Seismic Vulnerability of Existing Buildings in the Taroudant Urban

Area, Morocco, using Different Approaches

El Mehdi Nchiti

, Abdellah El Hammoumi

, Aomar Iben Brahim

, Kamal Gueraoui

Faculty of Sciences, Mohammed V University in Rabat, Morocco

Geophysics & Natural Risks Laboratory, Scientific Institute, Mohammed V University in Rabat, Morocco

Keywords: Seismic vulnerability, fragility curves, Taroudant, deterministic approach, overall approach, GIS, Pushover

analysis.

Abstract: Due to its location at the extreme north-west of Africa, a zone of collision between the African and Eurasian

plates, Morocco is a country exposed to seismic risk. In the context of the Morocco National Integrated Risk

Management Strategy, with the objective of strengthening the resilience to hazards of the national territory,

this article presents a study in which we evaluate the seismic vulnerability of buildings in the Taroudant urban

area. This city falls within the seismic zone 2 with a peak ground acceleration of 14%g, which is the second

important seismic zone in Morocco. Taroudant building are clustered according to the European Macro-

seismic scale. We then analyze one category building using two seismic vulnerability assessment methods; a

deterministic and overall approach. The results are quite similar for damage probabilities obtained by the

deterministic approach and those evaluated by the overall approach for a seismic intensity scenario between

VIII and IX. Using these results along with a Geographic Information System, maps of the spatial distribution

of seismic building categories and vulnerabilities are produced. These maps provide a scientific and technical

support to the authorities for the assessment of potential risk points within Taroudant city.

1 INTRODUCTION

Morocco has experienced several destructive

earthquakes, particularly in many of its larger cities.

During the 20th century, the recorded seismicity was

relatively moderate (Iben brahim et al., 2003) . The

1960 Agadir earthquake, with a magnitude of 5.7 on

the Richter scale, was the most violent and deadly

event, with more than 12,000 victims and more than

two thirds of the city's buildings and infrastructures

disappeared. More recently, the 6.3 magnitude Al

Hoceima earthquake of 2004, resulted in a death toll

of 629 people (Mouraouah et al., 2004; Talhaoui et

al., 2005). The Al Hoceima earthquake of 24

February 2004 has further shown deficiencies related

to the socio-economic and environmental

vulnerability of basic infrastructures. It also showed

institutional, technical and organizational gaps in

managing natural disasters of this scale.

The issue is then to suggest simple models to help

address the problem of studying seismic

vulnerability, and to present a tool to help decision-

https://orcid.org/0000-0002-5375-6667

making in planning and seismic risk management.

Thus, for the Taroudant urban area, this paper focuses

mainly on assessing the seismic vulnerability of its

buildings.

There are several methods for the assessment of

seismic vulnerability. The selected method is made

according to the quality and quantity of available data

and the desired accuracy, i.e. whether we seek the

estimation of the seismic vulnerability of a single

building or a group of buildings. We can thus, cite the

ATC methods (Rojahn et al., 1988) then taken up by

FEMA ((US), 2017) in the United States, the GNDT

method (Petrini, 1993) in Italy and the European

project RISK-EU (Milutinovic & Trendafiloski,

2003). In this work, the vulnerabilities are assessed

based on the direct methodology described by the

RISK-EU project, namely the overall approach level

1 based on the vulnerability index, where a system of

building classifications are proposed to group them

under a similar vulnerability index VI. In addition, we

also use a level 2 approach based on the Pushover

analysis, which is the basis of the deterministic

method for the elaboration of fragility curves.

(Combescure et al., 2005; E, 2020; Hammoumi et al.,

2009; M. A. El Azreq, Moudrik, A. El Hammoumi,

A. Iben Brahim, K. Gueraoui, A. El Mouraouah, A.

Lbadaoui, M. Kerroum, M. Kasmi, 2012).

