Hydro-Québec and Cemagref have implemented condition evaluation methods for water retaining structures: the condition index (CI) method for embankment dams in Quebec, and SIRS Digue for fluvial dykes in France. These methods were developed from similar approaches, including functional analysis, gathering and formalization of knowledge about failure mechanisms, and definition of performance indicators. Development of both methods was done within a group of experts and lead to technical guides that explain the application limits. The main objective is to prioritize maintenance tasks within a large inventory of dams for Hydro-Quebec, and for fluvial dykes, in France. The use of these methods reaches also other goals at the same time: aid to safety review and dam diagnosis, and experience transfer among the technical staff.
No abstract is provided for this article.
No abstract is provided for this article.
Forecasting flood characteristics (e.g., water levels and velocity) is a growing concern due to climate change. It is therefore necessary to consider the stability conditions of earthen levees used to mitigate floods during a flood risk assessment. This technical note presents a method to assess probabilistic flood hazard that takes into account levee failures, for a levee located along Etobicoke Creek in Toronto, Canada. We compute flood scenario probabilities resulting from multiple flood scenarios that accounts for both the levee failures across the length of the levee, and different levee-failure mechanisms (e.g., backward erosion and overtopping). Then, for each location of the flooded area, we compute a cumulative flood exceedance probability curve for flood depth and velocity. This method provides a flood-hazard map (depth and velocity) for a given probability and probabilistic maps for given values of depth or velocity.
Studies carried out to analyse the risks of levees must include an evaluation of the probabilities of occurrence of different failure mechanisms (overflow, internal erosion, sliding and scouring).The probabilistic quantitative evaluation of these mechanisms remains difficult due to often insufficient input data, the natural variability of the materials, structures of very long length, the availability of mechanical models for certain failure mechanisms, and the random nature of the stresses involved.This makes it necessary to call for expert judgement to evaluate the probabilities of failure.However, expert judgement is generally associated with a qualitative and subjective dimension, and it comprises biases liable to impair the capacities of an expert to elicit their evaluations.This article proposes an approach to processing expert judgement that includes the modalities of Individual expert Elicitation, Calibration, Aggregation, and Debiasing of expert judgement (IeCAD).This IeCAD approach has been developed for river levees in view to correcting biased expert evaluations in the case of evaluating the failure probability of structures.
No abstract is provided for this article.
No abstract is provided for this article.
France and other regions around the world frequently undergo devastating flood events. Any failure of a flood protection structure can lead to human casualties and material damage. Unfortunately, such long linear structures are often poorly maintained and have shown repeated signs of weakness. Therefore, river levee management raises a number of substantial issues for the decision‐makers responsible for ensuring maximum safety for the surrounding population at a reasonable management cost. The aim of the D igsure project is to provide levee managers with scientific methods and information technology ( IT ) tools for levee management. The D igsure method is a levee assessment method based on a probabilistic pattern. It produces levee performance indicators and integrates data and the uncertainty on results. D igsure is a geographic information system tool that implements the D igsure method. It estimates and displays levee performance and associated uncertainty intervals throughout levee assessments.
