Satellite-based flood mapping of coastal floods: The Senegal River estuary study case

Abstract

This study employs an integrated approach, combining remote sensing and numerical modelling techniques, to characterize flood-prone regions resulting from the combined effects of extreme river water elevations and long-term sea-level rise in the Senegal River Estuary. Four different case scenarios of hydrodynamic conditions have been investigated to provide a quantitative assessment of flooding. Simultaneously, a Land Type classification using machine learning techniques has been conducted. Subsequently, the resulting land type map has been integrated with flood mapping simulations obtaining the different land types impacted by flood dynamics. The analysis shows that the buildings classification is the most impacted followed by vegetation and roads. This study highlights the flood-affected areas at a district level, offering relevant understanding for the development of effective adaptation strategies, disaster planning, adjusting policies with scientific knowledge, and supporting adaptive governance in the Senegal River Estuary.