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Laurens van den Bos 10829148 Earth Sciences

Wesley Chin 10770216 Business Studies

Joey Hodde 10663924 Human Geography

Jorinde Guldenaar 10799753 Earth Sciences Interdisciplianry Project Tutor: Mw. R. Bakker Supervisor: Dhr. Dr. K. F. Rijsdijk 23-12-2016

MAPPING

SOCIOECONOMIC

EARTHQUAKE

VULNERABILITY

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Abstract

In this paper the spatial distribution of socioeconomic earthquake vulnerability in Aceh, Indonesia is assessed using a novel holistic approach. By analysing the geological setting of the region, tsunami hazard, earthquake amplification and landslide hazards are calculated. Drawing from a political ecology framework, social resilience is spatially distributed by using proxies for the different aspects of resilience. These outputs are combined with data concerning the economic value in different regions of the Aceh province. In doing so a map is constructed that contains information regarding earthquake vulnerability that takes in account both social and natural factors.

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Table of contents

1. Introduction……….3 2. Geological setting………...5 3. Underlying theories in natural and social sciences in analyzing earthquake prone areas in Aceh………..7 3.1 Underlying theories in natural sciences: earthquake vulnerable areas in Aceh……….7 3.1.1 Amplification and landslides……….8 3.1.2 Analyzing geological aspects of different topological sites……….8 3.1.3 Tsunami generation, propagation and inundation………9 3.2 Underlying theories in social sciences: earthquake vulnerable areas in Aceh………..10 3.2.1 The human geography of disaster……….10 3.2.2 Economic value of regions for companies and communities………..11 4. Methods………..13 4.1 Geological vulnerability map………..13 4.2 Tsunami vulnerability map………14 4.3 Resilience map………14 4.4 Economic value map……….16 4.5 Combining maps………..16 5. Results………..17 6. Conclusion……… 34 7. Discussion & Recommendations………..35 8. Literature………... 36

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1. Introduction

Indonesia is located in an area with very high tectonic activity, called the Pacific Ring of Fire. In the past Indonesia has suffered many earthquakes combined with floods and tsunamis (Cox et al., 2016). Earthquakes form a threat as the location and time are often unpredictable (CIT, 2008). These natural disasters have highly devastating impacts, including many deaths and destruction of the land area (Cox et al., 2016), therefore it is crucial and urgent to map the most vulnerable areas as a consequence of earthquakes. Furthermore, mapping vulnerable areas in Aceh is very useful in developing mitigation strategies in the near future. Especially Sumatra is very prone to earthquakes, because it is located along the Sumatran Subduction Trench. Furthermore, a second fault, the Sumatran Fault, located right of the subduction trench is enhancing the risks of earthquakes in this region (CIT, 2008). Offshore earthquakes in the Indian Ocean also have a large effect as they can trigger tsunamis. Due to mismanagement, lack of skills or corruption in Indonesia the weak infrastructure development is enhancing the destructive impact of earthquakes (Cox et al., 2016). These unfortunate characteristics have culminated to a catastrophic extent in 2004, when an earthquake and the resulting tsunami claimed the lives of over 283.000 people (Lay et al., 2005). The region has showed a great deal of seismic activity since, including a seismic event in Aceh that occurred during the writing of this paper at December 5th 2016. At the time of writing 97 people were reported dead and 73 seriously injured (Quiano & Westcott, 2016). Figure 1 shows the epicenter of the earthquake. Figure 1: epicenter of the 5 December 2016 earthquake in Aceh, Indonesia (Quiano & Westcott, 2016) These natural disasters have serious impacts on society and economy. In order to reduce the impacts of earthquakes it is important to understand the behaviour of these natural phenomena. Eventually we can strengthen our ability to reduce the impact and to make a smoother transition

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into a new stable state (Petak, 2002). The aim of this interdisciplinary research is the development of a disaster hazard map focusing on the province Aceh, which is representative for Sumatra, because particular settings are examined that occur along the whole island. Downscaling is necessary because of the complexity of determining vulnerability for various disciplines. This analysis in Aceh will result in a more clear picture of earthquake hazards. Together with the social, geographical and economic perspectives the most vulnerable areas in Aceh can be determined. As certain communities in Sumatra have different earthquake risks, institutional capacity, social and political environments, economic condition and financial capacity it is significant to combine different disciplines to gain deeper insights in the problem and how it can be solved. Furthermore, the inclusion of these different aspects will be an extension of the current scientific methods of risk determination and might be of use in further research. The following research question and subquestions will be answered during this interdisciplinary research: What areas in Aceh, located in Sumatra, are the most vulnerable for casualties due to earthquakes? ● What is the geological setting of Aceh, Indonesia? ● What are influences of geological and topographical aspects on earthquake vulnerability in Aceh? ● What coastal regions are most vulnerable for inundation in the case of tsunami events? ● How is social resilience to earthquakes and resilience spatially distributed? ● Which regions are most economic valuable for Aceh to be protected against natural hazards? This article will first describe the geological setting of Sumatra, which is important to understand the physical processes of earthquakes in this area. Secondly, the theoretical framework clarifies all necessary underlying theories that need to be known for the execution of this research. Then, the methodology is described and the results are shown. The article will be completed with a conclusion and discussion.

