Estimation of suspended matter concentration in manwan reservoir, lancang river using remotely sensed small satellite constellation for environment and disaster monitoring and forecasting (HJ-1A/1B), charge coupled device (CCD) data

ABSTRACT

The estimation of total suspended matter (TSM) concentration is crucial in monitoring, evaluating, and protecting water quality. Many empirical and semi-analytical models have been established for clear or extremely turbid water bodies; however, only a few are applicable to inland, extremely turbulent deep rivers. Using in situ data from the water of the Manwan reservoir, we developed a robust algorithm to estimate the TSM concentration in the Manwan reservoir, with a root mean square error (RMSE) ≤ 4.43 mg L⁻¹ and a mean absolute percentage error (MAPE) of 23.2%, indicating the feasibility of the empirical model for estimating TSM. The empirical model was then applied to 251 Small Satellite Constellation for Environment and Disaster Monitoring and Forecasting loaded with the Charge Coupled Device (HJ-CCD) images to derive TSM distribution maps from 2009 to 2018. The estimated TSM concentrations exhibited significant spatial and seasonal changes, revealing relationships among TSM, wind speed, and precipitation. The spatial heterogeneity was significantly higher downstream than upstream in the reservoir due to watershed inputs and anthropogenic dredging activity. The temporal heterogeneity of TSM, significantly higher in summer and autumn than in winter and spring, was mainly caused by seasonal rainfall. Our study shows that the empirical model for HJ-CCD images can be used to quantitatively monitor the TSM in inland rivers.

Acknowledgements

The authors would like to thank the China Centre for Resources Satellite Data and Application for providing the HJ-CCD data. This work was supported by the Strategy Priority Research Programme Project of the Chinese Academy of Sciences (Grant No. XDA23040102), National Natural Science Foundation of China (Grant No. 41571361) and Tianjin Intelligent Manufacturing Project (Grant No. Tianjin-IMP-2018-2). The authors declare no conflict of interest.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

If you are interested in our data, please contact [email protected].

Additional information

Funding

This work was supported by the National Natural Science Foundation of China [41571361]; Tianjin Intelligent Manufacturing Project [Tianjin-IMP-2018-2].