The tsunami observations produced by the 2018 magnitude 7.5 Palu strike‐slip earthquake challenged the traditional basis underlying tsunami hazard assessments and early warning systems. We analyzed ...an extraordinary collection of 38 amateur and closed circuit television videos to show that the Palu tsunamis devastated widely separated coastal areas around Palu Bay within a few minutes after the mainshock and included wave periods shorter than 100 s missed by the local tide station. Although rupture models based on teleseismic and geodetic data predict up to 5‐m tsunami runups, they cannot explain the higher surveyed runups nor the tsunami waveforms reconstructed from video footage, suggesting either these underestimate actual seafloor deformation and/or that non‐tectonic sources were involved. Post‐tsunami coastline surveys combined with video evidence and modeled tsunami travel times suggest that submarine landslides contributed to tsunami generation. The video‐based observations have broad implications for tsunami hazard assessments, early warning systems, and risk‐reduction planning.
Plain Language Summary
Tsunami hazard assessment is routinely based on assessing the impacts of long‐period waves generated by vertical seafloor motions reaching the coast tens of minutes after the earthquake in typical subduction‐zone environments. This view is inadequate for assessing hazard associated with strike‐slip earthquakes such as the magnitude 7.5 2018 Palu earthquake, which resulted in tsunami effects much larger than would normally be associated with horizontal fault motion. From an extraordinary collection of 38 amateur and closed circuit television videos we estimated tsunami arrival times, amplitudes, and wave periods at different locations around Palu Bay, where the most damaging waves were reported. We found that the Palu tsunamis devastated widely separated coastal areas within a few minutes after the mainshock and included unusually short wave periods, which cannot be explained by the earthquake fault slip alone. Post‐tsunami surveys show changes in the coastline, and this combined with video footage provides potential locations of submarine landslides as tsunami sources that would match the arrival times of the waves. Our results emphasize the importance of estimating tsunami hazards along coastlines bordering strike‐slip fault systems and have broad implications for considering shorter‐period nearly instantaneous tsunamis in hazard mitigation and tsunami early warning systems.
Key Points
Video footage shows tsunami inundation within 1‐2 min after the mainshock with periods shorter than those recorded by the local tide gauge
Published rupture models predict up to 5‐m tsunami runups but cannot explain their timing, amplitude, and period as reconstructed from videos
Videos reveal key role of suitably designed escape routes and vertical platforms for timely self‐evacuation from rapid tsunami inundation
Fluid injection can cause extensive earthquake activity, sometimes at unexpectedly large distances. Appropriately mitigating associated seismic hazards requires a better understanding of the zone of ...influence of injection. We analyze spatial seismicity decay in a global dataset of 18 induced cases with clear association between isolated wells and earthquakes. We distinguish two populations. The first is characterized by near-well seismicity density plateaus and abrupt decay, dominated by square-root space-time migration and pressure diffusion. Injection at these sites occurs within the crystalline basement. The second population exhibits larger spatial footprints and magnitudes, as well as a power law-like, steady spatial decay over more than 10 kilometers, potentially caused by poroelastic effects. Far-reaching spatial effects during injection may increase event magnitudes and seismic hazard beyond expectations based on purely pressure-driven seismicity.
A systematic decay of the aftershock rate over time is one of the most fundamental empirical laws in Earth science. However, the equally fundamental effect of a mainshock on the size distribution of ...subsequent earthquakes has still not been quantified today and is therefore not used in earthquake hazard assessment. We apply a stacking approach to well‐recorded earthquake sequences to extract this effect. Immediately after a mainshock, the mean size distribution of events, or b value, increases by 20–30%, considerably decreasing the chance of subsequent larger events. This increase is strongest in the immediate vicinity of the mainshock, decreasing rapidly with distance but only gradually over time. We present a model that explains these observations as a consequence of the stress changes in the surrounding area caused by the mainshocks slip. Our results have substantial implications for how seismic risk during earthquake sequences is assessed.
Plain Language Summary
The effect of a mainshock on the size distribution of subsequent earthquakes has not been quantified and is therefore not used in earthquake hazard assessment. To quantify this effect, we develop a stacking approach centered on the mainshock time and apply it to for 31 well‐recorded aftershock sequences from around the world. We found that after a mainshock the earthquake size distribution shifts toward relative more smaller events, increasing the so‐called b value by 20–30%. One of the consequences of our finding is that the rates of large aftershocks are overestimated by the currently used models. Our result is fully consistent with both laboratory measurements and modeling, and we present a conceptual model that explains our findings.