This article is structured as follows; the following

section provides an overview of the urban area of

Taroudant by introducing a description of its building

typology and construction methods. The spatial

distribution of these typologies is further mapped

using GIS (Geographic Information System) and is

discussed. Then, a type C building is analyzed using

the two above-mentioned methods of seismic

vulnerability. Finally, this paper presents probable

damage scenarios for our study area with a

comparison between the two assessment methods

adopted in this work.

2 DESCRIPTION OF THE STUDY

AREA, DATA AND RESOURCES

2.1 Study Area

Taroudant is a city located in the south-west

Morocco, this study concerns the overall urban area

of Taroudant, which covers an area of 13.3 Km². In

terms of seismicity, Taroudant occurs in seismic zone

two with a peak velocity PVA = 0.10 m/s and a peak

ground acceleration PGA=0.14g according to the

Moroccan Seismic Code (RPS2000, 2011). This zone

is the second most important seismic zone in

Morocco.

2.2 Building Typology and

Construction Procedures

For seismic vulnerability assessment, buildings in the

Taroudant urban area are grouped into five standard

typologies. These are selected such that each

building-type reflects a distinct vulnerability class

with respect to seismic hazard. The selection of the

classes is based on the EMS 98 scale (Grünthal, 1998)

and is completed by taking into account the state of

dilapidation, the materials and quality of

construction, the irregularity shape of the building,

the seismic design level etc. These criteria are also

used to assign to each class a basic vulnerability

index.

2.2.1 Types and Age of Housing

Data from the General Census of Population and

Housing of Morocco (RGPH 2014, 2014), shows that

the most common type of housing is the Moroccan

house 80.5%, apartments account for only 13.4%, the

proportion of villas is 2.3% while the parts of rural

and basic type housing only exceed 1.6% and 0.9%

respectively. Similarly, an analysis of data on the age

of housing shows that about half of urban houses were

less than 50 years old, compared with 22.8% of

houses between 10 and 19 years of age, 15.8% less

than 10 years old, and 13.8% are 50 years-old and

over.

In fact, the performances of the buildings appear

opposite. On one hand, older buildings perform

poorly, due to the lack of a building code and its

application, as well as the degradation of materials

and the need to repair them. On the other hand,

younger buildings are constructed or rehabilitated

with an acceptable level of seismic design, which

means that they are rather earthquake-resistant

buildings.

2.2.2 Definition of Typologies and the

Associated Vulnerability Class

The data we collected and analyzed from various

government sources does not contain detailed

information on building methods in the Taroudant

urban area. Thus, in order to collect information on

the different local construction methods and to rank

the housing stock in our study area, we conducted an

on-site data collection in February 2020. During this

visit, more than a hundred photos were taken and

georeferenced using GPS positions and the GIS

geographic information system. The results of the

survey helped identify five categories of buildings

based on different building materials and types of

structures “Table 1”.

This data set made it possible to define different

vulnerability classes based on the European macro-

seismic scale (EMS 98) and to map them. The

following pictures show examples of buildings that

can be considered as representative of the building

stock in our study area “Table 1” (Grünthal, 1998;

Ningthoujam & Nanda, 2018; RGPH 2014, 2014).

A GIS database of geographical maps defining the

different types of building structures and

vulnerability classes in our study area has been

elaborated “Figure 1” (Grünthal, 1998; Ningthoujam

& Nanda, 2018; RGPH 2014, 2014).

Table 1: Illustration of the selected building classification.

Vulnerability class Description

A (Type_1):

Unreinforced

constructions

- Constructed using a basic construction method with walls

consisting of small elements of adobe or mud bricks, arranged

irregularly.

- Floors are generally made of mixed materials (wood, earth,

zinc...).

A (Type_2):

Unreinforced masonry

constructions as a

whole

- made of masonry in rough rubble, dressed stone or mud

bricks and arranged regularly.

- Traditional floors generally built in wood on top of thick

walls and sometimes built out of an improved concrete slab.

- Non-homo

eneous an

condensed s

atial as

ect.

B (Type_3):

Reinforced masonry

constructions as a

whole

- Constructed mostly out of brick masonry walls and

reinforced concrete floors,

- Constructed without taking into account seismic rules of the

Morocco seismic code (RPS 2000),

- Are of one, two, three or four storeys types and generally

regular in plane and elevation. These buildings are in direct

contact against each other.

