Ground Acceleration Research Articles

Source characterization of the 20th May 2024 MD 4.4 Campi Flegrei caldera earthquake through a joint source-propagation probabilistic inversion

On May 20th, 2024, an earthquake of magnitude MD 4.4 nucleated at shallow depth (2.6 km) in the Campi Flegrei caldera (Southern Italy), a densely populated area where an increase in seismic activity has been observed since 2019 attributable to an on-going unrest episode. While the magnitude was moderate, the event produced a strong ground shaking with an observed maximum peak ground acceleration of 3.58 m s-2, and several buildings were damaged. Here, we characterize the earthquake source using a probabilistic joint source-propagation spectral inversion in the Fourier space. We estimate a moment magnitude Mw = 3.70 ± 0.13 and a corner frequency fc = 1.11 ± 0.19 Hz. Assuming a circular rupture model, we estimate a source radius r = 400 ± 70 m and a stress drop Δσ = 3.2 ± 2.2 MPa. The estimated stress drop suggests that future earthquakes in the hypocentral region, considering a possible rupture length of 3 km suggested by previous studies, can have magnitude increased by 1.2 ± 0.3 units with respect to May 20th event. A systematic source characterization of the recent seismicity in the caldera would hep in estimating the expected ground motions from future large-magnitude events.

Analyzing the dependency of earthquake insurance premium on the intensity measure used in probabilistic seismic hazard analysis and fragility curves

Considering the uncertainties associated with earthquake, seismic response of structures, damage caused by the response and the repair costs, determining Earthquake Insurance Premium (EIP) is a challenging task that requires a framework for modeling all inherent risks. Most of the models proposed for EIP determination have two basic components. The first component indicates the probability of seismic hazard (generally obtained from the probabilistic seismic hazard analysis), and the second component indicates the probability of occurrence of a given damage to the structure with respect to different seismic hazard levels (generally obtained from the fragility curves). These two components are interconnected through an intermediate parameter, known as the Intensity Measure (IM), which is of great importance in calculations and has hardly been considered so far. In this study, the dependency of EIP on the IM used in the probabilistic seismic hazard analysis and the fragility curves is analyzed. To this end, the EIP was determined for five types of buildings at low, medium and high seismic hazard levels using two IMs (peak ground acceleration and first mode spectral acceleration). The results of this study warn that the EIP can be highly dependent on the IM, so that for all studied structures, the EIP determined based on peak ground acceleration at a high seismic hazard level is nearly three times as many as the one determined by the first mode spectral acceleration. A significant finding is that when the first mode spectral acceleration is used as the IM, the ratio of EIP at different seismic hazard levels closely matches the ratio of IM at the same levels. This result can be valuable in developing insurance codes and regulations. However, this is not the case for the currently used IM, i.e., peak ground acceleration.

Novel Explicit Models for Assessing the Frictional Resistance of Pipe Piles Subjected to Seismic Effects

This paper introduces novel explicit models to predict the frictional resistance of open and closed-ended pipe piles subjected to seismic loading. This research employs genetic programming (GP) and multiobjective genetic algorithm-based evolutionary polynomial regression (EPR-MOGA) to develop closed-form expressions for estimating pile frictional resistance, utilizing widely used input parameters for enhanced practicality and applicability in engineering practice. The proposed models are developed using only three input variables: the corrected standard penetration test (SPT) blow count (N1)60, the pile slenderness ratio (L/D), and the peak ground acceleration (PGA). This deliberate reduction in input complexity significantly enhances the models' applicability across a wide range of geotechnical scenarios and industries. The accuracy of the developed models was assessed via the coefficient of determination (R2), root mean squared error (RMSE), and mean absolute error (MAE). In the case of the GP model, the evaluation metrics for the testing set for open-ended piles (R2, RMSE, and MAE values) are 0.89, 0.43, and 0.35, respectively, whereas the corresponding values for closed-ended piles are 0.93, 0.38, and 0.3, respectively. On the other hand, the EPR-MOGA approach achieves similarly encouraging results, with performance metrics of 0.92, 0.37, and 0.29 for open-ended piles and 0.91, 0.39, and 0.30 for closed-ended piles.