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2. Geological setting

The geological setting of Sumatra and its province Aceh is significant for analysing the casualties of earthquakes in this region. Sumatra is very prone to earthquakes, because it is located at the boundary of the southwest Australian oceanic plate and the north Eurasian continental plate. In short, the Australian plate is moving beneath the Sunda Plate, part of the Eurasian plate, in northern direction resulting in the Sumatran Subduction Trench (figure 2). In broad sense, when two plates become locked, as a consequence stress is building up. When the Sunda plate is pulled down, the area near the Sumatra Subduction Trench subsides, while the area further away from the trench lifts up. If the rising stress at some point exceeds the locking friction an earthquake is generated. The islands near the trench suddenly pops back up and the area further away subsides. Eventually the ocean floor moves suddenly upward and may cause large displacements of ocean water resulting in a tsunami (CIT, 2008). This is a simplistic interaction, in detail it is much more complex than that. Sumatra is even more vulnerable, because of a second fault, the Sumatran Fault, located right of the subduction trench as can be seen in figure 1 (ibid.). The Sumatran Fault passes through entire Aceh, which is enhancing the risks of earthquakes in this province. The rate in which the Sunda plate is converging against the Australian plate is somewhat slower than the opposite motion. Furthermore, the collision of the two plates is not in a right angle to the strike of the trench. The stress of the two faults thus results in the isolation of a wedge of forearc called the silver plate (figure 3a). Many frictions in different directions dominate in the Aceh region, which makes it very vulnerable to earthquakes (figure 3 and 4) (McCaffrey, 2009). Figure 2: Schematic cross-section of the Sumatran plate boundary (McCaffrey, 2009)

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Figure 3: Block diagram showing the collision of the subducting (Australian plate) and the overriding (Eurasian) plate with the frictions of the Silver plate in between (McCaffrey, 2009) Figure 4: Map of Aceh showing plate motions (McCaffrey, 2009)

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3. Underlying theories in natural and social sciences in

analyzing earthquake prone areas in Aceh

Elaborated in the previous section Aceh is very vulnerable to earthquakes, because of its complex geological setting. In this paragraph the earthquake prone area of Aceh is researched by analysing both natural and social underlying theories. Firstly, the earthquake prone area of Aceh is divided into zones with respect to aspects of natural sciences of the sites. This includes also the analysis of the local site effects of geology, geomorphology and tsunamis to create an earthquake vulnerability map for Aceh . In this way an earthquake hazard can be investigated very detailed in order to evaluate risks and to reduce casualties for Aceh’s population. These analysis can also be very useful in locating key facilities for citizens and financial zones (NIDM, n.d.). This interdisciplinary way of intergrating different disciplines to determine earthquake prone areas in Aceh is visualised in diagram 1. Diagram 1: Overview of the interdisciplinary discourse of this research

3.1 Underlying theories in natural sciences: earthquake vulnerable areas in Aceh

In this paragraph the relation between soil properties and the behaviour of seismic waves at different topographical sites in Aceh are described first. Consequently the processes of tsunami generation, propagation and inundation are explained.