- Geometrically rectangular or square spatial appearance.

C (Type_4):

Buildings with

columns / beams and

unreinforced hollow

brick infill walls

- Constructed mostly out of brick masonry walls and

reinforced concrete floors.

- Constructed with an acceptable level of seismic design

according to the RPS 2000 code, even though the rules of

construction in seismic zones are not perfectly respected,

- Are of type three or four storeys and generally regular in

plane and elevation.

- Homogeneous Spatial aspect.

D (Type_5):

Reinforced concrete

buildings: concrete

gantries and walls

- Constructed mostly with brick masonry walls and reinforced

concrete floors,

- Constructed with a medium level of seismic design

according to the RPS 2000 code,

- Spatial aspect geometrically rectangular or square and easy

to identify.

Figure 1: Geographical distribution of building-classes in

the Taroudant urban area.

3 METHODOLOGY SEISMIC

VULNERABILITY

ASSESSMENT AND DAMAGE

ESTIMATION

The procedures used to assess vulnerability or

construct vulnerability curves depend on the nature,

quantity of data collected, and the anticipated

purpose, i.e. whether we are concerned with an

estimate of seismic vulnerability for a single structure

or a group of buildings. In the following, a distinction

should be made between deterministic methods based

on numerical simulations for a structure defined by a

specific model, and probabilistic or statistical

methods developed based on statistical data that

group several typologies of structures with similar

structural properties, which may undergo similar

damages under a given seismic loading. For this

purpose, this work uses these two approaches as

techniques for estimating the vulnerability of a type

C structure as well as on a large scale (Combescure et

al., 2005; Dang, 2014; Hammoumi et al., 2009).

3.1 Seismic Vulnerability by a

Deterministic Approach

This approach, defined as the set of methods used to

accurately estimate damages caused by a seismic

event, is based on two models. A seismic

demand/capacity model obtained by dynamic

modelling of structures subjected to seismic loading,

and a model for calculating the probability of

damages using fragility curves in the form of a

probability distribution function of the log-normal

distribution (Bendada et al., 2017; Nchiti, El

Hammoumi, Gueraoui, Ibenbrahim, et al., 2020).

In the following, we will discuss in more detail a

procedure proposed by the European project RISK-

EU; namely the LM2 Method (Benjabrou et al., 2017;

E, 2020; El Azreq et al., 2010, 2011).

3.1.1 Case Study

We thus, apply the LM2 method for the analysis of a

type C building, which represents the Moroccan

house and apartments which are more common in the

Taroudant area. In addition, the mode of construction

of these types of buildings is currently the most

adopted one in our study area. The building we

consider is a four floors frame structure with columns,

beams and infill walls made out of unreinforced

hollow bricks as shown in “Figure 2”.

Figure 2: Plan, elevation views and details of the selected

Type C building.

The dimensions of the structural design are 9.90×20

and this structure is modelled using the

MIDASGEN finite element design software, while

the seismic lateral loading was appraised based on the

RPS2000 “Table 2”.

Table 2: Seismic parameters of the selected building

according to the seismic code RPS2000 version 2011.

Seismic parameters Style name:

Structural systems Frames

Structure classification III

Fundamental period of

vibration

T=0.075xH

3/4

=0.52s

Amplification spectrum Za/Zv ˃ 1

Ductility class ND1

Behavior factor 2

Seismic zoning

PVA = 0.10m/s

PGA=0.14

Site Influence S1

3.1.2 Pushover Analysis

Pushover analysis is a non-linear static analysis of a

structural element or structure under monotonous

loading to describe the relationship between shear

force and roof displacement (Ghobadi & Yavari,

2020; Mosleh et al., 2016). The method investigated

in part of this work is the spectrum response-capacity

method of Chopra & Goel (1999) (Chopra & Goel,

1999). According to Freeman's studies this method

consists of the following steps (S A Freeman, 1975;

Sigmund A Freeman, 1978) :

Step 1: Synthesis of a curve of shear force vs.

displacement at the root, under monotonic lateral

loading, is obtained by means of a finite element

modeling of the structure, called the Push-over curve

(V-∆R) “Figure 3”.

