Assessing the vulnerability of buildings to a tsunami in San Andrés de Canoa, Manabí, Ecuador an application of the PTVA-3 model

Running head: CANOA PTVA-3
Assessing the vulnerability of buildings to a tsunami in San Andrés de Canoa, Manabí,
Ecuador: an application of the PTVA-3 model
Liam Hartman, Oksana Bartosh, Filippo Dal’Osso
Abstract
San Andrés de Canoa (Canoa), located in the province of Manabí, Ecuador, is a coastal
community, with approximately 7,000 people, with an estimated 100,000 tourists per year. Due
to its geological proximity to the Carnegie Ridge, and the Nazca and South America tectonic
plates, the risk related to seismic activity is high. It is one of eighty-one communities in Ecuador
located to be in an area of tsunamigenic risk, identified in a report by the Ecuadorian
Oceanographic Navel Institute (INOCAR). There have been five major tsunami producing
earthquakes along the coast of Ecuador since 1906, the largest reaching a magnitude of M8.8
Richter (M). The Ecuadorian Oceanographic Navel Institute used the Tohoku University’s
Numerical Analysis Model for Investigation of Near-field tsunamis (TUNAMI) model to
conduct tsunami numerical simulations for the Ecuadorian coast. Using this simulation,
INOCAR was able to establish vulnerability levels for all the communities included in their
study.
The aim of this study is to access the vulnerability of buildings to damage from a tsunami
numerical simulation, used to identify vulnerable communities along the Ecuadorian coast. We
applied the Papathoma Tsunami Vulnerability Assessment Model – 3, to assess the vulnerability
of buildings for the community of San Andres de Canoa and produce thematic vulnerability
maps in regards to the projected tsunami scenario. The assessment allows us to make
recommendations about possible risk management and planning strategies for the community of
Canoa. Results show that the built form of Canoa has a high level of vulnerability to the
deterministic tsunami numerical simulation. This work has significant implications for
communities like Canoa along the western Ecuadorian coast.
1.0 Introduction
The Indian Ocean Tsunami of December 26, 2004 and the 2011 earthquake off the
Pacific coast of Tōhoku exposed the significance of tsunami threats to the world at large;
globally, nations have begun to take stock of their coastal vulnerability in order to safeguard their
own communities (Dall’Osso et al., 2012). These tsunamis were not unique, and it is known that
similar events have occurred in the past and will occur in the future (Dall’Osso & Dominey-
Howes, 2009). Tsunami warning systems, education, and disaster planning are becoming
common in at-risk areas around the world (Dall’Osso & Dominey-Howes, 2009). However,
detailed hazard, risk, and vulnerability assessments have not received the same amount of
attention (Dunning & Durden, 2013). Post et al. (2007) states that “the knowledge about
elements at risk, their susceptibility, coping and adaptation mechanisms are a precondition for
the setup of people centred warning structures, local specific evacuation planning and recovery
policy planning” (p.1). It is now imperative that tools that can forecast the physical impact of

TSUNAMI VULNERABILITY ASSESSSMENT AND CONSEQUENCE ANALYSIS
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future tsunamis on our communities must be advanced and implemented (Dall’Osso et al., 2012).
Tools that can quantify vulnerability posed by tsunamis will be vital to emergency managers,
urban planners, and end users in order to implement mitigative measures that can reduce
vulnerability and risk and aid in developing response and recovery plans.
San Andrés de Canoa (Canoa) is located in the province of Manabí, centred along the
Coast of Ecuador (Figure 1). It is a coastal community, with approximately 7,000 people, with an
estimated 100,000 tourists per year, generally between the months of December and April
(Dayson Vite, personal communications, March 12, 2013; Ministerio del Turismo, 2012b).
During holidays and weekends, the population of Canoa increases to five times its general
population with tourists (Ministerio del Turismo, 2012b). Canoa is located in a complex
geodynamic location where the Carnegie Ridge interrupts the Nazca and South America tectonic
plates, which meet and collide forming a pit or trench that runs roughly parallel to the coast
between 50 and 70 km (figure 2) (Gutscher, Malavieille, Lallemand & Collot, 1999, Rentería,
Lizano, Benavidas, Arreaga, & Pino, 2011). The Carnegie Ridge extends 930km from the
Galapagos Islands to the Ecuadorian mainland, where it further extends an estimated 700km at a
constant dip of 25°–35° down to 200 km under the South American Plate (Gutscher et al., 1999,
Rentería et al., 2011). This extension inland is suggested by the seismic gap and the perturbed,
broad volcanic arc (Gutscher et al., 1999). The impact of the Carnegie Ridge collision on the
upper plate causes transpressional deformation, extending inboard to beyond the Ecuadorian
mainland volcanic arc with seismicity comparable to the San Andreas Fault system (Gutscher et
al., 1999). This location provides a main seismic activity for Ecuador, as it divides the Nazca
Plate, and slips under the South American continental Plate (Rentería et al., 2011). These
collisions are capable of generating large earth and submarine quakes (Rentería et al., 2011).
Figure 1: Map of San Andres de Canoa, Ecuador, South America

