Name: Normal conditions (meters)

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Description: <DIV STYLE="text-align:Left;"><DIV><DIV><P><SPAN>This digital product contains gridded estimates of depth to water (dtw) under normal conditions for Delaware. This work is the final component of a larger effort to provide estimates of water-table elevations and depths to water for the Coastal Plain portion of Delaware. Mapping was supported by the Delaware Department of Natural Resources and Environmental Control and the Delaware Geological Survey. These grids were produced with the same multiple linear regression (MLR) method as Andres and Martin (2005). Briefly, this method consists of: identifying dry, normal, and wet periods from long-term observation well data (Nc45-01, Ng11-01, Qe44-01); estimating a minimum water table (Sepulveda, 2002) by fitting a localized polynomial surface to elevations of surface water features (e.g., streams, swamps, and marshes); and computing a second variable in the regression from water levels observed in wells. A separate MLR equation was determined for dry, normal, and wet periods, and these equations were used in ArcMap v.9 (ESRI, 2004) to estimate grids of water-table elevations and depths to water. The grids have 30-m horizontal and 1-ft vertical resolutions. Grid world files and ground-water level observation data are in UTM-18N, 1983 projection in meters and elevations are in feet, NAVD 1988. Files are in ESRI, Inc., grid format. These data were combined from DGS Digital Data Products DP05-01, DP05-03, and DP05-04 Digital Water-Table Data for Sussex, Kent, and New Castle counties, Delaware, respectively. REFERENCES CITED Andres, A. S., and Martin, M. J., 2005, Estimation of the water-table surface for the Inland Bays watershed, Delaware: Delaware Geological Survey Report of Investigations No. 68, 20p. ESRI, 2004, ArcMap v. 9, Redlands, California. Sepulveda, N., 2003, A statistical estimator of the spatial distribution of the water-table altitude: Ground Water, vol. 41, p. 66-71.</SPAN></P></DIV></DIV></DIV>

Copyright Text: Matthew J. Martin and A. Scott Andres

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