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3.1.1 Amplification and landslides An important concept in analysing earthquake risks is the effect of amplification, which refers to the influence of surface geology on seismic motion. Several studies have stated that damaged areas due to earthquakes are connected with geological site-dependent factors. Soil properties alter seismic motions (Johar, Majid, Jaffar & Yahya, 2013). The type and depth of soils have influence on seismic waves. According to Vusetic (1992) the Plasticity Index (PI) is important in determining the abundance of soils during an earthquake. The PI is characteristic for different kind of soils and is dependent on size, shape and mineralogy of soil particles. It is determined that clay has high levels of PI and are therefore capable of strongly amplifying the incoming seismic waves due to earthquakes. In contrast to saturated sand, for which PI = 0, has no or very low amplification. In contrast to shallow soils or rock, deep soils have very high amplification because resonance may occur. Often the instability of slopes caused by earthquakes has a higher devastating impact than the earthquake itself (Ambraseys & Srbulov, 1995). The major trigger of landslides is the intensity of seismic shaking, which is in turn influenced by soil properties. Instability of soil occurs often in mountainous slopes with loose sediments (BC Geological Survey, 1991). Most conventional research neglect the effect of amplification in analysing earthquake damage risks, but as explained above many studies found sufficient evidence geological site-properties change the amplitude and frequency of seismic waves. (Peng, Wang, Chen & Lee, 2009). In this research both amplification and landslide hazards will be analysed. The study area will be divided in three geological settings and discussed separately: the coastal area (beach ridges, estuaries and wetlands), the middle part (higher located alluvial plains and river valleys) and the mountain areas. 3.1.2 Analyzing geological aspects of different topological sites Mountain areas in Aceh may be highly affected by earthquakes as they are located along the Great Sumatra Fault. Whether a slope is unstable and causes a landslide depends on different factors, among material strength, slope configuration and ground motion (Ambraseys & Srbulov, 1995). In mountain ridges ‘the crocodile effect’ is also of significance, as it is suggested that seismic motion increases from wider to more narrow part of the ridges (Hack et al., 2007). Moreover, the tropical climate in Aceh has large influence on soil properties. The humid environment results in high weathering processes in the parent material of the soil and determines also the vegetation cover, which in turn influences soil development. Soils are mostly shallow on a hillslope, as runoff causes erosion and prevents soil development. Vegetation on hillslopes is therefore low and less water can be retained, resulting in more instability of slopes during an earthquake (Oh, Lee & Soedradjat, 2010). Earthquake-induced landslides are mostly triggered from slopes between 20 and 44 degrees (Lee, 2014). High alluvial plains, river valleys and flat footslopes have less relief, therefore accumulation of soil occurs and results in relative thick soils. The site response effect of soil amplification on thick soft alluvium and peat soils is very high (Setiawan & Kusuma, 2013) (Appendix 2), because alluvium contains unconsolidated deposits of gravel, sand, clay or other debris (USGS, 2004). Research suggests that in contrast to hard rock sites, earthquakes causes major destruction on thick alluvium soils (Bol, 2012). In the middle part foot slopes of less than 10 degree are taken into account. Because of the flat topography of these geological units, landslide risk is very low.

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The coastal area of Aceh consists of several sandbars, determined as silty sands (Johar, 2013). This can be reflected on the research of Vusetic (1992), because the soil at the coast has a high sand particle percentage, for which Pl = 0. As a consequence the deltaic area has very low amplification. Furthermore, it can be suggested that coastal areas with high dunes and beach ridges have lower damage risks, as these may form a barrier for tsunamis. 3.1.3 Tsunami generation, propagation and inundation To determine the vulnerability of an area to tsunamis, the inundation heights of tsunamis should be composed. To understand this, it should be known that a tsunamis consists of 3 phases: the generation phase, the propagation phase and the coastal phase. A tsunami is more likely to form if the hypocentre of an earthquake is located shallow and rates a high magnitude on Richter’s scale. The exact values differ from a depth of 30 to 60 km below the surface floor and a magnitude of 6 to 7 on Richter’s scale (Bernard, 2006; Jaimes Et al., 2016). When stress releases at an earthquake the plates quickly move to their original form (NWS, zd). This movement can be separated into two components. A vertical displacement component and a horizontal displacement component. The vertical ocean floor displacement is generally assumed to be the main tsunami forming motion (Mardi, Malek, Liew & Lee, 2015; Taymaz, Yolsal-Çevikbilen & Ulutas, 2016; Lay, Kanamori, Yamazaki, Cheung, Kwong & Koper, 2013; Bernard et al., 2006). The kinetic energy of the vertical- and horizontal movement of the ocean floor gets directly transferred to the water, which immediately sets the water in motion, creating a wave (Bernard, 2006). Studies have indicated that there is a linear relationship between the maximum tsunami wave amplitude and the magnitude of the causing earthquake (Suppasri et al., 2013) From the moment that the kinetic energy is transferred from the ocean floor to the water, the tsunami wave starts to move in all directions. The speed at which a tsunami wave travels, depends on the depth of the ocean. This is also an important reason why a tsunami wave does not disperse in a perfect circle (Bernard, 2006)(Okal & Synolakis, 2008). Ward (2010) constructed a table which shows the relationship between water depth and tsunami velocity shown in table 1. Ward (2010) calculated these speeds using the false assumption that the ocean floor is flat. However, these numbers give a good estimation of the tsunami speed. Depth ocean

floor [m] Tsunami velocity [m/s] Tsunami velocity [km/h]

100 30 108 500 70 252 1000 100 360 2000 140 504 4000 200 720 6000 240 864 Table 1 (Ward, 2010) Table 1: Ocean floor depth hand tsunami velocity (Ward, 2010) Due to the principle of conservation of energy, a tsunami wave amplitude decreases in distance (Okal, 2008). A constant amount of energy should lift up the water over a bigger periphery (Moore,