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Figure 2: Geodynamic map for Ecuador (Collot, Agudelo, Ribodetti, & Marcaillou,
2008)
1.1 Record of tsunamis generating earthquakes in Ecuador
In the past century there have been five registered tsunamigenic earthquakes off the coast
of Ecuador (Figure 3): one in 1906 (magnitude of M8.8 Richter), one in 1933 (M6.9), one in
1953 (M8.3), one in 1958 (M7.8), and one is 1979 (M7.9) (Espinosa, 1992, Rentería et al.,
2011). The 1906 event in particular was one of the strongest tsunamigenic earthquakes recorded
in history (Cruz De Howitt et al., 2005; Espinosa, 1992; Rentería et al., 2011). All of these
earthquakes would have devastated most of the Ecuadorian coastal communities if those areas
were developed and/or inhabited at those times (Cruz De Howitt et al., 2005).

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Figure 3: Locations of the previously registered tsunamis off the coast of Ecuador (Rentería et
al., 2011)
Figure 4 shows the location of several "seismic swarms" registered off the Ecuadorian
coast between 2009 to 2014 (Cruz De Howitt et al., 2005, Rentería et al., 2011). The seismic
swarms are areas of high concentration of earthquakes, ranging from M4 to M6, however, the
magnitude of these earthquakes were insufficient to generate a tsunami.
Figure 4. Seismic swarms near Canoa (Cruz De Howitt et al., 2005)

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On the basis of historical tsunamigenic records (Rentería et al., 2011) has estimated the
tsunami probability on the coast Ecuador to be high, While Espinoza`s study (1992) estimated
the next submarine earthquake to be at least 7.5M, and located off the coast of Jama, Manabí
province, 36 km north of Canoa. Given today’s high population density and the low engineering
standards of most dwellings, the impact of a major tsunami on the coast of Ecuador could be
catastrophic (Cruz De Howitt et al., 2005).
1.2 Ecuadorian Tsunami Hazard Identification and Risk Assessment
The Ecuadorian Oceanographic Navel Institute (INOCAR) began a coastal hazard
research program in the early 1990’s, conducting laboratory and field work comprised of
collecting and analyzing nautical and topographic maps and charts published by INOCAR and
the Instituto Geográfico Militar (IGM) for the Ecuadorian coast (Espinosa, 1990, Espinosa, 1991,
Espinosa, 1992). This study identified tectonic environments and vulnerable coastal populated
areas along the Ecuadorian coasts (Cruz De Howitt et al., 2005; Espinosa, 1992; Rentería et al.,
2011).
Firstly, the study identified three tectonic environments, which form trench runing
parallel to the coast roughly 50 to 70 km west of the continental coast (Espinosa, 1991). The
first located north of the Carnegie Ridge, between latitudes 1ºN and 7ºN where the main
submarine topographic feature is the Malpelo Ridge (3° 50' 00" N, 81° 13' 00" W ), the second
tectonic place it south of the Carnegie Ridge, among 2ºS and 4ºS latitudes, facing the Gulf of
Guayaquil (3.0000° S, 80.5000° W), among 1ºN and 2ºS, and the third environment
characterized by elevations of the Carnegie Ridge (1.0000° S, 83.0000° W), which is hitting the
American Continental Plate against Manabí Province; this ridge appears on the surface in the
Galapagos hot spot and Islands an located about 930 km from the Ecuadorian mainland
(Gutscher et al., 1999). Following the course of the Nazca Plate to the east, the Carnegie Ridge
is embedding 700km below the central coast of Ecuador at a constant dip of 25°–35° down to
200 km under the South American Plate (Renteria et al, 2011). This extension inland is suggested
by the seismic gap and the perturbed, broad mainland volcanic arc (Gutscher et al., 1999). The
dip of the Carnegie Ridge is manifested in the shallow depth of the pit or trench off the coast of
Ecuador, other manifestations can be found on the active lifting of the beach area and coastline
between 1ºN to 6ºS 83.0000° W in Ecuador and Peru (Gutscher et al., 1999, Renteria et al,
2011).
Secondly, the study used the Tohoku University’s Numerical Analysis Model for
Investigation of Near-field tsunamis (TUNAMI) model (Imamura, 1997; Imamura et al., 2006)
as the main program for numerical simulation of tsunamis. The model combines TUNAMI-N1,
Numerical Analysis Model for Investigation of Near-field tsunamis (linear theory with constant
grids), TUNAMI-N2 (linear theory in deep sea, shallow-water theory in shallow sea and runup
on land with constant grids), TUNAMI-N3 (linear theory with varying grids), TUNAMI-F1
(linear theory for propagation in the ocean in the spherical co-ordinates) and TUNAMI-F2
(linear theory for propagation in the ocean and coastal waters) (Imamura, 1997; Imamura et al.,
2006).
The tsunami numerical simulation used a projected submarine earthquake of a magnitude
of 2 on the Imamura scale (Renteria et al, 2011), equaling at M8 (Bryant, 2008), at depths of 100

