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Abstract

Seismic risk in the form of impending disaster has been seen from past records that moderate to large earthquakes have caused the loss of life and property in all parts of Nepal. Despite the availability of new data, and methodological improvements, the available seismic hazard map of Nepal is about two decades old. So an updated seismic hazard model at the country level is imperative and logical. The seismic hazard and risk model constitute important tools for framing public policies towards land-use planning, building regulations, insurance, and emergency preparedness. In fact, the reliable estimation of seismic hazard and risk eventually minimizes social and economic disruption caused by earthquakes. In this frame of reference, the seismic risk assessment at a country level is elementary in reducing potential losses stemming from future earthquakes. Thus, this study investigates structural vulnerability, seismic risk, and the resulting possible economic losses owing to future earthquakes in Nepal. To this end, seismic risk assessment in Nepal is done using an existing probabilistic seismic hazard, a newly developed structural vulnerability, and recently released exposure data. The OpenQuake-engine, the open source platform for seismic hazard and risk assessment from the Global Earthquake Model initiative, was used to calculate the seismic hazard and risk in Nepal. The seismic hazard and mean economic loss map were formulated for the 1%, 2%, 5%, and 10% probability of exceedance in 50 years. Finally, the distribution of building damage and corresponding economic losses due to the recurrence of the historical 1934 earthquake was presented in this study.
1 23
Natural Hazards
Journal of the International Society
for the Prevention and Mitigation of
Natural Hazards
ISSN 0921-030X
Nat Hazards
DOI 10.1007/s11069-015-1734-6
Seismic risk assessment and hazard
mapping in Nepal
Hemchandra Chaulagain, Hugo
Rodrigues, Vitor Silva, Enrico Spacone &
Humberto Varum
ORIGINAL PAPER
Seismic risk assessment and hazard mapping in Nepal
Hemchandra Chaulagain
1,2
Hugo Rodrigues
3
Vitor Silva
1
Enrico Spacone
4
Humberto Varum
5
Received: 19 June 2014 / Accepted: 31 March 2015
ÓSpringer Science+Business Media Dordrecht 2015
Abstract Seismic risk in the form of impending disaster has been seen from past records
that moderate-to-large earthquakes have caused the loss of life and property in all parts of
Nepal. Despite the availability of new data, and methodological improvements, the
available seismic hazard map of Nepal is about two decades old. So an updated seismic
hazard model at the country level is imperative and logical. The seismic hazard and risk
model constitute important tools for framing public policies toward land-use planning,
building regulations, insurance, and emergency preparedness. In fact, the reliable esti-
mation of seismic hazard and risk eventually minimizes social and economic disruption
caused by earthquakes. In this frame of reference, the seismic risk assessment at a country
level is elementary in reducing potential losses stemming from future earthquakes. Thus,
this study investigates structural vulnerability, seismic risk, and the resulting possible
economic losses owing to future earthquakes in Nepal. To this end, seismic risk assessment
in Nepal is done using an existing probabilistic seismic hazard, a newly developed
structural vulnerability, and recently released exposure data. The OpenQuake-engine, the
open-source platform for seismic hazard and risk assessment from the Global Earthquake
Model initiative, was used to calculate the seismic hazard and risk in Nepal. The seismic
hazard and mean economic loss map were formulated for the 1, 2, 5, and 10 % probability
of exceedance in 50 years. Finally, the distribution of building damage and corresponding
economic losses due to the recurrence of the historical 1934 earthquake was presented in
this study.
&Hugo Rodrigues
hugo.f.rodrigues@ipleiria.pt
1
Civil Engineering Department, University of Aveiro, 3810-193 Aveiro, Portugal
2
Civil Engineering Department, Oxford College of Engineering and Management,
Gaidakot, Nawalparashi, Nepal
3
School of Technology and Management, Polytechnic Institute of Leiria, 2411-901 Leiria, Portugal
4
Department PRICOS – Architettura, University of Chieti-Pescara, 65127 Pescara, Italy
5
Department of Civil Engineering, Faculty of Engineering of the University of Porto,
4200-465 Porto, Portugal
123
Nat Hazards
DOI 10.1007/s11069-015-1734-6
Author's personal copy
... This signifies the need to incorporate the seismic risk assessment with social characteristics. In this study, the country-level earthquake risk estimates from the global earthquake model OpenQuake (Pagani et al., 2014) were analyzed by using the input models (seismic hazard sources, fragility functions, and consequence model) given by Chaulagain et al. (2015). The results of earthquake risk estimates were integrated with vulnerability parameters (social and economic factors) of Nepal. ...
