Aquifer vulnerability assessment to heavy metals using ordinal logistic regression
Twarakavi, NKC; Kaluarachchi, JJ
HERO ID
365154
Reference Type
Journal Article
Year
2005
Language
English
PMID
| HERO ID | 365154 |
|---|---|
| In Press | No |
| Year | 2005 |
| Title | Aquifer vulnerability assessment to heavy metals using ordinal logistic regression |
| Authors | Twarakavi, NKC; Kaluarachchi, JJ |
| Journal | Groundwater |
| Volume | 43 |
| Issue | 2 |
| Page Numbers | 200-214 |
| Abstract | A methodology using ordinal logistic regression is proposed to predict the probability of occurrence of heavy metals in ground water. The predicted probabilities are defined with reference to the background concentration and the maximum contaminant level. The model is able to predict the occurrence due to different influencing variables such as the land use, soil hydrologic group (SHG), and surface elevation. The methodology was applied to the Sumas-Blaine Aquifer located in Washington State to predict the occurrence of five heavy metals. The influencing variables considered were (1) SHG; (2) land use; (3) elevation; (4) clay content; (5) hydraulic conductivity; and (6) well depth. The predicted probabilities were in agreement with the observed probabilities under existing conditions. The results showed that aquifer vulnerability to each heavy metal was related to different sets of influencing variables. However, all heavy metals had a strong influence from land use and SHG. The model results also provided good insight into the influence of various hydrogeochemical factors and land uses on the presence of each heavy metal. A simple economic analysis was proposed and demonstrated to evaluate the cost effects of changing the land use on heavy metal occurrence. |
| Doi | 10.1111/j.1745-6584.2005.0001.x |
| Pmid | 15819941 |
| Wosid | WOS:000227828300008 |
| Is Certified Translation | No |
| Dupe Override | No |
| Comments | |WOS:000227828300008 |
| Is Public | Yes |
| Language Text | English |
| Keyword | altitude; aquifers; arsenic; cadmium; catchment hydrology; chromium; clay fraction; cost analysis; decision making; economic analysis; environmental assessment; geochemistry; geology; groundwater; groundwater pollution; heavy metals; hydraulic conductivity; land use; lead; mathematical models; mercury; pollutants; probability; regression analysis; soil types; water quality; water table; USA; Washington; North America; America; Developed Countries; OECD Countries; Pacific Northwest States of USA; Pacific States of USA; Western States of USA; choice; costing; United States of America; water composition and quality; Natural Resource Economics (EE115) (New March 2000); Soil Physics (JJ300); Water Resources (PP200); Land Resources (PP300); Meteorology and Climate (PP500); Pollution and Degradation (PP600); Industrial Wastes and Effluents (XX400); Mathematics and Statistics (ZZ100); Geology and Geomorphology (General) (ZZ800) |
| Is Qa | No |