Assessment of liquefaction potential of sand distributed in the coastal area of Ninh Thuan based on SPT values

The liquefaction potential of sandy soil has been widely investigated in the world for many years, especially after the Niigata and Alaska earthquakes in 1964. In which, the SPT values were mostly used for the evaluation of liquefaction potential. In Vietnam, the potential for soil liquefaction has been recently investigated. In the coastal area of Ninh Thuan province, the sand is widely distributed and often exposed on the surface. Additionally, many wind power farms have been built in this area. Thus, it is necessary to evaluate the liquefaction potential of sand distributed in this area. In this study, the potential for sand liquefaction in the coastal area of Ninh Thuan will be evaluated based on SPT values. Two common methods for evaluation of liquefaction potential proposed by Seed and Idriss; Idriss and Boulanger were employed. The research results show that at peak ground acceleration (amax) = 0.07 g and M = 5.5, the sand in the study area is non-liquefiable (safety factor against liquefaction, FS ( 1.48). However, at amax = 0.18 g and M = 7.5, the FS varies from 0.78 to 3.66 for the Seed and Idriss method and from 0.68 to 2.05 for the Idriss and Boulanger method. In general, the FS obtained from the Seed and Idriss method is higher than that obtained from Idriss and Boulanger method. Nevertheless, this insignificantly affects the overall assessment of liquefaction potential. At amax = 0.18 g and M = 7.5, the sand distributed in the study area can be liquefied at a depth of 17 m. However, it is not liquefied when the Nspt is higher than 28 ((N1) 60cs > 20).

Soil Vulnerability Analysis Using the Microtremor Method for Mapping the Landslide Susceptibility Area in Batu City, Indonesia

Based on Regional Agency for Disaster Management (BPBD) Batu City data, Indonesia, 36 landslides have been recorded in the last three years around the Payung area, where this area connects several regions around Batu City. So, it is necessary to map areas with potential ground movement as an initial step for the local government in formulating a landslide disaster management strategy. This research aims to map landslide susceptibility areas around Payung, Batu City, identified based on the soil vulnerability index value range in the peak ground acceleration (PGA) mapping results. The data was measured using the microtremor method. There were 22 measurement points in 3 zones with different heights, and the microtremor signal was recorded for 35-40 minutes at each point. The microtremor signal from seismic recording is composed of three components (NS, EW, and Up-Down), which are used to develop the Horizontal to Vertical Spectral Ratio (HVSR) technique, where the ratio value is obtained by comparing horizontal (H) components (HNS and HEW) to the vertical component (Up-Down (V)). The research results show that landslide susceptibility areas are located at points M10, M13, and M16, with a soil vulnerability index range of 21-40.1. When a landslide occurs in that area with high vulnerability, it will impact points along Payung Street at points M3–M9. The points with high soil vulnerability index values need special treatment to reduce the impact of landslides.

Implications of Activity Rate Characterization and Fault-Based Partitioning on Probabilistic Seismic Hazard Assessment: A Case Study of Extensional Tectonic Regime in Western Anatolia, Türkiye

