Lake Chad vegetation cover and surface water variations in response torainfallfluctuations under recent climate conditions (2000-2020) br

Monitoring the evolution of the Sahelian environment is a major challenge because the great Sahelian droughts,marked by significant environmental consequences and social impacts, contributed, for example, to the drying up ofLake Chad. We combined remote sensing images with a water level database from the Hydroweb project to determinethe response of Lake Chad vegetation cover and surface water variations to rainfallfluctuations in the Lake Chad wa-tershed under recent climate conditions. The variance in lake surface water levels was determined by computing themonthly anomaly time series of surface water height and area from the Hydroweb datasets. The spatiotemporal vari-ability of watershed rainfall and vegetation cover of Lake Chad was highlighted through multivariate statistical anal-ysis. The spatial distribution of correlations between watershed rainfall and Lake Chad vegetation cover wasinvestigated. The results show an increase in watershed rainfall, vegetation cover, and surface water area and height,as their slopes were all positive i.e., 5.1 10-4(mm/day); 4.26 10-6(ndvi unit/day); 1.2 10-3(km2/day) and 6 10-5(m/day), respectively. The rainfall variations in the watershed drive those of Lake Chad vegetation cover and surfacewater, as the rainfall trend was strongly and positively correlated with those of vegetation cover (0.79), surface waterheight (0.57), and area (0.53). The time lag between the watershed rainfallfluctuations and lake surface water varia-tions corresponded to approximately similar to 112 days. Between rainfall variations and vegetation cover changes, the spatialdistribution of the time lag showed a response time of<16 days in the western shores of the lake and on both sides ofthe great barrier, about 16 days in the bare soils of the northern basin and the eastern part of the south basin, and>64 days in the marshlands of the southern basin. For the analysis of lakes around the world, this research provides a robust method that computes the spatiotemporal variances of their trends and seasonality and correlates these withthe spatiotemporal variances of climate changes. The correlations obtained have strong potential for predicting futurechanges in lake surface water worldwide