Figure 3: Numerical simulation and the resulting

displacement of the selected building computed using the

pushover analysis.

Step 2: Converting the capacity curve (V-∆R) into a

capacity spectrum (A-D), based on the following

formulations:





(1)









ii,1

iii,1

i1 i1















(2)

11,R







(3)

ii,1











(4)

A / D: Acceleration / spectral displacement;

W: Total mass of the structure;

: The per-story mass concentrated at the ith floor

level;

i,1

: Amplitudes of the first eigen-mode on the ith

floor;

: Coefficient of the modal mass of the first Eigen-

mode ;

R,1

: Amplitude of the first Eigen-mode at the roof

level (Nth floor);

PF1: Modal participation factor corresponding to the

first vibration mode;

Step 3:

Transformation of the normalized elastic

response spectrum (A-T) to pseudo-acceleration (A-

D).

The Moroccan seismic regulation RPS2000, proposes

an elastic spectrum that represents an idealization of

the envelope for various normalized response spectra.

It defines the dynamic amplification factor (D) of the

response in function of the fundamental period of the

structure (T). Then the definition of the elastic

spectrum (A-T) is made via the dynamic

amplification factor D (T) by:

max

A(T) (A / g) / D(T)A

)

Where A

max

is the peak ground acceleration and g is

the acceleration of gravity.

The inelastic response spectrum is obtained by the

introduction of the reduction factor K. The spectral

displacement is D = (T/2π

) A (Belmouden, 2004;

Fajfar, 2000).

Step 4:

Combining the capacity and response

spectrum and determining the performance point,

“Figure 4” shows the combination of the capacity

spectrum with the response spectrum in order to

obtain the performance point.

Figure 4: Combination of Capacity and Response Spectra.

3.1.3 Fragility Curves

For the development of fragility curves, all previous

work uses a log-normal cumulative distribution

model as a statistical distribution model to represent

the fragility curves of a structure. (Kumar & Samanta,

2020; Maio et al., 2020; Milutinovic & Trendafiloski,

2003):

/ln













dds

Pds S





)

Where:

Sd is the parameter related to seismic hazard;



,

is the median and β

is the standard deviation of

the spectral displacement for the building attaining a

certain degree of damage ds:

Sd =0.7D

)

=DSd

)

yuy

=D +0.25(D -D )Sd

)

Sd =D

(10

)

Sd1

β =0.25+0.07ln( )

(11

)

Sd2

β =0.2+0.18ln( )

(12

)

Sd3

β =0.1+0.4ln( )

(13

)

Sd4

β =0.15+0.5ln( )

(14

)

Φ is the probability distribution function of the

normal distribution;

Du is the ultimate point of spectral displacement;

Dy is the elastic yield point of spectral displacement;

“Table 3” presents the definitions of these states as a

function of spectral displacements derived from

capacitance spectra.

Table 3: Definition of limit states as a function of spectral

displacements (cm).

Sd,ds βds

d,1

1.4 S

d,3

4.25 β

Sd,1

0.369 β

Sd,3

0.782

d,2

2.0 S

d,4

11.0 β

Sd,2

0.507 β

Sd,4

1.002

“Figure 5” shows the fragility curves obtained from

the lognormal distribution hypothesis of the C-type

structure presented in “Figure 2”.

Figure 5: Derived fragility curves for our Type C building.

In addition, it is possible to identify the levels of

damage on the analyzed structure by means of

fragility curves and the value of the maximum

spectral displacement that can be obtained from the

point of performance, which is determined by the

intersection of the capacity curve with the inelastic

response spectrum. As shown in “Figure 4”, by

intersection with the fragility curves, the spectral

displacement occurs at 1.9 cm in “Figure 5”. The

statistical distribution of the obtained damage is given

in the histogram of “Figure 6”.

