A dataset of water transparency of Sanya River based on Sentinel-2 data during 2019–2021

Abstract

As one of the most important water quality parameters on the radar screen of environmental protection sectors, water transparency reveals the turbidity degree of water and plays an important role in the primary productivity of water body and water ecosystem. As an independent island water system, Hainan Province has abundant surface inland water resources and plentiful river runoff. However, due to the influence of dry and wet monsoons and topography, the aquatic systems are characterized by uneven spatial and temporal distribution, and there are few studies on the water quality of inland water bodies on Hainan Island. In this study, we took Sanya River in Sanya, Hainan Province as the study area, and used the QAAv6-based semi-analytic model to retrieve the water transparency of Sanya River in time series from 2019 to 2021 based on the GEE cloud computing platform and the massive Sentinel-2 surface reflectance data stored in Google Cloud. With regard to the extraction of dynamic water area from Sanya River, we adopted the algorithm combining the normalized water body index NDWI with OTUS automatic threshold segmentation to extract the small river water. The data are stored in GeoTiff raster format, and the pixel transparency value and coordinate information are stored at the same time for easy reading and analysis by relevant GIS software. The inversion of long time series transparency based on the GEE cloud database is highly efficient. The dataset can serve as valuable scientific evidence for the water quality monitoring, water pollution control, and aquatic ecological protection of Sanya River.