Assessing the impact of COVID-19 lockdowns on water quality in Anzali Wetland, Iran, using remote sensing data

Abstract

This study investigates temporal variations of two water quality indices, namely, turbidity and chlorophyll-a (Chl-a), from 2016 to 2021 in the Anzali Wetland. For this purpose, ground-based measurements were collected at four stations from 2016 to 2019, while Sentinel-2/MSI images were utilized to predict Chl-a and turbidity from 2016 to 2021. To validate the forecasted results, remote sensing data for Chl-a and turbidity were compared to measurements. After the validation step, Chl-a and turbidity were predicted using remotely sensed data for the first and fourth peaks of the COVID-19 pandemic, which coincide with the COVID-19 lockdowns in 2020 and 2021 in Iran, respectively. The results indicate 26 and 16% decrease in Chl-a and turbidity, respectively, in the COVID-19 lockdown imposed in 2020, while it yielded to 1% decrease in turbidity and 21% increase in the Chl-a concentration in the COVID-19 lockdown applied in 2021, compared to the corresponding mean values measured from 2016 to 2019. In conclusion, the lockdown imposed in 2020, which turned out to be a much more restricted quarantine than the one applied in 2021, was found to be one of the primary reasons behind improving water quality indices of Anzali Wetland in March and April of 2020.