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. Supplementary Information: The online version contains supplementary material available at 10.1007/s10113-022-01943-x.
ABSTRACT
While climate science has made great progress in the projection of weather and climate information, its uptake by local communities remains largely elusive. This paper describes two innovative approaches that strengthen understanding between the providers and users of weather and climate information and support-appropriate application: (1) knowledge timelines, which compare different sources and levels of certainty in community and scientific weather and climate information; and (2) participatory downscaling, which supports users to translate national and regional information into a range of outcomes at the local level. Results from piloting these approaches among flood-prone communities in Senegal and drought-prone farmers in Kenya highlight the importance of co-producing 'user-useful' climate information. Recognising that disaster risk management actions draw on a wide range of knowledge sources, climate information that can effectively support community-based decision-making needs to be integrated with local knowledge systems and based on an appreciation of the inherent uncertainty of weather and climate information.
