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

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

Experimental and numerical evaluation of the force due to the impact of a dam-break wave on a structure

Flood events caused by the collapse of dams or river levees can have damaging consequences on buildings and infrastructure located in prone areas. Accordingly, a careful prediction of the hydrodynamic load acting on structures is important for flood hazard assessment and potential damage evaluation. However, this represents a challenging task and requires the use of suitable mathematical models. This paper investigates the capability of three different models, i.e. a 2D depth-averaged model, a 3D Eulerian two-phase model, and a 3D Smoothed Particle Hydrodynamics (SPH) model, to estimate the impact load exerted by a dam-break wave on an obstacle. To this purpose, idealised dam-break experiments were carried out by generating a flip-through impact against a rigid squat structure, and measurements of the impact force were obtained directly by using a load cell. The dynamics of the impact event was analyzed and related to the measured load time history. A repeatability analysis was performed due to the great variability typically shown by impact phenomena, and a confidence range was estimated. The comparison between numerical results and experimental data shows the capability of 3D models to reproduce the key features of the flip-through impact. The 2D modelling based on the shallow water approach is not entirely suitable to accurately reproduce the load hydrograph and predict the load peak values; this difficulty increases with the strength of the wave impact. Nevertheless, the error in the peak load estimation is in the order of 10% only, thus the 2D approach may be considered appropriate for practical applications. Moreover, when the shallow water approximation is expected to work well, 2D results are comparable with the experimental data, as well as with the numerical predictions of far more sophisticated and computationally demanding 3D solvers. All the numerical models overestimate the falling limb of the load hydrograph after the impact. The SPH model ensures good evaluation of the long-time load impulse. The 2D shallow water solver and the 3D Eulerian model are less accurate in predicting the load impulse but provide similar results. A sensitivity analysis with respect to the model parameters allows to assess model uncertainty

Local time stepping applied to mixed flow modelling

Mixed flows in closed conduits are characterized by waves, celerity values of which lie within a range of up to two orders of magnitude due to the simultaneous occurrence of free-surface and pressurized flow. If an explicit numerical scheme is used to simulate these phenomena, the time step necessary to guarantee stability is considerably restricted by pressure wave celerity, and thus the computational efficiency is reduced. In order to address this specific problem this paper proposes the application of the local time stepping strategy to a finite-volume scheme for mixed flow modelling, which adopts the Preissmann slot approach. The results of several tests show that local time stepping reduces run time significantly, compared to the conventional global time stepping, especially when only a small region of the domain is surcharged. The accuracy and mass conservation in the proposed approach are not impaired. Moreover, in the free-surface region of the flow the accuracy slightly improves

Modellazione numerica 1D del sormonto di un ponte

 Si propone un modello numerico 1D in grado di simulare il funzionamento in pressione di ponti e tombini, nonché l’eventuale sormonto, grazie all’impiego di condizioni al contorno interne  Il modello consente di descrivere la geometria del manufatto e di simulare le diverse condizioni di moto che si verificano al di sotto dell’intradosso ed al di sopra dell’estradosso del manufatto stesso  Il modello è stato validato con dati di laboratorio e con soluzioni numeriche ottenute con HEC-RAS ed ha fornito soddisfacenti valutazioni del rigurgit

Flood Stage Forecasting Using Machine-Learning Methods: A Case Study on the Parma River (Italy)

Real-time river flood forecasting models can be useful for issuing flood alerts and reducing or preventing inundations. To this end, machine-learning (ML) methods are becoming increasingly popular thanks to their low computational requirements and to their reliance on observed data only. This work aimed to evaluate the ML models’ capability of predicting flood stages at a critical gauge station, using mainly upstream stage observations, though downstream levels should also be included to consider backwater, if present. The case study selected for this analysis was the lower stretch of the Parma River (Italy), and the forecast horizon was extended up to 9 h. The performances of three ML algorithms, namely Support Vector Regression (SVR), MultiLayer Perceptron (MLP), and Long Short-term Memory (LSTM), were compared herein in terms of accuracy and computational time. Up to 6 h ahead, all models provided sufficiently accurate predictions for practical purposes (e.g., Root Mean Square Error 0.99), while peak levels were poorly predicted for longer lead times. Moreover, the results suggest that the LSTM model, despite requiring the longest training time, is the most robust and accurate in predicting peak values, and it should be preferred for setting up an operational forecasting system

A combined colour-infrared imaging technique for measuring water surface over non-horizontal bottom

This paper presents a combined colour-infrared imaging technique based on light refraction and absorption for measuring water surface over a non-horizontal fixed bottom known a priori. The procedure requires processing simultaneous visible and near-infrared digital images: on the one hand, the apparent displacement of a suitable pattern between reference and modulated visible images allows to evaluate the refraction effect induced by the water surface; on the other hand, near-infrared images allow to perform an accurate estimate of the penetration depth, due to the high absorption capacity of water in the near-infrared spectral range. The imaging technique is applied to a series of laboratory tests in order to estimate overall measurement accuracy. The results prove that the proposed method is robust and accurate and can be considered an effective non-intrusive tool for collecting spatially distributed experimental data