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metres for all study sites. The study placed the epicentres at coordinates of 1.685° N, 79.0975°W
in the first tectonic environment in the province of Esmeraldas, the second was projection was
located at 2.85° S, 81° W, effecting Santa Elena and Guayas province and the third tectonic
environment is projected to be located at 0.5° S, 80.5° W, slightly below Canoa (0.467° S,
80.450° W), in Manabí province (Figure 5) (Renteria et al, 2011). These locations were derived
from mean locations of previous large to great seismic events (Renteria et al, 2011).
Figure 5: Tsunami numerical Simulation epicenter for the Coast of the Province of
Manabí (Renteria et al, 2011).
In this study we focus on the last tectonic environment, encompassing the province of
Manabí for this study. The projected epicentre of tsunami numerical simulation approximates
tsunami arrival between ten to thirty minutes of its generation with wave propagation at heights
fluctuating from 1.1 to 9.1 meters above sea level (Figure 6), depending on coastal proximity,
bathymetric slope and tide level for the surrounding coastal area (Renteria et al, 2011).

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Figure 6: The heights of the tsunami wave likely reach the coast of the province of
Manabí (2011).
The study by INOCAR placed the M8 projected tsunami numerical simulation at 100
metres deep and 6 km off the coast of Canoa (Renteria et al, 2011). It is estimated to receive a
wave projected to reach 2 metres at Mean Sea Level (MSL) tide (Renteria et al, 2011). Canoa is
located in a coastal plain surrounded by elevations up to 100 meters high (Renteria et al, 2011).
The occupied land is relatively low and flat between 2 and 3 metres above mean high tide level
of 2 metres, and is bordered by the Canoa River to the north of the town (Espinoza, 1992).
Canoa’s vulnerability to flooding from the projected tsunami waves is estimated to be low, due
to the bathymetric slope leading up to Canoa from the earthquake’s, which makes the wave loses
energy due to the processes of bottom friction (Renteria et al, 2011). However, depending on the
state of the tide at the time that the phenomenon occurs, waves could increase with astronomical
high tide.
Lastly, the study undertook a geomorphologic analysis and identified 81 coastal
communities’ vulnerability along the Ecuadorian coast, including the town of Canoa (Cruz De
Howitt, Acosta, & Vásquez, 2005; (Renteria et al, 2011). The research completed community
inundation and evacuation maps which estimated levels of vulnerability for coastal communities
located close to beaches with little slope, with presence of swamps, islands, sandy accumulations
and estuaries (Cruz De Howitt et al., 2005; SNGR, 2012). The Inundation and Evacuation Maps

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identified zones with high and low inundation probability at highest astronomical tide levels
(HAT), as to identify all potential vulnerable areas within the community (SNGR, 2012).
Canoa’s location comprises many of the aforementioned geomorphologic characteristics
and was rated to be at moderate risk (Renteria et al, 2011). Highest astronomical tide levels for
Canoa are measured at 3 metres above MSL (SNGR, 2012). The high inundation probability
zone identifies topography at one metre above HAT levels, while the low inundation probability
is at three metres above HAT (SNGR, 2012). The application of HAT level effectively raises the
projected waves to a height of 5 metres high. Canoa`s inundation and evacuation map can be
found in below in Figure 7.
Figure 7: Tsunami Inundation Map of Canoa, Manabí, Ecuador (SNGR, 2012).
.
The study conducted by INOCAR did not included a vulnerability assessment (Renteria
et al, 2011), which is a critical component of a tsunami risk analysis (Jelınek & Krausmann,
2008). A vulnerability assessment of coastal building and infrastructure is essential in order to
understand the potential implications of a tsunami. Canoa has been identified as having low to
moderate vulnerability in the INOCAR study. Our study targets the gap of a tsunami
vulnerability assessment in this region. Cruz De Howitt et al. (2005) identified the area of Canoa
as being exposed to the highest tsunami risk in Ecuador; yet, little is known about the
vulnerability of the vulnerability of buildings and infrastructure.

