SOCR 061708 NC Data Aquifer

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Contents

SOCR Datasets - Wolfcamp Aquifer Data

Data Overview

Texas Wolfcamp Aquifer

The Wolfcamp aquifer data (Cressie, 1993, pp. 212-214) was acquired by the U.S. Department of Energy in the 1980s to study a nuclear waste site, Deaf Smith County in Texas (bordering New Mexico). The contamination of the aquifer was a concern, and therefore the piezometric-head data were obtained at 85 locations by drilling a narrow pipe through the aquifer.


Data Description

Piezometric head measurements taken at the Wolfcamp Aquifer, Texas, USA. See Cressie (1993, p.212–214) for description of the scientific problem and the data. Original data were converted to SI units: coordinates are given in kilometers and pressure heads measures are in kilometers above the sea level.

  • X = Horizontal distance in kilometers from one location (an arbitrary point).
  • Y = Vertical distance in kilometers from one location (an arbitrary point).
  • Data = Pressure heads measures are in kilometers above the sea level

Data Table

X Y Data
42.78275 127.62282 1.464
-27.39691 90.78732 2.553
-1.16289 84.896 2.158
-18.61823 76.45199 2.455
96.46549 64.58058 1.756
108.56243 82.92325 1.702
88.36356 56.45348 1.805
90.04213 39.2582 1.797
93.17269 33.05852 1.714
97.61099 56.27887 1.466
90.62946 35.08169 1.729
92.55262 41.75238 1.638
99.48996 59.15785 1.736
-24.06744 184.76636 1.476
-26.06285 114.07479 2.2
56.27842 26.84826 1.999
73.03881 18.8814 1.68
80.26679 12.61593 1.806
80.23009 14.61795 1.682
68.83845 107.77423 1.306
76.39921 95.9938 1.722
64.46148 110.39641 1.437
43.39657 53.61499 1.828
39.07769 61.99805 2.118
112.8045 45.54766 1.725
54.25899 147.81987 1.606
6.13202 48.32772 2.648
-3.80469 40.4045 2.56
-2.23054 29.91113 2.544
-2.36177 33.82002 2.386
-2.1889 33.68207 2.4
63.22428 79.49924 1.757
-10.7786 175.11346 1.402
-18.98889 171.91695 1.364
-38.57884 158.52742 1.735
83.14496 159.11559 1.376
-21.80248 15.02551 2.729
-23.56457 9.41441 2.766
-20.11299 22.09269 2.736
-16.62654 17.25621 2.432
29.90748 175.12875 1.024
100.91568 22.97808 1.611
101.29544 22.96385 1.548
103.26625 20.34239 1.591
-14.31073 31.26545 2.54
-18.13447 30.18118 2.352
-18.12151 29.53241 2.528
-9.88796 38.14483 2.575
-12.16336 39.11081 2.468
11.65754 18.73347 2.646 61.69122 32.94906 1.739
69.57896 33.80841 1.674
66.72205 33.93264 1.868
-36.65446 150.91457 1.865
-19.55102 137.78404 1.777
-21.29791 131.82542 1.579
-22.36166 137.1368 1.771
21.14719 139.26199 1.408
7.68461 126.83751 1.527
-8.33227 107.77691 2.003
56.70724 171.26443 1.386
59.00052 164.54863 1.089
68.96893 177.2482 1.384
70.90225 161.38136 1.03
73.00243 162.98959 1.092
59.66237 170.10544 1.161
61.87249 174.30177 1.415
63.7081 173.91454 1.231
5.62706 79.0873 2.3
18.24739 77.39191 2.238
85.68824 139.81702 1.038
105.07646 132.03181 1.332
-101.64278 10.65106 3.51
-145.23654 28.02333 3.49
-73.99313 87.9727 2.594
-94.48182 86.62606 2.65
-88.84983 76.70991 2.533
-120.25898 80.76485 3.571
-86.02454 54.36334 2.811
-72.79097 43.09215 2.728
-100.17372 42.89881 3.136
-78.83539 40.82141 2.553
-83.69063 46.50482 2.798
-95.61661 35.82183 2.691
-87.5548 29.39267 2.946

References

  • Cressie, N.A.C (1993) Statistics for Spatial Data. New York: Wiley.
  • Papritz, A. and Moyeed, R. (2001) Parameter uncertainty in spatial prediction: checking its importance by cross-validating the Wolfcamp and Rongelap data sets. GeoENV 2000: Geostatistical for Environmental Applications. Ed. P. Monestiez, D. Allard, R. Froidevaux. Kluwer.





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