Retrieval of Dissolved Organic Carbon Storage in Plateau Lakes Based on Remote Sensing and Analysis of Driving Factors: A Case Study of Lake Dianchi - Yufeng Yang; Wei Gao; Yuan Zhang (Remote Sensing)
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 (μ and σ) 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 (R2 > 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.