Predictive modeling of soluble sulfate ion concentration in the Las Vegas Valley

This study investigates the process of identifying soluble sulfate ion concentrations in the Las Vegas Valley. Data utilized in this study were obtained from Clark County Department of Development Services records. Once collected, the data were reviewed and analyzed with traditional non-spatial statistics and spatial-based geostatistical modeling. This study was undertaken in an effort to identify factors that may correlate with soluble sulfate ion concentrations and to determine the feasibility of producing a predictive model capable of estimating soluble sulfate ion concentrations within the Las Vegas Valley; The study showed that relief, spatial location, soil grain size classification and Clark County Soils Guideline Map Areas may all provide useful correlations in predicting soluble sulfate ion concentrations. The study also produced a preliminary geospatial statistical model capable of identifying large scale trends in the distribution of soluble sulfate ion concentrations. It is likely that this preliminary model will be optimized in the future and serve as the basis for a more accurate and robust predictive model. This study represents the first steps in an effort to better understand the nature of soluble sulfate ion distribution and should be of interest to local geotechnical designers who routinely identify these concentrations in their professional activities.

Name thesis:degree_name

Master of Engineering (ME)

Level thesis:degree_level

Thesis

Discipline thesis:degree_discipline

Civil and Environmental Engineering

Grantor dc:publisher

University of Nevada, Las Vegas

Year

2003

Author dc:creator

• Hellmer, Werner K

Contributors dc:contributor

• Moses Karakouzian

Statement dc:rights

• IN COPYRIGHT. For more information about this rights statement, please visit http://rightsstatements.org/vocab/InC/1.0/

Language dc:language

English

Identifier

https://oasis.library.unlv.edu/rtds/1596

OAI identifier oai:identifier

oai:oasis.library.unlv.edu:rtds-2595