Lab 4-Tsunami Recovery Zones

Introduction

Tsunami recovery planning is becoming increasingly important for local and statewide representatives. As a result of their nature this type of disaster causes catastrophic damages to their impact and surrounding areas. First, an earthquake occurs off the coast, which causes intense flooding of coastal areas (NOAA). Due to the sudden nature of tsunamis it is important to create evacuation and recovery plants (Red Cross). The factors, which should be examined, are access to roads, potential damage to infrastructure, population and areas suitable for recovery (appropriate sites for tents, emergency service centers and food banks).

The most effective way to locate these areas is a GIS Multi-Criteria Evaluation. MCE are able to take several factors into account while creating a suitability analysis to determine the best options for recovery areas (Yahaya, 2008). MCE methods have recently been used when analyzing impacts of natural disasters; it allows the decision maker to combine a variety of factors, not just geologic factors, but also social and economic factors (Walker et. al., 2014).

Methods

The necessary layers were compiled to create a MCE for locating suitable recovery zones after a tsunami hits the coast. These data layers included county boundaries, DOGAMI tsunami evacuation zones, US census population blocks, city limits, highways and elevation. There were four criteria that needed to be met to consider a site “suitable”. The areas needed to be outside the inundation zone but inside the county, low slope (for emergency tent sites and medical care units set up), near highways that were not impacted by the tsunami and near areas of high population density. This analysis was conducted using Coos County as a case study and therefore all data was clipped to only show the features within Coos County.

I conducted my analysis step by step, beginning with creating a raster layer of areas in Coos County, outside the inundation zone. Using Euclidean distance I determined areas outside 5 miles of the tsunami evacuation zone. I reclassed this data assigning a value of 1 (or good) to areas outside of 5 miles and a 0 (or bad) to areas within 5 miles of the inundation zone (Red Cross stated that anything within 2 miles would be severely impacted). Then, to find areas of low slope I used elevation of Coos County to come up with a slope raster. I reclassified this layer so that anything above a 25% slope was assigned a value of 0 and anything under 25% was assigned a 1. To find the highways not impacted by the tsunami I clipped the highway layer to the tsunami layer then used Euclidean distance to come up with a raster of distance outside of tsunami zone. I then reclassified so that anything within 2 miles of the inundation zone was assigned a value of 0, and anything outside 2 miles was assigned a 1. Finally to determine areas of high population I created centroids of the census data then found the kernel density of the population. I reclassified this so that anything with above 10% of the population was valued a 1 and anything below was valued at 0.

Finally to conduct suitability analysis I used the raster calculator weighing each variable according to a perceived importance and created a suitability layer. When assigning weights to the variables I thought about what would be most impacted long term. My weights were assigned according to the table below.

After reading the DOGAMI and Red Cross site regarding Tsunami preparedness I assessed that the two most important immediate factors for tsunami evacuation is ability to access roads and distance from tsunami zones. The latter two factors are more important in establishing recovery zones after the tsunami hits where the former are most important in establishing routes out of areas impacted by the tsunami.

My model is presented below to allow for future analysis of tsunami recovery zones.

Results

My results showed that there are a few suitable locations in Coos County that may be established as tsunami recovery areas. When seen on a map my analysis was to be as expected with the areas closest to the evacuation zone not having many areas suitable for recovery zones but few locations, specifically two towns that exceed all criteria. The two areas I have highlighted as recovery zones are two towns located inside of Coos County along highway OR 542. The first location is the town of Myrtle Point, which is approximately a 30-minute drive from Coos Bay, OR (one of the most populous towns in Coos County). The second is farther away from the evacuation zone, past Myrtle Point another 30 minutes is the small town of Powers, OR. The distance of these locations to the evacuation zone might make it problematic for residents of towns in northern Coos County to travel, which is why I have highlighted a few other potential areas for short-term recovery zones. One zone is a small area just south of Lakeside, OR. There are no highways that run between this area and Lakeside, but there are smaller roads. Additionally there seem to be areas north of Lakeside that might be potential recovery zones, however those areas exceed the scope of this analysis and therefore could not be determined.

According to my findings 52% percent of the area of city limits of the coast will be impacted by the tsunami. Additionally 1,903,211 feet of Oregon highways will be unusable. I calculated these figures by clipping the data of city limits and highways then summarizing the attribute tables to calculate total area impacted. These findings show that the tsunami will have a large impact on Oregon coastal communities and surrounding areas. More research into impacts on infrastructures would be beneficial to assessing the costs associated with damages as well as harm on local economy. Below is an overview map of the statewide impacts of the tsunami.

Conclusion

Although my map is limited in showing recovery areas, I believe I created a sound foundation for future analysis to be conducted using my model. There were few areas identified as suitable for recovery zones and thus my recommendation is to prepare those sites. Additionally i believe the surrounding counties need to undergo the same analysis. Additionally more information needs to be gathered about evacuation routes on a town level basis. Every town should issue a plan to their residents about the closet recovery zones. For cities such as Coos Bay and North Bend this will be simple as they are right up the highway from Myrtle Point, but cities such as Lakeside do not have as clear of a route. Recovery zones were sparse in this county and therefore the county should consider investing in creating more areas, especially for short-term recovery that are closer to heavily impacted cities.

References

Walker, B., Taylor-Noonan, C., Tabbernor, A., McKinnon, T., Bal, H., Bradley, D., Schuurman, N. Clague, J. (2014). A multi-criteria evaluation model of earthquake vulnerability in Victoria, British Columbia. Nat Hazards, 74: 1209–1222.

Yahaya, S. (2008). Multi-criteria analysis for flood vulnerable areas in Hadejia-Jama’are river basin, Nigeria. University Putra Malaysia.

DOGAMI and Red Cross webpages regarding Tsunami recovery.