REGIONAL GROUNDWATER FLOWPATH IN TRANS-PECOS, WEST TEXAS

 

 

Thandar Phyu

Master Candidate - Hydrogeology

Department of Geological Sciences

CE 394K – Fall 2000 Term Project

 

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• Introduction
1. Objective
2. Location
3. DEMs
• Strontium isotopes
• Procedures
1. Strontium Distribution
2. Potentiometric Surface Map
• Problems
• Summary
• Acknowledgement

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Introduction

 

 

Objective

 

 

My objective of this project was to have experience in applying GIS technology in groundwater studies. This project was based on the PhD research of Mathew Uliana from the Department of Geological Sciences of University of Texas at Austin. He did three studies – Chemical, fracture trace, and isotope analyses – to delineate regional flowpath in the Trans-Pecos region of West Texas. For this project, I used his strontium isotope data to map conceptual regional flowpath.

 

 

Location

 

 

The location of Trans-Pecos region is shown below. It spreads out over five counties – Culberson, Hudspeth, Jeff Davis, Pecos, and Reeves – in the West Texas. Blue dots represent location of the 29 wells from which water samples were taken and strontium values were measured.

                  

 

 

 

 

Digital Elevation Models (DEMs)

 

 

Digital Elevation Models (1:250,000) were used to look at the general topography of the area. It is primarily located in the Toyah Basin. To the northwest, south, and southeast are several mountain ranges – Apache Mountains, Delaware Mountains, and Rustler Hills in west-northwest, Davis and Carrizo Mountains in south-southwest, and Star Mountains in southeast.

 

                  

 

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Strontium Isotopes

 

 

Strontium isotopes are used as a natural tracer for groundwater flowpath because they do not tend to undergo significant fractionation that is they do not tend to precipitate or dissolve during rock-water interaction significantly. Thus, the strontium values in groundwater reflect the strontium composition of the rock or minerals they get interact with. Strontium has four naturally occurring isotopes – ⁸⁸Sr, ⁸⁷Sr, ⁸⁶Sr, and ⁸⁴Sr – all of which are stable. The radiogenic ⁸⁷Sr is formed by the decay of naturally occurring rubidium ⁸⁷Rb. Therefore, the precise isotopic composition of strontium in a rock or mineral that contain ⁸⁷Rb depends on the age and Rb/Sr ratio of that rock or mineral (Faure, 1986). For this reason, the strontium composition in groundwater can be used to determine the source of that water.

 

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Procedures

 

 

(1) Strontium Distribution

 

 

The procedure required to map the strontium ⁸⁷Sr/⁸⁶Sr distribution was simple and straightforward. The data I was given were in (x,y) coordinates and therefore converted them into decimal degrees.

                       

Decimal Degree = Degree +(minute/60)+(second/3600)

 

The data table was first created in Excel and saved as a database file (*.dbf). Then the table was added to the project window in ArcView (Table/Add) and it was added as an event theme in a new view (View/Add Event Theme). Spatial Analyst and 3D Analyst Extensions were added (File/Extension) first to create the TIN (Surface/Create Theme from Features). The ⁸⁷Sr/⁸⁶Sr field was selected for Height Source and Mass Points for Input.

 

   

 

 

The TIN theme was then converted into a grid theme (Theme/Convert to Grid). Output grid extent cell size was chosen as the same as the TIN theme. Cell size, number of rows, and number of columns were automatically given. The counties.shp shape file from the exercise 3 was used to display the background and the extent. The grid interval can be changed in the legend editor by double clicking on the theme legend. Here the ⁸⁷Sr/⁸⁶Sr interval was 0.001.

 

 

 

Before contours were created from the grid theme, analysis properties of the theme from which contours will be created have to be specified. To do this, go to Analysis, select Properties, and set the analysis extent and analysis cell size the same as the grid theme. The values in the rest of the fields were automatically given. Then go to Surface and choose Create Contours. Contour interval here is 0.001.

 

 

 

The grid and the contours showed the ‘plume-like’ distribution of ⁸⁷Sr/⁸⁶Sr values. From this shape of distribution, the conceptual regional groundwater flowpath can be drawn as shown below. The black arrows shows the conceptual direction of groundwater flow in that region.

 

 

 

 

 

(2) Potentiometric Surface Map

 

 

The procedure for creating a potentiometric surface map involue some data manipulation. The water level data (wlevels.txt) and well data (weldta.txt) files for the five counties were downloaded from the Texas Water Development Board website. From these text files, the fields necessary for this project were selected such as state well number, longitude and latitude, water elevation from the land surface, etc. Then in Excel, the two data tables were joined together with the state well number which is common to both tables by using the paste function tool and choosing VLOOKUP function. Lookup_value is the field that is common to both tables. Table array is the range of data in the table to be looked up. Col_index_num is the index number of the column of the data field to find. Range_lookup is set to ‘true’ if to find the closet match. In this case, the exact match of the state well number is needed, so it was set ‘false’. By this way, latitude and longitude, land surface elevation, and aquifer codes from the well data table were joined with water level below land surface, and date of measurement from the water level data table. The elevation of water was calculated by subtracting the water level from the surface from the land surface elevation. Longitude and latitude were again converted into decimal degrees.

 

 

 

Then the new dataset was saved as a database file (*.dbf) and added to the ArcView the same way as for the Strontium distribution mapping. The water level measured in the recent years was desired, so using Query Building tool in ArcView only 1999 data were selected. For this project, it was assumed that all wells are in the same hydrostratigraphic unit/same aquifer. All selected data for 1999 were then converted to a shape file (Theme/Convert to Shapefiles).

 

 

 

 

 

The wells in the Hudspeth county that were measured in 1999 were so sparse that they were excluded. Using the newly created shape file, the TIN was created and then converted into grid the same way as in previous procedure. The grid interval here is 200 feet.

 

 

Contours for the potentiometric surface map were also created the same way as in the previous procedure. The contour interval is 200 feet.

 

                                               

 

The approximate groundwater flow direction was drawn below indicated by the black arrows. The flow lines should be perpendicular to the contours. The flow direction is in the general trend as drawn with the strontium distribution.

 

 

 

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Problems

 

 

The main problem with this project was the very limited data for strontium values. If more data were present, the grid and the contours of strontium distribution would be smoother.

 

 

 

Summary

 

 

GIS is a very effective way to present distribution of strontium or other constituents in the groundwater and to create potentiometric surface map. However, adequate data that are evenly spaced are needed to get a good representation. GIS can still be used with limited data but the other alternatives may be better to use.

 

 

 

Acknowledgement

 

 

Mathew Uliana, Department of Geological Sciences, University of Texas at Austin

 

Dr. David Maidment, Department of Civil Engineering, University of Texas at Austin

 

 

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