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Bangs, Taira, Kuramoto, Pangborn & Tobin, 2007). The Boussinesq model and the MOST code, are two reliable examples of models used to calculate the tsunami amplitude over distance from the origin of the wave (Mitsotakis, 2009). As explained by the article of Ward (2010), the velocity of the tsunami decreases if the waterbody gets shallower near the coast. Furthermore, because of the trapping of water in a smaller volume, combined with the principle of conservation of energy, the water height increases a lot. These models give a good estimation of the tsunami height over distance in open water. However, it dismisses the important aspects of coastal processes on a local scale. Water run-up heights in coastal processes are crucial for determining inundated areas (NWS, zd). Water run-up can be predicted in multiple ways. An inaccurate way, is to use a wave run-up factor between 2 and 5, which is done often for simplification (Titov, Rabinovich, Mofjeld, Thomson & González, 2005). Though, if a more accurate prediction is desired, models are used. These vary for the input of many different variables like topography, bathymetry, vegetation coverage, development, building strength, etcetera. If more different variables are incorporated in the models they tend to be more precise (Keon, Pancake & Yeh, 2015); (Muhari, Imamura, Koshimura & Post 2011). However, input data like this, is in many cases not available or inaccurate, especially in third world countries. In those cases the use of the Constant Roughness Model is recommended. This model predicts a worst case scenario based solely on elevation data, in which buildings do not reduce the destructive force of the tsunami wave (Muhari et al., 2011).

3.2 Underlying theories in social sciences: earthquake vulnerable areas in Aceh

In this part of the theoretical framework first political ecology will be discussed as a significant theory in analyzing the most vulnerable areas in Aceh. This will be followed up by explaining a framework which is able to encapsulate the inequalities between communities. Furthermore economic concepts, such as Performance Management, tragedy of the commons and Corporate Social Responsibility are important to take into account. 3.2.1 The human geography of disaster In order to map social the social aspects of vulnerability to these natural disasters, this paper will draw from a political ecology theory, assessing the issue of disproportionate vulnerability of poor communities to natural disasters. After this, resilience theory will be addressed in order to stipulate a framework regarding the capacity of communities to cope with the effects of natural disasters.

The concept of political ecology has been used in a variety of ways and contexts, among which developmental political ecology (Bryant, 1998) and feminist political ecology (Rocheleau et al, 2013). However, even though there is no ready made, universal and unambiguous definition of political ecology, the general consensus in the literature seems to be that the common denominator between the different apprehensions is a realization that natural scientists often tend to ignore the politics of human societies (Peterson, 2000). According to this point of view, natural disasters occur in political space. Of course, tsunami’s and earthquakes are in no way inherent political events, but the level of government preparedness and response can determine in a large part the ways and intensity in which these events can affect certain populations (Cohen et al., 2008).

Taking this into account we can now work towards a framework that is able to encapsulate these inequalities and provides us with a basis for assessing spatial distribution. The concept of resilience was introduced by Holling (1973) and described as determining “the persistence of relationships within a system and is a measure of the ability of these systems to absorb changes of

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state variables, driving variables, and parameters, and still persist.” A growing body of research has incorporated a resilience perspective within the social realm. The concept of social resilience was coined by Adger (2000) and defined as “the ability of communities to withstand external shocks to their social infrastructure.”

Walker et al. (2004) state that there are four crucial aspects of resilience; latitude, resistance, precariousness and panarchy. These aspects will determine the frame of our further research, by providing dimensions that will be operationalized in order to create a spatial distribution of resilience using GIS-software. First, a description will be given of each of these crucial aspects after which a first step towards operationalization will be made.

Latitude is the maximum amount a system can be changed before losing its ability to recover. Resistance is the ease or difficulty of changing the system; how resistant it is to being changed. Precariousness is a measure for how close the current state of the system is to a limit or threshold; the tipping point and Panarchy is the extent to which dynamics or states from scales above and below the described system can trigger local surprises and regime shifts, i.e. climate change, globalization, market shifts, oppressive politics. 3.2.2 Economic value of regions for companies and communities To analyse the economic value of regions in Aceh, we have to first analyse which criteria of economic value should be measured and why. There will also be discussed how these values could give information of the potential risk and , if possible, how these risks subsequently could be affected. The three concepts which will be discussed are Performance Management, Tragedy of the Commons, and Corporate Social Responsibility. After the concepts, a map will be shown which regions are most economic valuable and what companies would do in such situations. An essential concept for companies is aligning goals from companies with goals from the employees. This concept is derived from the theory Performance Management (PM). PM has several definitions and the progressive definition is “A process for establishing a shared understanding about what is to be achieved, and how it is to be achieved, and an approach to managing people that increases the profitability of achieving success” (Weiss & Hartle, 1997). Therefore, it focuses on optimization of human resources, such as communication and processes. Inside PM, long-term survivability of the company plays a key role. The goals of the employees have a positive effect on the community, such as better training, education, and more appraisals. This affects that people are mentally healthier by not only being appraised by their loans or verbally, but also by given paid education and trainings, if they are performing well enough. By new ways of their employer’s appraisal, the employees are happier. The employees are stimulated to perform better and more educated employees has not only affect on the production, however, also on the awareness of environmental hazards. The community are able to think more critical and also even more able to think of new mitigation strategies and executing them not only by companies, but now also by themselves. Therefore, the fit of goals between the employers and employees affects the long-term survivability for the companies and the community (Hitt & Sirmon, 2003). To conclude, PM with aligning goals has a positive effect on the community and the companies on the long-term. The concept tragedy of the commons is a problem where collective loss is neglected and personal gain by every individual is trying to be achieved (Hardin, 1968). This concept is related to the advice from business perspective to stakeholders and is not displayed in the maps. Hardin’s

