Abstract
Recent years have witnessed considerable developments in multiple fields with the potential to enhance our capability of forecasting pluvial flash floods, one of the most costly environmental hazards in terms of both property damage and loss of life. This work provides a summary and description of recent advances related to insights on atmospheric conditions that precede extreme rainfall events, to the development of monitoring systems of relevant hydrometeorological parameters, and to the operational adoption of weather and hydrological models towards the prediction of flash floods. With the exponential increase of available data and computational power, most of the efforts are being directed towards the improvement of multi-source data blending and assimilation techniques, as well as assembling approaches for uncertainty estimation. For urban environments, in which the need for high-resolution simulations demands computationally expensive systems, query-based approaches have been explored for the timely retrieval of pre-simulated flood inundation forecasts. Within the concept of the Internet of Things, the extensive deployment of low-cost sensors opens opportunities from the perspective of denser monitoring capabilities. However, different environmental conditions and uneven distribution of data and resources usually leads to the adoption of site-specific solutions for flash flood forecasting in the context of early warning systems.
Highlights
IntroductionFlash floods (FFs) are among the most damaging types of weather-related disasters faced nowadays
Flash floods (FFs) are among the most damaging types of weather-related disasters faced nowadays.They may be caused either by extreme precipitation, by the failure of human-made structures, such as dams, or by complex water-snow interactions
The flash flood guidance (FFG) is probably the most prominent framework of this approach. It was adopted by river forecast centers in the United States’ (US) in the 1970s and has been recently implemented operationally in different countries [6]. It is based on the recurrent estimation of the total raw precipitation needed to occur during specific time intervals to cause flood scenarios, and the rainfall-runoff transformation is usually performed by a continuous hydrological model, be it spatially lumped flash flood guidance (LFFG) or gridded flash flood guidance (GFFG) [29,30]
Summary
Flash floods (FFs) are among the most damaging types of weather-related disasters faced nowadays. As cyclones are usually associated with synoptic-scale patterns and have their specific and extensive research field, they are not explicitly discussed in this work From this perspective, FF forecasting is highly related to the challenging meteorological problem of predicting extreme local rainfall events [9]. When both boundary definitions are acceptable, the expressions “zone” or “environment” are interchangeably used As this type of hazard is mainly characterized by occurring with short development time and on small catchments, advances towards: (1) increase in the spatiotemporal resolution and precision of input and output data, (2) increase of overall lead time and awareness, and (3) reduction of the total computational expenses for the generation of relevant products are assumed to be of interest to the problem and are explored in this work. Differenttypes types flash flood-prone environments include (a) non-urban catchments (b) urban neighborhoods served or (c) not by a central drainage channel, and (d) coastal urban zones. (b) urban neighborhoods served or (c) not by a central drainage channel, and (d) coastal urban zones
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
