Integrating Geodetic Constraints into Earthquake Source Characterization for Probabilistic Seismic Hazard Analysis: A Dual Statistical–Physical Framework

Abstract. Reliable earthquake source characterization is essential for probabilistic seismic hazard analysis (PSHA), yet remains particularly challenging in low-seismicity regions where sparse earthquake catalogs introduce substantial epistemic uncertainty. Although geodetic observations provide independent constraints on contemporary crustal deformation, existing hybrid earthquake source models have generally been selected solely on the basis of statistical forecasting performance without explicitly considering their physical consistency with regional deformation. This study presents a statistical–physical hybrid framework that integrates independently validated catalog-based and GNSS-derived geodetic earthquake source models for PSHA. The proposed framework combines retrospective earthquake forecast evaluation using the Collaboratory for the Study of Earthquake Predictability (CSEP) with independent physical screening based on the regional geodetic moment budget. A total of 126 candidate hybrid models were evaluated for Kalimantan, Indonesia, representing alternative catalog models, geodetic scenarios, and hybrid formulations. Although several candidates improved retrospective forecasting skill, only three satisfied both the statistical and physical selection criteria, with the preferred adaptive-smoothing hybrid model achieving the highest average retrospective pass rate (67.5 %). Physical screening rejected six of the seven evaluated geodetic scenarios because their implied seismic moment release exceeded the available geodetic moment budget. Incorporating the selected hybrid models into PSHA increased median peak ground acceleration by approximately 2–29 % for the 475-year return period and 2–23 % for the 2475-year return period. In contrast, equal-weight and performance-based logic-tree ensembles produced nearly identical hazard estimates, differing by less than 1.5 %. These results demonstrate that integrating statistical forecasting skill with independent geodetic constraints provides a physically consistent framework for earthquake source characterization and a transferable methodology for improving earthquake hazard assessment in low-seismicity regions.