ABSTRACT Complex fault geometries with multiple sets of inclined active faults pose a challenge to the accurate representation of fault-based seismic sources in probabilistic seismic hazard assessment (PSHA). In the absence of slip rates associated with fault segments and the presence of sparse seismic and geodetic data, the estimation of segment-specific activity rate includes significant uncertainty. This study proposes a comprehensive procedure for defining the segment-specific activity rates and associated uncertainties in fault-based PSHA for extensional tectonic regimes and applies the procedure in the northern margin of Western Anatolian Extensional Province. The seismic sources are modeled as rupture systems with individual fault segments using the connections between available active fault traces, first-order geological complexities, earthquake catalog, and focal mechanism solutions. Alternatives to estimate and partition segment-specific activity rates based on annual slip rate, seismicity rate, and moment rate are explored. Each alternative is implemented in PSHA, and the results are compared in terms of peak ground acceleration (PGA) maps for a 475-year return period. A comparison of the 475 yr PGA maps showed that the activity rates based on annual slip rates translate into higher hazard estimates and a more uniform distribution of PGA; whereas, the activity rates based on seismicity and moment rate result in a PGA distribution that is more sensitive to the occurrence and location of previous large-magnitude events. The approach utilized to partition activity rates among parallel segments has a noticeable effect in the areas where highly asymmetric fault activity is inferred from morphology. Hence, alternative approaches for estimation and partition of activity rates are combined to model the epistemic uncertainty in segment-specific activity rates, and a repeatable procedure is developed to build fault-based seismic source models in the presence of complex fault geometries.

Co-seismic landslides susceptibility evaluation of Bayesian random forest considering InSAR deformation: a case study of the Luding Ms6.8 earthquake

Strong earthquakes can frequently trigger a large number of co-seismic landslides. Obtaining an accurate susceptibility map of co-seismic landslides is crucial for post-disaster rescue and reconstruction efforts. In this study, the pre-seismic average annual surface deformation rate of the study area was obtained using Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technology. Furthermore, the landslide hazards prior to the earthquake in multiple locations within the study area were analyzed. Subsequently, the deformation data was combined with 11 evaluation factors, including the distance to the fault and the Peak Ground Acceleration (PGA), to model the susceptibility of landslides. We constructed four models to evaluate the susceptibility of landslides in the study area: the Bayesian optimization random forest (BO-RF) model, the random forest model (RF), the logistic regression model (LR), and the support vector machine model (SVM). The BO-RF model outperformed the other models, achieving an AUC value of 0.984, an accuracy of 0.952, a precision of 0.953, a recall of 0.952, and an F1 score of 0.953. Furthermore, incorporating pre-seismic deformation features in the evaluation of co-seismic landslide susceptibility can effectively improve the reliability of model predictions, as compared to the evaluation model results without incorporating deformation factors. The obtained research results provide valuable data support for the rescue and management of disaster-stricken areas.

Parametric seismic fragility model for elephant-foot buckling in unanchored steel storage tanks

The parametric seismic fragility model of elephant-foot buckling (EFB) in the tank wall of the unanchored storage tanks is introduced by utilizing the results of a parametric study of eighteen tank-soil configurations. The model can be used to rapidly assess the seismic vulnerability to EFB for a larger number of tanks. The parametric study involved a 1D cloud-based soil response analysis to relate the ground-motion intensity measure at the bedrock with that at the free surface, and a pushover analysis of the refined finite element model of the tank to assess the engineering demand parameter in terms of axial compressive stress in the tank wall and the critical value that triggers EFB. As a consequence, the parametric seismic fragility model can be applied to intensity measures at the bedrock, as it is demonstrated for the spectral acceleration at the tank’s impulsive period, Se,bedrock,EFB, and the peak ground acceleration, PGAbedrock,EFB. The input parameters of the introduced seismic fragility model are the harmonic average shear-wave velocity in the top 30 m of soil, Vs,30, the slenderness ratio of the tank, H/R, the ratio between radius and wall thickness of the tank, R/t, and the standard deviation of log values for the intensity measure causing EFB. The model reliably predicts the median intensity measure causing the onset of EFB in the investigated tank-soil configurations, especially when Se,bedrock,EFB is selected for the intensity measure. However, further investigation is required to enhance the accuracy of predicted intensity measures that trigger EFB by considering the dynamic impact between the base plate and the foundation during an earthquake and accounting for the complete soil-structure interaction effects.

