## 4 Discussion
### Toward an Integrated Framework for GNSS-Based Seismic Hazard Modeling  
To overcome the limitations inherent in elastic strain models, it is essential to adopt an integrative approach that combines GNSS-derived strain field data with detailed fault maps, geological cross-sections, and region-specific elastic models. Such multidisciplinary integration enhances the physical realism of deformation modeling and contributes to a more accurate understanding of long-term fault system behavior. However, the temporal variability observed in GNSS strain fields presents additional challenges for interpretation. Short-term anomalies may result from seasonal surface loading, transient aseismic deformation, or noise within the observational dataset, all of which complicate the distinction between sustained tectonic loading and episodic perturbations [1]. Furthermore, although maximum shear strain is a useful proxy for assessing fault slip potential, it does not directly indicate rupture probability or timing. Therefore, the interpretation of elastic strain fields should be conducted in conjunction with complementary datasets, including paleoseismic records, seismicity catalogs, geomechanical models, and geological parameters such as lithological heterogeneity, fault zone material properties, and structural boundary conditions. This integrated framework enables a more comprehensive and reliable assessment of regional seismic hazards and plays a crucial role in improving the predictability of future seismic events by advancing our understanding of complex crustal deformation processes.  
To advance this integration, observed geodetic strain rates can serve as critical input parameters for probabilistic seismic hazard models (PSHM), especially in regions with sparse or incomplete historical seismicity. By linking the rate of strain accumulation to long-term seismic moment release, it becomes possible to estimate the frequency and spatial distribution of future earthquakes over defined time intervals. For instance, ref. [73] demonstrated a strong correlation between strain rate and seismicity in the India-Asia collision zone, suggesting that geodetic strain can act as a proxy for estimating seismic hazard in tectonically active but data-limited regions. Similarly, refs. [74; 75] employed geodetic strain rates to calibrate moment rate budgets and spatially refine seismic source zones in New Zealand and Mainland China, respectively.  
These studies show that the inclusion of geodetic data improves the spatial resolution and physical basis of PSHM, particularly by informing slip rate models and constraining the Gutenberg-Richter parameters. Moreover, as [42] emphasizes, careful treatment of strain rate uncertainties further enhances the robustness of probabilistic forecasts. Therefore, integrating GNSS-derived strain data into PSHM frameworks represents a promising approach for refining regional seismic hazard assessments on the Korean Peninsula.  
Figure 12 presents a conceptual roadmap outlining the integrative workflow for GNSS-based strain analysis and its application to seismic hazard assessment and policy planning. The framework emphasizes the sequential linkage from data acquisition to decision support, incorporating strain anomaly detection and probabilistic hazard modeling. This diagram underscores the importance of combining geodetic observations with geological  
and seismological data to inform risk mitigation strategies and enhance regional seismic resilience.