Publications

Yang, YF; Gao, W; Zhang, Y (2025). Retrieval of Dissolved Organic Carbon Storage in Plateau Lakes Based on Remote Sensing and Analysis of Driving Factors: A Case Study of Lake Dianchi. REMOTE SENSING, 17(10), 1791.

Abstract
Dissolved organic carbon (DOC) is an essential form of carbon in lakes and has significant impact on thermal structure and carbon source-supporting food webs. Current remote sensing studies on DOC mainly focus on the retrieval of surface concentration of lakes, with limited understanding of three-dimensional carbon storage. This study proposes a novel vertical retrieval methodology for plateau lakes by integrating remote sensing and vertical profile analysis. Specifically, a Gaussian function-based vertical fitting model was developed to characterize DOC concentration distribution along water columns, where parameters (mu and sigma) were calibrated against surface DOC concentrations retrieved from MODIS reflectance. A result-oriented storage algorithm was established by linking surface DOC concentration to DOC storage through linear relationships (R-2 > 0.9), with slope and intercept functions optimized as depth-dependent equations. The mixed-layer depth (2 m) was determined through error minimization analysis of 16 vertical profiles. Applied to the eutrophic Lake Dianchi, results show significant vertical DOC variations (CV up to 101.4%) but consistent distribution patterns across profiles. Spatially, higher DOC storage occurred in central regions (80-120 g.m(-2)) with seasonal peaks in summer and autumn. Interannual analysis reveals wind speed and forest coverage as dominant drivers, while monthly variations correlate strongly with water temperature. This methodology advances real-time monitoring of carbon storage in deep plateau lakes, providing critical insights into lacustrine carbon cycling.

DOI:
10.3390/rs17101791

ISSN:
2072-4292