Probabilistic Seismic Hazard Assessment of the Southwestern Region of Saudi Arabia

In relation to its rapid infrastructure expansion, exemplified by projects like the Najran Valley Dam or the rehabilitation of agricultural terraces, Saudi Arabia stands out among the Arabian Gulf nations. To mitigate the earthquake-related risks effectively, it is imperative to conduct an exhaustive analysis of its natural hazards. The southwesternmost region of Saudi Arabia is the main subject area of this study for the probabilistic seismic hazard assessment (PSHA), which aims to identify the peak ground acceleration (PGA) and spectral acceleration (SA) values. The investigation encompasses a 10% and 5% probability of occurrence over a 50-year exposure time for both B/C and C NEHRP soils. In order to take into account the earthquake activity that takes place in the vicinity of the Red Sea Rift, which in fact may have an impact on the seismic hazard in this active tectonic region, different seismic source zones were especially designed for this evaluation. Various characteristics such as the uncertainties related to the b-value, the expected maximum magnitude, and different ground motion prediction equations (GMPEs) were integrated using a logic tree scheme. Additionally, regression relationships between the computed ground motion values were established, and a novel design response spectrum was developed and recommended for several cities. Regarding the key findings, it is significant to highlight that the seismic hazard decreases towards the northeast, when moving away from the Red Sea Rift, confirming anticipated trends where proximity to the rift corresponds to increased seismic hazard. Notably, cities such as Farasan Island, Jazan, Al Qunfundhah, Al Lith and Al Birk present the highest observed hazard values among all the cities analyzed. For these cities, the obtained maximum SA values for both 475 and 975 years under B/C site conditions are as follows: 0.268 g and 0.412 g, 0.121 g and 0.167 g, 0.099 g and 0.150 g, 0.083 g and 0.135 g, and 0.066 g and 0.118 g, respectively. These results emphasize the crucial necessity of adequately evaluating and thoroughly updating the seismic hazard inherent to these particular areas to enhance the risk reduction and disaster readiness initiatives.

Spatial distribution law of landslides and landslide susceptibility assessment in the eastern Himalayan syntaxis region

The eastern Himalayan syntaxis region is located on the eastern edge of the Qinghai–Tibet Plateau, and it is one of the regions with the most intense geological tectonic activity in the world. There have been many large-scale landslides in the eastern Himalayan syntaxis region and the distribution of these landslides is of great significance for the inversion of regional tectonic activity strength, major engineering construction and urban–rural planning. However, no researchers have systematically studied all these landslides of this area. In this study, based on Google Earth satellite imagery, landslides were identified using artificial visual interpretation. Then, we analysed 11 landslide-influencing factors were selected, comprising topographic factors (elevation, slope, aspect, curvature), geological environmental factors (strata, distance to faults, distance to water, distance to roads, normalized difference vegetation index), inducing factors (peak ground acceleration, rainfall), the relationships between the distribution law of landslides and influencing factors. Finally, we used the logistic regression model, the weight of evidence model and the weight of evidence–logistic regression coupled model to evaluate the landslide susceptibility.

Performance of hydraulic structures during 6 February 2023 Kahramanmaraş, Türkiye, earthquake sequence

The earthquake sequence that occurred on 6 February 2023 in Türkiye, Kahramanmaraş, had a significant impact on 140 dams, most of which are located within a distance of 50 km from surface projection of the fault rupture. These dams experienced moderate to high levels of seismic intensity, with peak ground acceleration (PGA) estimated to vary between 0.1 and 1.3 g during the Pazarcık earthquake and 0.15 to 0.45 g during the Elbistan earthquake, depending on their proximity to the fault rupture. Although all dams were able to maintain water-retaining capabilities, some of them suffered from moderate to large permanent deformations. As part of the emergency response measures, the water levels at two of these dams, namely Sultansuyu and Arıklıkaş, were lowered in a controlled manner. Following the earthquakes, a comprehensive survey of all hydraulic structures within the influence zone was conducted, and the findings are represented in this study. These findings revealed that earthfill and rockfill dams sustained more significant damage compared with concrete dams, particularly in areas close to the fault rupture, where the shaking intensity was most pronounced. The amount of permanent displacements was observed to consistently increase with the height of the dam’s transverse section.

