Case Studies
Apr 27, 2018

GIS-Based Method for Estimating Surficial Groundwater Levels in Coastal Virginia Using Limited Information

Publication: Journal of Irrigation and Drainage Engineering
Volume 144, Issue 7

Abstract

In many coastal areas, high water tables are present, complicating installation of some stormwater best management practices (BMPs) that rely on infiltration. Regional estimates of the seasonal high water table (SHWT) often rely on sources such as soil surveys taken over a decade ago; these data are static and do not account for groundwater withdrawals or other anthropogenic impacts. To improve estimates of the SHWT, we developed a GIS-based methodology relying on surface water elevations. Data sources included a 1.5-m (5.0 ft) resolution Lidar-derived digital elevation model (DEM), aerial imagery, and publicly available shapefiles of water boundaries. Twenty-six groundwater monitoring wells were screened to eliminate well locations influenced by pumping, yielding 22 wells. In coastal Virginia, tidal water bodies and ditches form terminal boundaries for discharge from the water-table aquifers and permit water table elevations to be fixed at the landward boundaries of surface water bodies. Water table elevations interpolated from well data and boundary elevations were used to create a triangulated irregular network representing the water table elevations for November 2012, which was the date of the DEM. An adjustment factor, calculated from the highest recorded April water table depth from long-term groundwater monitoring data, was added to estimate the SHWT elevation. SHWT elevations were subtracted from the DEM to yield SHWT depth, which was compared with long-term monitoring well data, yielding an R2 value of 0.91. Residual errors were random, although the method underpredicted the highest expected SHWT and overpredicted the median SHWT. The SHWT depth map was validated by using water table depths from 57 soil borings at 10 different sites, and consistently matched observations better than available soil survey estimates. The SHWT depth map could be useful for BMP siting and feasibility studies in similar hydrogeological settings.

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Acknowledgments

The authors express their appreciation to Greg Johnson, Department of Public Works, City of Virginia Beach, Virginia; Kathleen Hancock, Department of Civil and Environmental Engineering, Virginia Tech; and Conrad Heatwole and Durelle Scott, Department of Biological Systems Engineering, Virginia Tech, who facilitated and helped guide this research, and provided constructive comment. Portions of this research were funded by the City of Virginia Beach, Project 449263; however, opinions expressed within are entirely of the authors and reflect no endorsement by the City. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the US Government. Funding for this research was also was provided in part by the Virginia Agricultural Experiment Station and the Hatch program of the National Institute of Food and Agriculture, US Department of Agriculture, which also does not imply endorsement of opinions contained herein.

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Go to Journal of Irrigation and Drainage Engineering
Journal of Irrigation and Drainage Engineering
Volume 144Issue 7July 2018

History

Received: Mar 20, 2017
Accepted: Jan 5, 2018
Published online: Apr 27, 2018
Published in print: Jul 1, 2018
Discussion open until: Sep 27, 2018

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Authors

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R. D. Johnson [email protected]
Graduate Student, Dept. of Biological System Engineering, Virginia Polytechnic Institute and State Univ., Blacksburg, VA 24061. Email: [email protected]
D. J. Sample, M.ASCE [email protected]
Associate Professor, Hampton Roads Agricultural Research and Extension Center, Virginia Polytechnic and State Univ., Virginia Beach, VA, 23455 (corresponding author). Email: [email protected]
K. J. McCoy [email protected]
Hydrologist, Virginia-West Virginia Water Science Center, US Geological Survey, 1730 E Parham Rd., Richmond, VA 23228. Email: [email protected]

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