessment  temporal-spatial distribution
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