Seismic Response Prediction of Rigid Rocking Structures Using Explainable LightGBM Models

This study emphasizes the explainability of machine learning (ML) models in predicting the seismic response of rigid rocking structures, specifically using the LightGBM algorithm. By employing SHapley Additive exPlanations (SHAP), partial dependence plots (PDP), and accumulated local effects (ALE), a comprehensive feature importance analysis has been performed. This revealed that ground motion parameters, particularly peak ground acceleration (PGA), are critical for predicting small rotations, while structural parameters like slenderness and frequency are more significant for larger rotations. Utilizing an extensive dataset generated from nonlinear time history analyses, the trained LightGBM model demonstrated high accuracy in estimating the maximum rotation angle of rigid blocks under natural ground motions. The study also examined the sensitivity of model performance to lower bound thresholds of the target variable, revealing that reduced feature sets can maintain predictive performance effectively. These findings advance ML-based modeling of seismic rocking responses, providing interpretable and accurate models that enhance our understanding of rocking structures’ dynamic behavior, which is crucial for designing resilient structures and improving seismic risk assessments. Future research will focus on incorporating additional parameters and exploring advanced ML techniques to further refine these models.

Probabilistic prediction of post-earthquake rubble distribution range for masonry structures

In previous earthquakes, masonry structures have experienced large-scale localized or total collapse, and the rubble distribution formed after the collapse has had a significant impact on the post-earthquake transportation system. This paper analyses the rubble distribution characteristics of masonry structures on different floors (3, 5, and 7 floors) under 22 FEMA-recommended far-field ground motion records. A range model for debris distribution for masonry structures considering peak ground accelerations and building height is first proposed. Then, the risk range model for masonry structure rubble distribution was developed by considering the fragility of building collapse and the uncertainty of rubble distribution. Based on the model, it is able to predict the range of rubble distribution and the risk range of rubble distribution for buildings of different heights under different peak ground accelerations, and calculate the acceptable rubble distribution distance according to the exceeding probability of rubble appearing within a certain distance. It can provide data support for government decision makers to formulate emergency plans for post-earthquake transportation systems before the earthquake.

Seismic performance and cost comparison of RC moment resisting and dual frames using UBC 97 and IBC 2021

The transition from the Uniform Building Code (UBC-97) to the International Building Code (IBC-21) marked a major shift in the definition of seismic hazard. The term “seismic hazard” in the form of peak ground acceleration (PGA) is replaced by spectral acceleration. This paper investigates the effect of using new seismic hazards on the structural performance of reinforced concrete (RC) buildings. It also looks into the financial impact on the capital costs of new buildings. Useful insights are made to understand the structural performance and financial impact of adopting IBC 21 for structural design in contrast to UBC 97. This study was carried out from the perspective of a developing country, Pakistan. Reinforced concrete moment resisting and dual frames are used as the main structural system of a typical 7-story residential building to investigate the aforementioned effect. The frames are assumed to be located in two locations with high and low seismic hazards. The effect on structural performance is investigated via nonlinear pushover analysis. Financial impact is judged mainly through cost estimation for steel and concrete. A detailed discussion is also presented on the seismic design guidelines in both codes.

