Methods
Data sources
The
data sets required for this analysis were:
·
USA Counties Dataset: I downloaded the data
from UNM learn, this was part of the database used for assignment 2. In order
to select Socorro county, I used the select by attribute and export data tools.
·
Shape files of the Rhodes property: I
acquired these files thanks to GeoSystems Analysis
(GSA), a company that collaborates in this project with SOBTF. They provided a
group of people in the class with all the GIS data they had available.
·
Location of wells, water elevation and
quality data: I directly contacted the Interstate Stream Commission (ISC) and
they provided me with all the data they had regarding groundwater in the
property.
Projection
used
I chose to project all the
data in Universal Transverse Mercator (UTM) Zone 13N with NAD 83 Datum because
most of the shape files provided were already represented using this
projection.
Software
I used ArcGIS 10.3.1 and
ArcGIS 10.1 (ArcMap and ArcCatalog). I specifically
used the latest version for the Spatial Analyst toolbox and the Georeferencing toolbox.
For the groundwater
elevation analysis, I was provided with an extensive amount of data from different
data loggers as well as point measurements from the different wells in the
property. In order to process all this data more efficiently I decided to use the
Arc Hydro Tools for Groundwater analyst (AHGW), due to the availability of a
user friendly interface and statistical analysis within the toolbox. The
groundwater analyst application was not compatible with ArcGIS 10.3.1, in that
sense I had to use ArcGIS 10.1 for this portion of the project.
General
Methodology
I started by introducing the
shape file of the property to make sure all the following data introduced would
be projected On the fly.
Groundwater
elevation and water quality statistics
Using the data provided by
the ISC, I created different tables in excel where I could classify the data
(land elevation, water elevation, depth to water, field and laboratory measured
water quality parameters) by well location and time period. Then I imported the
well features into ArcMap using the AHGW Text Import command, I assigned the
proper labels to each parameter and decided which ones I wanted to map.
Moreover, I imported the
time series data using again AHGW Text Import command pairing a Feature ID
column with the wells numbers in order to be able to match information from the
previously imported data. Once the importing and fixing was completed, I
performed a time series statistical analysis using AHGW Make Time Series
Statistic tool for specific time intervals (summer and spring combined, as well
as, fall and winter combined) for the wells with transient data, I established
the mean values as the output statistical parameter. In order to make this
process more efficient, I created a simple model using the Model Builder tool.
Finally, for the groundwater
elevations I interpolated the point statistics to a raster using the Inverse
Distance Weighted (IDW) interpolation tool within the Spatial Analyst toolbox
making sure to set up the environment delimitations to fit the shapefile of the
Rhodes property.
For the water quality I
joined all the output statistical analysis for each of the available water
quality parameter and created a feature class with all the information.
Furthermore, I introduced this feature class to the map and changed the Symbology to Charts and then Pie.
Vegetation
restoration goals
For
this section I wanted to overlay the proposed vegetation plan with a raster
that I created for the salinity in groundwater. The new vegetation approach was
created by other group in our class which provided me a jpeg with the proposed
plan. Because this picture did not have any spatial information I had to use
the Georeferencing toolbox to make the figure match
with the shape file of the property that had the salinity raster and the wells.
I chose 4 identifiable common points in the image and the shape file, then I
georeferenced it and adjusted the transparency of the salinity raster to obtain
the desired final product.