Diego Antonio Hidalgo-Leiva

Identification of proper predictors of structural damage in buildings after the occurrence of seismic events is essential for performance-based design. In this study, 4, 6, 8, and 10-story reinforced concrete (RC) special moment-frame buildings are designed and analyzed through nonlinear dynamic analyses (NLDA) to assess structural damage estimated from lateral displacement (maximum and average inter-story drift ratios, MIDR, and AIDR respectively). The structures were designed following the Costa Rican Seismic Code and the NLDA were performed using records from the Costa Rican Strong Motion database. Several seismic intensity measures (IMs) were estimated directly from the recorded time history and the response of a 5% damped elastic single degree of freedom oscillator with a period equal to the fundamental period of the buildings studied. These IMs were contrasted with the MIDR and AIDR obtained from the NLDA to explore their correlation in terms of the coefficient of determination, R2. Finally, the coefficients of determination for linear and nonlinear regressions were arranged into four clustered matrices that ranked the influence that each IM showed on the expected damage. These matrices unveiled that spectral acceleration (Sa) and spectral velocity (Sv), both based on the oscillator response, represented the highest damage predictors. For the IMs based on records at the ground level, the peak ground velocity (PGV) and acceleration (PGA), presented the highest and lowest correlations respectively.

SUMMARY: A slow-slip event (SSE) is a slow release of tectonic stress along a fault zone, over periods ranging from hours to months. SSEs have been recorded in most of the geodetically well-instrumented subduction zones. Although these transient events observed by geodesy are typically excluded from probabilistic seismic hazard analysis (PSHA), they might play a crucial role in the seismic cycle by reducing the seismic slip rate (slip rate discounting the aseismic process). This effective reduction implies that incorporating SSEs into PSHA may improve the reliability of hazard assessments. Costa Rica, located at the southern end of the Middle American Trench, hosts large earthquakes as well as SSEs. Shallow and deep SSEs have long been detected at the Nicoya peninsula, in northern Costa Rica, and recently, also in the southern part of the country at the Osa peninsula. In this study, we first collect geodetic and SSE observations in Costa Rica. Then, we propose a method to incorporate them into PSHA, based on identifying regions where SSEs occur, inferring slip deficits and estimating seismic slip rates in each subduction segment. Next, we analyse the implications for PSHA and its epistemic uncertainty, using these seismic slip rates, the resulting seismic moment rate budgets, and determining earthquake rates and maximum magnitudes with different approaches. Finally, we compute a countrywide PSHA following the 2022 Costa Rica Seismic Hazard Model (CRSHM 2022) but modifying the seismic source characterization using geodetic information for the regions where SSEs occur. Compared to the CRSHM 2022, this approach leads to reductions of the resulting peak ground acceleration at return period of 475 yr (PGA-475) of up to ∼15 per cent in the Nicoya peninsula, but also to an increase up to ∼40 per cent in the Central Pacific region and ∼30 per cent in the Osa peninsula. Moreover, we find that, under a geodetic-based approach and disregarding SSEs, the PGA-475 would increase by up to ∼10 per cent. Our novel approach underscores the relevance of incorporating geodetic observations and particularly SSEs into PSHA, especially in subduction margins near the coast.

The world population affected by seismic risk is increasing due to urban sprawl, especially in vulnerable areas of countries with high population growth. Despite this trend, seismic exposure assessments have predominantly focused on cities in high-income countries, leaving a knowledge gap in data-scarce, seismically active urban areas. This research presents a novel, scalable geospatial methodology for seismic exposure assessment in contexts with limited data availability and its application to San José, Costa Rica, evaluating its time and cost efficiency. The methodology prioritizes the use of free and open-access geospatial data to construct city-scale Geospatial Exposure Databases (city-GEDs) at the individual building level. These databases integrate key attributes from the Global Earthquake Model (GEM) taxonomy, including the building footprint, the plan regularity, the construction date, the roof material, the relative position within the urban block, and urban block compactness. Random Forest classification models were developed to assign buildings to expert-defined building typologies (BTs). In the case of San José, 7226 buildings were classified into eight typologies using the derived attributes, achieving a classification error of 46%. When the building height—visually sampled—was included, the error decreased significantly to 13%, confirming its importance in typology prediction and emphasizing the need for efficient acquisition strategies. This approach is essential for quick pre- or post-disaster seismic risk assessment, allowing time and cost-effective data collection and analysis. This contribution is particularly relevant for Central America and other seismically active regions with limited data, supporting improved risk analysis and urban resilience planning.

On 8 July 2024, a magnitude 5.3 earthquake struck the province of Chiriquí in Panama, primarily impacting areas characterized by informal settlements and low-income neighborhoods. The earthquake was recorded by both the Panama Accelerographic Network and the Costa Rican Strong Motion Network, with accelerations exceeding 150 cm/s². The National Civil Protection System (SINAPROC) reported damage to 24 residences and public infrastructure, including hospitals and schools. Despite the material damage, no fatalities were reported. The Ministry of Housing and Land Management (MIVIOT), the Ministry of Education (MEDUCA), and the Ministry of Social Development (MIDES) also participated in the assessment and response efforts. This report presents the measurements and damage observed during the event.

