A Method to Improve the Flood Maps Forecasted by On-Line Use of 1D Model

Abstract

Forecasting floods in urban areas during a heavy rainfall is the aim of every early warning system. 2D-models produce the most accurate flood maps, but they are practically useless as quasi real-time tools, because their run times are comparable to times of propagation of floods. Run times of 1D-model are of tens of seconds, but their predictions lack accuracy and many useful indicators of flood severity. Our aim is the identification of the 2D-model map that is more similar to the actual map, chosen among those simulated off-line. To this aim, we produce a rough flood map of the occurring event, through a quasi real-time simulation of the rainfall-runoff using a 1D-model. Then we apply an original method, named “ranking approach”, to perform the best matching. This method is applied to the Corace torrent (Calabria, Southern Italy), using 17 synthetic hyetographs to simulate the same number of rainfall-runoff events, using 1D (SWMM) and 2D (MIKE) models. The method proves to be effective in 65% of the cases, while in 82% of cases (i.e., for 14 cases out 17), the event produced by the same ietograph falls within the third rank.

An Evaluation Matrix to Compare Computer Hydrological Models for Flood Predictions

“…It is worth noticing that the computation effort is not a strict requisite according to the stakeholders' opinion (score = 3.2), in particular for the public administration officials (score of 2.8) and freelancers (3.0). This may be quite surprising, since, when the flood maps are required as model predictions, the computation times of 2D models (such as the models of the MIKE-family and WEC-FLOOD) can be high and this may be a limitation for a model [5].…”

“…These models enable simulations of the effects of watershed processes and management activities in a cost-effective and time-efficient way [4]). For instance, the time and magnitude of floods can be predicted, often in real-time, allowing the authorities to forewarn the population [5]. Several watershed-scale models that vary in terms of complexity and data input requirement terms have been developed in recent decades [6].…”

Analyzing the Performances of Water User Associations to Increase the Irrigation Sustainability: An Application of Multivariate Statistics to a Case Study in Italy

“…The irrigation at the farm level is mainly based on surface and sprinkler irrigation systems, only a few farmers use micro-irrigation. Water fees are charged from the Many of these WUAs are paid by local administrations for the ordinary maintenance of land reclamation works, purposed to soil conservation and watershed management; several works managed by the WUAs are important to avoid the flooding risk in valley areas, often highly urbanized [36][37][38]. Each WUA takes care of a portion of the Calabrian territory, where it manages most irrigation systems covering the command area.…”