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1.4 Aim of this work
This study aims to apply the Papathoma Tsunami Vulnerability Assessment-3 model
(PTVA-3) (Dall’Osso & Dominey-Howes, 2009) to assess the vulnerability of existing buildings
in the San Andres de Canoa to tsunami. The PTVA-3 Model calculates a Relative Vulnerability
Index (RVI) for every inundated structure.
This work relies on study by INOCAR, which carried out lab and field work that used nautical
and topographic maps published by INOCAR and Instituto Geográfico Militar (IGM) for the
Ecuadorian Coast and which conducted a tsunami numerical simulation (Renteria et al, 2011)..
This analysis is used in order to establish vulnerability for the study area. The results of this
study will be used to make a series of recommendations for emergency services, community
planners, and end-users. It will assist them in planning for and managing tsunami risk, inform
land-use zoning, buildings standards and codes, and emergency and evacuation planning.
2.0 Applying the Papathoma Tsunami Vulnerability Assessment Model (PTVA-3 Model)
2.1 Methodological Approach
This study applied the Papathoma Tsunami Vulnerability Assessment Model – 3 (PTVA-
3) (Dall’Osso et al., 2009) to examine the structural vulnerability to a projected tsunamigenic
hazard for the community of Canoa, Manabí, Ecuador. According to the authors, it concentrates
on the physical effects of a hazard and includes the identification of the elements at risk.
(Dall’Osso & Dominey-Howes, 2009)
This model is inherently qualitative in its approach, but uses quantitative data to define
the initial scenario parameters and to calculate the vulnerability scores. The PTVA-3 assessment
uses qualitative data in the forms of researcher field observations of the built form of Canoa,
along with building reference images which were then scored using a scoring rubric, and the
resulting quantitative data was used to calculate a relative vulnerability index for the buildings
within the study area. The information was then described in detail and presented using thematic
maps.
2.2 The Papathoma Tsunami Vulnerability Assessment Model – 3
The PTVA-3 Model was developed using detailed information about the impacts of
historic tsunamis and the results of numerous post-tsunami damage surveys (Dall’Osso &
Dominey-Howes, 2009; Dall’Osso et al., 2009a, Dall’Osso et al., 2009b; Dall’Osso et al., 2010;
Dominey-Howes and Papathoma, 2007; Dominey-Howes; 2010; Papathoma, 2003; Papathoma
& Dominey-Howes, 2003; Papathoma et al., 2003).
The PTVA-3 provides an effective means of identifying vulnerable buildings in locations
where tsunami fragility curves or more sophisticated engineering models are not available or not
fully validated (Dall’Osso & Dominey-Howes, 2009; Tarbotton et al., 2012).

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Dall’Osso and Dominey-Howes (2009) identified and ranked engineering and
environmental attributes that were reported to be responsible for controlling tsunami damage to
building structures, producing a model that offers a robust framework to explore building
vulnerability without certified engineering assessment models.
The main building attributes are grouped in three different categories: the physical
attributes of the building; the environment surrounding each building; and the depth of water
expected at the building location (Dall’Osso et al., 2010). The PTVA-3 Model requires all of the
necessary building attributes to be entered as numerical scores which are assigned according to
their contribution to the overall building vulnerability (Dall’Osso & Dominey-Howes, 2009;
Dall’Osso et al., 2010). To the PTVA-3 Model, each building is equally important, and since its
value is based on the structural-functional service, it does not account for the economic value of
buildings, or on the value of their contents (Dall’Osso et al., 2010; Dall’Osso & Dominey-
Howes, 2009). Also, contributions of individual engineering attributes are weighted using pair-
wise comparisons between attributes (Saaty, 1986). Using this technique, the contribution made
by separate attributes to the structural vulnerability of a building can be compared via a rigorous
mathematical approach, avoiding biases and reducing to a minimum the inevitable subjective
component of every decision making process (Dall’Osso & Dominey-Howes, 2009).
The PTVA-3 has been successfully implemented in two coastal areas of Sydney,
Australia (Dall’Osso & Dominey-Howes, 2009) and field tested in the Aeolian Island of Italy
(Dall’Osso et al., 2010). In the Aeolian study, the PTVA-3 model outputs were qualitatively
compared with post tsunami damage data from the 2002 Stromboli Tsunami, which showed
fairly accurate results (Dall’Osso et al., 2010).
2.3 Adapting the PTVA-3 Model to the construction standards of San Andrés de Canoa
As was stated in Dall’Osso et al. (2010), the PTVA-3 was developed to be applied
anywhere, though, RVI calculations rely upon type of architecture to be relatively consistent, but
may need to be modified to specific circumstances. For this study of Canoa, the researcher had to
adapt the building material factor slightly, as Dall’Osso et al. (2010) did in their application in
Italy. This paper uses the same building material adaptation as Dall’Osso et al. (2010), and added
bamboo and thatched roofs to the building material list where timber is located, and added
‘poorly cemented bricks’ in lieu of single brick, as much of the buildings in Canoa use these
(INEC, 2010) and the materials Dall’Osso et al. (2010) outlines in Italy (Figure 7).
-1 -
0.5
0 +.05 +1
Material
(M)
Reinforced
concrete
Double
Brick,
Single brick
(Ecuador - Poorly
cemented brick)
Timber
(Ecuador - Bamboo/
thatched Roof)
Table 1: Scores given to the attribute “m” (building material). These scores have been modified
with respect to the original PTVA-3 Model in order to fit with the common construction
practices used in Canoa, and along the Coast of Ecuador.

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Figure 8. Typical buildings located in Canoa (Ministerio del Turismo, 2012a)
2.4 Data Gathering
The field site of Canoa was selected using the SNGR Inundation and Evacuation Map for
Canoa, which identified inundation zones with high and low inundation probability at highest
astronomical tide levels (HAT) (figure 7) (SNGR, 2012). Highest astronomical tide levels for
Canoa are measured at 3 metres above MSL (INOCAR, 2013). The high inundation probability
zone identifies topography at an average of one metre above HAT levels, while the low
inundation probability is at an average of 3 metres above HAT (Renteria et al, 2011; SNGR,
2012). The tsunami numerical simulation projected waves to reach heights at 2 metres high
(Renteria et al, 2011). Therefore, in order to be congruent with the HAT levels used in the
inundation and evacuation map for Canoa, we used a wave height of five metres in order to
calculate relative vulnerability for the PTVA-3 model.
To complete the PTVA-3 for Canoa, this study relied upon field surveys including an
examination of the building structures within the target area using filed observations and ground
truthing field surveys to develop a relative vulnerability index to be applied to thematic maps in
order to display structural vulnerability within the study area of Canoa.