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article discussed major global problems, as overpopulation, resource depletion, and air and water pollution, and concluded that freedom in the commons brings ruin to all. The article has been part of ecology, political, environmental, political, economics, and policy studies (McEvoy, 1988). The way of treating resources can be analysed by looking at state or private ownership. Has the government a very active or passive role in society? State ownership could reduce extremes and control consumption and production in Aceh. Also, state ownership could use the profit of their ownership to invest in reducing risk of external factors. This could be linked to the long-term survivability, only this way from the state’s perspective. The profit of the resources could be invested by the state in stronger building support for earthquakes and in education to increase awareness of possible hazards. Education also stimulates new mitigation strategies. Only problem of state ownership is that it often does not work in developing countries. The government will not represent the community and could exclude the people too much from the resources. Private property could work, however, it could not fix completely the exclusion, which leads to overexploiting resources. (Feeny, Berkes, McCay, & Acheson, 1990) The third, and maybe the most important concept, is Corporate Social Responsibility. CSR is broadly interpreted. The Commission of European Communities has defined the most frequently used definition in academic literature of CSR in 2001: “A concept whereby companies integrate social and environmental concerns in their business operations and in their interaction with their stakeholders on a voluntary basis” (Dahlsrud, 2006). CSR can be seen as long-term investments to secure their survivability by investing in the well-being the employee, the community, and the natural environment. Determinants of the size of demand of CSR are price of good with CSR attributes, preferences and taste, advertising, income, demographics, and price of substitutes. However, the suppliers of CSR are more important to discuss for the paper because they can start a trend in society and in the market. The suppliers of CSR are capital, materials and services, and labour (McWilliams & Siegel, 2001). Since demand of CSR is influenced by the demographics, price, and income, the criteria Gross Regional Domestic Product for a map is chosen to measure the demand of CSR in Aceh. Also, GRDP is directly linked to economic value of a region for Aceh. Secondly, the amount of students in a region as criteria is a factor of demand of CSR. The richer and more intellectual population do not only want a good product, but also a product with status (McWilliams & Siegel, 2001). The amount of students shows where the economic value could be high or has the potential to grow more. Thirdly, the criteria amount of labour in medium and large industries could show where for Performance Management could be improved. Since industry is a secondary sector and is, in most cases, less capital valuable than the tertiary sector, it shows where most-likely improvement is possible. This is where PM and CSR has room for improvement in Aceh.

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4. Methods

Maps are easy ways to visualize data of many different kinds. Furthermore, benefit of mapping is that data of different kinds can easily be combined if it is scaled on the same ordinal scale. Consequently, mapping is the most suitable way to shown the spatial risk variation in this research. This holds for the individual maps as well as for the combined maps. All maps are created using the mapping software ArcGis. Initially maps with risk and vulnerability information of Aceh on a single topic are made in order to combine them later on. The initial maps consider four topics: geological vulnerability, tsunami vulnerability, resilience and economic value. The following paragraphs describe the creation of each individual map. However, it is important that all maps are set to the same spatial reference and that they are all converted to raster datasets, otherwise the maps can not be combined.

4.1 Geological vulnerability map

To point out the most geological vulnerable areas in Aceh it first is necessary to design two separated maps, involving amplification and landslides. Firstly, the basic geological map of Aceh is developed. Data from a Web Map Service (WMS) containing geological units for South-east Asia should be added to ArcMap, gathered via the OneGeology Portal (figure 5). Also the basemap of Aceh via ArcGis Online is added. Eventually the geological units are clipped to the basemap, maintaining only the geology units of the province Aceh. Secondly, a Digital Elevation Model (DEM) is added to the basic geological map of Aceh, collected from Nasa’s Shuttle Radar Topography Mission. Following, the ‘slope’ function develops a slope map, representing the rate of change for each DEM cell in degrees. In addition, a hill shade map is created again using the DEM. In each map the hillshade layer is located at the background, behind a transparent layer to make the map more clear with respect to elevations. Thirdly, the amplification map is created (figure 6). Examined in the theoretical framework thick soil, such as alluvium, peat, and other flat areas, determines high amplification and as a result high damage. The collected data mentioned above contained also the slope degree of the foothills. These foothills can be divided in limestone, volcanic, acid igneous and other foothills. With the use of the slope map the degree of the foothills could be confirmed. Another feature class is added to divide these polygons into three categories: low amplification risk (1), moderate amplification risk (2) and high amplification risk (3). Polygons of the geological map referring to alluvial plains, river valleys, wetlands/peat swamps, foothills (5-10 degree), foothills (2-5 degree) and foothills (<2 degree) are indicated to be high amplification risk as there is high soil development is in these areas. All other foothills are indicated to have moderately amplification risk. Finally, coastal beach ridges and swales, coastal estuarine flats (large percentage of sand), limestone ridges, volcanic ridges, acid igneous ridges, alpine peaks, limestone ridges (>20 degree) and lakes are considered to have low amplification risk. Fourthly, landslide hazards are mapped (figure 7), using the same geological map and its data.Again a new feature class was created to indicate polygons in three categories: low landslide risk (1), moderate landslide risk (2) and high landslide risk (3). Foothills (>20 degree) and alpine

