A modelling-chain linking climate science and decision-makers for future urban flood management in West Africa

Abstract

Intensification of the hydrological cycle resulting from climate change in West Africa poses significant risks for the region’s rapidly urbanising cities, but limited research on flood risk has been undertaken at the urban domain scale. Furthermore, conventional climate models are unable to realistically represent the type of intense storms which dominate the West African monsoon. This paper presents a decision-first framing of climate research in co-production of a climate-hydrology-flooding modelling chain, linking scientists working on state-of-the-art regional climate science with decision-makers involved in city planning for future urban flood management in the city of Ouagadougou, Burkina Faso. The realistic convection-permitting model over Africa (CP4A) is applied at the urban scale for the first time and data suggest significant intensification of high-impact weather events and demonstrate the importance of considering the spatio-temporal scales in CP4A. Hydrological modelling and hydraulic modelling indicate increases in peak flows and flood extents in Ouagadougou in response to climate change which will be further exacerbated by future urbanisation. Advances in decision-makers’ capability for using climate information within Ouagadougou were observed, and key recommendations applicable to other regional urban areas are made. This study provides proof of concept that a decision-first modelling-chain provides a methodology for co-producing climate information that can, to some extent, bridge the usability gap between what scientists think is useful and what decision-makers need.

Future precipitation projections for Brazil and tropical South America from a Convection-permitting climate simulation

“…These models provide more detailed information, which is essential for the climate impacts community who, with the aid of downstream models can provide more localised climate advice and relevant information for policy making and managements decisions (e.g. Miller et al, 2022).…”