## 1 Introduction  
Proper bridge management is vital to maintain a satisfactory performance level of the large stock of built infrastructures. Its main goal is to define optimal repair, maintenance, and replacement strategies for bridge inventory. Nonetheless, there are numerous challenges for achieving this goal since bridges are subjected to different demands, such as increasing traffic loads and exposure to harsh environmental conditions, which lead to serious deterioration processes that reduce their structural performance over time [1, 2]. Therefore, the lack of inspections and inappropriate maintenance may result in partial or total bridge failures [3]. Moreover, the occurrence of extreme natural events (e.g., earthquakes, landslides, floods, scour, hurricanes, typhoons) has also caused sudden bridge collapses in the past. Among these natural causes, flood-induced scour has been identified as one of the predominant triggers of bridge failure worldwide [4]. Between the different bridge types, masonry arch bridges (MAB) are recognized as highly vulnerable to scour effects due to their rigid behavior, which is sensitive to settlements, and the fact that they were typically built on shallow footing foundations [5, 6, 7]. Furthermore, there is a reduction of the global load-carrying capacity of an MAB when the water level rises above the deck, thus making the arch barrel and surrounding fill saturated; the buoyancy effects reduce the self-weight contribution of the masonry and of the fill to strength capacity of the arch [8]. For these reasons, the safety assessment of MAB against flooding and scour effects is of utmost importance to identify possible mitigation plans. When assessing bridge safety, the lack of information causes high uncertainties when representing the loads and material properties. Thus, by explicitly considering the uncertainties and implementing fully probabilistic approaches, the lack of information can be mitigated [9]. In this regard, fragility functions have become broadly used to represent the probability of exceeding an undesirable limit state for a given intensity of a hazard. Multiple methods have been used for the definition of fragility functions, especially in the field of seismic assessment (see [10] for an overview). Some key differences between each method may include but are not limited to the level of detail, type of failure mode, and the use of numerical simulations. Methods, such as the safety factor, use safety margins to assess uncertainties, which have the advantage of not using time-consuming numerical simulations [11]. Analytical approaches have also been implemented when there is a lack of damage information [12]. Conversely, numerical simulation methods can provide a detailed response of the structure, and when combined with regression methods, they can be applied to a great range of intensity measures. Nonetheless, this comes at the cost of more time-consuming numerical analyses [10]. Published literature on fragility functions for bridges exposed to flood events is less common than for other natural hazards, such as earthquakes (see [13] for an overview). Some efforts have been made to assess the combined effect of flood-induced scour on the seismic fragility of bridges (e.g., [14; 15; 16]). However, these studies account for scour as an aggravated condition for seismic fragility rather than as a collapse failure mechanism by itself. More recently, flood-related fragility curves for concrete bridges have been developed, considering multiple failure modes due to local scour, together with the action of additional demands, such as hydraulic forces, hydrodynamic pressure due to debris accumulation, and deterioration effects due to corrosion (e.g., [17; 18; 19; 20]). Nevertheless, the methodologies implemented in these research efforts are case-specific and time-consuming due to the use of finite element modeling for probabilistic analysis, which hinders the possibility of applying them at a network level scale, i.e., for a large portfolio of assets [21].