On Georeferenced Soil Engineering Properties and Interpolations
Publication: Geo-Congress 2023
ABSTRACT
Due to the inherent variability of soil properties, geotechnical engineers often leverage multiple tools to estimate site subsurface conditions, including historical records, in situ measurements, and laboratory testing data. A comprehensive site investigation may be uneconomical for certain projects; thus engineers typically perform site characterization, which potentially could balance project costs and the extent of site investigation. To aid in preliminary analyses of site conditions, we have created a web-GIS database to compile soil engineering properties across the state of Oregon. The database, Georeferenced Oregon Soil Engineering Properties (GOSEP), is populated by existing data across projects from all over the state, including monotonic strength, laboratory characterization data, borehole logs, and in situ test results. In this paper, a detailed procedure showing kriging was used to generate three-dimensionally interpolated standard-penetration-test (SPT) data through the GOSEP interface. In addition, this study reveals the use of oblate spheroid as a kriging search geometry and the approach to dealing with modeling variograms with few data points. Ultimately, a cross-validation analysis was performed to study the accuracy of predicted values, and the limitations were discussed regarding the estimation.
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REFERENCES
Bekele, A., Downer, R., Wolcott, M., Hudnall, W., and Moore, S. (2003). Comparative Evaluation Of Spatial Prediction Methods In A Field Experiment For Mapping Soil Potassium. Soil Science, 168(1), 15–28.
Bierkens, M., and Burrough, P. (1993). The indicator approach to categorical soil data. Journal of Soil Science, 44(2), 361–368.
Coduto, D. P., Kitch, W. A., and Yeung, M.-C. R. (2016). Foundation design: Principles and practices. Pearson, Boston.
Deutsch, C., and Journel, A. (1992). GSLIB. New York: Oxford University Press.
Gotway, C., Ferguson, R., Hergert, G., and Peterson, T. (1996). Comparison of Kriging and Inverse-Distance Methods for Mapping Soil Parameters. Soil Science Society of America Journal, 60(4), 1237–1247.
Hengl, T. (2009). A practical guide to geostatistical mapping. Amsterdam: University of Amsterdam.
Hengl, T., Toomanian, N., Reuter, H., and Malakouti, M. (2007). Methods to interpolate soil categorical variables from profile observations: Lessons from Iran. Geoderma, 140(4), 417–427.
Ijaz, Z., Zhao, C., Ijaz, N., Rehman, Z., and Ijaz, A. (2021). “Spatial mapping of geotechnical soil properties at multiple depths in Sialkot Region, Pakistan.” Environmental Earth Sciences, 80(24).
Journel, A. (1983). Nonparametric estimation of spatial distributions. Journal of the International Association for Mathematical Geology, 15(3), 445–468.
Journel, A. (2010). Fundamentals of geostatistics in five lessons. Washington, D.C: American Geophysical Union.
Journel, A. G., and Huijbregts, C. J. (1976). Mining geostatistics.
Kim, M., Kim, H., and Chung, C. (2020). A Three-Dimensional Geotechnical Spatial Modeling Method for Borehole Dataset Using Optimization of Geostatistical Approaches. KSCE Journal of Civil Engineering, 24(3), 778–793.
Lu, G., and Wong, D. (2008). An adaptive inverse-distance weighting spatial interpolation technique. Computers & Geosciences, 34(9), 1044–1055.
Longley, P., Goodchild, M. F., Maguire, D. J., and Rhind, D. W. (1999). Geographical Information Systems. John Wiley, New York.
Laslett, G. (1994). Kriging and Splines: An Empirical Comparison of Their Predictive Performance in Some Applications: Rejoinder. Journal of the American Statistical Association, 89(426), 406.
Pokhrel, R., Kuwano, J., and Tachibana, S. (2013). A kriging method of interpolation used to map liquefaction potential over alluvial ground. Engineering Geology, 152(1), 26–37.
Pyrcz, M., and Deutsch, C. (2014). Geostatistical reservoir modeling. New York: Oxford University Press Inc.
Roe, W., and Madin, I. (2013). 3D geology and shear-wave velocity models of the Portland, Oregon, metropolitan area.
Remy, N., Boucher, A., and Wu, J. (2009). Applied geostatistics with SGeMS. Cambridge, UK: Cambridge University Press.
Setianto, A., and Triandini, T. (2015). “Comparison of Kriging and inverse distance weighted (IDW) interpolation methods in lineament extraction and analysis.” Journal of Applied Geology, 5(1).
Wu, J., He, J., and Christakos, G. (2021). Quantitative analysis and modeling of earth and environmental data.
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Published online: Mar 23, 2023
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