Earthquake risk assessment of Blida (Algeria) using GIS

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International Conference On Materials And Energy 2015, ICOME 15, 19-22 May 2015, Tetouan, Morocco, and the International Conference On Materials And Energy 2016, ICOME 16, 17-20 May 2016, La Rochelle, France The 15th International Symposium on District Heating and Cooling

Earthquake risk assessment of Blida (Algeria) using GIS Assessing the feasibility of using the heat demand-outdoor Khalida Tadjera*, Mahmoud Bensaibib temperature Department function for a long-term district heat demand forecast of Civil Engineering University Blida 1, Soumaa, Blida 09000, Algeria. a

b

Department of Material and Structures High National School of Public Works, Kouba, Algiers 16000, Algeria.

I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a

IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France

Abstract

The seismic vulnerability of an urban area is of a great deal for local authorities especially those facing earthquakes. So, it is important to have an efficient tool to assess the vulnerability of existing buildings. Blida is located in the north part of Algeria, an area prone to seismicity. It is classified zone III according to the Algerian Seismic Code (RPA99 version 2003). The town is Abstract among the oldest cities in the north. Build especially during the colonial period, Blida is characterized by vulnerable urban conditions with dense buildings and narrow roads. Using geographic information systems (GIS), the seismic vulnerability of District heating networks are commonly addressed in the literature as onethen of the most seismic effectivescenarios. solutionsDamage for decreasing Blida is assessed. First the vulnerability indexes of buildings are calculated, making rates arethe greenhouse gas emissions from building sector. These systems investments which are returned through the heat determined taking into account thethe seismotectonic aspect of the regionrequire and thehigh vulnerability curves of structures commonly found theofchanged conditions and building renovation policies, highlighted heat demand thevulnerability future couldofdecrease, insales. Blida.Due The to rates damage climate caused by the earthquake considered in the scenario the inhigh Blida. prolonging return period. These results the caninvestment allow elaborating strategic countermeasure plans for the earthquake risk mitigation in the city. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 ©forecast. 2017 TheThe Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific of ICOME and ICOME buildings that vary in both construction periodcommittee and typology. Three2015 weather scenarios2016. (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were Keywords: Blida ; Earthquake ; Seismic Vulnerability ; GIS ;model, Vulnerability Index ;developed Scenario ; Vulnerability compared with results from a dynamic heat demand previously and validatedCurves by the; Damage authors. The results showed that when only weather change is considered, the margin of error could be acceptable for some applications (the error in annual demand was lower than 20% for all weather scenarios considered). However, after introducing renovation the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). 1.scenarios, Introduction The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the decrease the numberand of heating hours of 22-139h heating season (depending on thedisasters combination weather and Human, ineconomic ecological costs andduring lossesthe associated with earthquake areofincreasing renovation scenarios considered). the pose other ahand, function increased for 7.8-12.7% per decade on the exponentially and these cost and On losses systemic riskintercept to society’s political and economic bases.(depending Even utilizing coupled scenarios). The values suggested could be used to modify the function parameters for the scenarios considered, and the most advanced technology, it is almost impossible, at the present state of knowledge, to predict exactly when improve the accuracy of heat demand estimations. and where an earthquake will occur and how big it will be [1]. An earthquake suddenly hits an area where people are © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling. * Corresponding author. Keywords: Heat demand; Forecast; Climate change E-mail address: [email protected] 1876-6102 © 2017 The Authors. Published by Elsevier Ltd.

Peer-review under responsibility of the scientific committee of ICOME 2015 and ICOME 2016. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the scientific committee of ICOME 2015 and ICOME 2016 10.1016/j.egypro.2017.11.266

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neither prepared nor alerted. Hence, the earthquake often causes huge damage to human society. Different strategies may be taken to mitigate earthquake disasters, based on appropriate risk assessment. Throughout the last thirty years scientific and technical action has been oriented towards the definition of new building-methods that tend to increase buildings’ seismic resistance [2,3]. However, the old structures vulnerability that represent the majority of these buildings, is also quite worrying and its assessment is a considerable task [4,5]. In Algeria, the last earthquakes show that the seismic activity is important. In fact, this activity is linked to faults that illustrate compression movements along the limit of Algeria-Europe’s plates and which mostly touches the north of the country where the biggest towns are situated [8]. The city of Blida as regards its location in a high seismic activity region (south of the Mitidja’s seismogene basin), its high population’s condensation, its generally very old buildings and its administrative importance in the region requires a particular attention concerning its protection against that natural phenomenon that highly threatens it and that may hit the town at any moment [9]. In this study, we have assessed an earthquake risk in the city of Blida determined as a convolution of seismic hazard (in terms of the surface peak ground acceleration, PGA) and the vulnerability (due to building construction fragility). To do this, the different data of the study’s zone have been structured under a geographic information system (GIS) [8]. In our study we have used the vulnerability index method to calculate the vulnerability index of the study area constructions, to deal with this a software called the Vulnerability Index Program (VIP) has been developed (Bensaibi & al. 2011) [10] . The damages provoked by the earthquake taken into account in the scenarios have been calculated by a GIS established program. 2. The Region under Study 2.1. Location of the study area The situation of Blida, its geographic and tectonic context highly requires a vulnerability analysis of its existing buildings. The zone under study includes the historical center considered as the oldest district where most of the buildings date from the colonial era [6]. This area is mostly composed of single or two storied buildings of which most are in an advanced state of decay. We may find, in the same surroundings, some recent buildings and some others dating from the Ottoman era, Fig. 1 and Fig. 2.

