Dynamics of euphotic zone depth in the Bohai Sea and Yellow Sea

Shengqiang Wang; Jun Lv; Junwei Nie; Deyong Sun; Hanwei Liang; Zhongfeng Qiu; Wei Yang

doi:10.1016/j.scitotenv.2020.142270

Dynamics of euphotic zone depth in the Bohai Sea and Yellow Sea

Sci Total Environ. 2021 Jan 10:751:142270. doi: 10.1016/j.scitotenv.2020.142270. Epub 2020 Sep 9.

Authors

Shengqiang Wang¹, Jun Lv¹, Junwei Nie¹, Deyong Sun², Hanwei Liang³, Zhongfeng Qiu¹, Wei Yang⁴

Affiliations

¹ School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China.
² School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China. Electronic address: sundeyong@nuist.edu.cn.
³ Key Laboratory of Coastal Zone Exploitation and Protection, Ministry of Natural Resources, China; School of Geographic Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China.
⁴ Center for Environmental Remote Sensing, Chiba University, Chiba 263-8522, Japan.

PMID: 33182001
DOI: 10.1016/j.scitotenv.2020.142270

Abstract

Euphotic zone depth (Z_eu) plays an important role in studies of marine biogeochemical processes and ecosystems. Remote sensing techniques are ideal tools to investigate Z_eu distributions because of their advanced observation ability with broad spatial coverage and frequent observation intervals. This study aims to develop a new approach that derives Z_eu directly from remote sensing reflectance (R_rs(λ)) values rather than by using other intermediate variables and then reveals the dynamic characteristics of Z_eu in the Bohai Sea (BS) and Yellow Sea (YS). To do this, in situ data collected from various seasons were first used to assess the ability of several spectral indicators of R_rs(λ) for deriving Z_eu and the optimal spectral indicator was determined to build a Z_eu retrieval model. This model was further applied to Geostationary Ocean Color Imager (GOCI) data to study the spatial and temporal variations in Z_eu. The results showed that the new Z_eu retrieval model performed well with R², RMSE and MAPE values of 0.843, 4.42 m and 17.9%, respectively. High Z_eu levels were generally observed during summer for both coastal and offshore waters while the lowest Z_eu values were observed during winter. Changing concentrations of total suspended matter, which are often modulated by sediment resuspension and transportation, are probably the main factor responsible for the spatial and temporal variability of Z_eu. These findings provide crucial information for modeling primary production, carbon flux, and heat transfer, etc., in the BS and YS, as well as contribute a useful alternative approach that will be easily implemented to study Z_eu from satellite data for other water environments.

Keywords: Driving factor; GOCI satellite data; Retrieval algorithm; Spatiotemporal variations; Spectral indicator.