... On top of that, very little research has been conducted in terms of attenuation relationships in Nepal. Previous studies like Chaulagain et al. (2015) and Stevens et al. (2018) have used a combination of ground motion prediction equations (GMPEs) within the logic tree. The past seismic hazard analyses (Stevens et al., 2018;Chaulagain et al., 2015;Thapa and Guoxin, 2013) have produced a varying range of seismic hazard analyses of Nepal. ...
... Previous studies like Chaulagain et al. (2015) and Stevens et al. (2018) have used a combination of ground motion prediction equations (GMPEs) within the logic tree. The past seismic hazard analyses (Stevens et al., 2018;Chaulagain et al., 2015;Thapa and Guoxin, 2013) have produced a varying range of seismic hazard analyses of Nepal. According to Stevens et al. (2018), in the large part of Nepal, the accelerations in the range of 0.4-0.6 and 1.0-3.0 ...
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Seismic risk analysis is necessary to mitigate the potential losses resulting from future earthquakes and supplement scientific risk management. In order to assist systematic evaluation and management of risk, it is indispensable to interpret risk in terms of social and economic consequences due to hazardous events like earthquakes. There is an interrelationship between hazards, physical risk, and the social characteristics of populations. Therefore, based on the existing studies focusing on each of these aspects, this paper presents the integrated seismic risk assessment along the subdivisional administrative units of Nepal using 2011 census data. The administrative unit “provinces” are subdivided into districts and each district into municipalities and village development committees (VDCs). The districts, municipalities, and VDCs were considered as our study units. In this paper, the physical or seismic risk was evaluated from the exposure model, hazard curves, and the vulnerability model of the country, whereas the social vulnerability was assessed using social vulnerability index (SoVI) methods. To formulate the physical risk, the assets used were five types of buildings under the exposure model. This model was combined with the physical vulnerability functions of the building and the hazard curves of the country. The result of the physical risk has been presented as annual average loss (AAL). Similarly, among 92 social vulnerability variables, 54 variables were reduced to 7 weighted parameters using principal component analysis (PCA). The scores of a total of 45 parameters were used to evaluate the SoVI index, which was further combined with the physical risk to evaluate integrated risk. The results showed that populated cities like Kathmandu, Hetauda, and Janakpur have a highly integrated risk index. Similarly, the Terai region bordering its neighbor India and some parts of the central hilly region are highly vulnerable, while most parts of the mountainous region in the central and eastern regions are the least vulnerable. The results from the present study can be utilized as a part of a comprehensive risk management framework at the district level to recuperate and recover from earthquakes.
... Eurocode 8 type 1 spectral shape for soil class C is used (the most common soil type in Kathmandu valley). Chaulagain et al. [9] suggest a value of 0.38 g for a 475 year return period earthquake. This value is used for the anchorage PGA. ...
... Many probabilistic seismic hazard assessment (PSHA) studies have been carried out for Nepal in literature [9,70,80,68]. The PSHA study carried out by Stevens et al. [80] is used in this study. ...
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Seismic risk for a stone masonry template health centre developed by the NGO Pahar Trust is assessed for the entirety of Nepal, accounting for the latest probabilistic seismic hazard analysis available for the country. Micro-modelling in OpenSees is employed to derive a high-fidelity model of the Pahar Trust health centre and to perform a cloud analysis deriving fragility curves. Regularisation criteria are carried out to optimise irregular stone masonry modelling and validated against consolidated analytical formulations and recent experimental campaigns. The study contributes to establishing a strategy for defining the implicit seismic risk for the case of implementation of template designs in a highly variable seismic hazard for which a detailed numerical study can be applied to an entire region. Micro-modelling represents a very convenient approach given the limited availability in low and middle-income countries of experimental results for the masonry and the easier accessibility of separate material tests on the masonry components. Results are also benchmarked against empirical and numerical studies developed in the literature for the same country context finding a relatively good matching with a less conservative results in terms of vulnerability due to the higher accuracy of the modelling strategy. Risk assessment results obtained for the health centre are comparable to the acceptable risk targets for developed countries in all cases for which quality controls guarantee the rigorous implementation of structural details.
