Areas at risk of flooding along Pine Creek
Determining structures that would be affected by any of the 5 yearly floods (10,50,100,200,500) located along Pine Creek.
Figure 1: Map representing where Pine Creek is located within the state of Pennsylvania. Also shown are the counties that Pine Creek flows through.
Introduction
Pine Creek is located in northern Pennsylvania and flows through Lycoming, Potter, Tioga, and a small piece of Clinton county. The total area that Pine Creek covers is 87.2 miles and is a tributary to the west branch of the Susquehanna River. Within Tioga County, 23.25 miles of Pine Creek have been designated to the Pennsylvania scenic rivers. The creek got its name for the many pine trees that lined (and currently still line) the banks of the creek. Pine Creek is the largest known "Creek" in the United States. Today, it is used for many different recreational activities and runs parallel to the 62-mile Pine Creek rail trail. Pine Creek is home to the Pennsylvania Grand Canyon. This area is especially important to my family and I because we have a cabin in Tioga County and love visiting the creek on a regular basis.
Purpose
The purpose of my GIS 3 Capstone Project is to collect and analyze the appropriate data to answer the following question: What buildings are at risk of damage within the 10, 50, 100, 200, and 500-year floods? Based on the areas at risk, what is the economic loss of the properties based on the yearly floods?
Figure 2: Representing Pine Creek flooded in Tioga County after a major rain event in 2016
Objectives
- Determine the exact location of Pine Creek and where all it flows
- Determine the total number of buildings that have the possibility of being impacted
- Find what areas along the creek would be impacted by the economic loss
- Determine the total economic loss along Pine Creek for each of the yearly floods based on a 100- foot buffer of the creek
- Find which county would be impacted the most for each of the yearly flood events
Methods
To start, I downloaded all of the data from the Pennsylvania Spatial Data Access (PASDA) that I would need to complete and answer my Capstone question. As shown in Table 1, I chose to project all of the data in NAD 1983 (2011) StatePlane Pennsylvania North FIPS 3701 (meters). This allowed for the most detail based on the area of study.
Table 1: Represents the entire data set used during my analysis. This includes the name used within the project, the projection of the data originated from ArcPro, and the coordinate system I chose to project the data in
Figure 3: Once I finished downloading all of the data, I began the geoprocessing steps to answer my capstone question. The first step I took was based on the Pennsylvania Counties layer. Using a definition query of "Name = Lycoming or Name= Tioga or Name=Potter or Name= Clinton" I was able to clearly represent where Pine Creek flows.
Next, using the Select by Attribute tool based on the National Flood Hazard Layer (NFHL), I selected "WTR_NM= Pine Creek". This gave me an output of only attributes of Pine Creek. I repeated these same steps for the other 3 counties to get the total area where Pine Creek flows. I exported each of the 4 selections into separate layers.
The final step is merging all of the NFHL layers together to form one layer representing the Pine Creek flow area. This helped make the analysis easier to work through.
Figure 4: After merging each of the separate county layers into 1, I ran a 100-foot buffer around the creek. This was in preparation for the analysis of the economic loss areas and damaged buildings based on each of the yearly floods.
Based on the 100-foot buffer, I did a Select by Location in order to find each of the economic loss areas that are within 100 feet of the creek. This was done for each of the 5 yearly floods.
The final step shown includes the damaged building layer for each of the 5 floods. Based on the 100-foot buffer, I ran another Select by Location in order to find all of the areas where there is a risk of damaged homes. This also helped to determine hot spots that were more at risk of damage. Once each Select by location was complete, I was able to begin going more in-depth with the analysis. The same steps were taken to determine economic loss areas.
Figure 5: Once I had all of the economic loss areas and damaged buildings within the 100-foot buffer, I started to begin thinking of ways I could compare each of the economic loss areas with damaged buildings during a flood. Initially, I used the intersect tool to find where there are similarities in economic loss and damaged buildings. To do this, I ran intersects based on the economic loss area and damaged buildings layer. These same steps were taken for the remaining 3 yearly floods.
Figure 6: Next I determined how many total buildings would be damaged due to each of the yearly floods. This was done using the Dissolve tool. Each of the inputs for the dissolve field either is total build or total loss depending on which layer is being worked. The dissolve field was "total build", which was based on the total buildings in the attribute table. Finally, the statistics field was total build and the type was "SUM". This helped to determine the total number of buildings at risk of being damaged during any of the yearly floods.
