A framework for probabilistic assessment of clear-water scour around bridge piers

Abstract

Scouring at the base of bridge piers is the major cause of bridge collapses worldwide. Computing the scour risk of bridge foundations is therefore key for a correct management and allocation of resources for maintenance and scour mitigation works. Existing risk-assessment models compute the vulnerability of bridge foundations to scour by comparing the equilibrium scour depth associated with peak-flow discharges characterized by a given return period (usually of 100–200 years) with the critical foundation depth of the bridge. This approach neglects completely the history-dependent and time-dependent nature of scour. Yet, it is well known that bridge collapses can often be induced by the accumulation of scour during multiple flood events. This study aims at developing a novel probabilistic framework for the computation of bridge-pier vulnerability to scour using a Markovian approach to account for memory effects in scour development. The paper focuses on the case of local pier scour occurring in clear-water conditions whereby cumulative effects are significant, well understood and known to be the cause of recent reported bridge collapses. A simplified numerical example consisting of an idealised bridge pier in a canal is considered to clarify the application of the proposed framework and to shed light on the effects of some assumptions introduced to simplify the probabilistic scour assessment

Quantification of Modelling Uncertainties in Bridge Scour Risk Assessment under Multiple Flood Events

“…The scour progression process under clear-water conditions is modelled via a discrete-time and discrete-state Markovian process, originally developed in Tubaldi et al [28]. The Markovian assumption essentially implies that the change (increment) of the scour depth during a certain flood event depends on the scour depth reached when the flood occurs, rather than on the entire hydrologic and scour history.…”

“…where P n (t) represents the probability of having n floods in t years, which is controlled by the occurrence rate of the floods. Further details about the framework can be found in Tubaldi et al [28].…”

“…The results reported in the table shows how the relative differences between the results according to the various models change with k. Figure 7 shows E[z] in function of the ratio between time-to-peak and total flood duration, defined as the percental time-to-peak (PTP). The total flood duration is computed deterministically by the relation t = 0.0263 Q p − q 0 days [28,47]. PTP ranges between 0.2 and 0.5 in this study.…”

“…The fractional integrated autoregressive moving average (ARFIMA) process was fitted to the historic streamflow record and used to generate synthetic hydrologic time-series with the same statistical properties as the observed ones. Recently, Tubaldi et al [28] developed a Markovian framework for describing the probabilistic evolution of clear water scour at bridge piers accounting for memory effects. According to the Markovian process assumption, the change of the scour depth during one flood event depends on the scour depth reached before the occurrence of the event itself, rather than on the entire hydrologic and scour history.…”

Scour at Bridge Foundations in Supercritical Flows: An Analysis of Knowledge Gaps

“…Lately, a number of authors have explored alternative strategies for bridge failure predictions in order to account for the non-stationarity of the flow and the stochastic nature of floods. These studies highlighted that scour evolution over time is strongly controlled by factors like the shape of flood hydrographs [83], and also the time-sequence of floods occurring at a given location [100]. Moreover, hydrological variability has been amplified even more significantly by the effects of global climate change [101].…”