Analysis And Summary Of Water-Table Maps For The Delaware Coastal Plain

Author(s)Martin, M.J.
Author(s)Andres, A.S.
Date Accessioned2008-04-02T19:00:49Z
Date Available2008-04-02T19:00:49Z
Publication Date2008
DescriptionThis report has two plates listed as separate files.en_US
AbstractA multiple linear regression method was used to estimate water-table elevations under dry, normal, and wet conditions for the Coastal Plain of Delaware. The variables used in the regression are elevation of an initial water table and depth to the initial water table from land surface. The initial water table is computed from a local polynomial regression of elevations of surface-water features. Correlation coefficients from the multiple linear regression estimation account for more than 90 percent of the variability observed in ground-water level data. The estimated water table is presented in raster format as GIS-ready grids with 30-m horizontal (~98 ft) and 0.305-m (1 ft) vertical resolutions. Water-table elevation and depth are key facets in many engineering, hydrogeologic, and environmental management and regulatory decisions. Depth to water is an important factor in risk assessments, site assessments, evaluation of permit compliance data, registration of pesticides, and determining acceptable pesticide application rates. Water-table elevations are used to compute ground-water flow directions and, along with information about aquifer properties (e.g., hydraulic conductivity and porosity), are used to compute ground-water flow velocities. Therefore, obtaining an accurate representation of the water table is also crucial to the success of many hydrologic modeling efforts. Water-table elevations can also be estimated from simple linear regression on elevations of either land surface or initial water table. The goodness-of-fits of elevations estimated from these surfaces are similar to that of multiple linear regression. Visual analysis of the distributions of the differences between observed and estimated water elevations (residuals) shows that the multiple linear regression-derived surfaces better fit observations than do surfaces estimated by simple linear regression.en_US
SponsorDelta Development Group, Inc.en_US
URLhttp://udspace.udel.edu/handle/19716/3173
Languageen_USen_US
PublisherNewark, DE: Delaware Geological Survey, University of Delawareen_US
Part of SeriesReport of Investigationsen_US
Part of Series73en_US
Keywordsmultiple linear regression methoden_US
Keywordswater-table elevationen_US
KeywordsCoastal Plainen_US
KeywordsDelawareen_US
TitleAnalysis And Summary Of Water-Table Maps For The Delaware Coastal Plainen_US
TypeTechnical Reporten_US
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