Quantifying total suspended matter (TSM) in waters using Landsat images during 1984-2018 across the Songnen Plain, Northeast China

Yunxia Du; Kaishan Song; Ge Liu; Zhidan Wen; Chong Fang; Yingxin Shang; Fangrui Zhao; Qiang Wang; Jia Du; Bai Zhang

doi:10.1016/j.jenvman.2020.110334

Quantifying total suspended matter (TSM) in waters using Landsat images during 1984-2018 across the Songnen Plain, Northeast China

J Environ Manage. 2020 May 15:262:110334. doi: 10.1016/j.jenvman.2020.110334. Epub 2020 Mar 6.

Authors

Yunxia Du¹, Kaishan Song², Ge Liu³, Zhidan Wen³, Chong Fang¹, Yingxin Shang¹, Fangrui Zhao³, Qiang Wang³, Jia Du³, Bai Zhang³

Affiliations

¹ Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China; University of Chinese Academy of Sciences, No.19A Yuquan Road, Beijing, 100049, China.
² Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China; School of Environment and Planning, Liaocheng University, Liaocheng, 252000, China. Electronic address: songkaishan@iga.ac.cn.
³ Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, 4888 Shengbei Road, Changchun, Jilin Province, 130102, China.

PMID: 32250811
DOI: 10.1016/j.jenvman.2020.110334

Abstract

Understanding the spatiotemporal dynamics of total suspended matter (TSM) in waters is necessary to promote efficient water resource management. In our study, we have estimated the spatiotemporal pattern of TSM with the combination of time-series Landsat images and field survey. Among various remote sensing-derived parameters, the red/blue band turns to be robust and the most sensitive to the TSM from field measurements. In Songnen Plain, the mean annual TSM in 60.5% of the water bodies decreased from 1984 to 2018. The decreasing of TSM is likely due to the increasing of vegetation in the area. The TSM concentration in waters declined from April to July, and then increased from September onwards. We also found the TSM in water bodies in Songnen Plain has very high spatial variation. Our results indicated that the meteorological factors such as wind and precipitation may affect the variation of TSM. Our results demonstrate that long-term Landsat data are useful to examine TSM in inland waters. Our findings can support for water resource management under human activities and climate change.

Keywords: Inland water; Landsat images; TSM; Water quality parameters.

MeSH terms

China
Climate Change
Environmental Monitoring*
Wind*