E3S Web Conf.
Volume 7, 20163rd European Conference on Flood Risk Management (FLOODrisk 2016)
|Number of page(s)||6|
|Section||Forecasting and warning|
|Published online||20 October 2016|
Rainfall thresholds derivation for warning pluvial flooding risk in urbanised areas
1 DICAM, University of Palermo, 90128 Viale delle Scienze, Palermo, Italy
2 Dipartimento di Ingegneria, University of Messina, 98166 Contrada Di Dio, Messina, Italy
a Corresponding author: firstname.lastname@example.org
Aim of this work is the development of an operational tool for pluvial flooding warning in an urban area based on off-line rainfall thresholds derived by coupling a rainfall–runoff modelling and a hydraulic routing. The critical conditions considered for issue flood warnings were not only based on the water stage, but also on the extension of the flooded area. Further, a risk assessment framework for quantifying the reliability of the rainfall thresholds has been included; rainfall thresholds used in pluvial flooding warning should be influenced by the uncertainties in the rainfall characteristics (i.e. rainfall duration, depth and storm pattern). This risk assessment framework incorporates the correlated multivariate Monte Carlo simulation method, an hydraulic model for the simulation of rainfall excess propagation over surface urban drainage structures, i.e. streets and pathways. Thresholds rainfall are defined using a number of inundation criteria, to analyze the change in the rainfall threshold due to various definitions of inundation. Starting from estimated water stages and flooded area from inundation simulation rainfall thresholds can be obtained according a specific inundation criterion, including, together, a critical water depth and a critical flooding area. Finally, the second phase concerns the imminence of a possible hydrological risk by comparing the time when cumulative rainfall and rainfall thresholds meet to each other. The developed procedure has been applied to the real case study of Mondello catchment in Palermo (Italy).
© The Authors, published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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