Empirical relationships between Arias Intensity and peak ground acceleration for western China

There is little available attenuation relationship for Arias Intensity (AI) in China. Empirical relationships between AI and peak ground acceleration (PGA) provide another option for predicting AI. We establish empirical relationships for AI and PGA for western China, utilizing 3,169 horizontal and 979 vertical strong motion records with PGA ≥0.01 g from 274 earthquakes (MS 4.0–8.0), originating in eight provinces in southwest (Yunnan, Sichuan) and northwest China (Gansu, Shaanxi, Ningxia, Qinghai, Inner Mongolia, and Xinjiang). The influences of MS epicenter distance, and site conditions indicators VS30, generic site classes (i.e., rock and soil) are explored. The results show that the logarithm of AI increases linearly with the increase of the logarithm of PGA and MS, and decreases with the logarithm of VS30. However, the influence of site conditions on AI-PAG relationships can't be recognized by the simple generic rock and soil site classes. The epicenter distance has little effect on the AI-PAG relationships. Empirical relationships are developed to estimate horizontal or vertical AI as a function of PGA (basic model), PGA and MS (model 2) for southwest, northwest, and western China, using all the records. Empirical relationships for AI as a function of PGA, MS, and VS30 (model 1) are established using the 2,248 horizontal (70.9% of the total) and 670 vertical (68.4% of the total) records with VS30 between 148 and 841m/s. The notable disparity between model 1 of the southwest and northwest regions is chiefly attributed to local site conditions, indicating that the AI-PGA correlation is region-dependent. These findings enable one way of estimating AI for western China and will contribute to a better understanding of AI attenuation.

Behavior of a Precast Bridge Pier with Basalt Fiber-Reinforced Polymer (BFRP)-Strengthened Segments under Seismic Loading.

The precast segmental column (PSC) has been proposed for reducing onsite construction time and minimizing impacts on traffic and the environment. It has been proven to have good seismic performance according to previous studies. However, due to the rocking behavior of the column, the toe of the bottom segment could experience excessive compressive damage. In addition, the commonly used steel rebars in the PSC could experience corrosion problems during the service life of the structure. Moreover, ordinary Portland cement concrete (OPC) is normally used in the construction of the PSC, but the manufacturing processes of the OPC could emit a lot of carbon dioxide. This paper investigates the seismic performance of PSCs incorporating Basalt Fiber Reinforced Polymer (BFRP) bars and geopolymer concrete (GPC) segments. To mitigate the concrete crushing damage of the segment, the BFRP sheet was used to wrap the bottom segment of one of the specimens. The results revealed that the BFRP-reinforced geopolymer concrete PSC exhibited good seismic performance with minimal damage and small residual displacement. Strengthening the bottom segment with BFRP wrapping proved to be effective in reducing concrete damage. As a result, the column with BFRP wrap demonstrated the ability to withstand ground motions with higher Peak Ground Acceleration (PGA) compared to the column without strengthening.

Estimating S-wave amplitude for earthquake early warning in New Zealand: Leveraging the first 3 seconds of P-Wave

This study addresses the critical question of predicting the amplitude of S-waves during earthquakes in Aotearoa New Zealand (NZ), a highly earthquake-prone region, for implementing an Earthquake Early Warning System (EEWS). This research uses ground motion parameters from a comprehensive dataset comprising historical earthquakes in the Canterbury region of NZ. It explores the potential to estimate the damaging S-wave amplitude before it arrives, primarily focusing on the initial P-wave signals. The study establishes nine linear regression relationships between P-wave and S-wave amplitudes, employing three parameters: peak ground acceleration, peak ground velocity, and peak ground displacement. Each relationship’s performance is evaluated through correlation coefficient (R), coefficient of determination (R²), root mean square error (RMSE), and 5-fold Cross-validation RMSE, aiming to identify the most predictive empirical model for the Canterbury context. Results using a weighted scoring approach indicate that the relationship involving P-wave Peak Ground Velocity (Pv) within a 3-second window strongly correlates with S-wave Peak Ground Acceleration (PGA), highlighting its potential for EEWS. The selected empirical relationship is subsequently applied to establish a P-wave amplitude (Pv) threshold for the Canterbury region as a case study from which an EEWS could benefit. The study also suggests future research exploring complex machine learning models for predicting S-wave amplitude and expanding the analysis with more datasets from different regions of NZ.

