Earthquake risk assessment for Kuwait City, Kuwait

4.1 Seismic hazard model

The hazard model is defined as the severity and frequency of a hazard, which may be an earthquake, volcano, landslide … etc., at a specific location. To create such a module (Cornell 1968; Esteva 1970; McGuire 1978; Bender and Perkins 1987), Seismic hazard was estimated using PSHA. A comprehensive and unified catalog of quakes has been prepared that includes all the historical and instrumental events recorded in Kuwait and its surroundings to study the local and regional effects of earthquakes on Kuwait. These quakes were compiled from many sources and linear regression relationships were used to standardize the magnitude of these events to the moment magnitude (Mw) scale. Any duplicates were eliminated and the catalog de-clustering was applied to exclude the dependent events (Abd el-aal et al 2022). Based on the geographical distribution of earthquakes, structural and tectonic settings, and focal mechanism, a seismotectonic source model was built to show the seismic sources (local and regional) affecting Kuwait. This model consists of 27 area-source-type seismic sources (Fig. 3). Each source was subdivided into 1-unit magnitude bins. In each bin, the earthquake cumulative number was graphed vs. time to estimate the magnitude of completeness (Mc) (Burkhard and Grunthal, 2009; Abd el-aal et al. 2021a,b,c&Abd el-aal et al 2022).

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Fig. 3

Seismotectonic source model shows the regional and local seismic sources affecting Kuwait.

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The recurrence parameters b, β, and λ were estimated to define the ratio between small and large earthquakes, tectonics, and the activity rate, respectively, for each seismic source (Table 1). The highest quake magnitude was predicted for the seismic sources using the Kijko (2004) procedure and by adding ½ unit of magnitude to the maximum observed at the seismic source. Moreover, two attenuation relations (García et al. (2005) and Abrahamson and Silva (1997)) were used to predict the ground motion on bedrock. The earthquakes at each source were modeled to follow a Poisson process.

Finally, a set of stochastic seismic events should be produced to include all the probabilities of the expected magnitude and hypocenters to identify the intensity and frequency of the expected stochastic events for each seismic source. By modeling the attenuation characteristics of an event from the focus to a site and evaluating local geologic conditions, the severity of the event on a particular site can be determined. In this study, 14238 seismic hazard scenarios were generated to assess the seismic risk in Kuwait City using six magnitudes for each hypocenter. These six magnitudes are evenly spaced between the smallest and highest magnitudes of each seismic source.

4.2 Exposure model

The exposure model is an important and necessary input for seismic risk calculation. The study area was divided into several polygons, each polygon representing an exposure element. The potential economic and social losses are calculated for each exposure element in the event of an earthquake. To do these calculations, tabulated databases can be used for each exposure element. If this data is not available, mathematical methods that depend upon the availability of social info such as population density (human exposure) or economic statistics such as building statistics and their monetary value (economic exposure) can be used to create a database using available technologies and programs such as Geographic Information Systems (GIS) and remote sensing or using cadastral information (Cardona et al. 2012).

In this study, a database was created for 33,066 exposure elements (Fig. 1) exposed in Kuwait City, which includes information about the characteristics of these elements (constructions). The database includes the building’s locations, age, shapes, geometric, physical, and social characteristics, area, vegetative cover area, levels number, height, and the height of each floor as well. It also includes information on the economic activity of each building, the construction type, the materials these buildings are made of, and the building’s replacement values. It is also important to calculate the building occupancy to calculate the social impact, such as the maximum occupancy of each exposure element and its percentage over different hours during day and night, in order to create different temporal seismic scenarios for earthquake occurrence. However, if this information is not available, it is sufficient to calculate the occupancy density according to the building category (Coburn and Spence 1992) as is the case in the current study. The accuracy of these data greatly governs the accuracy and quality of the results. This study focused on calculating exposure to residential buildings and vital infrastructure including commercial, industrial, and governmental buildings such as hospitals, schools, malls, hotels, banks, schools, universities, bridges, mosques, churches, … etc., in order to preserve them to ensure a quick and effective recovery in times of disasters.

