In recent years, numerous flood events have caused loss of life, widespread disruption, and damage across the globe. These devastating impacts highlight the importance of a better understanding of flood generating processes, their impacts, and their variability under climate and landscape changes. Here, we argue that the ability to better model flooding is underpinned by the grand challenge of understanding flood generation mechanisms and potential impacts. To address this challenge, the World Meteorological Organization-Global Energy and Water Exchanges (GEWEX) Hydrometeorology Panel (GHP) aims to establish a Global Flood Crosscutting project to propagate flood modeling and research knowledge across regions and to synthesize results at the global scale. This paper outlines a framework for understanding the dynamics and impacts of runoff generation processes and a rationale for the role of a Global Flood Crosscutting project to address these challenges. Within this Global Flood Crosscutting project, we will establish a common terminology and methods to enable the global research community to exchange knowledge and experiences, and to design experiments toward developing actionable recommendations for more effective flood management practices and policies for improved resilience. This harmonization of rich perspectives across disciplines will foster the co-production of knowledge primed to advance flood research, particularly in the current period of heightened climate variability and rapid change. It will create a new transdisciplinary paradigm for flood science, wherein different dimensions of mechanistic understanding and processes are rigorously considered alongside socioeconomic impacts, early warning communications, and longer-term adaptation to alleviate flood risks in society.

Interactions between spatial and temporal variability of rainfall and catchment characteristics strongly influence hydrological response. In urban areas, where runoff generation is fast due to high imperviousness degree, it is especially relevant to capture the high spatiotemporal rainfall variability. Significant progress has been made in the development of spatially distributed rainfall measurements and of distributed hydrological models, to represent the variability of catchment's characteristics. Interactions between rainfall and basin scales on hydrological response sensitivity, however, needs deeper investigation. A previous study investigated the hydrological response in the small urbanized catchment of Cranbrook (8 km ² , London, UK) and proposed three dimensionless “scale factors” to identify if the available rainfall resolution is sufficient to properly predict hydrological response. We aim to verify the applicability of these scale factors to larger scales, with a distinct physiographic setting, in Little Sugar Creek (111 km ² , Charlotte, USA), to identify the required rainfall resolution and to predict model performance. Twenty-eight events were selected from a weather radar data set from the National Weather Radar Network, with a resolution of 1 km ² and 15 min. Rainfall data were aggregated to coarser resolutions and used as input for a distributed hydrological model. Results show that scale factors and associated thresholds are generally applicable for characterization of urban flood response to rainfall across spatiotemporal scales. Additionally, application of scale factors in observation-based analysis supports identification of event characteristics that are poorly captured and critical improvements that need to be made before the model can benefit from high-resolution rainfall.

Rainfall spatial and temporal variability are key points in the prediction of hydrological response. At the same time, catchment scale and characteristics also play important roles, especially in urban areas, where the high level of imperviousness combined with intense and localised rainfall causes fast responses (Ochoa-Rodriguez et al., 2015). New instruments such as weather radars have been developed in recent decades able to better capture the spatial and temporal variability of storm events. At the same time, large improvements have been made to create high-resolution hydrological models that are able to represent the catchment with a high level of detail. However, the interactions between rainfall and catchment variability and their effects on the hydrological response remains poorly understood. In this work, we aim to evaluate the critical space and time scales that characterize rainfall variability and catchment characteristics in relation to hydrological response in urban areas. Critical scales based on dimensionless parameters developed in a previous work (Cristiano et al, 2018) will be evaluated for two urban areas in different climatological regions, one in Europe and one in the US.