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A fast simplified model for predicting river flood inundation probabilities in poorly gauged areas
Author(s) -
Massari Christian,
Tarpanelli Angelica,
Moramarco Tommaso
Publication year - 2014
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.10367
Subject(s) - floodplain , flood myth , channel (broadcasting) , digital elevation model , hydrology (agriculture) , environmental science , elevation (ballistics) , sensitivity (control systems) , flow (mathematics) , geology , computer science , statistics , remote sensing , mathematics , geometry , geography , cartography , geotechnical engineering , engineering , computer network , archaeology , electronic engineering
Abstract The capability of a simple kinematic‐storage model (KSM) is analysed to be used as a tool for a Decision Support System for the evaluation of probability inundation maps in near real time in poorly gauged areas. KSM simulates the floodplain as a storage and assumes no exchange of momentum with the channel. For the in‐bank flow, the storage is modified through a coefficient for taking the variations of channel cross sections into account. The generalized likelihood uncertainty estimation approach is used for addressing the probability flood maps along with their associated uncertainties. The model is tested on two river reaches along the Tiber River in Central Italy where observed inundation maps are available for two recent flood events. Despite the inherent uncertainties present in the input data and in the model structure, the results show that the model reproduces reasonably well, in terms of both precision and accuracy, the observed inundated areas. Tests were performed at different digital elevation model resolutions, showing a small effect of the geometry on the maximum performance obtained. The very low computational times, the parsimony of the model and its low sensitivity to the quality of the geometry representation of the channel and the floodplain makes KSM very appealing for flood forecasting and early warning system applications in poorly gauged and inaccessible areas. Copyright © 2014 John Wiley & Sons, Ltd.

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