Surface water and flood-based agricultural systems: Mapping and modelling long-term variability in the Senegal river floodplain - Andrew Ogilvie; Cheickh Sadibou Fall; Ansoumana Bodian; Didier Martin; Laurent Bruckmann; Djiby Dia; Issa Leye; Papa Malick Ndiaye; Donissongou Dimitri Soro; Jean Homian Danumah; Jean-Claude Bader; Jean-Christophe Poussin (Agricultural Water Management)
In the alluvial plains of large rivers, annual flooding is essential for numerous ecosystem services, including flood-based agriculture, biodiversity and groundwater recharge. Remote sensing provides increased opportunities to monitor surface water dynamics across large floodplains that are currently poorly captured by local hydrological monitoring and modelling due to data scarcity and the flat, heterogeneous topography. Combining the advances in earth observations with hydrological modelling and extensive in situ fieldwork, this research seeks to improve our understanding of surface water dynamics and associated agricultural practices in the Senegal river floodplain. 2813 mosaics from Landsat, MODIS and Sentinel-2 earth observations are created to map and monitor surface water variations using a site specific MNDWI classification adapted to complex, wetland environments. Validated against ground truth data, the approach is upscaled using cloud computing across this 2250 km2 floodplain over 1999–2022. Statistical regression models are then developed to estimate flooded and cultivated areas based on upstream flow values since 1950 and analyse trends and exceedance probabilities over time. Results reveal extreme interannual variations in peak flooded areas, ranging from 30,000 ha and 720,000 ha between 1950 and 2022, while annual water modules fluctuate between 210 and 1460 m3/s. After 1994, flooded areas show partial recovery, with 95th percentile reaching 89,000 ha during 1994–2022 compared to 37,000 ha in 1972–1993. Flood-based agricultural practices cover between 13,000 ha and 133,000 ha over the same period, highlighting the pronounced variability faced by local rural communities. Occurrence maps and predictive models for annual flooded and cultivated areas based on upstream flows can support early warning tools, helping to prepare for extreme floods and droughts. These outputs are crucial to assess the impact of future climatic and anthropic changes in the region, including planned dams, on the amplitude of annual floods and their associated environmental benefits.