Urban climate adaptation is generally attained --- in a hydrological perspective -- by implementing stormwater management techniques, such as grey, blue and green adaptation measures. Implementing such multi-functional adaptation measures touches on the interests of many stakeholders who need to work together to find resilient and suiting solutions in urban climate adaptation. To facilitate this cooperation, Deltares developed the Adaptation Support Tool. The AST defines eight different performance indicators to compare the effectiveness of urban runoff reduction measures, among which the runoff volume reduction factor. This factor is defined as the rate at which a specific adaptation measure increases the return time of the extreme runoff event. This factor is determined by the underlying model of the AST, the Urban Water Balance Model (UWBM).
The UWBM has the benefit of using long times series instead of single precipitation events (design storms) as input to determine the effectiveness of measures; antecedent conditions for every extreme event are therefore known. Currently, the UWBM is only determining the runoff volume reduction factor. At the same time, the literature shows the importance of analysing the effectiveness of measures using both flow peak reduction and storage peak reduction. Exploration of the possibility to implement these two reduction factors into the UWBM forms the challenge of this study.
This research aims to define a flow peak- and storage peak reduction factor based on modelling systems in the UWBM using long time series. Because the model describes these factors over the measure area, the second goal of this study is to investigate the possibility of converting this measure factor to a whole project area factor and combining this factor for a combination of measures. Main conclusions of this research are as follows: A flow peak reduction factor can be empirically determined based on the proposed method in this study. A storage peak reduction factor can not be empirically determined based on the proposed method in this study. It is recommended to do more research into the analysis of the storage peaks using time series, since it can give an extra insight into the effectiveness of measures. Converting the found flow peak reduction factor for the measure area to the project area with multiple interventions is substantiated with a proposed equation. However, it is recommended to do more research into the conversion equation to be used in the Adaptation Support Tool. By determining the flow peak reduction factor together with the runoff volume reduction factor, the effectiveness of urban runoff reduction measures in a project area can be quantified and used to compare alternative solutions for their effectiveness in flood risk reduction. The added flow peak reduction factor gives a more thorough insight into this effectiveness of measures.