Goals & Objectives
The goal of this lab was to perform network analysis in order to calculate the impact of frac sand trucking on local roads as a part of our semester-long GIS II project.
Background:
Before beginning this lab, I completed some background reading to inform myself on the effects of fracking truck transportation upon local communities by reading the white paper "Transportation Impacts of Frac Sand Mining in the MAFC Region: Chippewa County Case Study." As the text explains, frac sand mines are often located in remote areas in the country, which means that many of the resources used for the mining process (water, sand, chemicals, drilling equipment) need to be transported to and from the mining site. This transportation has adverse effects upon local roads, which has caused local governments to explore ways to mitigate this damage. Chippewa County, for example, has developed a series of road upgrade maintenance agreements (RUMA) to deal with recovering road damages, funding maintenance, and grading cross improvements (Figure 1).
It is important for counties to be aware of the level of heavy truck traffic so they are able to plan accordingly for repairs. Different types of sand mining operations have different transportation impacts as well, all of which require varying levels of cost and mitigation efforts (Figure 2). Wisconsin legislation states that counties must be reimbursed for damage incurred on county highways, so knowledge and tracking of damages can be financially beneficial to county governments.
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| Figure 1: list outlining aspects of a quality RUMA (white paper) |
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| Figure 2: table detailing impacts of different frac mining operations (white paper) |
Methods
At the beginning of this lab, I wrote a Python script (view here under Python Script #2) to select the mines to be used in my network analysis. This script selected mines that were:
- active
- did not have a rail loading station
- not within 1.5 kilometers of a railroad
After this, I utilized Model Builder in ArcMap to create a model (Figure 3) that achieved these objectives:
- determined to which rail terminal each mine should travel
- determined the most efficient route from each mine to a rail terminal
- determined the length of each route (and cumulative lengths within each WI county)
- estimated hypothetical costs that each route/county would incur
To achieve the first two objectives, I utilized the Make Closest Facility Layer tool to specify a route from each mine to a rail terminal. Then, I projected these routes as well as my counties feature class to a Wisconsin projection. After this, I used the Tabulate Intersection tool to carry out an intersection between the routes and counties boundaries feature classes. Then, I added two new fields to the resulting table, namely a Roads Length and a Costs field. In the first, I used Field Calculator to calculate the total length of roads affected by trucks in each county. In the second newly created field, I used hypothetical values to calculate a cost estimate. In this hypothetical scenario, I assumed that each mine had 50 trucks travel to the rail terminal and back again, with it costing 2.2 cents per truck per mile. It is important to note that these values are purely hypothetical and do not represent actual transportation costs by any means. The final attribute table displayed route lengths and estimated costs by county (Figure 4).
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| Figure 3: network analysis model in ArcMap |
Results & Discussion
The results of my methods can be seen below (Figure 4, Figure 5). The table and map clearly display the scope of frac sand mine trucking and its effects, which are especially prevalent in Chippewa County, Eau Claire County and Barron County. It is interesting to consider these routes after reading the aforementioned white paper; each county government has a say in how these routes and roads are used and maintained by frac sand mine trucks. In Chippewa County, RUMAs are implemented to ensure that roads are kept up and frac sand mine companies are held accountable for the damage they incur on the roads. Such results could prove useful to county governments in negotiating compensation from frac sand mining companies.
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| Figure 4: output table from model displaying road length & cost by county |
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| Figure 5: final map showing truck routes |
Conclusions
Prior to completing this lab, I had primarily only considered the negative effects that frac sand mining has upon humans and the environment. This lab, however, caused me to think about the ethics involved in fracking. Public roads are free to be used by everyone, but when certain vehicles' intensive use causes damages, should they be held accountable? According to Wisconsin law and my own convictions, yes. The process behind calculating the effects of such damage and the monetary compensation required can be done via network analysis in ArcMap.
Sources
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