The Use of Landsat 8 and Sentinel-2 Time Series Data for Monitoring Drought, Chlorophyll-a and Turbidity in Lake Chad

A decline in Lake Chad’s water level has been observed for over two decades. With millions of people relying on the lake, and considering its dynamic behavior, methods for the continuous and spatially distributed retrieval of water quantity and quality parameters are vital for proper monitoring and management initiatives. Here, we propose an integrated approach for drought, chlorophyll-a (Chl-a) and turbidity monitoring in Lake Chad using satellite datasets.

First, we used remote sensing information to constrain drought patterns over the immediate lake environment. Vegetation conditions within and around the lake was used to assess drought conditions in this area. Using Landsat multispectral images obtained between 1999 and 2018, Vegetation Temperature Condition Index (VTCI) was derived and used as an indicator for drought monitoring. Vegetation proportion from WorldView-03 images was used to evaluate the accuracy of methods used to derive VTCI. Obtained results showed that most areas experienced mild drought conditions.

Secondly, we assessed the performance of band algorithms in estimating Chl-a concentrations and turbidity levels from Landsat-8 and Sentinel-2A and 2B images. A two-band semi-analytical Chl-a and turbidity retrieval model was used for estimating the Chl-a concentrations and turbidity levels between 2015 and 2019. Due to the absence of in-situ data, estimates from the extraction models were statistically compared with datasets obtained from WorldView-03. Further inter-comparison of Chl-a and turbidity retrieved from the two sensors was carried out.

This study shows how satellite observations can be used to complement sparse and declining in situ drought, Chl-a and turbidity monitoring networks in this area. Solidifying the importance of remote sensing in areas that are difficult to access or with poor availability of conventional data sources.