Scenario-based seismic hazard for horizontal and vertical ground motions in central Italy

We propose an innovative methodology for seismic emergency planning and earthquake risk mitigation in central Italy by integrating three prototypal earthquake scenarios. The different scenarios derive maximum earthquake magnitudes from different input data. The first scenario utilizes local rheological, geological, and geophysical conditions; the second scenario considers the study area fault characteristics, while the third scenario relies on the cluster analysis of historical and instrumental earthquake records. The magnitudes and related uncertainties are combined using a conflation method to derive the expected ground motions for a grid of sites in central Italy. The resulting scenarios include peak ground acceleration and spectral ordinates, presented as maps and spectra for two selected localities. The vertical component of ground motion is also presented, because it is essential for accurately assessing the response of short-period structures. Our methodology complements the more classic seismic hazard analyses, offering additional insights for earthquake contingency planning and loss analysis. The proposed methodology is flexible; multiple models and ongoing advancements in scenario practice (near-field effects, vertical ground motion, and the choice of ground motion models) can be easily incorporated, increasing the effectiveness of seismic scenario modeling in seismic emergency planning and risk mitigation.

Co-seismic and rainfall-triggered landslide hazard susceptibility assessment for Uganda derived using fuzzy logic and geospatial modelling techniques

AbstractUganda has suffered from many damaging landslides like the 1966 Rwenzori, 1994 Kisomoro and 2010 Bududa events. Despite escalating landslide risks exacerbated by rapid deforestation, urbanization and population growth coupled with a substandard building stock, comprehensive national co-seismic and rainfall-induced landslide hazard and risk maps for Uganda do not exist. This study therefore aims to conduct landslide hazard assessment and zonation for Uganda using a geospatial-based fuzzy logic methodology. In this methodology, landslide frequency ratios obtained for the 1966 Toro and 1994 Kisomoro earthquakes are assigned to the stochastic event-based probabilistic seismic hazard map derived using OpenQuake-engine. The available co-seismic and rainfall-induced landslide inventory datasets are used to derive the distribution of landslide frequency ratios based on geology, topographic slope position index, slope aspect, slope angle, distance from streams, and proximity to major active faults. The spatial distribution of fuzzy membership functions obtained from frequency ratios are overlaid and aggregated to produce landslide susceptibility maps showing relative probabilities of landslide occurrences across Uganda. Results indicate that the highest overall landslide hazard susceptibility is expected in areas comprising highly weathered outcropping rocks of precambrian granites, dominantly metasedimentary, and granulites and gneisses geologies within 40 km from major active faults; where the bedrock peak ground acceleration ≥ 0.1 g, topographic position index ≥ 3.8, slope gradient ≥ 10°, and the distance from streams ≤ 1.25 km. These findings can inform Uganda’s directorate of disaster preparedness and management towards pioneering the development of co-seismic landslide risk mitigation measures for the country.

An Earthquake Ground-Motion Model for Southwest Iberia

ABSTRACT Ground-motion models (GMMs) are fundamental for the estimation of ground shaking for probabilistic seismic hazard assessment. Because of the paucity of ground motion recordings in regions of low seismicity, stochastic approaches are often employed to generate synthetic data. In this study, we developed a GMM using a stochastic simulation approach for southwest Iberia—a zone for which seismic hazard is usually assessed using models developed for other regions. We collected geological, tectonic, and ground-motion data for offshore and inland Iberia, and calibrated several parameters for a stochastic simulation. The resulting synthetic response spectra were used to train a machine learning algorithm (artificial neural network) capable of predicting peak ground acceleration, peak ground velocity, and spectral acceleration on rock (VS30=760 m/s), along with the associated between-event and within-event terms. The resulting model was compared against other existing models for stable continental regions and ground-motion recordings for Portugal and Spain. The results indicate a good agreement with observations and the model can be used directly in probabilistic seismic hazard analysis for southwest Iberia.