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We undertook field surveys to ground truth 506 buildings identified as being exposed to
the selected tsunami scenario. During field surveys we acquired data about the building attributes
as required by the PTVA-3 model. These include attributes of the building structure (i.e. number
of stories, building material, ground floor hydrodynamics, foundation type, the presence of
moveable objects, shape and orientation and preservation condition), and attributes of the
building surroundings (i.e. building row, presence of natural barriers, seawall height and shape,
and height of any brick walls around a building). Once collected, data were used to calculate the
Relative Vulnerability Index (RVI) of each building. A full description of the details regarding
the calculation of RVI scores can be found in Dall’Osso et al., (2009a). While the PTVA-3
model uses a GIS platform for undertaking the calculation, we obtained the same result using an
excel spreadsheet. The calculated RVI scores were used to generate a thematic building
vulnerability map for the area of Canoa, where buildings having different vulnerability levelS are
represented with different colours.
3. Results
Field survey results indicate that all the buildings in this area typically have shallow
foundation (one metre or less); and are not protected by seawalls or natural barriers. Out of 506
buildings assessed in this study, 115 (23%) buildings have been classified as having very high
vulnerability, 82 (16%) high vulnerability, 86 (17%) average vulnerability, 205 (40%) moderate
vulnerability, and only 18 (4%) minor vulnerability (Table 2). This means that over 50% of the
exposed buildings have average to very high vulnerability to the selected tsunami scenario.
(Table 3).
RVI ranking Number and Percentage of buildings
Very High 115 (23%)
High 82 (16%)
Average 86 (17%)
Moderate 205 (40%)
Minor 18 (4%)
Total Buildings Assessed 506
Table 2: Distribution of Relative Vulnerability scores

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RVI ranking Portion of buildings (Total Buildings 506)
Average to Very High 283 (56%)
Minor to moderate 223 (44%)
Table 3: Distribution of building Vulnerability
Figure 9 illustrates the relative vulnerability of the exposed buildings in Canoa. Most of
the buildings rated as ‘very high’ or ‘high’ vulnerability are located within high inundation
probability zone. This area also included 95% (or 82 structures) of all the buildings ranked as
‘average’ and 22% of ‘moderate’ vulnerable structures. This area is projected to have an
inundated depth of four meters (designated by the light-orange area on Figure 9). The buildings
located within the low inundation probability zone (designated by the yellow-green area on
Figure 9) have with the projected inundation depth of two metres, included 78% of the moderate
risk, 4% of the average risk and 100% of the minor risk buildings (Table 4).
Figure 9: Relative Vulnerability Map of Canoa

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RVI rating (High Inundation) (Low inundation)
Very High 115 (100 %) 0 (0%)
High 82 (100%) 0 (0%)
Average 82 (95%) 4 (5%)
Moderate 45 (22%) 160 (78%)
Minor 0 (0%) 18 (100%)
Table 4: Building Relative Vulnerability within high and low probability inundation
zones.
The exposed buildings were classified on the basis of their main use in the following
classes: private residences, hotels & hostels, restaurants, bars & discos and critically important
buildings (e.g. police stations, hospitals, schools, municipal offices). These are the official ‘use’
of buildings of locally owned tourist driven businesses. Many of these buildings provided
multiple services, such as hotel, bar and restaurant, but in this study, we grouped them into their
official business role. Residential buildings hosting unregistered commercial activities were
classified as private residences.
Table 5 presents the distribution of RVI scores across the five building use classes. These
include 374 private residences, 49 hotels/hostels, 57 restaurants, 20 bars/discos and 6 critically
important buildings.
Use of Building #buildings Very High High Average Moderate Minor
Private Residences 374 (74%) 48 (13%) 59(16%) 66 (18%) 184 (49%) 17 (4%)
Hotels & Hostels 49 (10%) 6 (12%) 14 (29%) 16 (33%) 12 (24%) 1 (2%)
Restaurants 57 (11%) 44 (77%) 6 (11%) 3 (5%) 4 (7%) 0 (0%)
Bars & Discos 20 (4%) 17 (85%) 2 (10%) 1 (5%) 0 (0%) 0 (0%)
Important buildings 6 (1%) 0 (0%) 1 (17%) 0 (0%) 5 (83%) 0 (0%)
Table 5: Buildings divided by class with Relative vulnerability rating.
Critically important buildings included the one police station, one health clinic, one
school, one gas station, one municipal building, one cemetery, and the church. The police
station, schools, gas station, municipal building, cemetery, and the church were all rated as
moderate. Their elevation and location far back in the community, along with other building
vulnerability and protection factors, contributed to these ratings. Consequently, the health clinic,
located within the high inundation zone received a high vulnerability rating also based on the
same elements of the PTVA-3 model.

