Urban floods cannot be managed in isolation at the city scale and responses to potential flood impacts are complicated by interlinked political, socio‐economic and environmental changes. To understand the unique features of urban flood management, a framework should be developed in which spatio‐temporal relations are further defined and investigated. This should provide clarity regarding both the feedback loops that cause vulnerability as well as those that build resilience, and how they interact across differing spatial scales. Various insights and methods from system and complexity theory could provide hands‐on methods to create such a framework. Yet the transition towards system‐based approaches is still surrounded by many unknown factors; more effort should be put into developing a roadmap towards this transition. It is argued that local‐scale pioneering and experimentation are essential in this process to encourage the cultivation of resilience through bottom‐up initiatives that can shape strategy and policy development.

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In this paper, a set of GIS-based tools is presented that combines information from hydraulic modelling results, spatially varied object attributes and damage functions to assess flood damage. They can directly process the outputs of hydraulic modelling packages to calculate the direct tangible damage, the risk to life, and the health impact of individual flood events. The tools also combine information from multiple events to calculate the expected annual damage. The land cover classes from urban growth models can be also used in the tools to assess flood damage under future conditions. This paper describes the algorithms implemented, and the results of their application in the mega city of Dhaka in Bangladesh. Complications and technical issues in real-world applications are discussed, and their solutions are also presented. Although it is difficult to obtain reliable 123Nat Hazards (2016) 82:857-890 DOI 10.1007/s11069-016-2223 data for model validation, the sensitivity of the results to spatial resolution and input parameters is investigated to demonstrate that the tools can provide robust estimations even with coarse data resolution, when a fine masking cell size is used. The tools were designed to be flexible, so that they can also be used to evaluate different hazard impacts, and adopted in various GIS platforms easily.

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Climate change increases uncertainty regarding the frequency and severity of flood events, posing new challenges for urban areas often located along major rivers. Current flood damage assessment methods often ignore the level of differentiation found in the urban fabric; their level of detail is too coarse and limits possibilities of tailor‐made solutions based on refined insights on the severity, distribution and horizon of expected impacts. As part of the Urban Flood Management project for the city of Dordrecht, the Netherlands, a flood damage assessment model was developed using a substantially higher level of detail than used in current practice. The model incorporates methods of analysis linking the spatial distribution of flood damages, flood damage composition, age of the building stock and a range of other attributes to gain a comprehensive view on the financial consequences of urban flooding. The output provides a foundation for integration of flood proofing schemes into urban development and/or redevelopment.