Chromophoric dissolved organic matter (DOM) is called as CDOM which could affect the optical properties of surface waters, and is a useful parameter for monitoring complex inland aquatic systems. Large-scale monitoring of CDOM using remote-sensing has been a challenge due to the poor transferability of CDOM retrieval models across regions. To overcome these difficulties, a study is conducted using Sentinel-2 images, in situ reflectance spectral data, and water chemical parameters at 93 water reservoirs across China classified by trophic state. Empirical algorithms are established between CDOM absorption coefficient aCDOM(355) and reflectance band ratio (B5/B2,vegetation Red Edge/Blue) acquired in situ and via Sentinel-2 MSI sensors. Relationships are stronger (r2 0.7, p < 0.05) when analysis is conducted separately by trophic states. Validation models show that, by accounting for trophic state of reservoirs and using B5/B2 band ratios, it is possible to expand the geographical range of remote sensing-based models to determine CDOM. However, the accuracy of model validation decreased from oligotrophic (r2: 0.86) to eutrophic reservoirs (r2: 0.82), likely due to increased complexity of CDOM sources in nutrient-rich systems. This study provides a strategy for using local and remotesensing data to monitor the spatial variations of CDOM in reservoirs based on different trophic states, and will contribute to water resources management.

Chromophoric dissolved organic matter (DOM) is called as CDOM which could affect the optical properties of surface waters, and is a useful parameter for monitoring complex inland aquatic systems. Large-scale monitoring of CDOM using remote-sensing has been a challenge due to the poor transferability of CDOM retrieval models across regions. To overcome these difficulties, a study is conducted using Sentinel-2 images, in situ reflectance spectral data, and water chemical parameters at 93 water reservoirs across China classified by trophic state. Empirical algorithms are established between CDOM absorption coefficient aCDOM(355) and reflectance band ratio (B5/B2,vegetation Red Edge/Blue) acquired in situ and via Sentinel-2 MSI sensors. Relationships are stronger (r2 0.7, p < 0.05) when analysis is conducted separately by trophic states. Validation models show that, by accounting for trophic state of reservoirs and using B5/B2 band ratios, it is possible to expand the geographical range of remote sensing-based models to determine CDOM. However, the accuracy of model validation decreased from oligotrophic (r2: 0.86) to eutrophic reservoirs (r2: 0.82), likely due to increased complexity of CDOM sources in nutrient-rich systems. This study provides a strategy for using local and remotesensing data to monitor the spatial variations of CDOM in reservoirs based on different trophic states, and will contribute to water resources management.