About this Research Topic
Urban flooding induced by cloudburst has caused widespread disruption and damage worldwide. This is most likely to increase in severity and frequency owing to continuing urbanization and economic growth in the context of climate change.
Although often associated with shallow water depths compared with fluvial and coastal flooding, the impact of urban surface water floods can be equally far-reaching and widespread. In cities, concentration of population, key infrastructure and businesses make flood impact particularly severe, including both direct damage and indirect consequences such as loss of productivity and business opportunities.
The dynamics of cloudburst-induced urban flooding and the way it interacts with urban infrastructures greatly challenge conventional approaches both to short-term forecasting for emergency response and long-term planning for climate adaptation. This brings into sharp focus the imminent risk imposed by urban flooding and the need for improved approached for the prediction of, management of, and adaptation to potential risks.
However, there are still challenges and knowledge gaps in understanding and predicting rainfall-induced urban flood processes for preparedness and adaptation, including observation and modelling. First, there is a significant lack of high-quality observational data during an event to inform model development and understanding of surface water flooding. Gauge records in urban areas yield data of limited tempo-spatial resolution, therefore their practical value for verifying model outputs and understanding of surface water flooding is poor. The other challenge is how to appropriately represent urban surface water dynamics processes in a numerical model to balance the two indicators of computational accuracy and efficiency. It has been recognized that hydraulic models to predict urban flood impacts have fundamental limitations and is an urgent need to develop new advanced modelling tools to balance the two indications.
In this focused Research Topic, we welcome paper submissions that showcase research advance in terms of urban flood monitoring, development of advanced urban surface water flood models (e.g. shallow-water based models, paralleled algorithms), as well as their application. Particular topics of interest include:
- Novel urban flood model development;
- Robust algorithms and paralleled approaches for increasing computational accuracy and efficiency;
- Demonstration of data acquisition approaches in real-world events (e.g. remote sensing, wireless sensor network, AI, social media or citizen science etc.);
- Urban flood model calibration and validation with the support of data acquisition approaches; and
- Physical complexity to reliable model rainfall-induced urban flooding.
Although often associated with shallow water depths compared with fluvial and coastal flooding, the impact of urban surface water floods can be equally far-reaching and widespread. In cities, concentration of population, key infrastructure and businesses make flood impact particularly severe, including both direct damage and indirect consequences such as loss of productivity and business opportunities.
The dynamics of cloudburst-induced urban flooding and the way it interacts with urban infrastructures greatly challenge conventional approaches both to short-term forecasting for emergency response and long-term planning for climate adaptation. This brings into sharp focus the imminent risk imposed by urban flooding and the need for improved approached for the prediction of, management of, and adaptation to potential risks.
However, there are still challenges and knowledge gaps in understanding and predicting rainfall-induced urban flood processes for preparedness and adaptation, including observation and modelling. First, there is a significant lack of high-quality observational data during an event to inform model development and understanding of surface water flooding. Gauge records in urban areas yield data of limited tempo-spatial resolution, therefore their practical value for verifying model outputs and understanding of surface water flooding is poor. The other challenge is how to appropriately represent urban surface water dynamics processes in a numerical model to balance the two indicators of computational accuracy and efficiency. It has been recognized that hydraulic models to predict urban flood impacts have fundamental limitations and is an urgent need to develop new advanced modelling tools to balance the two indications.
In this focused Research Topic, we welcome paper submissions that showcase research advance in terms of urban flood monitoring, development of advanced urban surface water flood models (e.g. shallow-water based models, paralleled algorithms), as well as their application. Particular topics of interest include:
- Novel urban flood model development;
- Robust algorithms and paralleled approaches for increasing computational accuracy and efficiency;
- Demonstration of data acquisition approaches in real-world events (e.g. remote sensing, wireless sensor network, AI, social media or citizen science etc.);
- Urban flood model calibration and validation with the support of data acquisition approaches; and
- Physical complexity to reliable model rainfall-induced urban flooding.
Keywords: Urban flood, Hydrodynamic modelling, Data-driven, Flood monitoring, Urban hydrology and hydraulics
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
