Estimation of Dissolved Organic Carbon Using Sentinel-2 in the Eutrophic Lake Ebinur, China

Author:

Cao Naixin1,Lin Xingwen2ORCID,Liu Changjiang3,Tan Mou Leong4ORCID,Shi Jingchao5,Jim Chi-Yung6ORCID,Hu Guanghui2,Ma Xu1ORCID,Zhang Fei2ORCID

Affiliation:

1. College of Geography and Remote Sensing Sciences, Xinjiang University, Urumqi 830046, China

2. College of Geography and Environmental Sciences, Zhejiang Normal University, Jinhua 321004, China

3. College of Geographic Science and Tourism, Xinjiang Normal University, Urumqi 830054, China

4. GeoInformatic Unit, Geography Section, School of Humanities, Universiti Sains Malaysia, Penang 11800, Malaysia

5. Departments of Earth Sciences, The University of Memphis, Memphis, TN 38152, USA

6. Department of Social Sciences and Policy Studies, Education University of Hong Kong, Lo Ping Road, Tai Po, Hong Kong, China

Abstract

Dissolved organic carbon (DOC) in lakes, as a regulatory agent and light-absorbing compound, is a key component of the global carbon cycling in lacustrine ecosystems. Hence, continuous monitoring of the DOC concentration in arid regions is extremely important. This study utilizes the QAA-CDOM semi-analytical model, which has good accuracy in retrieving the CDOM (colored dissolved organic matter) concentration of Lake Ebinur. We chose to invert the CDOM time-series data from May to October during the 2018–2022 period. A DOC estimation model was then established using the linear regression approach based on the CDOM inversion data and the field DOC measurements. In general, the DOC concentration in Lake Ebinur exhibited an increasing trend from 2018 to 2022, typically lower in May and higher in June. When comparing the average values of DOC in Lake Ebinur for the same months across different years, it can be observed that the month of September exhibits the greatest variability, whereas June shows the least variability. In sum, this study successfully retrieved CDOM concentrations for a saline lake within an arid region and developed a DOC estimation model, thereby providing a reference for investigating carbon cycling in typical lakes of arid areas.

Funder

National Natural Science Foundation of China

Key Laboratory of Lake Science and Environment

Tianshan Talent Project (Phase III) of the Xinjiang Uygur Autonomous Region

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

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