Fig. 1. Location of study area

Fig. 2. Town center (Didouche Mourad Street)

2.2. Sectors division To make the inventory draw up of the study-zone structures easier, we have divided the study zone into identified sectors inside the soils occupation plan as base-sectors composing the town center. In our case, we have chosen a sectors division including 20 analysis units (district), each representing one area identified with a number. Fig. 3 shows the map of the study area with its districts.



Khalida et al./ Energy / EnergyProcedia Procedia00139 (2017) 645–650 K. Tadjer and M.Tadjer Bensaibi (2017) 000–000

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Fig. 3. Sectors division of the study zone in 20 analysis units on GIS

2.3. General population and housing census Population and housing data analysis done for our study’s needs is based on the results of the drawn by the national statistics office (ONS. 2008). In our study zone, the total number of buildings is 2512 for a population of 14997 inhabitants [7]. 3. Scenarios 3.1. Seismic hazard analysis The different studies of the seismic hazard in the region of Blida have shown the presence of many active sources that may provide more or less important earthquakes, Fig. 5. For the study needs, the fault of Blida also called Soumaa Bouinan fault has been considered as the one that could generate most damages because it crosses Blida’s downtown, Fig 4. The maximum magnitude generated by this fault has been estimated by the CRAAG (Astronomy, Astrophysics and Geophysics’ research Centre) at 7.08 on Richter scale [8].

Fig. 4. Active faults for Algiers and Blida region [9]

Fig. 5. Blida historical seismicity between 1825 and 2005 [9]

In our study, we have considered two seismic scenarios. The characteristics of these latter are summed up in table 1and table 2. Table 1. First scenario Seismic source

Magnitude

Epicenter

Attenuation law

Blida fault

7.08

downtown

Joyner-Boor (1981)

Table 2. Second scenario Seismic source

Magnitude

Epicenter

Attenuation law

Blida fault

7.08

15 km from downtown

Joyner-Boor (1981)

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3.2. Urban structure analysis The data collected for each structure recorded are treated by the VIP program (Vulnerability Index Program) in order to determine the seismic vulnerability index. This number is obtained by a weighted sum of the numerical values expressing the seismic quality of the structural and non-structural items which are deemed to play a significant role in the seismic response of the building [12,13]. All the data are treated and analyzed afterwards with a geographic information tool (GIS). The total number of analyzed buildings reaches 370 of which 300 are built in masonry and 70 in reinforced concrete. 3.3. Assessment of damage rates The damages provoked by the earthquake considered in the scenarios are assessed through the use of seismic vulnerability functions programmed under SIG, [14,15], Fig. 6 and 7. These curves are defining the relation between the seismic intensity and the rate of damage for various Algerian structural types (masonry structures, reinforced concrete structures, framework structures.) belonging to different vulnerability classes. The PGA (Peack Ground Acceleration) is calculated using joyner & Boor attenuation law (1981) and the value of the seismic intensity is obtained by converting the PGA to MMI (Modified Mercalli Intensity) using the general relation of Trifunac & Brady (1975).

Fig. 6. Vulnerability curves of Masonry structures

Fig. 7. Vulnerability curves of Reinforced Concrete structures

4. Result Concerning results, we have considered the following damage rates classification, tables 3 and 4. Table 3. Masonry structure Rate of damage

0 – 20%

classification

green

20% - 60%

60% - 100%

orange

red

Table 4. Reinforced concrete structure Rate Damage classificatio n

of

0

–

40%

40% 70%

green

-

70%

-

100% red

orange



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4.1. First scenario After a GIS analysis, on a total number of 370 buildings of which 300 in masonry and 70 in reinforced concrete, we have numbered 69 classified green, 10 classified orange and 291 classified red, Fig 8. Figure 9 represents the proportions of the different classes of damage. The proportion of the buildings classified orange and red represents nearly 81 % of the total number of buildings, an extremely important proportion. Moreover, almost 79 % of the constructions are classified red which leads to assert that this zone’s estate-park shows big vulnerability to earthquake. The distribution of the rates of damage in the study area shown in Fig. 8 stresses on the high, the moderate and the weak risk zones. Therefore, one notices that the risk increases as and when one approaches the historical center of the city.