Key Points
We develop a stacking approach to b value time series centered on the mainshock time in order to extract the generic behavior
Applying this approach to well‐recorded aftershock sequences, we demonstrate that the b value increases by 20–30% after a mainshock
We develop a Coulomb stress‐based model explaining the postmainshock b value increase and propose an empirical relationship to be used to forecast aftershock hazard
Globally and yearly, individual hazards and hazard interrelations have the potential to result in socio-economic losses. Here, in this critical review, we use grey- and peer-review literature to ...identify and compare current research available for the quantification of hazard interrelations, focussing on 14 different natural hazards. We first provide a historical context for quantitative single hazard and multi-hazard assessment. We then construct a literature database with 146 references related to multi-hazard interrelations. We use our literature database to identify trends for hazard interrelation and multi-hazard and from these group hazard interrelations into five types: triggering, change condition, compound, independence and mutually exclusive. Our critical review identifies 19 different modelling methods to quantify natural hazard interrelationships which we cluster into three broad modelling approaches: stochastic, empirical, and mechanistic. We then synthesize results of our classification of quantification methods for hazard interrelationships and using two matrices illustrate this in practice for 24 different interrelations between 14 natural hazards, one for cascading hazards (temporal order in the multi-hazard event) and one for compound hazards (two or more hazards acting together). Finally, we provide examples of applications for each the three quantitative modelling approaches defined. We believe that this review will lead to a better understanding of quantification methodologies for hazard interrelations between different sub-disciplines that focus on natural hazards, thus aiding cross-disciplinary approaches for better understanding potential risk related to multi-hazard events.
This study is an investigation on spatio-chemical, contamination sources (using multivariate statistics), and health risk assessment arising from the consumption of groundwater contaminated with ...trace and toxic elements in the Chhaprola Industrial Area, Gautam Buddha Nagar, Uttar Pradesh, India. In this study 33 tubewell water samples were analyzed for 28 elements using ICP-OES. Concentration of some trace and toxic elements such as Al, As, B, Cd, Cr, Mn, Pb and U exceeded their corresponding WHO (2011) guidelines and BIS (2012) standards while the other analyzed elements remain below than those values. Background γ and β radiation levels were observed and found to be within their acceptable limits. Multivariate statistics PCA (explains 82.07 cumulative percent for total 6 of factors) and CA indicated (mixed origin) that natural and anthropogenic activities like industrial effluent and agricultural runoff are responsible for the degrading of groundwater quality in the research area. In this study area, an adult consumes 3.0 L (median value) of water therefore consuming 39, 1.94, 1461, 0.14, 11.1, 292.6, 13.6, 23.5 μg of Al, As, B, Cd, Cr, Mn, Pb and U from drinking water per day respectively. The hazard quotient (HQ) value exceeded the safe limit of 1 which for As, B, Al, Cr, Mn, Cd, Pb and U at few locations while hazard index (HI) > 5 was observed in about 30% of the samples which indicated potential health risk from these tubewells for the local population if the groundwater is consumed.
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•Spatio-chemical of trace and toxic elements in the groundwater of an industrial area.•Comparative analysis of concentration with WHO and BIS standards for elements.•Survey study on background radiation in the study area.•Estimation of total daily intake and body burden from ingestion of trace elements.•Health risk assessment for trace and toxic elements.
The paper presents the results of roof fall hazard analysis for the copper mines in Poland. At first, RMR and RFRI systems have been checked as a tool for roof fall hazard assessment. It was proved ...that rock mass deteriorates in time because of mining operation at the site, hence the roof fall phenomena analysis needs a new approach. In the next step of the analysis the key factors of roof deterioration were determined, and divided into four groups: geological, mining, technical and monitoring. It was demonstrated that only regular roof monitoring can ensure the proper rock fall hazard assessment. Subsequently, the artificial neural network was created and several dozen simulations were conducted. As a result, two dimensionless indices were developed. The first one shows predisposition of a part of the rock mass to destruction, dislocation and deformation - CRFP - Coefficient of Roof Fall – Predisposition and the second one represents predisposition and possibility of maintaining of the working - CRFM- Coefficient of Roof Fall - Maintenance. The research on roof fall details and the running workings’ roof observations allowed for categorization of the values of both indices, and providing that way the information about roof stability CRFP, and the information about necessary measures and solutions for the supervisory staff in regard of monitoring of the roof rocks CRFM. Both indices allow for a reliable roof fall hazard assessment by comprehensively combining information from monitoring, observations and investigations.
