Monitoring-Informed Scenario Forecasting of Spatial Seismic Demand for Proactive Resilience in the İzmir Basin

Abstract. Recorded seismic observations from monitoring networks provide a direct empirical basis for updating regional representations of earthquake demand, yet their use in scenario forecasting and proactive resilience planning remains limited. This study proposes a monitoring-informed sense–forecast–adapt workflow for forecasting spatial seismic demand in the İzmir Basin, western Türkiye. The framework transforms accumulated strong-motion records into a regional residual correction layer, embeds this layer within active-fault-based earthquake scenarios, and translates the resulting demand fields into adaptation-oriented spatial indicators.

A transparent reference ground-motion representation is first fitted using event magnitude, source-to-site distance, and site-condition information. Event–station residuals are then aggregated at the station level and interpolated to construct monitoring-informed residual and residual-variability fields. These updating layers are embedded within five representative active-fault scenarios around the İzmir Basin to generate baseline and monitoring-updated PGA fields. The resulting demand fields are evaluated through persistence, scenario sensitivity, monitoring/inspection priority, rank variability, and spatial concentration of high-demand domains.

The workflow is evaluated through residual-field validation, Gaussian-process benchmarking, robustness analyses, cumulative model-version tracking, and Monte Carlo uncertainty propagation. The results identify the Tuzla Fault scenario as the dominant demand case and the Yenifoça Fault scenario as the main secondary case. High-demand zones organize into spatially coherent regions, several locations remain repeatedly critical across multiple source scenarios, and the virtual regional demand representation stabilizes as the monitoring archive expands from 1977–2010 to 1977–2025.

The main contribution is an updateable forecasting workflow that integrates monitoring-derived residual updating, scenario-based spatial demand simulation, uncertainty-aware exceedance mapping, and resilience-oriented decision indicators. By transforming accumulated strong-motion observations into an evolving regional demand representation, the proposed framework moves beyond pointwise ground-motion estimation and provides a digital-twin-oriented basis for proactive seismic resilience planning in monitored basin environments.