## 1 Introduction  
Rockfalls and rock avalanches are natural hazards in mountainous regions. They can cause severe damage to settlements and infrastructure as well as serious injuries and fatalities due to their extremely high velocities and runout distances [1]. Rockfalls are classified as types of rock slope failure characterized by the detachment of single or clusters of individual rock blocks from a steep slope followed by a rapid down-slope motion by falling, bouncing, rolling and sliding [2, 3]. Fragmental rockfall is related to the movement of individual fragments which interact with the substrate and thus can be simulated by physical models based on rigid body ballistics. The dynamic interaction of individual blocks of a rockfall event is minor and has no relevant impact on the runout behavior. Rock avalanches are moving in a flow-like manner as masses of fragments that have a strong dynamic interaction of blocks [1]. Many of these events, particularly the large ones, show unexpected long runout distances. From a modelling perspective, this type of movement requires a completely different mechanical approach, which is considering the rapid coherent flowing mass by granular flow models (e.g., [4]). By nature, there is no distinct boundary between rock avalanches and rockfalls, but rather a gradual transition influenced by the rock type, structural setting, rock fragmentation, substrate properties, and slope topography of the runout path. Nevertheless, also for rock avalanches, single or clusters of blocks can separate during motion from the flowing mass resulting in movements of individual fragments like rockfall events. Although there is a completely different movement mechanism between these two types of rock slope failure, both are influenced by geometrical rock mass characteristics of the discontinuity network, such as orientation and number of sets, frequency and spacing, size and persistence, and intact rock bridges of the failure area. These parameters influence one important rock mass parameter termed the in situ block size distribution (IBSD [5]). Discontinuities intersecting a rock mass are causing separated rock blocks with sizes ranging from mm\({}^{3}\) in crushed rocks to several m\({}^{3}\) in massive rocks. The IBSD influences the size of the runout area and impact energy of the rockfall and rock avalanche events in case of a failure. Thus, the IBSD in the source area is a crucial rock mass property for rockfall/rock avalanche hazard assessment comprising both runout modelling and designing of protective measures [6; 7; 8; 9; 10]. Generally, the non-persistence of the fractures increases the percentage of bigger blocks compared to a discrete fracture network (DFN) with similar fracture set spacings and orientations but persistent fractures (Figure 1). However, for a rock mass with non-persistent fractures, intact rock bridge failure between pre-existing fractures can have a major impact on the IBSD. Fracture coalescence and crack growth driven by time-dependent changes of the in situ stresses due to thermal, freezing-thawing, and pore water pressure fluctuations, etc., can lead to the failure of intact rock bridges between the fractures, provided that the intact rock bridge is small enough [11]. This commonly observed process usually leads to a decrease of the resulting block sizes of a DFN, the stability of rock slopes and an increase in hydraulic connectivity, and consequently, conductivity. The impact of rock bridge failure of non-persistent fractures on the resulting block sizes as well as the shape of the cumulative block size distribution curve has not been investigated in detail so far because of the difficulty in assessing various relevant parameters in the field. This contribution presents stochastic analyses of the two-dimensional in situ block area distribution and the mean block area of a non-persistent fracture network based on simulated DFNs. Due to the large amount of time required for the calculations, this article focuses on two-dimensional fracture networks.