This article presents the findings of a study on the directionality effect observed in strong motion records. We set out to establish ratios between several seismic intensity measures that depend on sensor orientation (e.g., GM_ar, Larger) and others that are orientation-independent (e.g., RotDpp, GMRotDpp, and GMRotIpp), with the intention of proposing multiplicative correction factors. The analysis included an evaluation of the impact of site conditions, ground motion intensity, earthquake magnitude, and hypocentral distance on these ratios. Following a concise overview of the directionality effects and the associated intensity measures, the Costa Rican Strong Motion Database, comprising a total of 4199 horizontal accelerograms (two components), was employed to determine the correction factors. The analysis was carried out for 5% damped response spectra within the 0.01–5 s period range. The study focuses on orientation-independent intensity measures that are derived by combining the maximum values from the recorded motions. In the comprehensive analysis of the complete database, a trend was observed between these intensity measures and the magnitude of the earthquake along with the hypocentral distance. Specifically, records from earthquakes with greater magnitudes exhibited a lower maximum spectral response to the geometric mean of the response spectra of the as-recorded (ar) components ratio (RotD100/GM_ar), similar to records from earthquakes with larger hypocentral distances. Based on these findings, a proposal was put forth to estimate RotD100 values using GM_ar values. This ratio can prove useful in transforming data from previous seismic hazard studies, including those applied in many seismic codes, and in defining the maximum anticipated seismic intensity for design purposes in a more straightforward manner.

Se presenta el impacto de los modelos de consecuencias en la estimación de riesgo sísmico físico determinista para el cantón Central de San José, Costa Rica. Para ello se recopiló información de ocho iniciativas internacionales de estimación de riesgo sísmico enfocadas en la estimación de pérdidas económicas, cinco en estimación de víctimas y dos en escombros. Se utiliza el programa OpenQuake de la Fundación Global Earthquake Model (GEM) para realizar los cálculos de riesgo sísmico. En el caso de la estimación de víctimas, se generan curvas de vulnerabilidad a partir de funciones de fragilidad y modelos de consecuencias para un total de 17 tipologías constructivas. Los cálculos se enfocan en el cantón Central de San José, dando continuidad a una serie de investigaciones enfocadas en dicha región que han permitido determinar un modelo de exposición el cual es un insumo básico para las estimaciones de riesgo sísmico. Con respecto a la amenaza, se considera un escenario determinista con un evento generado por la falla de Cipreses con una magnitud de 6.0 Mw y una profundidad de 15 Km. Se encuentra que para el caso de estudio considerado los modelos de consecuencias enfocados en pérdidas económicas tienen un alto impacto en dichas estimaciones, con diferencias de hasta $144 millones de dólares americanos para una diferencia de 1% en los factores de pérdidas. En caso de las víctimas, se encuentran resultados con alta variabilidad también, sin embargo, en dicho caso se tienen estimaciones mediante modelos de consecuencias empíricos y semi-empíricos, por lo que se atribuye a ello dicha variabilidad.

Different seismic risk studies have been carried out in the Central American region to quantify the human and economic losses caused by seismic events. The appropriate use of seismic fragility curves (FCs) allows a better approximation of the level of performance of a structural system in the face of seismic hazards. In this respect, an inadequate selection of FCs can lead to a notably unreliable estimation of damages and losses. This research contributes a methodology for assessing and selecting FCs for seismic risk studies from a catalog of existing proposals available in the literature. The methodology has been applied to the case study of Costa Rica, encompassing a bibliographic search, meetings with Central American experts, and the compilation of a catalog with the FCs used in different vulnerability projects. The conclusion drawn is that FCs with very different probabilities of damage are being used in the diverse vulnerability projects for buildings with the same attributes. Moreover, the proposed methodology allows knowing the reliability level of the FCs obtained depending on which class the curve was classified into based on its score. Therefore, it allows the adequacy and uncertainty related to the selected FCs to be established, a subject that researchers should consider in seismic vulnerability and risk studies.

Costa Rica is located at the boundary of four tectonic plates where the regularity of destructive earthquakes highlights the necessity of seismic hazard estimations. This study contains the most recent Probabilistic Seismic Hazard Assessment (PSHA) for Costa Rica, calculated with the largest and the most updated earthquake database from both—the Earthquake Engineering Laboratory and the National Seismological Network of the University of Costa Rica. For the PSHA, we updated the seismicity parameters for the upper plate, subduction interplate, and intraslab tectonic domains, characterized the upper‐plate zones by percentages of fault types, and used weighted ground‐motion models for each of the tectonic domains. The resulted maps of peak ground acceleration (PGA) at return periods of 475 yr (PGA‐475) and 2475 yr, as well as the spectral accelerations, show geographic trends that allow for the division of the country in four seismic hazard levels: (1) extremely high for the Nicoya, Osa, and Burica peninsulas, situated directly above the subduction interplate, where the PGA‐475 could be 0.55–1.20g; (2) very high for most of the Guanacaste Province, where the PGA‐475 may be 0.55–0.70g; (3) high for most of the country (∼41%) with PGA‐475 values of 0.40–0.55g, including Central Costa Rica and the capital city of San Jose; and (4) moderate for the Talamanca Cordillera and Northern Costa Rica, with PGA‐475 up to 0.40g. These ground‐motion values are 0.1–0.6g higher than the previous PSHA for the Pacific peninsulas, Guanacaste, and the southeastern Caribbean. Further, hazard curves, uniform hazard spectra, and a hazard disaggregation indicate that the seismic hazard is lower but more complex in San Jose than in Liberia—the largest city in Guanacaste.