Figure 6: Summary of the fragility probabilities for the

selected building.

3.2 Seismic Vulnerability by the

Overall Approach

The overall approach is used for large-scale

vulnerability analyses using a collection of

geographical data to define a differentiation of

structures into vulnerability classes according to the

European macro-seismic scale (EMS 98) (Grünthal,

1998) as shown in “Table 1”.

3.2.1 Vulnerability Index Method

The RISK-EU project suggests a semi-empirical

method (LM1 Method) by which semi-empirical

mean vulnerability functions are defined that relate

the mean degree of damage μ

to the macroseismic

intensity I and vulnerability index V

. This method

proposes a system of building classifications to group

them into similar vulnerability index V

values

ranging from 0 (less vulnerable building) to 1 (more

vulnerable building) (Nchiti, El Hammoumi,

Gueraoui, & Iben Brahim, 2020). For each type of

building, RISK-EU gives the most probable V

value, [V

; V

] the possible range and [V

min

; V

max

]

maximum and minimum limits of the vulnerability

index value V

. For each seismic class, these values

are evaluated according to the percentage of different

types of buildings identified in the chosen class

“Table 4”. The basic vulnerability index V

associated with the typology will then be amplified in

accordance with the constructive parameters specific

to each structure (Rezaei Ranjbar & Naderpour,

2020).

3.2.2 Fragility Curves

In order to obtain the damage probability of our

seismic class C building , it is necessary to define,

first of all, the mean degree of damage for different

intensities as follows (Nchiti, El Hammoumi,

Gueraoui, & Iben Brahim, 2020; Rezaei Ranjbar &

Naderpour, 2020) :

Table 4: Vulnerability index for different classes of buildings in our study area.

Vulnerability

class

resentative values

∆V

Vulnerability

index

min

max

A 0.50 0.659 0.767 0.895 0.980 0.02 0.04 0.827

B 0.3 0.49 0.627 0.817 0.883 0.02 0.04 0.688

C -0.02 0.007 0.402 0.76 0.98 0.1 0.04 0.542

D -0.02 0.047 0.386 0.67 0.86 0.05 0.04 0.476

I 6.25V 13.1

2.5 1 tanh

2.3







 









(15)

Subsequently, it is possible to calculate the damage

distribution for each seismic class, using probability

density and cumulative distribution equations:



tq1

(x a) b x

(t)

p(x)

(q) (t q)

(b a)



















(16)

Pp(z)dz







(17)

Where a=0, b=6, t and

DD D

q t(0.007 0.052 0.2875 )are the

distribution factors, and x is the continuous variable

in the interval [a,b]. The discrete beta density

probability function is calculated from the

probabilities associated with damage states k and k+1

(k = 0, 1, 2, 3, 4, 5), as follows:

pP(k1)P(k)





(18)

P(D D ) 1 P (k)





(19)

Figure 1: Summary of the fragility probabilities for the

selected building.

Based on the fragility curves shown in “Figure 7”, it

is possible to deduce the state of damage for a given

seismic intensity. For a scenario of seismic intensity

between VIII and IX, class C buildings will suffer

78% of negligible to slight damage, 40% of moderate

damage, 12% of significant to important damage, 2%

of very important damage. These results show a good

agreement with those evaluated by the deterministic

approach “Figure 6” for a type C building within the

urban area of Taroudant under a seismic intensity

VIII.

4 CONCLUSIONS

In this paper, two models for assessing the seismic

vulnerability of buildings are developed for typical

structures in the urban area of Taroudant, in particular

for type C buildings which are more abundant in this

city. The first model is based on a seismic

vulnerability index system for buildings. Then, a

reference model is developed according to a more

precise method, the non-linear static analysis, for

comparison of the damage assessed by the two

methods. Maps of the spatial distribution of seismic

building categories are developed.

For type C buildings and for a seismic intensity

scenario between VIII to IX, the results turn-out to be

quite similar between the damage probabilities

obtained by the deterministic approach and those

evaluated by the overall approach.