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peaks are indicated as high landslide risk, according to the theoretical framework. Foothills (10-20 degree) are considered to have moderate landslide risk. Lastly coastal plains, alluvial plains, river valleys, wetlands, peat swamps and all sorts of foothills (5-10 degree, 2-5 degree and <2 degree) are indicated as low landslide risk, because landslides risk is high for steep slopes. Finally, the risk values of the amplification and landslide map were combined into one layer using the ‘union’ function of ArcGIS. Eventually the geological vulnerability map visualizes the actual geological risk in Aceh (figure 8).

4.2 Tsunami vulnerability map

The tsunami hazard map is constructed with the edit tool on ArcGIS, through the idea of the Constant Roughness Model. As explained in the theoretical framework, this is the most accurate, worst case scenario map. This method should be used if the only complete and reliable dataset of the mapped area is elevation. Included in the tsunami vulnerability map are the elevation of Aceh, the distance through the water to the trench and a basemap with the periphery of Aceh. Firstly, data used for digital elevation modelling (DEM) is downloaded from Nasa’s Shuttle Radar Topography Mission. This data shows elevation every 30 meter, it is the most accurate elevation data of Aceh. The right coordinates should be placed on a basemap of indonesia, which can be collected from the ArcGIS online database. This data should be clipped so that solely the province of Aceh remains with the elevation data. Secondly, with the use of the editing tool, polygons are created that divide Aceh in 3 classes: not vulnerable, moderately vulnerable and very vulnerable. Because the subduction trench is located practically parallel to the the coastline, the whole southwest coastline is divided in the same way, while to the northeast the vulnerability decreases with distance from the trench. For the coastal areas facing the trench an elevation < 8m is considered very vulnerable, from 8 to 30 m is considered moderately vulnerable and >30 is considered not vulnerable. These values are chosen after analyzing data records collected from previous tsunamis (Titov, Rabinovich, Mofjeld, Thomson & González, 2005; Nohara 2011). In the north these border values decrease to 5 m and 25 m at the point furthest from the trench. Finally, the polygons surrounded by polygons of a higher value should be filtered out, so that a low altitude is not vulnerable if it is surrounded by hills. In this way, the very vulnerable areas are always directly next to the waterbody. Furthermore, not vulnerable areas will never totally surround another polygon. 4.3 Resilience map The spatial distribution of resilience is assessed using proxies for each of the aforementioned aspects of the concept. Drawing on data from Badan Pusat Statistik (BDS), the Indonesian Central Bureau of Statistics, spatial distributions of latitude, resistance and precariousness are calculated and combined in order to create a comprehensive oversight of the ability of different regions of Aceh to cope with earthquakes and tsunamis. The first aspect that should be computed is latitude. It is in no way possible to calculate the actual maximum amount a system can be changed before losing its ability to recover. However,

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certain regions might have a comparative advantage over others when it comes to the ability to recover. Allen et al. (2005) argue that functional redundancy improves the ability of a system to cope with stress, because of the fact that certain functions can still be performed when part of the system sustains damage. This has been operationalized by using data concerning the percentage of households per regency that have access to a particular water source (BPS, 2013a). The indicator is constructed by taking the sum of the square root of the percentages of access per water source. This is done because, as demonstrated in table 2, there are situations conceivable where 100% access to one water source and 0% access to 9 others would give the same value as 10% access to 10 different water sources, even though the latter situation represents more functional redundancy. In order to compensate for this bias the square root of the percentage of access per water source was taken and these values were added. The result of this operationalization is depicted in figure 10. Table 2: Demonstration of bias in constructing an indicator for latitude The second aspect is resistance. The difficulty of changing the system within the context of natural hazards like earthquakes and tsunamis could be measured using a focus on the built environment. Building material and construction methods, access to water and existing infrastructure could all provide insights in the amount of effort and money that went into constructing and maintaining buildings and infrastructure (Haigh et al., 2010). The indicator for resistance is created by using data concerning the amount of villages that have access to the electrical grid (BPS, 2013b) and calculating the percentage of villages connected to this grid per regency. The result of this operationalization is depicted in figure 11.

