Epistemic Uncertainty in Ground-Motion Characterization in the Indian Context: Evaluation of Ground-Motion Models (GMMs) for the Himalayan Region

One of the major challenges in probabilistic seismic hazard analysis (PSHA) studies, particularly for risk-based decision-making, is to constrain epistemic uncertainties. Epistemic uncertainty associated with ground-motion characterization (GMC) models exerts a strong influence on the hazard estimate for a given target level of ground shaking. In the Indian context (mainly along the Himalayan arc), constraining epistemic uncertainty is a significant challenge owing to the lack of recorded data. This study investigates the epistemic uncertainty associated with ground-motion models (GMMs) considered appropriate for the Himalayan region. First, a review of GMMs considered applicable to the Himalayan region is provided. Subsequently, a graphical comparison of median models is performed, followed by residual and statistical analysis. The evaluation utilizes observations from a recently compiled strong-motion dataset across the Himalayas and Indo-Gangetic plains of northern India. The dataset comprises 519 acceleration traces from 150 events in the moment magnitude (M<inf>w</inf>) range M<inf>w</inf> 3–7.4, recorded at epicentral distances in the range R<inf>Epi</inf> < 300 km. The analysis demonstrates significant between-model variability, particularly with regard to median magnitude and distance scaling. The residual analysis also indicates a large bias and aleatory uncertainty. Moreover, some of the GMMs exhibit trends with distance and magnitude. Overall, our evaluation analysis shows that there is clearly significant aleatory and epistemic uncertainty associated with the GMC modeling owing to the paucity of recorded data. The range of epistemic uncertainty represented by the GMMs (available in the literature) is much larger than that typically captured by the (multiple) global models often used in PSHA studies across India.