Joe Anderson – Introduction, Logistics of the Project, Tasks

 

Christian Michaelson – Data manipulation, Evaluation

 

 

 

Getting Water from the Colorado River to the Wasatch Front

 

Introduction

 

            Utah at the present time has enough water for the residents of Utah to live comfortably without the water costing excessive amounts.  However as time passes and the population of the state continues to grow something needs to chance.                                                                                                                                               

                                                        

                                                                                                                                Table 1 Wasatch Front Available Water

                                                                                           

                                                                                                                                           Table 2 Developable Supply

 

Figure 1 shows the water that is available to the Wasatch Front, and also the water that will be available in the next 50 years.  The available water increases because as can be seen in Figure 2 there is still more developable water in the three basins that are listed, that drain into the Wasatch Front.  However even with this developable water with the expected population growth in Utah something will need to be done to keep the per capita usage at the same rate.  Either the price of the water needs to go up, or the amount of water used per capita needs to decrease, or new water sources need to be found in order to keep the per capita usage the same.  This paper focuses on finding new sources to get the water from.  Specifically it focuses on bringing water from the Green River drainage, where The Upper Colorado River Contract provides Utah a substantial amount of water, and delivering it to the Wasatch Front.

Table 3 The Year a New Water Source Will Be Needed

 

Logistics of the project

 

            As can be seen in Table 3 the population in 2050 in Utah is expected to arrive at 3.15 million people, which is almost 1.4 million more people then now live in the state.  Obviously once the state arrives to this population a new water source will be needed.  The purpose of this table however is to show when the new project will be needed, and what kind of benefit the project will be to the people of Utah.  Also included in this table is the states goal of decreasing the water usage by 25% of the present per capita usage.  Using this conservative water usage amount the state will need the water from the project by the year 2024.

            The diversion point for the water also needed to be found.  For this project water was diverted from Fontenelle Reservoir in Wyoming and was brought by pressurized pipe to Echo Reservoir and then to the Wasatch water distribution center.  We chose to divert water from Fontenelle because it’s a large reservoir along the Colorado River in which the flow does not fluctuate as much as the streams do.  Also it has a high elevation, which will save on costs of pumping the water.  Below, Figure 1 shows the location of this project on a map of Utah, Idaho, and Wyoming.

           

Figure 1 -  Diversion and Drop-off Points for the water

Tasks

            The tasks involved in carrying out a project of this magnitude are many.  These tasks include the following:

•         Use GIS to choose optimal alignment of the transmission system

•         Do hydrologic study to determine water quantities

•         Identify cost items

For diversion and transmission facilities

For pipes, pump stations, turbines, and construction 

•         Benefits of the project

•         Institutional and environmental concerns

•         Conclusion

Of the tasks listed above this project will concentrate its efforts on using GIS to choose the optimal alignment of the transmission system from Fontenelle Reservoir to Echo Reservoir.  In order to create this map, data must be found.  The shapefiles used for Utah were found on the Automated Geographic Reference Center website.  Those found for Wyoming were in large part from the University of Wyoming’s GIS database, and the DEM’s used were found on the USGS seamless website.  The data found was either vector data that was eventually converted to raster data, or raster data.  Raster data was used because it could be processed using the raster calculator which will be explained more in detail later in the paper.

 

Data Manipulation

Using the USGS seamless data website 8 DEM’s were found that cover this area.  Three of these DEM’s are shown below in order to demonstrate that although the data was “seamless” the eight DEM’s still needed to be merged together in order for our path to go from one DEM to another.

 

Figure 2 - three of the eight unmerged DEM’s

            In order to merge the data a tool called “Grid Pig” was used.  Once Grid Pig was used the resulting layer of DEM’s was formed.

           

Figure 3 - Merged DEM layer

The GIS solution to this problem consists of the construction of a cost surface which is the sum of several other grids, which will be discussed later. Once these DEM’s are merged and you have one continuous DEM you are well on your way to constructing a cost surface which will allow you to find the best cost path using the Spatial Analyst in ArcGIS.

POINT SYSTEM

Slope                                      x = degrees

Elevation                                 elev/100 (m)

Wetlands (50 ft buffer)            50 points

Other                                      0 points 

National Park                          50 points

Forest Service                         50 points

Private Land                            50 points

Water                                      50 points

Public Land                             0 points

Other                                      0 points

            The first step to creating the cost surface is to select the criteria which will be used to select the location of the proposed route alignment. The criteria we selected are listed above. While these criteria are limited, the scope of possibilities is basically unlimited. The alignment of the road, utility line or in this case pipeline is highly dependent upon the criteria selected. The pipeline required to deliver the necessary amount water would require quite a bit of right of way to construct and maintain, therefore we selected 50 ft buffers for all areas designated as wetlands. Additionally all land which would be difficult to cross either physically or politically was given a cost value of 50 to cross. Water bodies such as lakes and ponds were assigned this cost value as well because crossing them is unpractical. Areas that did not meet these criteria received a value of 0 as not to impede the progress of the pipeline. Null values were also assigned zero values. Elevation of the construction was taken into account in order to provide compensation for transportation and mobilization of equipment and pipe to remote areas. Lastly the slope of the path to be crossed was assigned a value equal to that slope. These values were assigned using a newly created field in the attribute table of each feature class called value.

Figure 4 - The slope map created in Spatial Analyst.

 

 

Figure 5 - Administrative Data Used

Figure 6 - Utah Wetlands

Figure 7 - Wyoming Wetlands

            Data from all the previous figures (5-7) had to be downloaded as shapefiles, buffered and then converted to rasters to allow processing in the raster calculator. Since the slope and elevation data were derived from the DEM they were already in raster form and needed no further processing. Once all the necessary data is in raster format and can therefore be manipulated with the raster calculator it is time to make the cost surface.

Figure 8 - The cost surface

           

This is the object of much work. Although it does not look like much this is the key to performing a best cost path analysis. The cyan areas are the highest cost values and the grey areas are the lowest cost areas. From this cost surface Spatial Analyst derives two more surface raster that it needs to calculate the best path. The first is the Cost Direction Grid.

 

Figure 9 - The Cost Direction Grid

Figure 10 - Cost Distance Grid

            Once these two rasters are calculated there is only one more step to finding your least cost path. Using the Spatial Analyst in ArcGIS the least cost path can be calculated. This is done by going to the Distance and then Cost Weighted commands in the drop down menu. The result after some calculation should be the leas cost path from your start to end points. These points need to be created as shapefiles in the earlier stages of constructing the least cost path. Our least cost path from one point to the other ended up looking like this.

Figure 11 - Final Least Cost Path

                                         

           

 

Evaluation

In the end the path along this least cost surface was quite surprising. It should be noted that the order in which you insert your start and end points into the spatial analyst does make a difference in the path. Multiple variations of path alignment based on start to end and end to start alterations as well as the values assigned to various desired parameters could result. These numbers can be tweaked until the most desirable result occurs. Many factors that are hard to associate with geo-spatial data should also be considered. Political influences and public sentiment are a few of these factors which are hard to quantify and associate with location.

Some technical details that need to be discussed. Projections are key when working in an area this large. All projection data must be carefully managed. Although nationwide data is available statewide data is often more accurate and has higher resolution. This results in downloading data from many state websites when working across state borders. While one state organizes its data one way another may do it differently. Unfortunately this can prove to be challenging when doing a consistent study near a border. While this project was a great challenge is was also a great opportunity to learn and explore the possibilities of ArcGIS.