... The epicenter and depth of the earthquakes and local site conditions play a vital role in seismic hazard analysis of civil infrastructure [22,25]. Prediction of shaking intensity in future earthquakes plays an important role in seismic risk assessment that involves reliable data selection and proper ways to process [14]. ...
... log A max,h = 0.5091 -0.00028*r + 0.40234*M -0.79477*log r ± 0.3615 σ (13) log A max,h = 0.29059+0.3826*M+0.01918*M 2 +(-0.4733 -0.0841*M) log r ± 0.36177 σ (14) Predicted attenuation equations for the near field (equation [15][16], far-field earthquakes (equation [17][18] according to Joyner and Boore (1981) model [23] and Bommer and Akkar (2012) model [5] From the results of Figure 3, it is perceived that the attenuation curves are magnitude independent for shallow depth earthquakes. For both models, shallow depth earthquake equations provide the same peak ground prediction value for magnitudes 6 and 7. Therefore, shallow depth earthquakes do not affect the attenuation models for both models for the current database. ...
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This article represents Ground-Motion Prediction Equations (GMPEs) for the NorthEast Indian region and Bangladesh derived from Indian Meteorological Department (IMD) strong motion database, following a standard regression approach. The database consists of 1608 three-component (North-South, East-West, and Vertical) time history records from 160 earthquakes having a magnitude between 2 to 8 from 2005 to 2017. The predicted ground parameters are expressed as a function of magnitude, distance (epicentral distance or hypocentral distance), and site category. The model uses a magnitude-independent shape according to geometrical spreading and anelastic attenuation for the attenuation relationships. The parametric GMPEs based on horizontal and vertical ground motions (peak ground acceleration, peak ground velocity) and spectral values (0.3 s, 1.0 s & 2.0 s.) have been developed in this study for rock, soft rock, and firm soil sites. The predictive values of horizontal and vertical components for firm soil sites are larger than those of soft rock and rock sites under the same conditions for a given earthquake event. Moreover, this study compares the effects of near-field earthquakes with far-field earthquakes and reveals that near-field earthquakes amplify more than far-field ones. This research also explains that the developed attenuation curves are depth and magnitude-independent and have no distance dependency.
... The significance (and influence) of amplitude and frequency-content characteristics on ground-motion-induced damage/losses have already been comprehensively investigated and quantified (e.g., in refs. 1,3). However, it is not until recent years that some consensus has been reached on the impact of duration on structural response (e.g., in refs. ...
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Earthquake‐induced ground‐motion duration can have a non‐negligible impact on the nonlinear seismic performance of structures. However, in current seismic risk assessment practice, hazard and vulnerability analyses generally only consider ground motion's amplitude and frequency‐content features, often relegating duration to implicit considerations. This study introduces a simulation‐based framework to explicitly quantify the impact of ground‐motion duration on building‐portfolio direct economic losses. Case‐study synthetic building portfolios located at different distances from a case‐study seismic source (i.e., fault) are assembled considering – individually and in combination – three building typologies representing distinct vulnerability classes in Southern Italy. Such typologies correspond to non‐ductile moment‐resisting reinforced concrete (RC) infilled frames designed to only sustain gravity loads (i.e., pre‐code infilled frames), and ductile moment‐resisting RC infilled and bare frames designed considering seismic provisions for high‐ductility capacity (i.e., special‐code infilled and bare frames). Event‐based probabilistic seismic hazard analysis is performed explicitly simulating duration jointly with spectral‐shape‐related intensity measures (IMs), accounting for their spatial and cross‐correlation. Sets of ground‐motion records are selected to conduct cloud‐based nonlinear time‐history analyses (NLTHAs) and derive fragility models for each considered building typology through archetype structures, simulating their structural response using computational models that account for stiffness and strength cyclic and in‐cycle deterioration as well as destabilising P−Δ$P - \Delta $ effects. Fragility models are derived using average pseudo‐spectral acceleration (in a range of periods of interest) as the primary IM and alternatively: (1) the dissipated hysteretic energy as an engineering demand parameter (EDP), implicitly accounting for duration given the cumulative nature of such an EDP and the adopted nonlinear modelling strategy, in a scalar format; (2) the dissipated hysteretic energy as an EDP, as before, explicitly considering duration as an IM together with spectral shape, in a vector‐valued format. Vulnerability models are then derived using the fragility models and appropriate building‐level damage‐to‐loss models. The portfolio loss exceedance curves and expected annual losses computed for each combination of exposure, hazard, and vulnerability models are critically assessed and discussed. Depending on the portfolio's size, exposure composition, location relative to the fault, site conditions and the seismic source model, the impact of duration on the loss estimates can be significant. For the considered settings, relative variations up to 200% between the scalar‐ and vector‐valued‐based portfolios expected annual losses are observed, attaining the highest discrepancies as the fault‐to‐portfolio distance increases.