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4 Discussion
Results show that large portions of Canoa’s buildings have high levels of vulnerability.
Most buildings are made of wood, bamboo, and other light materials, with roofs of corrugated
iron or zinc, tile or thatched leaves. Many of these dwellings do not comply with local law
construction requirements and safety standards, which further increases their vulnerability
(Rentería et al., 2011; INEC, 2010). Some of the houses are raised off the ground by two or three
feet and supported by wooden pillars, increasing hydrodynamics, but most cases did not and are
one to two storeys, in poor preservation condition (INEC, 2010). Additionally, most of the
buildings generally have wood, straw or dirt floors and use recycled materials such as
newspapers, cardboard, magazines; branches, asbestos, cans, and plastic as building materials
(INEC, 2010). Moreover, buildings in Canoa typically have shallow foundation levels, a
common rectangle building shape, which contributes to a poor hydrodynamics; and have further
increased vulnerability due to the lack of a seawall, or any type of natural barriers.
The PTVA-3 model results clearly show a generalised high vulnerability level of the
study area. Over 50% of the exposed buildings were classified as having average to very high
vulnerability scores. An overwhelming portion of the buildings (i.e. 197 buildings out of 506) to
have high to very high vulnerability, however 48 of the Very High rated buildings are
improvised restaurants known locally as ‘chozas’ or huts located on the main beach, and the
majority of them are only used often only occasionally for national holidays.
There are some anomalies to the pattern of vulnerability revealed in the findings. Ninety-
six percent of the buildings classified as average vulnerability are scattered throughout the high
inundation zone, a location that is predominantly occupied with high and very high vulnerability.
This has revealed some major differences in the construction of these buildings compared to the
general practice within the rest of the community, as their classification showed considerable
resiliency to the tsunami scenario. The differences in construction standards are reflected by the
PTVA-3 model scores. In most cases, buildings with lower RVI scores are generally built with
better standards for tourism purposes and have better preservation conditions. This is consistent
with what Calgaro and Lloyd (2008) observed in Thailand after the 2004 Indian Ocean Tsunami;
while smaller wooden structures were demolished by the tsunami waves, larger foreign owned
open concept/well-constructed buildings remained structurally intact.
Another interesting finding was the visible difference between the high and low probable
inundation zones, where one can see a remarkable difference in levels of vulnerability in
buildings. It is documented that buildings located within the low inundation probability zone and
faired considerably better. This visible rift in ratings is predominantly based on which row they
were located in, in combination with their elevation level; acquiring lower vulnerability levels
the further back a building was located.
The historic record of tsunami impacting Ecuador’s coast shows that 5 tsunamis have
occurred in the area, thus indicating a significant tsunami hazard threat for this region (Cruz De
Howitt et al., 2005; Espinosa, 1992; Rentería et al., 2011).

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The main limitations of this work are:
- The tsunami hazard assessment is based on a single tsunami event triggered by
a submarine earthquake of 8.0M at a depth of 100 metres. This examples does
not represent the worst case scenario for Canoa and further research should
address this issue.
- The impact of cascade effects, such as the tsunami flow triggering landslides or
sandy liquefaction, is not considered.
- Tsunami flow velocity is not considered.
- The effect of debris is qualitatively considered only for large movable objects
such as cars or trucks through the attribute “mo” of the PTVA-3 model. The
impact of smaller debris trapped in the tsunami flow is not considered.
- The PTVA-3 model is solely a building vulnerability assessment tool. The
vulnerability of the population or other socio-economic impacts is not
considered in this work and should be addressed by future research.
5.0 Recommendations
Based on the PTVA-3 assessment results, the following recommendations have been
made to the municipality of San Vicente, where Canoa is located:
- The design of new buildings should comply with safety codes and standards for flood-
prone areas. Generally speaking, Canoa is known to be an area where building codes are ignored
and not enforced. The municipality needs to reinstate guidelines for floor layouts, heights of
buildings, numbers of floors, material, and orientation which are generally followed in most
urban centres of Ecuador. Solid materials such as reinforced concrete, steel, or 30m think
masonry walls should be preferred over timber, bamboo or other temporary materials. Deep
foundations and open ground floors would further decrease the vulnerability to inundation.
- The Municipality should make sure that public buildings, particularly those providing
important services such as schools, health clinics, utility and government buildings, have the
necessary engineering requirements to be fully operative during marine inundations caused by
tsunamis or storms.
- Financial support should be made available for retrofitting existing private buildings to
comply with the national construction and safety standards. It is suggested that the SNGR work
with the local community to reduce the vulnerability of those structures.
- Land use planners should ensure that existing natural areas along the coast are
maintained and new green areas are included in future urban plans. Natural barriers would not
only act as buffers against the hydraulic forces of tsunami inundation, but would add value to
area and help support the tourism sector.
- Tsunami evacuation maps and plans should be shared with the local community and
visibly posted in buildings that operate in tourism, recreation or cultural sector, such as
restaurants, hotels/ hostels, travel agencies and recreational or cultural centers. This is especially