The Xianshuihe (XSH) fault in eastern Tibet is one of the most active faults in China, with the next large earthquake most likely to occur along its SE part, where the fault splits into three ...parallel branches: Yalahe, Selaha and Zheduotang (ZDT). Precisely quantifying their slip rates at various timescales is essential to evaluate regional earthquake hazard. Here, we expand our previous work on the Selaha fault to the nearby ZDT and Moxi (MX) faults, and add observations on the Yalahe fault and on the newly discovered Mugecuo South fault zone. Using tectonic‐geomorphology approaches with 10Be dating, we had previously determined average late Quaternary slip rates of 9.75 ± 0.15 and 4.4 ± 0.5 mm/yr along the NW and SE Selaha fault, respectively. Using the same methods here, we determine a slip rate of 3.4–4.8 mm/yr on the ZDT fault and of 9.6–13.4 mm/yr on the MX fault. This is consistent with the southeastward slip rate increase we had proposed along the XSH fault system from 6‐8 mm/yr (Ganzi fault) to ∼10 mm/yr (Selaha fault), and >9.6 mm/yr (MX fault). We propose a new model for the SE XSH fault, where the large‐scale Mugecuo pull‐apart basin lies within an even larger scale compressive uplift zone in a restraining bend of the XSH fault, where the highest peak in eastern Tibet is located (Gongga Shan, 7,556 m). Our slip rate determination helps to constrain a relatively high regional Mw ∼ 7 earthquake hazard at present on the SE XSH fault.
Plain Language Summary
The Xianshuihe (XSH) fault in eastern Tibet is one of the most active faults in China, with the next large earthquake most likely to occur along its southeastern part, where the fault zone consists of four parallel branches with complicated geometries. Studying the activity and slip rate of each branch is essential to evaluate regional earthquake hazard, especially because they cross a major city (Kangding), and because of the imminent construction of the Chengdu‐Lhasa railroad. Here, we expand our previous slip rate study on one fault branch (Selaha) to two additional ones (Zheduotang and Moxi), together with key observations on the newly discovered “Mugecuo South fault zone.” We find that the rate over the last ∼100,000 years may increase southeastwards along the XSH fault system, as previously suggested. The fast slip rates and their complex spatial distribution in the Kangding region reveal a high earthquake hazard (Mw ∼ 7) at present.
Key Points
We determined late Quaternary slip rates of 3.4–4.8 and 9.6–13.4 mm/yr along the Zheduotang (ZDT) and Moxi segments, respectively
We suggest a SE rate increase along the Xianshuihe fault system from Ganzi to Moxi
We discovered a new active fault (Mugecuo South) between Selaha and ZDT segments, a large‐scale pull‐apart within an uplift zone
The identification of landslide-prone areas is an essential step in landslide hazard assessment and mitigation of landslide-related losses. In this study, we applied two novel deep learning ...algorithms, the recurrent neural network (RNN) and convolutional neural network (CNN), for national-scale landslide susceptibility mapping of Iran. We prepared a dataset comprising 4069 historical landslide locations and 11 conditioning factors (altitude, slope degree, profile curvature, distance to river, aspect, plan curvature, distance to road, distance to fault, rainfall, geology and land-sue) to construct a geospatial database and divided the data into the training and the testing dataset. We then developed RNN and CNN algorithms to generate landslide susceptibility maps of Iran using the training dataset. We calculated the receiver operating characteristic (ROC) curve and used the area under the curve (AUC) for the quantitative evaluation of the landslide susceptibility maps using the testing dataset. Better performance in both the training and testing phases was provided by the RNN algorithm (AUC = 0.88) than by the CNN algorithm (AUC = 0.85). Finally, we calculated areas of susceptibility for each province and found that 6% and 14% of the land area of Iran is very highly and highly susceptible to future landslide events, respectively, with the highest susceptibility in Chaharmahal and Bakhtiari Province (33.8%). About 31% of cities of Iran are located in areas with high and very high landslide susceptibility. The results of the present study will be useful for the development of landslide hazard mitigation strategies.
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•Landslide prone areas delineated based on CNN and RNN deep learning algorithms.•CNN model shows higher performance than RNN in landslide spatial prediction.•20% of the land areas of Iran are highly or very highly susceptible to landslide.•31% of cities are located in areas with high or very high landslide susceptibility.•Slope, geology, land use and distance from the faults are the most effective factors on landslide occurrences in Iran.
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