Remote Sensing Estimation of CDOM for Songhua River of China: Distributions and Implications

Abstract

Rivers are crucial pathways for transporting organic carbon from land to ocean, playing a vital role in the global carbon cycle. Dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) are major components of dissolved organic matter and have significant impacts on maintaining the stability of river ecosystems and driving the global carbon cycle. In this study, the in situ samples of aCDOM(355) and DOC collected along the main stream of the Songhua River were matched with Sentinel-2 imagery. Multiple linear regression and five machine learning models were used to analyze the data. Among these models, XGBoost demonstrated a superior, highly stable performance on the validation set (R2 = 0.85, RMSE = 0.71 m−1). The multiple linear regression results revealed a strong correlation between CDOM and DOC (R2 = 0.73), indicating that CDOM can be used to indirectly estimate DOC concentrations. Significant seasonal variations in the CDOM distribution in the Songhua River were observed: aCDOM(355) in spring (6.23 m−1) was higher than that in summer (5.3 m−1) and autumn (4.74 m−1). The aCDOM(355) values in major urban areas along the Songhua River were generally higher than those in non-urban areas. Using the predicted DOC values and annual flow data at the sites, the annual DOC flux in Harbin was calculated to be approximately 0.2275 Tg C/Yr. Additionally, the spatial variation in annual CDOM was influenced by both natural changes in the watershed and human activities. These findings are pivotal for a deeper understanding of the role of river systems in the global carbon cycle.