This study builds on previous site-specific hazard studies for North Iceland, specifically regarding delineation of seismic sources and seismicity parameters. Using a Monte Carlo approach to generate synthetic earthquake catalogues for North Iceland, and multiple ground motion models (GMMs) that have been proposed and used for probabilistic seismic hazard analysis (PSHA) in Iceland in the past, the variability of the resulting hazard estimates is presented in a map-form. The variability in the hazard estimates is quite large, which is a direct result of the inconsistency in the GMMs used in previous studies. We show how this is caused by the inability of these models to capture the characteristic amplitude attenuation of Icelandic earthquake ground motion with distance, thus casting doubt on the validity of the resulting PSHA of past studies. In contrast, we re-evaluated the variability of PSHA for North Iceland based on new empirical Bayesian GMMs that not only satisfy all the conditions required for use in PSHA, but also fully capture the characteristics of the existing Icelandic ground motion dataset and in addition contain elements that account for the saturation of near-fault peak ground motions at large magnitudes. The results quantify how the variability in the GMMs, contribute to the range of spatial distribution of PSHA amplitudes and uncertainties. The results show that the confidence in the PSHA values is significantly increased using the new models vs. the older ones. The confidence of the PSHA values is quantified through the coefficient of variation. The confidence is shown to be largest over distance ranges where data is most abundant. On the other hand, the confidence decreases considerably at near-fault and far-field distances, primarily because of lack of data for those distances. The findings highlight the importance of using appropriate GMMs for PSHA in Iceland and give a spatial sense of the relative levels of confidence of hazard estimates. They moreover highlight the need for a revision of the PSHA using not only the new GMMs, but also physics-based earthquake source models.

这项研究建立在先前针对冰岛北部的特定地点灾害研究的基础上，特别是关于地震源和地震活动参数的描述。使用蒙特卡罗方法为冰岛北部生成合成地震目录，以及过去在冰岛提出并用于概率地震危险性分析 (PSHA) 的多个地面运动模型 (GMM)，由此产生的危险估计的可变性为以地图形式呈现。危险估计的可变性相当大，这是先前研究中使用的 GMM 不一致的直接结果。我们展示了这是如何由于这些模型无法捕捉冰岛地震地面运动随距离的特征振幅衰减而造成的，从而对过去研究所得 PSHA 的有效性产生怀疑。相比之下，我们基于新的经验贝叶斯 GMM 重新评估了冰岛北部 PSHA 的可变性，该 GMM 不仅满足在 PSHA 中使用所需的所有条件，而且充分捕捉了现有冰岛地面运动数据集的特征，此外还包含解释近断层峰值地面运动在大震级上饱和的元素。结果量化了 GMM 的可变性如何影响 PSHA 幅度和不确定性的空间分布范围。结果表明，与旧模型相比，使用新模型显着提高了 PSHA 值的置信度。PSHA 值的置信度通过变异系数进行量化。在数据最丰富的距离范围内，置信度显示为最大。另一方面，近断层和远场距离的置信度显着下降，主要是因为缺乏这些距离的数据。研究结果强调了在冰岛使用适当的 GMM 进行 PSHA 的重要性，并给出了危险估计的相对置信水平的空间意义。此外，他们强调需要不仅使用新的 GMM，而且使用基于物理的地震源模型来修订 PSHA。