4.3 Vulnerability model

The vulnerability model is one of the models necessary to calculate the probable seismic risk. This module calculates loss (L) quantitatively and numerically in terms of damage to constructions, interruption of services, and human and social weakness. This module is characterized by the ability to provide the entire information essential to compute the likelihood of reaching /or exceeding loss values in what is known as seismic demand (S) (Cardona et al. 2012). It describes the loss's statistical moment variation (the Mean Damage Ratio (MDR) and its standard deviation) to different seismic demand values.

This model determines the destruction of each exposed element by the intensity of a particular event at a location (Miranda 1999). Developing or choosing a vulnerability equation for an exposed element depends on the structure classification. The classification of a structure depends on the building’s type, use, age, materials, and number of stories. Most buildings in Kuwait City are made of reinforced concrete materials, the construction of which has increased in recent decades. The height of the stories also varies for each exposed element in the city from single-story buildings to high-rise towers whose height exceeds 300 m. There are also buildings whose floor height is 3.5 m and others whose floor height is 6 m. An appropriate vulnerability function was determined for each exposure element in Kuwait City. The vulnerability function calculates the damage for each building using the vulnerability curve. This curve defines MDR versus the earthquake intensity in terms of peak and spectral ground accelerations.

5.1 Seismic hazard maps and spectra

Fig. 4 shows hazard maps demonstrating 5 % damped Spectral Acceleration (SA) for the Peak Ground Acceleration (PGA) and 0.1, and 1sec. spectral periods for return periods of 475, 975, and 2475-year. This figure shows a gradual increase in seismic activity from the eastern side to the western side of Kuwait City at the PGA and 0.1sec SA. Also, the seismic hazard at Failaka Island shows small seismic hazards. However, the seismic activity at the 1sec SA shows a gradual increase from west to east of Kuwait City. Also, the hazard at this spectral acceleration is the highest at Failaka Island. Overall, these figures show higher seismic hazards at the short period SA (0.1sec) compared to those at the long period SA (1sec). Furthermore, these maps show the highest hazard at the return period 2475-year followed by that at the 975-year return period. While it shows its lowest acceleration values at return period 475-year. These maps clearly reflect the seismicity and structures in the study area.

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Fig. 4

Probabilistic seismic hazard maps for PGA, 0.1 and 1 s at 475 (a), 975 (b), and 2475 (c) years return period for Kuwait city.

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Furthermore, UHS was assessed at three sites in Kuwait City to define the hazard at SA from 0 to 4secs at return periods of 475, 975, and 2475-year., equivalent to the probability of ground motion exceeding 10 %, 5 %, 2 %, respectively, over 50 yr (expected building design life). Fig. 5 shows the highest hazard values at 0.1sec SA except for site 1 where the highest hazard (81.7 Gal) is observed at 0.2sec SA for only the return period 475-year. The hazard is increasing from the eastern side (79.3 Gal) to the western side (113.04 Gal) at 0.1sec SA for the 475-year return period. At the remaining spectral periods, the hazard values are very close. In addition, the highest hazard (203.5 Gal at 0.1 sec SA) is observed at the 2 % probability of ground motion exceedance over the expected building design life. These results confirm the results obtained from the hazard maps.

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Fig. 5

The 5 % damped spectral acceleration UHS at 475, 975, and 2475 years return periods on bedrock for three sites in Kuwait city. The location of these sites is shown in Fig. 1 in the same colors drawn here.

