Mapping of diffuse attenuation coefficient in optically complex waters of amazon floodplain lakes

•A novel study was developed for diffuse attenuation retrieval in Amazon floodplains.•Semi-Analytical Kd algorithm from Lee et al. (2013) performed well for turbid waters.•Uncertainties were lower than 22% for Sentinel-2 images in the visible bands. The modeling of underwater light field is essential for the understanding of biogeochemical processes, such as photosynthesis, carbon fluxes, and sediment transports in inland waters. Water-column light attenuation can be quantified by the diffuse attenuation coefficient of the downwelling irradiance (Kd) using semi-analytical algorithms (SAA). However, the accuracy of these algorithms is currently limited in highly turbid environments, such as Amazon Floodplains, due to the SAA parametrization steps. In this study, we assessed an SAA approach for Kd retrieval using a sizeable (n = 239) and diverse dataset (e.g., Kd (490) ranging from almost 0 to up to 30 m−1 with mean values of 5.75 ± 3.94 m−1) in Amazon freshwater ecosystem. The main framework of this study consists of i) re-parametrization of a quasi-analytical algorithm using regional in-situ inherent optical properties (IOPs) and ii) application and validation of SAA for Kd retrieval using in-situ and Sentinel-2/MSI (n = 49) derived from Remote Sensing Reflectance (Rrs). Overall, the performance of the calibrated SAA was satisfactory for both in-situ and satellite Rrs. The validation results with in-situ data achieved a Mean Absolute Percentage Error (MAPE) lower than 22%, Correlation Coefficient (R) > 0.80, Root Mean Square Error (RMSE) lower than 1.7 m−1, and bias between 0.73 and 1.34 for simulated visible bands of Sentinel-2/MSI (490, 560 and 660 nm) (VIS). The results using MSI imagery were similar to those of in-situ, with R > 0.9, MAPE