TITLE:
Hydrological Variability in the Yaéré Floodplain (1984-2024): A Landsat-Based Remote Sensing Study of Surface Water Dynamics under Climate Change
AUTHORS:
Steven Chouto, Elisabeth Fita Dassou, Sylvain Aoudou Doua, Bernard Gonne, Nathalie Annavaï, Thierry C. Fotso-Nguemo, Bruno Kolaouna-Labara
KEYWORDS:
Remote Sensing, Surface Water Dynamics, Flooding, Climate Variability, Yaéré
JOURNAL NAME:
Advances in Remote Sensing,
Vol.14 No.3,
September
25,
2025
ABSTRACT: The Yaéré floodplain, located in the Logone watershed south of Lake Chad, is highly vulnerable to recurrent flooding that threatens local populations and the regional economy. This study quantifies the floodplain’s hydrological dynamics over a 40-year period (1984-2024) by analysing 683 cloud-free Landsat images to map surface water changes. The results reveal substantial hydrological variability, with flooded areas ranging from complete absence (0 km2) to a record maximum of 17,559 km2 in October 2022, and an average flooded extent of approximately 1630 km2. Flooding exhibits a pronounced seasonal pattern, peaking mainly in September and October, corresponding to key rainfall periods and river inflows critical for ecosystem functioning. Strong interannual variability is evident, contrasting exceptionally wet years such as 1999, 2022, and 2024 with notably dry periods including 1984, 1987, and 2007. Since 2019, a discernible increase in extreme flood events suggests intensifying precipitation trends consistent with regional climate change. Anthropogenic factors also shape the flood regime, notably the Maga dam and associated dykes constructed in the 1970s, which have modified natural inundation patterns and downstream hydrology. Diachronic mapping of flooded zones provides an essential tool for identifying areas of significant hydrological change, supporting targeted ecological restoration and risk management efforts. These findings offer critical insights for adaptive management of this vulnerable wetland in a changing climate. Integrating this remote sensing data into local and regional policy frameworks can enhance flood forecasting and early warning systems, improving community resilience to extreme hydrological events. Ultimately, this study contributes to the sustainable management of water resources and flood risk reduction in the Lake Chad basin, fostering more effective responses to future climatic uncertainties.