Urban areas are frequently built along rivers and earthen levees are commonly used to protect areas from fluvial floods. Levees are designed to protect assets from flooding, however, they deteriorate over time. Maintenance checks are required to maintain their efficacy but even in good condition, a levee structure may fail during a flood, hence flood risk assessments in fluvial areas require an investigation of levee failures, e.g. by overtopping, erosion, or sliding. In this research, we investigate the failure probability due to backward erosion of an adapted levee in the Etobicoke Creek watershed, in Toronto, Canada. The study proposes an adapted levee as the residential area is often flooded. Backward erosion is the most probable and challenging failure mechanism for our case study based on the levee shape and soil type. For this probabilistic study, the levee was modelled using GeoStudio, which produces seepage analysis from geotechnical and hydrological parameters. The seepage analysis provides hydraulic gradients from which we determine the failure probability of backward erosion based on a critical hydraulic gradient value. To obtain the flood hazard, we use a steady flow hydraulic model (HEC-RAS) to simulate the 350-years return period flow through the River. We compare two backward failure scenarios: one with a levee breach and one without, to better understand how failure of the levee will impact flood risks, and therefore, highlighting the importance of on-going levee maintenance. To obtain flood risk maps, the flood hazard (i.e., flood extent) is combined with flood exposure. The flood exposure includes land-use type (residential, commercial, etc.) and demographic information. Flood hazard and exposure data are combined using ArcGIS. The flood hazard and exposure rasters are reclassified in a new scale to determine flood risk. We then overlay the rasters to determine the spatial distribution of flood risk for both scenarios. We compare the resulting flood risk maps and calculate the change in flood risks for the area protected by the levee. Accounting for potential failure of infrastructure in flood risk mapping results in more accurate risk estimations. We also demonstrate the positive impact of the levee.
More and more floods occurred over the last two decades causing important damages. Moreover, levees are often not well maintained, so they hardly resist to major floods and can break easily. At French national scale, the length of levees and the lack of data complicate their management. In this frame, levee managers need approaches and tools to be helped in their maintenance decision. First, we have developed a Levee Geographic Information System. This GIS application allows collecting data necessary for managing a levee portfolio. Secondly, we have developed a SDSS to assist levee managers in their prioritizing maintenance activities. This SDSS is using Operational Safety methods to assess levee performance along their length. The SDSS is aggregating performance indicators with a rule-based multi-criteria assignment method. All these tools and methods are operational and now used by levee managers in their regular infrastructure portfolio maintenance.
Flood hazard assessment is crucial to mitigate the risks associated with flooding. Integrating levee failure scenarios into these assessments should improve the evaluation of flood risks and enhance the resilience of communities and infrastructure. This research presents a probabilistic flood hazard approach to assess levee failure and its impact on flood hazard. Our method includes a comprehensive assessment of backward erosion and overflowing failure mechanisms, integrated within a 1D/2D hydraulic model that simulates flood propagation and levee breaching. We calculate the cumulative probability of flood depth and velocity considering various scenarios, taking into account levee failure breaching for various failure mechanisms and several flood intensities. We apply the method to a residential area along Etobicoke Creek in Ontario, Canada. The results highlight which levee segment has the most impact on flood hazard, emphasizing the importance of incorporating levee failure scenarios in flood hazard assessments. The cumulative probability curve provides a more holistic result in locating the most hazardous areas rather than considering one return period or one failure mechanism. It can be expended to every location of the protected area, allowing for the creation of a probabilistic map for a desired probability.
In France as in others countries, design of dams is not considered into probabilistic format and is deterministic. In addition, there are no formal rules for the design of dams that remains based on guidelines, leading to strong heterogeneities in French practice. In this context, the French Committee of Dams and Reservoirs produced a work which aims at examining the feasibility of a limit states method for the design of gravity dams. This article synthesises the study leaded over two years by a group of experts representing French engineering and dam public organizations. It establishes a synthesis of the current practices, develops a limit state methodology and examines the feasibility of its calibration. The medium-term prospects for this work are to build up guidelines to design gravity dams in a limit state format.
The breaching of river levees can have dramatic economic and human impacts. In many countries, including France, laws and regulations require the assessment and inspection of hydraulic structures. Methods are required to carry out these missions. The following article presents a method for assessing the impacts of tree vegetation on the resistance of river levees to internal erosion. Indeed, the presence of trees—particularly following the decomposition of their roots—may cause damage in the structure through contact erosion, concentrated erosion, backward erosion or suffusion. The proposed method takes into account the possible presence of trees and especially roots in different parts of the levee. The method is based on the formalization and aggregation of expert knowledge. It permits the calculation of a performance indicator, which is obtained by aggregating criteria determined using formalized status indicators. The entire method is available in the article. The method was tested on two real cases.
