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

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.

A two-stage storage routing model for green roof runoff detention.

Green roofs have been adopted in urban drainage systems to control the total quantity and volumetric flow rate of runoff. Modern green roof designs are multi-layered, their main components being vegetation, substrate and, in almost all cases, a separate drainage layer. Most current hydrological models of green roofs combine the modelling of the separate layers into a single process; these models have limited predictive capability for roofs not sharing the same design. An adaptable, generic, two-stage model for a system consisting of a granular substrate over a hard plastic 'egg box'-style drainage layer and fibrous protection mat is presented. The substrate and drainage layer/protection mat are modelled separately by previously verified sub-models. Controlled storm events are applied to a green roof system in a rainfall simulator. The time-series modelled runoff is compared to the monitored runoff for each storm event. The modelled runoff profiles are accurate (mean Rt(2) = 0.971), but further characterization of the substrate component is required for the model to be generically applicable to other roof configurations with different substrate.

A generic hydrological model for a green roof drainage layer.

A rainfall simulator of length 5 m and width 1 m was used to supply constant intensity and largely spatially uniform water inflow events to 100 different configurations of commercially available green roof drainage layer and protection mat. The runoff from each inflow event was collected and sampled at one-second intervals. Time-series runoff responses were subsequently produced for each of the tested configurations, using the average response of three repeat tests. Runoff models, based on storage routing (dS/dt = I-Q) and a power-law relationship between storage and runoff (Q = kS(n)), and incorporating a delay parameter, were created. The parameters k, n and delay were optimized to best fit each of the runoff responses individually. The range and pattern of optimized parameter values was analysed with respect to roof and event configuration. An analysis was performed to determine the sensitivity of the shape of the runoff profile to changes in parameter values. There appears to be potential to consolidate values of n by roof slope and drainage component material.

Experimental analysis of green roof substrate detention characteristics.

Green roofs may make an important contribution to urban stormwater management. Rainfall-runoff models are required to evaluate green roof responses to specific rainfall inputs. The roof's hydrological response is a function of its configuration, with the substrate - or growing media - providing both retention and detention of rainfall. The objective of the research described here is to quantify the detention effects due to green roof substrates, and to propose a suitable hydrological modelling approach. Laboratory results from experimental detention tests on green roof substrates are presented. It is shown that detention increases with substrate depth and as a result of increasing substrate organic content. Model structures based on reservoir routing are evaluated, and it is found that a one-parameter reservoir routing model coupled with a parameter that describes the delay to start of runoff best fits the observed data. Preliminary findings support the hypothesis that the reservoir routing parameter values can be defined from the substrate's physical characteristics.