Improving Urban Seismic Risk Estimates for Bishkek, Kyrgyzstan, Incorporating Recent Geological Knowledge of Hazards

Many cities are built on or near active faults, which pose seismic hazard and risk to the urban population. This risk is exacerbated by city expansion, which may obscure signs of active faulting. Here we estimate the risk to Bishkek city, Kyrgyzstan, due to realistic earthquake scenarios based on historic earthquakes in the region and improved knowledge of the active faulting. We use previous literature and fault mapping, combined with new high-resolution digital elevation models to identify and characterise faults that pose a risk to Bishkek. We then estimate the hazard (ground shaking), damage to residential buildings and losses (economical cost and fatalities) using the Global Earthquake Model OpenQuake engine. We model historical events and hypothetical events on a variety of faults that could plausibly host significant earthquakes. This includes proximal, recognised, faults as well as a fault under folding in the north of the city that we identify using satellite DEMs. We find that potential earthquakes on faults nearest to Bishkek - Issyk Ata, Shamsi Tunduk, Chonkurchak and the northern fault - would cause the most damage to the city. An Mw 7.5 earthquake on the Issyk Ata fault could potentially cause 7,900 ± 2600 completely damaged buildings, a further 16,400 ± 2000 damaged buildings and 2400 ± 1500 fatalities. It is vital to properly identify, characterise and model active faults near cities as modelling the northern fault as a Mw 6.5 instead of Mw 6.0 would result in 37% more completely damaged buildings and 48% more fatalities.

Source reconstruction of the 1969 Majene, Sulawesi earthquake and tsunami: A preliminary study

We studied the February 23rd, 1969 M7.0 Majene, Sulawesi earthquake and tsunami. It was followed by tsunami reported at five locations. At least 64 people were killed and severe damage on infrastructures were reported in Majene region. Based on damage data, we estimated that the maximum intensity of the earthquake was MMI VIII. Focal mechanisms, derived using first motion polarity analysis, indicated that the earthquake had a thrust mechanism. Furthermore, we built hypothetical earthquake scenarios based on a rectangular fault plane of 40 km × 20 km with a homogeneous slip model of 1.5 m. We run the Open Quake and the JAGURS code to validate the macroseismic and tsunami observation data, respectively. Our best-fitted earthquake model generates maximum intensity of 8+ which is in line with the reported macroseismic data. However, the maximum simulated tsunami height from all scenario earthquakes is 2.25 m which is smaller than the 4 m tsunami height observed at Pelattoang. The possibility of contribution of another mechanism to tsunami generation requires further investigation.

Characteristics of building fragility curves for seismic and non-seismic tsunamis: case studies of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean tsunamis

Indonesia has experienced several tsunamis triggered by seismic and non-seismic (i.e., landslides) sources. These events damaged or destroyed coastal buildings and infrastructure and caused considerable loss of life. Based on the Global Earthquake Model (GEM) guidelines, this study assesses the empirical tsunami fragility to the buildings inventory of the 2018 Sunda Strait, 2018 Sulawesi–Palu, and 2004 Indian Ocean (Khao Lak–Phuket, Thailand) tsunamis. Fragility curves represent the impact of tsunami characteristics on structural components and express the likelihood of a structure reaching or exceeding a damage state in response to a tsunami intensity measure. The Sunda Strait and Sulawesi–Palu tsunamis are uncommon events still poorly understood compared to the Indian Ocean tsunami (IOT), and their post-tsunami databases include only flow depth values. Using the TUNAMI two-layer model, we thus reproduce the flow depth, the flow velocity, and the hydrodynamic force of these two tsunamis for the first time. The flow depth is found to be the best descriptor of tsunami damage for both events. Accordingly, the building fragility curves for complete damage reveal that (i) in Khao Lak–Phuket, the buildings affected by the IOT sustained more damage than the Sunda Strait tsunami, characterized by shorter wave periods, and (ii) the buildings performed better in Khao Lak–Phuket than in Banda Aceh (Indonesia). Although the IOT affected both locations, ground motions were recorded in the city of Banda Aceh, and buildings could have been seismically damaged prior to the tsunami's arrival, and (iii) the buildings of Palu City exposed to the Sulawesi–Palu tsunami were more susceptible to complete damage than the ones affected by the IOT, in Banda Aceh, between 0 and 2 m flow depth. Similar to the Banda Aceh case, the Sulawesi–Palu tsunami load may not be the only cause of structural destruction. The buildings' susceptibility to tsunami damage in the waterfront of Palu City could have been enhanced by liquefaction events triggered by the 2018 Sulawesi earthquake.

