## 1 Introduction  
Diffusive surfaces are widely used in performance spaces since they are considered an important design aspect that improves the room's acoustic quality and the listener's enjoyment [1]. Based on this, it has become important to consider their effects on the overall acoustic quality during the early architectural planning stages of a concert hall, usually investigated through geometrical acoustics (GA)-based software. Thus, a lot of effort has been put into the implementation of algorithms that take into account the scattering phenomenon due to diffusive surfaces [2]. However, there is not a clear conclusion as to how the presence, position, and shape of these surfaces influence the acoustic parameters and the subjective perception [3]. Consequently, the correct modeling of these surfaces in GA software is not a trivial task [4]. Therefore, this study aims to investigate the effects of two different modeling alternatives of diffusive surfaces on the reliability and accuracy of the prediction of objective room acoustic parameters and on the perceptual aspects of a concert hall sound field. Furthermore, the surface-distance-dependent sensitivity of the listener has been investigated by comparing the reflective and diffusive configuration of one of the lateral walls. This paper is presented as a follow-up study of the previous paper [5], which dealt with in-field measurements only. GA-based models have been used as an alternative to both scale-model and in-field measurements after continuous improvements to their accuracy since their first development by [PERSON] and [PERSON] [6]. In particular, additional physical acoustic phenomena have been included such as diffraction and scattering [7; 8; 9; 10; 11; 12]. Further interest in auralization has required improvements in the diffusion modeling algorithms, in binaural processing, and in reproduction techniques [2; 13; 14]. In the last decades, several studies have investigated these aspects based on objective results and on human auditory perception [15; 16]. The very demanding field of Virtual Reality has pointed out the need for less computational effort and more realistic auralizations [17; 18]. Thus, it becomes important to identify the properties of room acoustics simulation that are perceptually relevant. This affects an important aspect, the modeling level of detail, which in turn might be very time-consuming. The perceptual effects of different surface modeling have not yet been fully investigated. Moreover, the task becomes harder considering that the major drawback, at the actual state of the art of the modeling software, is that the different simulation tools require different input data [19; 20]. Thus, the material properties of surfaces or objects, such as absorption and scattering coefficients, have been shown to be aspects that significantly contribute to the uncertainty in simulations and affect their benchmarking [21]. The level of modeling detail is considered a systematic uncertainty factor in GA models and must be decided taking into account the validity of the computational method, which depends on the dimensions of the object or surface irregularities compared to the wavelengths. Practically, this means that objects or surface irregularities that are not large compared to the wavelengths should be considered as flat surfaces with specific properties. No exact guidelines are given regarding this issue, which might lead to significant errors since a GA model might not give accurate results when using either a very detailed model or a very simple one. Several studies have investigated the most appropriate degree of detail in prediction models. [PERSON] et al. [22] investigated the modeling detail of the audience area in two different kinds of software (Odeon and CATT-Acoustic), while [PERSON], [PERSON], and [PERSON] [23] assessed the quality of the simulations as function of the model level of detail (LOD).