Thirdly, the aspect of precariousness was computed. Birkmann et al. (2008) demonstrate that there is a negative correlation between socioeconomic position and knowledge of tsunami and coastal hazards, membership of local organizations and receipt of financial support after natural disasters. Since GDP per capita can give a biased view because a relatively small portion of really wealthy citizens may positively skew this number even though it wouldn’t tell us anything about precariousness, the relative amount of Indonesians living below the poverty line was used as an indicator (BPS, 2013c). The result of this operationalization is depicted in figure 12. The different maps are merged by taking the aggregate of the three indicators, ranking the different regencies accordingly and dividing them in three classes. A correction for population was made by dividing this number through the total amount of inhabitants per regency and ranking and reclassing this result, ending in a map that shows the amount of resilience per regency as being low, medium or high, as shown in figure 13.

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4.4 Economic value map To create the economic value maps, not only ArcGIS is used, but also Excel, Google Maps, Wikipedia and Badan Pusat Statistik (BDS), the Indonesian Central Bureau of Statistics. The maps show criteria related to the economic value of regions which are GRDP, students, and amount of labour in medium and large industries. The data of the GRDP was founded in the database of the BDS and needed no calculations. The borders of the empty map in ArcGis differed from the provincial borders which were used in the BDS data. Therefore, Google Maps and Wikipedia were used to know which province of the empty ArcGis map belonged to which region in the database, which wa also needed for the next two maps. All the data was configured in the map by creating a new vertical table in the ‘Attribute Table’ in ArcGis and filling in the data. Figure 14 displays the result. Secondly. the data of the amount of students per region in Aceh could be found in the database in absolute numbers. To gave a clearer view of the amount of students per region, since the size of population of regions differed, the number of students per region were divided by population per region. By using excel and the database to find the population per region, calculations were made and configured in the ArcGis map. Figure 15 displays the result. Thirdly, the map of the amount of labour in medium and large industries in Aceh was created, which consisted of unknown numbers per region. The database did not have sufficient data per region for each economic sector, however, it did have one for the industry. Still, it lacked numbers, which were not clear if it meant those regions had zero industry or that the number of labour in those regions were unknown. Therefore, the limited database resulted in a map not fully covering the study area. However, it still showed valuable information where the industry in Aceh was most present. Figure 16 shows the result. At last, the merging of these 3 maps was computed by the function ‘union’ in ArcGis. Union leads to merging attribute tables of different maps or layers. By creating a new vertical table and using the field calculator to sum up these 3 tables from the 3 maps, it created new data for the economic value of Aceh per region. The sum was divided by 3 to become useful when merging with the Resilience map of the Human Geography, and to end up with values between 1 and 3. The result is shown in figure 17. 4.5 Combining maps The maps of the four disciplines were combined with the ‘union’ tool. First, the maps Earth sciences were combined in figure 18 and secondly the maps of Business Studies and Human Geography in figure 19. Chosen attributes for every grid cell of a raster dataset were summed up with the same grid cell of another dataset. In this way, multiple aspects are shown in a new layer. Maps have to have the same ordinal scale of risk (1,2 or 3), to make sure that different aspects have the same impact.

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5. Results

Figure 20 depicts the quake hazard as a result of the aggregate of both the earth- and the social sciences. Whereas landslide risk is highest in mountainous areas, the highest amplification risk is at the lowlands. Moderate amplification risk occurs on flat foothills, similar to the landslide risk. The highest actual geological vulnerability is thus on foothills. Thereby, the middle part is also hit by massive debris of rocks and soils due to earthquake triggered landslides in higher elevated parts (Karnawati, 2009). The constructed tsunami hazard map (figure 9) shows mostly expected results. Sumatra is an island formed by a subduction zone and therefore contains a lot of relief. Because of this relief, maximum inundation distances vary from 0 km at rocky coasts to 30 km from the coast in river deltas. Remarkable is that the tsunami vulnerability in the north in most regions is higher, even though the distance to the trench is further. The map of economic value (figure 17) shows that the north-western part is the economic core of Aceh. However, also in northeast, southern, and western part are noticeably crucial parts for the economy where mitigation is required to protect all of the human and economic capital for natural hazards, which are the students, GRDP, and industries. When these 3 criteria are high in a region, it shows that this region plays a significant role in the economy of the province Aceh. On the one hand, the western and southern parts have high amount of labour in medium and large industries, but on the other hand, the GRDP is very high in north-eastern and north-western part of Aceh. All of these economically highly valuable areas are close to the sea. The resilience map (figure 13) indicates that there clearly is an uneven distribution in resilience in Aceh. Namely the Northeast and Northwest regions of Aceh are vulnerable for natural disasters. It is unfortunate that these regions contain coastal areas that are prone to tsunami incidents, as becomes apparent in the combined maps. The combined maps of natural sciences and social sciences (figure 18 & 19) show significant overlap in high-risk regions. Both maps show high-risk on the east and west coast of Aceh. The only difference is that social sciences states that there a lot more high-risk parts on the whole coastline of Aceh, so also on the northern and southern part. The map of natural sciences looks more optimistic, because there are more low-risk regions found on the map. Figure 20 can be expected when observing the combined maps of natural and social sciences, since both are very similar. Especially the western and eastern part of Aceh have a high risk to be strongly affected by natural hazard and are advised to implement mitigation strategies on these vulnerable regions.