17
important for this community, as it receives tourists from all over the world, and the temporary
residents of these buildings change on a regular basis.
- Tsunami emergency management educational activities should be organised in schools
and cultural centres.
- This study primarily focused on the structural vulnerability of Canoa’s built form.
Further research into the examination of risk perceptions, awareness and preparedness of a
tsunami or seismic hazard within the community of Canoa as well as emergency management
staff and responders, using either quantitative or qualitative methods, could greatly benefit the
SNGR as well as the community itself.
- Given the high tsunami risk for Ecuador, we recommend undertaking vulnerability
assessment using the latest PTVA model available or other validated assessment tools in
different Ecuadorian coastal locations.
- This study adopted the tsunami hazard assessment undertaken by INOCAR, which was
undertaken by running the TUNAMI numerical simulation of the tsunami generation,
propagation and inundation. We recommend repeating this study using an accurate DEM of the
study area to improve the accuracy of the hazard assessment, as elevations below 10 metres were
dubious and used only as averages.
6 Conclusions
Historical records show that Ecuador is exposed to relatively frequent tsunamis triggered
by earthquakes along the [insert name of subduction zone here]. The exposure of Ecuador coastal
areas has significantly increased in the last century due to intense urbanisation and elevated
population growth. Yet, in part for lack of resources, no comprehensive tsunami vulnerability
assessment has been undertaken anywhere in Ecuador. This work demonstrates how a
comprehensive building vulnerability assessment can be undertaken in Ecuador using the
available data and minimal resources. For the first time, we used the PTVA-3 model without GIS
support and generated thematic vulnerability maps for the area of Canoa.
Results confirmed that Canoa’s built environment is very vulnerable to tsunamis. Multi-
storey reinforced concrete buildings, with open ground floor plans or good hydrodynamic shape
were assessed as being less vulnerable than typical local dwellings in timber or bamboo, even if
most of the resilient buildings were located close to the beach, where inundation depth would be
larger.
This research informed the municipal disaster plan for Canoa, developed by the SNGR
and broad tsunami research in Ecuador. Results may be used to help local disaster and
emergency managers determine preparedness and response strategies, as well as to develop

18
suitable mitigation actions through an improved land use planning and new building codes and
regulations. This analysis of building vulnerability to tsunamigenic risk can enable local
authorities and emergency planners to focus their limited resources in the most effective way.
Moreover, this analysis can help the SNGR and other governmental or non-governmental
agencies tasked with the responsibility of managing and responding to actual disasters and
preplanning mitigative measures. The study results may enable various end-users to produce a
series of maps that can help those agencies respond better, by knowing where the most
vulnerable building and, potentially, persons, households and businesses are located (Dall’Osso,
et al., 2009; Dall’Osso, et al., 2009b; Dominey-Howes & Papathoma, 2003).
References
Arreaga, Patricia. (1996) Estudio de los tsunamis en la costa sur del Ecuador (golfo de
Guayaquil), Guayaquil, Departamento de ciencias del mar centro de alerta de tsunamis,
Instituto Oceanográfico de la Armada [INOCAR], Ecuador.
Bryant, E. (2008). Tsunami: the underrated hazard. Springer.
Calgaro, E., & Lloyd, K. (2008). Sun, sea, sand and tsunami: Examining disaster vulnerability in
the tourism community of Khao Lak, Thailand. Singapore Journal of Tropical
Geography, 29(3), 288-306.
Collot, J.-Y., W. Agudelo, A. Ribodetti, and B. Marcaillou , 2008. Origin of a crustal splay fault
and its relation to the seismogenic zone and underplating at the erosional north Ecuador–
south Colombia oceanic margin, J. Geophys. Res., 113, B12102,
doi:10.1029/2008JB005691, 2008. 005691, 2008.
Cruz De Howitt, M. A., Acosta, M.C., & Vásquez, N.E. (2005). Riesgos por tsunami en la costa
Ecuatoriana. [Tsunami hazards in the Ecuadorian coast]. Sangolquí, Sección Nacional
del Ecuador del Instituto Panamericano de Geografía e Historia.
Dall’Osso, F., & Dominey-Howes, D. (2009). A method for assessing the vulnerability of
buildings to catastrophic (tsunami) marine flooding, unpublished report, 139 pp.

