Hydrological and Hydraulic Flood Hazard Modeling in Poorly Gauged Catchments: An Analysis in Northern Italy

Abstract

Flood hazard is assessed for a watershed with scarce hydrological data in the lower plain of Northern Italy, where the current defense system is inadequate to protect a highly populated urban area located at a river confluence and crossed by numerous bridges. An integrated approach is adopted. Firstly, to overcome the scarcity of data, a regional flood frequency analysis is performed to derive synthetic design hydrographs, with an original approach to obtain the flow reduction curve from recorded water stages. The hydrographs are then imposed as upstream boundary conditions for hydraulic modeling using the fully 2D shallow water model PARFLOOD with the recently proposed inclusion of bridges. High-resolution simulations of the potential flooding in the urban center and surrounding areas are, therefore, performed as a novel extensive application of a truly 2D framework for bridge modeling. Moreover, simulated flooded areas and water levels, with and without bridges, are compared to quantify the interference of the crossing structures and to assess the effectiveness of a structural measure for flood hazard reduction, i.e., bridge adaptation. This work shows how the use of an integrated hydrological–hydraulic approach can be useful for infrastructure design and civil protection purposes in a poorly gauged watershed.

A Silhouette-Width-Induced Hierarchical Clustering for Defining Flood Estimation Regions

“…The index-flood method is intended for regional flood frequency analysis [46,47]. This method combines data from several HSs to obtain one theoretical distribution function, i.e., regional growth curve, supposing an index (scaling factor) can be found at ungauged HS elsewhere or by some other method [17].…”

SABER: A Model-Agnostic Postprocessor for Bias Correcting Discharge from Large Hydrologic Models

“…To identify and mitigate these errors, SABER compares the bias-corrected flows against values that are statistically likely to determine if flow values seem reasonable. Specifically, SABER compares the distribution of corrected flows against a Gumbel Type 1 distribution, which is commonly used for estimating high-flow values [60][61][62]. SABER replaces flows with a return period of 100 years or larger with the 100-year discharge predicted by the Gumbel Type 1 distribution.…”

Flood Early Warning and Risk Modelling

“…Therefore, it was concluded that many of them influence the flood depth and the extent of flooded areas upstream of the bridges. The final results are the more important, the easier they are to be included in the design of road infrastructure and hydrotechnical builds for civil protection [15].…”