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5.2 Seismic risk assessment

After completing the hazard, exposure, and vulnerability modules and designing them in the required format, the seismic risk is calculated to evaluate the potential impacts and losses of future seismic risks, whether economic losses and/or loss of life or injuries. Seismic risk is measured by calculating the anticipated number of events per unit time that will cause losses L greater than or equal to the loss l, which is known as the loss exceedance rate v(l). The total probability theory is used to calculate the loss exceedance rate as follows: $$v\left(l\right)=\sum _{i=1}^{\mathit{Events}}\mathrm{Pr}\left(L>l|Eventi\right)F_A\left(Eventi\right)$$ where $Pr\left(L>l|Eventi\right)$ is the probability of exceeding the loss, and F_A(Event i) is the annual frequency of event i and depends on the seismic hazard assessment results.

The vulnerability module is included in the calculations of the previous equation, which indicates the inherent uncertainties in seismic risk calculations. Therefore, the economic loss is calculated from the product of the damage ratio and the value at risk for each exposed element (building). The losses are then gathered using Ordaz et al. (1998, 2000) and Ordaz (2000) procedures. Finally, the net total losses are estimated.

The Loss exceedance curve (LEC) is a very important measure used to assess seismic risk. This curve estimates the financial cost necessary to achieve the risk managers' objectives. LEC is defined as the yearly frequency of exceeding a definite loss. It can be calculated for the most sever seismic event in a year. However, it is preferable to calculate it for all events, cumulatively, in one year, as it calculates the probability of one or more dangerous seismic events occurring. After calculating this curve, other measures can be obtained to evaluate seismic risk, including probable maximum loss (PML) and average annual loss (AAL). AAL (expected loss per year) can be estimated for each building and building groups while the PML can be estimated for the entire study area (Ordaz and Santa-Cruz 2003).

The AAL is the sum of future losses expected during an event and the probability of its occurrence annually for all stochastic events. Assuming that the process of dangerous earthquake occurrence is stationary and that the damaged constructions will be restored immediately after the seismic event, the predicted annual loss can take into account the economic losses of each structure for all predicted events. The AAL for the entire portfolio for Kuwait City was calculated and found to be $12,793,319.52.

The PML is the amount of loss for a certain annual exceedance frequency. In the PML curve, the percentage or economic value of loss is determined in relation to return periods. For buildings, PML represents an assessment of the expected maximum losses resulting from a hazardous event. Its importance is highlighted in determining the size of the reserves that the government or insurance companies must keep to evade extreme losses that may exceed their ability to adapt. Fig. 6 shows the probable maximum loss curve for the entire buildings of Kuwait City. It shows increasing of the loss with increasing the return period with an exponential relationship. Fig. 7 shows the annual economic loss expected for Kuwait City. This figure indicates that the average economic annual loss for each property in the city is nil. Fig. 8 shows the expected absolute monetary loss for each property in Kuwait City. The median expected absolute monetary loss is $386.81. These results show a small risk situation in Kuwait city. It is attributed to the small to moderate levels of both seismicity and seismic hazards in Kuwait City. In addition, the buildings in the City are well-prepared and are mostly made of reinforced concrete materials. Therefore, their vulnerability is small to moderate, and can resist small to moderate earthquakes.

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Fig. 6

The PML curve for the entire portfolio of buildings of for Kuwait city.

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Fig. 7

The expected annual economic loss, represented building by building, for Kuwait city and the western coast of Failaka island.

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Fig. 8

The expected absolute monetary loss, represented building by building, for Kuwait city and the western coast of Failaka island.

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Furthermore, the critical seismic risk was calculated to determine the facilities where damage may be concentrated in the event of a devastating future earthquake. Table 2 shows the five worst deterministic earthquake scenarios. This table shows that earthquake scenarios from seismic source 15 would cause the greatest damage to Kuwait City property. Also, this seismic source would produce the highest annual scenario recurrence frequency. Moreover, the uncertainty inherent in the models, specifically with regard to hazardous earthquakes, their frequency, and resulting losses, has been minimized by incorporating uncertainty into hazard and risk assessment. These results are very useful to risk managers, insurance companies, and decision-makers and should be taken into consideration when designing future urban development plans to reduce risks resulting from future earthquakes in Kuwait City.