19
Dall'Osso, F., Gonella, M., Gabbianelli, G., Withycombe, G., & Dominey-Howes, D. (2009a). A
revised (PTVA) model for assessing the vulnerability of buildings to tsunami
damage. Natural Hazards and Earth System Science, 9(5), 1557-1565.
Dall'Osso, F., Gonella, M., Gabbianelli, G., Withycombe, G., & Dominey-Howes, D. (2009b).
Assessing the vulnerability of buildings to tsunami in Sydney. Natural Hazards and
Earth System Science, 9(6), 2015-2026.
Dall’Osso, F., Bovio, L., Cavalletti, A., Immordino, F., Gonella, M., & Gabbianelli, G. (2010). A
novel approach (the CRATER method) for assessing tsunami vulnerability at the regional
scale using ASTER imagery. Rivista Italiana di Telerilevamento, special issue:
Geomatics technologies for coastal environment observation, 42(2), 55-74.
Dall’Osso, F., Maramai, A., Graziani, L., Brizuela, B., Cavalletti, A., Gonella, M., & Tinti, S.
(2010). Applying and validating the PTVA-3 Model at the Aeolian Islands, Italy:
Assessment of the vulnerability of buildings to tsunamis. Nat. Hazards Earth Syst. Sci.
Dominey-Howes, D., & Papathoma, M. (2007). Validating a tsunami vulnerability assessment
model (the PTVA Model) using field data from the 2004 Indian Ocean tsunami. Natural
Hazards, 40(1), 113-136.
Dunning, C. M., & Durden. S. (2013). Social vulnerability analysis: A comparison of tools.
Alexandria, VA: U.S. Army Corps of Engineers, Institute for Water Resources.
Espinoza, J. (1990) Posibles efectos de un tsunami en las costas de la península de Santa Elena -
Ecuador [Potential effects of a tsunami on the north coast of the province of Esmeraldas -
Ecuador]. Guayaquil, Departamento de ciencias del mar centro de alerta de tsunamis,
Instituto Oceanográfico de la Armada [INOCAR], Ecuador.

20
Espinoza, J. (1991) Efectos potenciales de un tsunami en la costa norte de la provincia de
Esmeraldas - Ecuador [Potential effects of a tsunami on the north coast of the province of
Esmeraldas - Ecuador]. Guayaquil, Departamento de ciencias del mar centro de alerta de
tsunamis, Instituto Oceanográfico de la Armada [INOCAR], Ecuador.
Espinoza, J. (1992) Informe de Evaluación del Riesgo de Tsunamis de las Poblaciones de la
Costa Central del Ecuador - Ecuador [Risk Assessment Report Tsunami Stocks Central
Coast of Ecuador - Ecuador]. Guayaquil, Departamento de ciencias del mar centro de
alerta de tsunamis, Instituto Oceanográfico de la Armada [INOCAR], Ecuador
Geist, E. L., Titov, V. V., & Synolakis, C. E. (2006). Tsunami: Wave of Change. Scientific
American, 294(1), 56-63.
Gutscher, M. A., Malavieille, J., Lallemand, S., & Collot, J.Y. (1999) Tectonic segmentation of
the North Andean margin: impact of the Carnegie Ridge collision. Earth and Planetary
Science Letters 168, 255–270
Instituto Oceanográfico de la Armada del Ecuador. (2013). Tabla de Mareas [Tide Table].
http://www.inocar.mil.ec/mareas/mareas.php
Instituto Nacional de Estadística y Censos. (2010). Plan de Desarrollo y Ordenamiento
Territorial Parroquia rural de San Andrés de Canoa. [Rural Land and Plan development
of San Andrés de Canoa]. San Vicente, Manabí.
Imamura, F. (1997). IUGG/IOC Time Project: Numerical method of tsunami simulation with the
leap-frog scheme. UNESCO IOC.
Imamura, F., Ozyurt, G., & Yalciner, A. (2006). Tsunami modelling manual. UNESCO IOC
International Training Course on Tsunami Numerical Modelling.
Jelınek, R., & Krausmann, E (2008). Approaches to tsunami risk assessment. Luxembourg:
European Communities, OPOCE.

21
Ministerio del Turismo. (2012a). Catastro de alojamientos, bares, discotecas y restaurantes de
San Andrés de Canoa. [Registration of accommodation, bars, clubs and restaurants of
San Andrés de Canoa]. Quito, Ecuador.
Ministerio del Turismo. (2012b). Provincia Manabí Cantón San Vicente Playa de Canoa.
[Canoa beach, municipality of San Vicente, Manabí]. Quito, Ecuador.
Papathoma, M. (2003). Assessing tsunami vulnerability using GIS with special reference to
Greece. Unpublished PhD thesis, Coventry University (UK).
Post, J., Zosseder, K., Strunz, G., Birkmann, J., Gebert, N., Setiadi, N., ... & Siagian, T. (2007,
July). Risk and vulnerability assessment to tsunami and coastal hazards in Indonesia:
conceptual framework and indicator development. In A paper for the international
symposium on disaster in Indonesia, Padang, Indonesia (pp. 26-29).
Rentería, W., Lizano, M., P., Benavidas, Arreaga, P. & Pino, L. (2010). Diagnóstico de la
amenaza tsunamigenica de las costas Ecuatorianas. [Diagnosis of the tsunamigenic
threat of the Ecuadorian coasts]. Guayaquil Instituto Oceanográfico se la Armada
(INOCAR).
Saaty, T.L. (1986). Axiomatic foundation of the Analytic Hierarchy Process. Management
Science, 32, 841-855
Secretaria Nacional Gestión de Riesgos. (2012). Mapa de inundación y ruta de evacuación. [Map
Flood and evacuation route map]. Guayaquil. SNGR.
Tarbotton, C., Dominey-Howes, D., Goff, J. R., Papathoma-Kohle, M., Dall'Osso, F., & Turner,
I. L. (2012). GIS-based techniques for assessing the vulnerability of buildings to tsunami:
current approaches and future steps. Geological Society, London, Special
Publications, 361(1), 115-125.

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