Based on these results and the maps of the spatial

distribution of seismic building categories, this study

provides a valuable technical support to the

authorities for the identification and assessment of

potential risk sites.

Future research on the development of seismic

vulnerability assessment models for buildings can

take this work as a standard and unified procedure for

studying vulnerable areas on a national scale.

REFERENCES

(US), F. E. M. A. (2017). Rapid visual screening of

buildings for potential seismic hazards: A handbook.

Government Printing Office.

Belmouden, Y. (2004). Analyse spectrale non itérative des

oscillateurs simples sous l ’ action des tremblements de

terre. 1–10.

Bendada, A., El Hammoumi, A., Gueraoui, K., Sammouda,

M., & Ibenbrahim, A. (2017). Vulnerability analysis of

a school building under tsunami loading in the gulf of

Cadiz. International Review of Civil Engineering, 8(1),

11–18. https://doi.org/10.15866/irece.v8i1.10912

Benjabrou, M., Zeggwagh, G., Gueraoui, K., Sammouda,

M., & Driouich, M. (2017). Evaluation of Seismic

Vulnerability of Existing Reinforced Concrete

Structure by Non-Iterative Spectral Method Using

Pushover Analysis with Interpretation of Fragility

Curves by RISK UE,(2017). International Review of

Civil Engineering (IRECE), 8(4), 177–186.

Chopra, A., & Goel, R. (1999). Capacity-Demand-Diagram

Methods for Estimating Seismic Deformation of

Inelastic Structures: SDF Systems. Pacific Earthquake

Engineering Research Center, April.

Combescure, D., Guéguen, P., & Lebrun, B. (2005).

Vulnérabilité sismique du bâti existant: approche

d’ensemble.

Dang, C.-T. (2014). Méthodes de construction des courbes

de fragilité sismique par simulations numériques.

E, N. (2020). Assessment of Tsunami and Seismic

Vulnerability of Buildings in the Agadir Bay Area,

Morocco. Journal of Advanced Research in Dynamical

and Control Systems, 12(SP4), 1727–1737.

https://doi.org/10.5373/JARDCS/V12SP4/20201655

El Azreq, M. A., El Hammoumi, A., Brahim, A. I.,

Gueraoui, K., El Mouraouah, A., Lbadaoui, A.,

Kerroum, M., Kasmi, M., Birouk, A., & El Harrouni,

K. (2011). Seismic Vulnerability of Traditional Earthen

Buildings.

El Azreq, M. A., El Hammoumi, A., Iben Brahim, A., El

Mouraouah, A., Kerroum, M., Gueraoui, M., Kasmi,

M., & Birouk, A. (2010). Spectrum response of earthen

buildings. International Review of Civil Engineering,

1(4), 266–274.

Fajfar, P. (2000). A nonlinear analysis method for

performance-based seismic design. Earthquake

Spectra, 16(3), 573–592.

Freeman, S A. (1975). Evaluations of existing buildings for

seismic risk-A case study of Puget Sound Naval

Shipyard. Proc. 1st US Nat. Conf. on Earthquake

Engrg., Bremerton, Washington, 1975, 113–122.

Freeman, Sigmund A. (1978). Prediction of response of

concrete buildings to severe earthquake motion. Special

Publication, 55, 589–606.

Ghobadi, M. S., & Yavari, H. (2020). Progressive collapse

vulnerability assessment of irregular voided buildings

located in Seismic-Prone areas. Structures, 25, 785–

797.

Grünthal, G. (1998). European macroseismic scale 1998.

European Seismological Commission (ESC).

Hammoumi, A. E. L., Brahim, A. I., Birouk, A., Toto, E.

A., Mouraouah, M. K., Gueraoui, K., & Kasmi, M.

(2009). Assessment of Seismic Vulnerability of Urban

Buildings in Morocco. Assessment.