Answering my final objective includes determining the total amount of economic loss and where economic losses occur. The input field in the Dissolve tool will be each yearly flood I was attempting to find the total loss for. The dissolve field consisted of total loss, and the statistics field also included total loss. The type of "SUM" was used to determine the TOTAL amount of economic loss in thousands of dollars for each of the yearly floods.
Figure 7: In order to make the layers easier to display on the map, I decided to change the layers to point features. This represented the economic loss and damaged buildings along Pine Creek in Northern PA during each of the yearly floods.
Using the Feature to Point Geoprocessing tool, helped to give a better representation of where everything is occurring along the creek. I ran this tool for each of the yearly floods for both economic loss and damaged buildings. This also helped to compare all of the yearly floods with one another and see where economic loss is occurring for multiple events.
Results
I successfully analyzed all of the areas around Pine Creek based on a 100-foot buffer that is at risk of economic loss and damaged buildings during any of the 5 yearly floods. I determined that all of the structures that are at risk of damage are residential properties (rental, seasonal, permanent residents). After completing the first part of my analysis, I successfully found there are a total of 65 locations that are both affected by economic loss and at least 1 damaged building on the property.
Also during my analysis, I found the county that would be at risk for the most economic loss and damaged buildings would be Lycoming county. The majority of the damage in Lycoming county tended to be towards the southern end of the county where Pine Creek comes to an end and flows into the West branch of the Susquehanna River. This is also true because the population along the creek tends to be higher in Lycoming than in the other three counties. It was determined from my analysis that there are only 65 locations along the creek that are affected by all of the 5 yearly floods and have both damaged buildings and economic losses.
Figure 8: Representation of where there is both Economic Loss and Damaged Buildings along Pine Creek over any of the 5 yearly floods occurs.
The next objective that I analyzed was determining what the economic cost would be for each of the 5 yearly floods. After completing this analysis I found the total loss from all 5 of the yearly floods on Pine Creek would total $192,828,000.00. I also found the minimum and maximum costs of each economic loss area during the floods. For each, the minimum was set at $1,000 and the maximum between each of them was during the 500-year flood with a total amount of $3,733,000.00
Figure 9: Representation of all the areas that are at risk of economic loss and the total amount of economic loss per point based off of thousands of dollars.
Table 2: Representing the sum of total loss for each of the 5 yearly floods and the sum of all 5 yearly floods combined.
Table 3: Representing the minimum economic loss on a property along with the maximum economic loss on properties from the yearly floods.
The final objective I had to complete in order to answer my Capstone question was determining the total number of buildings that would be at risk for damage. My findings concluded a total of 4,063 buildings that would be at risk and are located within close vicinity of the creek. The 500-year flood had the most damaged buildings with a total of 1,330.
Table 4: Representing the total amount of buildings that are at risk of being damaged along Pine Creek by each of the 5 major year floods.
Figure 10: Representing all of the Damaged buildings that would occur during any of the 5 yearly floods that are located along Pine Creek
Figure 11: This image is showing the creek flooded after an extreme rain event along Pine Creek.
Summary
Pine Creek's banks are prone to flooding even when the yearly floods are not occurring. This is because of the very low-lying banks and houses being close to the creek. Overall, this project has helped to recognize all of the areas at risk of economic loss and determine the number of buildings that are at risk during each of the 5 yearly floods. From my analysis, I was able to conclude the county that would have the most damage from each of the yearly floods would be Lycoming County. All of the buildings that were located within 100 feet of the creek are residential properties.
I believe I was successful in completing my Capstone because I was able to answer my question of "What areas are at risk of damage within the 10, 50, 100, 200, and 500-year floodplains? Based on the areas at risk, what is the economic loss of the properties located within the yearly flood for each?" I was able to answer my question by using the appropriate coordinate system, geoprocessing tools, and knowledge from GIS 1,2, and 3 to make my analysis successful. I really enjoyed looking more in-depth at the flooding involved at Pine Creek as my family has a cabin on 18.5 acres and we enjoy going to Pine Creek for many different leisure activities. It was interesting to map the areas that would actually be at risk of flooding at Pine Creek. While working through my Capstone the major issue I ran into included, trying to find the easiest way to map all of the economic losses and damaged buildings without making the map too crowded. Once I decided to put damaged buildings and Economic loss areas on separate maps, it helped to show in a much clearer manner where the risk areas are located along the creek.
