Eutrophication monitoring of lakes in Wuhan based on Sentinel-2 data

Abstract

Eutrophication is the leading cause of freshwater impairment. Of China’s major cities, Wuhan has the largest coverage of the lake area, while lake eutrophication is increasing. Thus, the objective of this study was to monitor and assess lake eutrophication in Wuhan. For this purpose, the lake eutrophication was quantified using the Trophic Level Index (TLI). The TLI was modeled by building a radial basis function neural network (RBFNN) model with a set of indices derived from Sentinel-2 Multispectral Instrument (MSI) imagery and a parameter of lake environmental characteristics. Applied MSI indices are the Maximum Chlorophyll Index (MCI) and the spectral band ratio of b5/b4 and b3/b4. In addition, the applied lake environmental parameter is the chlorophyll-a dependent month. Based on 54 MSI images from April 2018 to March 2020, the lake eutrophication was successfully determined. The main findings are as follows: 1) The higher percentage of eutrophic area was registered in the autumn (from September to November) and the highest was registered on September 12th, 2019; 2) Compared to the same period in 2018, the eutrophic area in the autumn of 2019 was significantly higher. In the autumn of 2018, from 74.94% to 86.38% of the lakes were eutrophic, while from 83.54% to 93.24% of the lakes were eutrophic in the autumn of 2019; 3) The TLI values were between 30 and 70 for the majority of lakes in Wuhan, suggesting that most lakes were mesotrophic, light eutrophic, or medium eutrophic, with few oligotrophic and heavy eutrophic lakes. Most oligotrophic and mesotrophic lakes were located in northern Wuhan, while eutrophic lakes were located in central and southern Wuhan. Our result indicates that the developed algorithm from this study could be applied for rapid and effective monitoring of eutrophication in lakes.

Keywords

• water quality
• eutrophication
• tli
• lakes in wuhan
• sentinel-2
• radial basis function neural network (rbfnn)