LEGOS, Université de Toulouse, IRD, CNES, CNRS, UPS, Toulouse, France.
LEGOS, Université de Toulouse, IRD, CNES, CNRS, UPS, Toulouse, France; Present address Collecte Localisation Satellites SA, Ramonville saint agne, France.
Sci Total Environ. 2023 Jan 20;857(Pt 2):159302. doi: 10.1016/j.scitotenv.2022.159302. Epub 2022 Oct 8.
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 of Lake Chad. We combined remote sensing images with a water level database from the Hydroweb project to determine the response of Lake Chad vegetation cover and surface water variations to rainfall fluctuations in the Lake Chad watershed under recent climate conditions. The variance in lake surface water levels was determined by computing the monthly anomaly time series of surface water height and area from the Hydroweb datasets. The spatiotemporal variability of watershed rainfall and vegetation cover of Lake Chad was highlighted through multivariate statistical analysis. The spatial distribution of correlations between watershed rainfall and Lake Chad vegetation cover was investigated. 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 (mm/day); 4.26 10 (ndvi unit/day); 1.2 10 (km/day) and 6 10 (m/day), respectively. The rainfall variations in the watershed drive those of Lake Chad vegetation cover and surface water, as the rainfall trend was strongly and positively correlated with those of vegetation cover (0.79), surface water height (0.57), and area (0.53). The time lag between the watershed rainfall fluctuations and lake surface water variations corresponded to approximately ∼112 days. Between rainfall variations and vegetation cover changes, the spatial distribution of the time lag showed a response time of <16 days in the western shores of the lake and on both sides of the 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 with the spatiotemporal variances of climate changes. The correlations obtained have strong potential for predicting future changes in lake surface water worldwide.
监测萨赫勒地区环境的演变是一项重大挑战，因为萨赫勒地区的大干旱造成了重大的环境后果和社会影响，例如导致乍得湖干涸。我们结合遥感图像和 Hydroweb 项目的水位数据库，确定了在近期气候条件下，乍得湖流域降雨波动对乍得湖植被覆盖和地表水变化的响应。通过计算 Hydroweb 数据集的地表水高度和面积的月度异常时间序列，确定了湖泊表面水位的变化。通过多元统计分析突出了流域降雨和乍得湖植被覆盖的时空可变性。研究了流域降雨与乍得湖植被覆盖之间的相关性的空间分布。结果表明，流域降雨、植被覆盖和地表水面积和高度均呈增加趋势，其斜率均为正值，分别为 5.1 10（mm/天）；4.26 10（ndvi 单位/天）；1.2 10（km/天）和 6 10（m/天）。流域降雨变化驱动着乍得湖植被覆盖和地表水的变化，因为降雨趋势与植被覆盖（0.79）、地表水高度（0.57）和面积（0.53）呈强烈正相关。流域降雨波动与湖泊表面水位变化之间的时间滞后约为 112 天。在降雨变化和植被覆盖变化之间，时间滞后的空间分布显示，在湖泊西岸和大屏障两侧的响应时间<16 天，在北部盆地的裸地和南部盆地的东部的响应时间约为 16 天，在南部盆地的沼泽地的响应时间>64 天。对于世界各地湖泊的分析，本研究提供了一种强大的方法，可计算其趋势和季节性的时空方差，并将其与气候变化的时空方差相关联。获得的相关性具有很强的潜力，可以预测全球湖泊表面水的未来变化。