The Making of the NEAM Tsunami Hazard Model 2018 (NEAMTHM18)

The NEAM Tsunami Hazard Model 2018 (NEAMTHM18) is a probabilistic hazard model for tsunamis generated by earthquakes. It covers the coastlines of the North-eastern Atlantic, the Mediterranean, and connected seas (NEAM). NEAMTHM18 was designed as a three-phase project. The first two phases were dedicated to the model development and hazard calculations, following a formalized decision-making process based on a multiple-expert protocol. The third phase was dedicated to documentation and dissemination. The hazard assessment workflow was structured in Steps and Levels. There are four Steps: Step-1) probabilistic earthquake model; Step-2) tsunami generation and modeling in deep water; Step-3) shoaling and inundation; Step-4) hazard aggregation and uncertainty quantification. Each Step includes a different number of Levels. Level-0 always describes the input data; the other Levels describe the intermediate results needed to proceed from one Step to another. Alternative datasets and models were considered in the implementation. The epistemic hazard uncertainty was quantified through an ensemble modeling technique accounting for alternative models’ weights and yielding a distribution of hazard curves represented by the mean and various percentiles. Hazard curves were calculated at 2,343 Points of Interest (POI) distributed at an average spacing of ∼20 km. Precalculated probability maps for five maximum inundation heights (MIH) and hazard intensity maps for five average return periods (ARP) were produced from hazard curves. In the entire NEAM Region, MIHs of several meters are rare but not impossible. Considering a 2% probability of exceedance in 50 years (ARP≈2,475 years), the POIs with MIH >5 m are fewer than 1% and are all in the Mediterranean on Libya, Egypt, Cyprus, and Greece coasts. In the North-East Atlantic, POIs with MIH >3 m are on the coasts of Mauritania and Gulf of Cadiz. Overall, 30% of the POIs have MIH >1 m. NEAMTHM18 results and documentation are available through the TSUMAPS-NEAM project website (http://www.tsumaps-neam.eu/), featuring an interactive web mapper. Although the NEAMTHM18 cannot substitute in-depth analyses at local scales, it represents the first action to start local and more detailed hazard and risk assessments and contributes to designing evacuation maps for tsunami early warning.

Modeling earthquake occurrence and recurrence for supercycles and clusters

<p>Long records often show large earthquakes occurring in supercycles—temporal clusters of seismicity, cumulative displacement, and cumulative strain release separated by less active intervals. Presently used earthquake recurrence models do not account for the time dependence and clustering. Poisson models assume that earthquake recurrence is time-independent, but seismicity studies have shown that time is needed to accumulate strain along a fault before another large earthquake. Seismic cycle/renewal models account for this time-dependence but assume that all strain is released after large earthquakes and fail to replicate clustered earthquake behavior. The resulting probability estimates for recurrence of the next earthquake thus depend crucially on whether the cluster is treated as ongoing or over.</p><p>In this study, we have reformulated our previously developed Long-Term Fault Memory (LTFM) earthquake model as a Markov process to better quantify long-term earthquake behavior and the probability of future earthquakes. In the LTFM model, the probability of a large earthquake reflects accumulated strain rather than elapsed time. The probability increases with accumulated strain (and time) until an earthquake happens, after which the probability decreases, but not necessarily to zero. This simple, strain-driven recurrence model yields realistic sequences of large earthquakes with periods of elevated activity followed by longer quiescence. Using the Markov formulation, we explore long-term earthquake behavior and how to use paleoseismic records to better estimate the recurrence and probability of future large earthquakes.</p>

Contribution of a new seismic amplification factor map approach for shakemaps improvement: the Croatia Mw=6.4 earthquake scenario.