Iben brahim, A., Mouraouah, A. El, Kasmi, M., & Birouk,

A. (2003). A preliminary Instrumental Seismicity

Catalog for the Western Mediterranean Region,

Proceedings of the Workshop on "la Sismicité et la

Gestion du Risque Sismique dans la Région Euro-

Méditerranéenne. Le Centre Euroméditerranéen de

Prévention Du Risque Sismique (CEPRIS), 49–55.

Kumar, P., & Samanta, A. (2020). Seismic fragility

assessment of existing reinforced concrete buildings in

Patna, India. Structures, 27, 54–69.

M. A. El Azreq, Moudrik, A. El Hammoumi, A. Iben

Brahim, K. Gueraoui, A. El Mouraouah, A. Lbadaoui,

M. Kerroum, M. Kasmi, K. E. H. (2012). Seismic

Vulnerability of Traditional Buildings in the Medina of

Fez. International Review of Civil Engineering, Vol.

3(n. 2), 206–217.

Maio, R., Estêvão, J. M. C., Ferreira, T. M., & Vicente, R.

(2020). Casting a new light on the seismic risk

assessment of stone masonry buildings located within

historic centres. Structures, 25, 578–592.

Milutinovic, Z. V, & Trendafiloski, G. S. (2003). Risk-UE

An advanced approach to earthquake risk scenarios

with applications to different european towns.

Contract: EVK4-CT-2000-00014, WP4: Vulnerability

of Current Buildings.

Mosleh, A., Rodrigues, H., Varum, H., Costa, A., & Arêde,

A. (2016). Seismic behavior of RC building structures

designed according to current codes. Structures, 7, 1–

13.

Mouraouah, A. El, Iben brahim, A., Kasmi, M., Birouk, A.,

El Mrabet, T., & zouine. (2004). Le séisme d’Al

Hoceima du 24 Février 2004 : Surveillance sismique et

analyse préliminaire : situation au 31 mai 2004 : Edition

Du CNRST-CEPRIS, 162.

Nchiti, E., El Hammoumi, A., Gueraoui, K., & Iben

Brahim, A. (2020). A Comparative Study of Seismic

and Tsunami Vulnerability of Structures Located in the

Coastal Area of Rabat-Salé, Morocco. International

Review of Mechanical Engineering (IREME); Vol 14,

No 4 (2020).

https://doi.org/https://doi.org/10.15866/ireme.v14i4.18

159

Nchiti, E., El Hammoumi, A., Gueraoui, K., Ibenbrahim,

A., & Bendada, A. (2020). Simulated Tsunami and

Earthquake Impact on RC Structures: a Comparative

Study. International Review of Civil Engineering

(IRECE); Vol 11, No 5 (2020).

https://doi.org/10.15866/irece.v11i5.18106

Ningthoujam, M. C., & Nanda, R. P. (2018). A GIS system

integrated with earthquake vulnerability assessment of

RC building. Structures, 15, 329–340.

Petrini, V. (1993). Rischio sismico di edifici pubblici, parte

I, Aspetti metodologici. Pubblicazione Del GNDT-

CNR, Roma, Italia, 0, 2.

Rezaei Ranjbar, P., & Naderpour, H. (2020). Probabilistic

evaluation of seismic resilience for typical vital

buildings in terms of vulnerability curves. Structures,

23, 314–323.

https://doi.org/10.1016/j.istruc.2019.10.017

RGPH 2014. (2014). General Census of Population and

Housing. http://rgphentableaux.hcp.ma/

Rojahn, C., Poland, C. D., & Scawthorn, C. (1988). Rapid

Visual Screening of Buildings for Potential Seismic

Hazards: A Handbook (Vol. 21). Applied Technology

Council.

RPS2000, S. code. (2011). RPS 2000—version 2011.

Ministère de l’Habitat et de La Politique de La Ville.

Rabat, Morocco.

Talhaoui, A., Aberkan, M., Brahim, I., & El Mouraouah, A.

(2005). Risques géologiques et activité sismique dans

la région d’{Al} {Hoceima} ({Maroc}): {Approche} de

la quantification des facteurs responsables du

déclenchement des instabilités de terrain {Geological}

hazards and seismic activity within the area of {Al} {H.