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Figure 5: Geological map Aceh, Indonesia

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6. Conclusion

It was examined that Aceh is very vulnerable to earthquake because of the risk for landslides, amplification and tsunamis. With the help of the geological vulnerability map and the tsunami risk map the most vulnerable areas in Aceh can be analysed with respect to natural sciences. Weighing up the different factors is of significance, in order to calculate the actual risk of natural science and to compare the results with respect to the social aspects. In this research it is suggested that the most significant factor of natural science is tsunami risk, as many people may be killed as result of such an enormous secondary disaster. Followed up by the risk for landslides, another secondary disaster, but differs from tsunami risk in scale of impact. Last but not least, the impact of amplification is taken into account as it has not as much impact as tsunami or landslide risk, but can surely not be neglected. Drawing from a political ecology framework, resilience can be constructed by using proxies for three different aspects of the concept: latitude, resistance and precariousness. Taking these aspects into account, a social map of resilience corrected for population can be formed. From a business perspective, the economic value, the number of students and the amount of labour in regions are included to form a holistic view of Aceh. The highest economic value region of Aceh is located in northeast, however, also in northern, southern, and western regions have priorities to be protected from natural hazards. These high economic value regions have potential to enforce CSR and Performance Management, which results in minimizing the risks in the future of these crucial economic regions for the province Aceh. The earth science map displays a clear separation of vulnerable regions in coastline areas and inland areas. Predominantly coastal areas contain a risk level higher than moderate. This is mainly due to the tsunami and amplification risks in these areas. The social studies also indicate a greater risk level in coastal areas. However, this map also shows a bigger threat in the west compared to the south. The resilience, especially the precariousness, of this area is responsible for this East-West division. The final Quake Risk Map, which combines all the disciplines, shows the highest hazard rating at the upper part of the Southwest coast and at the middle and the most eastern part of the Northeast coast. These areas are most at risk and would be advised to apply mitigation strategies. While this study is focussed of Aceh, it could also be of use to apply this method to other provinces of Sumatra or even of other countries. The method used in this research is relatively easy to reproduce and therefore, valuable for many areas near fault lines worldwide.

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7. Discussion & Recommendations

By dividing an earthquake prone area into zones with respect to geological aspects there are many more complex factors that can also be taken into account to create an even more realistic geological hazard map. For example, the effect of liquefaction may also be an important factor to take into account. Liquefaction is the process whereby loose sand and silt becomes saturated and will behave like a liquid during an earthquake (USGS, 2014). The geological vulnerability map could also be more detailed if the effect of slope face and vegetation type could be examined, because these factors have much influence in the development of soils and thus the risk for landslides and amplification. By improving the analysis a seismicity map can also be created, in which past records of earthquakes are used in combination with their magnitude. Recurrence intervals of these data can be analysed. Consequently the risks in the complex fault areas may be increased. However, many data and research is necessary for creating such an accurate map. The tsunami hazard map could also be improved in multiple ways. Detailed data about urbanized areas, building strength for example, could be a good improvement of inundation predictions. Models in natural science are a simplification of the true situation. Therefore, improvement is always possible. The limited business data of the database resulted in a different focus in economics which was not intended. The map of the industry could be better acknowledged if the database made clear if information of some regions were unknown or there is no industry present in those regions. It could be more interesting to focus on import, export, and amount of labour in each sector per region in a possible next research. It is important to note that the proxies used in the generation of the resilience map in no way give a complete image of the different aspects of resilience. Within the scope of this research and with the data available within the time frame of this research the techniques used can give a reasonable image, but to fully apply the theoretical framework an aggregate of proxies would have to be constructed for each of the aspects. Furthermore, further research could focus on, or collect data with a higher resolution than the level of regencies. The social resilience data (figure 13) was combined with the data concerning economic value (figure 17). This construction leaves intact the differentiated nature of both sets of data, and leaves more space for interpretation by readers, but there is also a downside to this. In giving the data sets equal weight, the result resides on the assumption that economic value is equally important as social resilience and thus inherently puts a price to human lives. This issue could be dealt with by encapsulating economic value in the social resilience framework, by taking the different components that were used to calculate economic value and use these as proxies for the different aspects of the resilience framework. We have chosen not to do this in order to keep our analysis as transparent as possible. This interdisciplinary project can be used to develop mitigation strategies. Further research should be done on the implementation of different kinds of mitigating strategies to prevent devastating effects of earthquakes and tsunamis.

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8. Literature

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