<p>Estimation of site effects over large areas is a key-issue in a seismic risk mitigation perspective.</p><p>We prove here that the IGAG20 approach (Falcone et al., 2021), developed for the estimation of the stratigraphic Amplification Factors (AF) at a national scale for Italy, can be used in international context, as it is based on AF-V<sub>s30</sub> laws developed according to 40 geo-morphological clusters available globally after Iwahashi et al. (2018) and V<sub>s30 </sub>proxy laws after Mori et al. (2020).</p><p>The availability of AF maps is fundamental for the improvement of the estimates of surface shaking for the "shakemaps" produced after the seismic events, and for the consequent improvement of the preliminary estimates of coseismic effects (i.e. landslides and liquefaction) and damage of residential buildings.</p><p>The IGAG20 approach was implemented for evaluating the shaking maps for the recent Mw=6.4 Croatian seismic event, with a focus on the three most affected localities: Petrinjia, Sisak, and Glina. From the OpenQuake engine, Silva et al. (2014), a stochastic scenario analysis was performed and PGV and PGA shaking maps amplified with AF maps were produced. With the PGV map, landslide and liquefaction probability maps are produced respectively with the Nowicki et al. (2018) and Zhu et al. (2017) models. With the PGA map, a preliminary residential buildings damage estimation is produced and compared with the EMS98 damage distribution available from the grading maps produced by COPERNICUS (https://emergency.copernicus.eu/mapping/list-of-components/EMSR491 ). Finally, all the shaking maps are compared with USGS products (https://earthquake.usgs.gov/earthquakes/eventpage/us6000d3zh/executive).</p><p><strong>References </strong></p><p>Falcone, G., Mendicelli, A., Moscatelli, M., Romagnoli, G., Peronace, E., Naso, G., Acunzo G., Porchia, A., Tarquini, E., 2021. Seismic amplification maps of Italy based on site-specific microzonation dataset and one-dimensional numerical approach Eng. Geol. - Under review</p><p>Iwahashi, J., Kamiya, I., Matsuoka, M., Yamazaki, D., 2018. Global terrain classification using 280 m DEMs: segmentation, clustering, and reclassification. Prog. Earth Planet. Sci. https://doi.org/10.1186/s40645-017-0157-2</p><p>Mori, F., Mendicelli, A., Moscatelli, M., Romagnoli, G., Peronace, E., Naso, G., 2020. A new Vs30 map for Italy based on the seismic microzonation dataset. Eng. Geol. https://doi.org/10.1016/j.enggeo.2020.105745</p><p>Nowicki Jessee, M.A., Hamburger, M.W., Allstadt, K., Wald, D.J., Robeson, S.M., Tanyas, H., Hearne, M., Thompson, E.M., 2018. A Global Empirical Model for Near-Real-Time Assessment of Seismically Induced Landslides. J. Geophys. Res. Earth Surf. https://doi.org/10.1029/2017JF004494</p><p>Silva, V., Crowley, H., Pagani, M., Monelli, D., Pinho, R., 2014. Development of the OpenQuake engine, the Global Earthquake Model’s open-source software for seismic risk assessment. Nat. Hazards. https://doi.org/10.1007/s11069-013-0618-x</p><p>Zhu, J., Baise, L.G., Thompson, E.M., 2017. An updated geospatial liquefaction model for global application. Bull. Seismol. Soc. Am. https://doi.org/10.1785/0120160198</p>

Estimating of the b-Value Based on the Characteristic Earthquake Model

[Formula: see text]-value of the Gutenberg–Richter relation as an earthquake precursor depends on the tectonic setting features. This paper presents an alternative method to calculate [Formula: see text]-value in the presence of characteristic earthquakes. The proposed equation is based on the maximum likelihood method applied on the probability density function of the characteristic earthquake model. Data from real and simulated catalogs were used to evaluate the accuracy of the proposed model. For this purpose, 224 seismic event catalogs with various properties including catalogs’ sample size, the ratios of characteristic earthquakes number to catalog’s sample size [Formula: see text] and different magnitude of characteristic earthquakes were simulated. According to the estimated [Formula: see text]-values, the earthquake occurrence probability was calculated and discussed. The results indicate that the proposed method of estimation for [Formula: see text]-value has more adaptable consideration of the characteristic earthquake behavior.

Synthetic seismicity distribution in Guerrero–Oaxaca subduction zone, Mexico, and its implications on the role of asperities in Gutenberg–Richter law

Seismicity and magnitude distributions are fundamental for seismic hazard analysis. The Mexican subduction margin along the Pacific Coast is one of the most active seismic zones in the world, which makes it an optimal region for observation and experimentation analyses. Some remarkable seismicity features have been observed on a subvolume of this subduction region, suggesting that the observed simplicity of earthquake sources arises from the rupturing of single asperities. This subregion has been named SUB3 in a recent seismotectonic regionalization of Mexico. In this work, we numerically test this hypothesis using the TREMOL (sThochastic Rupture Earthquake MOdeL) v0.1.0 code. As test cases, we choose four of the most significant recent events (6.5 < Mw < 7.8) that occurred in the Guerrero–Oaxaca region (SUB3) during the period 1988–2018, and whose associated seismic histories are well recorded in the regional catalogs. Synthetic seismicity results show a reasonable fit to the real data, which improves when the available data from the real events increase. These results give support to the hypothesis that single-asperity ruptures are a distinctive feature that controls seismicity in SUB3. Moreover, a fault aspect ratio sensitivity analysis is carried out to study how the synthetic seismicity varies. Our results indicate that asperity shape is an important modeling parameter controlling the frequency–magnitude distribution of synthetic data. Therefore, TREMOL provides appropriate means to model complex seismicity curves, such as those observed in the SUB3 region, and highlights its usefulness as a tool to shed additional light on the earthquake process.

Nowcasting Avalanches as Earthquakes and the Predictability of Strong Avalanches in the Olami-Feder-Christensen Model

Nowcasting earthquakes, suggested recently as a method to estimate the state of a fault and hence the seismic risk, is based on the concept of natural time. Here, we generalize nowcasting to a prediction method the merits of which are evaluated by means of the receiver operating characteristics. This new prediction method is applied to a simple (toy) model for the waiting (natural) time of the stronger earthquakes, real seismicity, and the Olami-Feder-Christensen earthquake model with interesting results revealing acceptable to excellent or even outstanding performance.