Fig. 8. Classification of the buildings according to their damage rates

Fig. 9. Buildings proportion for each class

4.2. Second scenario For this second scenario we have numbered 71 buildings classified green, 192 classified orange and 107 buildings classified red, Fig. 10. The damage rate has significantly decreased, the number of buildings classified red decreased by 64% compared to the first scenario. This damage-decrease in this second scenario is obviously due to the remoteness of the epicenter from the study area. The seismic vulnerability of the different districts was assessed on the basis of the rate of damage and the number of inhabitants. A GIS request has allowed us to carry out this analysis. The result is shown in Fig. 11. Therefore, we are to retain the four most vulnerable districts according to the percentage of the buildings classified red and according to the population number. The district 19 is thus considered as being the most vulnerable with a percentage of 51% for the red classified buildings, and a population of 639 inhabitants. This one is followed by district 33 with a percentage of 48% and a population of 832 inhabitants. Then comes in the third position district 18 with a red buildings’ percentage of 37% and a population of 780 inhabitants. The last one is district 77 with 36% of red buildings and a population of 736 inhabitants. So, it would be advisable to center reinforcement or rehousing actions towards these districts which include a population of 2987 inhabitants that is to say 20% of our study zone.

Fig. 10. Classification of the buildings according to their damage rates

Fig. 11. Districts vulnerability

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5. Conclusion The carrying out of Blida town’s seismic scenario has permitted to quantify the local risk. In fact, the results clearly demonstrate the high vulnerability of the city and the fragility of its urban fabric. The use of GIS in this work has allowed the exploitation of the data collected in situ and the diagnosis of the most vulnerable zones. A spatial analysis has permitted to locate geographically the structures and their rates of damage, their typology and their number of floors. Through this study, we can know now the weak points of the town which are downtown districts. These districts (17, 18, 19 and 33) are characterized by a big concentration buildings and very narrow streets. These results may help in decision-making concerning Blida’s development. They may also be useful in the organization of the first aids, the state of readiness, the reinforcement of buildings and reconstruction’s actions particularly if we consider that the available budget and efforts in case of a seismic event are often limited or even non-available in a town like Blida submitted to earthquakes. References [1] G. Babayev, A. Ismail-Zadeh, and J.-L. Le Mou¨el. Scenario-based earthquake hazard and risk assessment for Baku (Azerbaijan). Nat. Hazards Earth Syst. Sci., 2010, 10, 2697–2712. [2] AFPS (Association Française du Génie Parasismique), Vulnérabilité sismique du bâti existant, Approche d’ensemble. Cahier technique n°25. [3] Silvia del Carmen MOQUERA MACHADO. Analyse multi-aléas et risque naturels dans le département du Chocó (nord-ouest de la Colombie). Doctorate thesis N° 3351, 2002, Genève [4] Sarvar H., Amini J., Laleh-Poor M. Assessment of Risk Caused By Earthquake in Region 1 of Tehran Using the Combination of RADIUS, TOPSIS and AHP Models. Journal of Civil Engineering and Urbanism, 2011, Volume 1, Issue 1: 39-48. [5] Lang, K. Seismic Vulnerability of Existing Buildings. Doctorate thesis, Swiss Federal Institute of technology, 2002, Zurich, Swiss. [6] URBAB (Centre d’étude et de réalisation en urbanisme). PDEAU du grand Blida analyse et diagnostic phase1. 2004, Algeria. [7] ONS (office national des statistiques), Recensement Général de la population et de l’Habitat (RGPH). 2008, Algeria. [8] RPA (Règlement Parasismique Algérien, RPA99 version 2003), CGS Centre Génie Parasismique. 2003, Algeria [9] K. Tadjer. Scenario Catastrophe Sismique du Centre-Ville de Blida. 2007, Master thesis. [10] Bensaibi, M., Djaalali, F., Belheouane, F I., Amellal, O. and Yousfi, N. Seismic Vulnerability Index Method - Algerian case studies. 9th International Conference on Urban Earthquake Engineering, Tokyo Institute of Technology, 7-8 Mars 2011, Tokyo, Japan. [11] Bensaibi, M., Djaalali, F., Belheouane, F I., and Bourahla, Nourredine, 2011, Vulnerability Index Method – Algeriers case study. Seventh National Conference of Earthquake Engineering. [12] Belheouane, F I., Bensaibi, M, 2011, Evaluation De l’Indice De Vulnérabilité Sismique Des Structures En Béton Armé, Cas D’étude : Structures En Béton Armé En Algérie. Actes du 8em Colloque National AFPS, Paris, France. [13] Boukri, M., Détermination de l’Index de Vulnérabilité Pour les Constructions en Maçonnerie de la Ville d’Alger. Master thesis. University Blida 1. 2003, Algeria [14] Belheouane, F I., Vulnerability curves of reinforced concrete structure, Doctorate thesis, Department of Material and Structures High National School of Public Works, 2014, Algeria. [15] Djaalali, F., Vulnerability curves of masonry structure, Doctorate thesis, Department of Material and Structures High National School of Public Works, 2014, Algeria.