Monitoring and understanding the water transparency changes of fifty large lakes on the Yangtze Plain based on long-term MODIS observations

Feng, Lian1,3; Hou, Xuejiao2; Zheng, Yi1,3

2019-02

10.1016/j.rse.2018.12.007

REMOTE SENSING OF ENVIRONMENT   影响因子和分区

0034-4257

1879-0704

Various aspects of the water qualities of the large lakes in the Yangtze Plain (YP) have been studied, while the efforts have been spent on one of the most important parameters-water transparency were only limited to several large lakes. Using in situ remote sensing reflectance and Secchi-disk depth (Z(sd)) datasets, we assessed the performance of a semi-analytical model recently proposed by Lee et al. (2015) for remote sensing of the Z(sd) (Z(sd), (Lee)). The results show that a linear scaling correction over Z(sd), (Lee) (Z(sd)', (Lee)) could lead to improved agreement between remote sensing estimates and field measurements (root mean square error < 35%) in the study region. The Z(sd)'(,) (Lee) scheme was then applied to MODIS/Aqua observations between 2003 and 2016 to obtain the spatial and temporal dynamics of water transparency in 50 large lakes in the YP. The long-term mean Z(sd) of the entire region was 0.39 +/- 1.17 m during the observation period, with high and low values occurring in warm and cold seasons, respectively. Of the 50 examined lakes, half demonstrated decreasing or increasing Z(sd) trends, and the number of lakes exhibiting significantly decreasing trends also comparable to the number exhibiting increasing trends. The relative contributions of the seven potential driving factors (from both human activities and natural processes) to the interannual changes in water clarity were quantified for each lake using a multiple general linear model regression analysis. The responses of Z(sd) to these drivers showed considerable differences among lakes, and human activities demonstrated significant roles in more lakes than those affected by natural variability, accounting for 50% (25/50) and 20% (10/50) of the lakes, respectively. This study provides the first comprehensive basin-scale estimate of the water transparency in the lakes in the YP, and the Z(sd) results and analysis of driving forces can provide important information for local water quality conservation and restoration.

Water clarity Remote sensing Semi-analytical model Yangtze Plain Nutrients MODIS

SCI ; EI

英语

第一 ; 通讯

Southern University of Science and Technology[G01296001]

Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology

Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology

WOS:000456640700050

ELSEVIER SCIENCE INC

20185106259766

Analytical models ; Mean square error ; Nutrients ; Quality control ; Radiometers ; Regression analysis ; Remote sensing ; Transparency ; Water quality

Water Analysis:445.2 ; Light/Optics:741.1 ; Quality Assurance and Control:913.3 ; Mathematics:921 ; Mathematical Statistics:922.2 ; Radiation Measuring Instruments:944.7

GEOSCIENCES

Web of Science

1.Southern Univ Sci & Technol, Sch Environm Sci & Engn, State Environm Protect Key Lab Integrated Surface, Shenzhen, Peoples R China
2.Wuhan Univ, State Key Lab Informat Engn Surveying Mapping & R, Wuhan, Hubei, Peoples R China
3.Southern Univ Sci & Technol, Shenzhen Municipal Engn Lab Environm IoT Technol, Shenzhen, Guangdong, Peoples R China

Feng, Lian,Hou, Xuejiao,Zheng, Yi. Monitoring and understanding the water transparency changes of fifty large lakes on the Yangtze Plain based on long-term MODIS observations[J]. REMOTE SENSING OF ENVIRONMENT,2019,221:675-686.

Feng, Lian,Hou, Xuejiao,&Zheng, Yi.(2019).Monitoring and understanding the water transparency changes of fifty large lakes on the Yangtze Plain based on long-term MODIS observations.REMOTE SENSING OF ENVIRONMENT,221,675-686.

Feng, Lian,et al."Monitoring and understanding the water transparency changes of fifty large lakes on the Yangtze Plain based on long-term MODIS observations".REMOTE SENSING OF ENVIRONMENT 221(2019):675-686.