Integrated monitoring of lakes’ turbidity in Wuhan, China during the COVID-19 epidemic using multi-sensor satellite observations
Xianghan Sun, Jianqiang Liu, Wang Jianru, Liqiao Tian, Qu Zhou, Jian Li
Abstract
During the COVID-19 epidemic in Wuhan, China, a series of measures were implemented by the government to prevent the spread of disease, including the lockdown policy and construction of emergency hospitals. To estimate the impact of these measures on aquatic environments, turbidity of lakes in Wuhan was dynamically monitored by integrating multi-sensor satellite observations. Calibrated against field measurements, empirical turbidity models were developed with high accuracy (R2 = 0.77, RMSE = 3.13 NTU). Time series of lake turbidity during COVID-19 were then retrieved, and possible factors for the turbidity change were discussed, including meteorological conditions and human activities. Results demonstrated that (1) the mean turbidity showed a 24.9% decline from 33.4 NTU to 25.1 NTU after the lockdown in Wuhan, which dropped 16.0% compared to that in the previous year. This decline might be related to the sharp reduction in human activities after the lockdown; (2) no obvious turbidity disturbance was observed in the lakes around emergency hospitals during their construction, and the lakes remained stable after the operation of hospitals. The method of integrating multi-sensor satellite observations used in this study shows great performance in term of temporal resolution for dynamic monitoring of inland water.