... Finally, in Nepal, a majority of the building typology inventory collected after the 2015 earthquake holds a good match with the building typology inventory as observed in the 2011 national census (Chaulagain et al., 2015). Thus, the findings from this study seems promising to the Nepal's exposure context. ...
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Assessing post-seismic damage on an urban/regional scale remains relatively difficult owing to the significant amount of time and resources required to acquire information and conduct a building-by-building seismic damage assessment. However, the application of new methods based on artificial intelligence, combined with the increasingly systematic availability of field surveys of post-seismic damage, has provided new perspectives for urban/regional seismic damage assessment. This study analyzes the effectiveness and relevance of a number of machine learning techniques for analyzing spatially distributed seismic damage after an earthquake at the regional scale. The basic structural parameters of a portfolio of buildings and the post-earthquake damage surveyed after the Nepal 2015 earthquake are analyzed and combined with macro-seismic intensity values provided by the United States Geological Survey ShakeMap tool. Among the methods considered, the random forest regression model provides the best damage predictions for specified ground motion intensity values and structural parameters. For traffic-light-based damage classification (three classes: green-, amber-, and red-tagged buildings based on post-earthquake damage grade), a mean accuracy of 0.68 is obtained. This study shows that restricting learning to basic features of buildings (i.e. number of stories, height, plinth area, and age), which could be readily available from authoritative databases (e.g. national census) or field-surveyed databases, yields a reliable prediction of building damage (4 features/3 damage grade accuracy: 0.64).
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... Several previous PSHA studies exist for Nepal, but a step change has occurred since the 2015 Gorkha earthquake. Most of the pre-Gorkha studies (e.g., Parajuli et al. 2010 [8]; Thapa and Guoxin 2013 [9]; Chaulagain et al. 2015 [10]) are based on a seismic source zonation dividing the country into twenty-three zones based mainly on a subdivision of the Main Himalayan Thrust (MHT) into Main Central Thrust (MCT), Main Boundary Thrust (MBT) and Himalayan Frontal Thrust (HFT). Evidence from the Gorkha earthquake led to the definition of a new model for the MHT (Elliott et al. 2016 [11]) that in turn led to a number of new PSHA studies for Nepal. ...
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This paper presents a sensitivity study of simulation-based Probabilistic Seismic Hazard Analysis (PSHA) for Kathmandu, Nepal. Two aspects are investigated in detail: (i) the technique for simulating fault ruptures compatible with scaling laws and fitting into the Main Himalayan Trust (MHT) and (ii) the choice of different Ground Motion Prediction Equations (GMPEs). Since the 2015 Gorkha earthquake, a number of new studies have provided new approaches to model the MHT as a single seismic source. This more realistic characterization of the MHT has resulted in higher peak ground acceleration (PGA) for all of Nepal and in particular for the Kathmandu Valley. Here, the results of a new simulation-based code are compared with those by the software OpenQuake. It is specifically assessed how different source simulation methods influence the hazard calculations. Furthermore, the influence of different GMPEs assumed for subduction earthquakes is assessed for the specific case of Kathmandu, which is only 11 km above the MHT. Results show that because of the proximity to the megathrust, the estimated hazard is very sensitive to different choices. The results of this study may be useful for informing ongoing efforts in Nepal to update the building code with a new seismic hazard map. Understanding the sensitivity and robustness of PSHA is critical from a policy and preparedness perspective.
... This analysis is conducted for the entire seismic hazard of Nepal, to better reflect the distribution of potential events to impact Kathmandu Valley. A probabilistic seismic hazard analysis (PSHA) was developed for the school building sites based on twenty-three independent seismic source zones for Nepal identified by Ram and Wang (2013) and adopted in Chaulagain et al. (2015)'s PSHA model. The ground motion prediction equation by Chiou and Youngs (2014) for active shallow crust regions is used within a logic tree for an event-based probabilistic seismic hazard calculation in the OpenQuake-engine (Silva et al., 2014). ...
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