Estimated Depth to Ground Water and Configuration of the Water Table in the Portland, Oregon Area

Modeling vulnerability of groundwater to pollution under future scenarios of climate change and biofuels-related land use change: A case study in North Dakota, USA

“…The data were retrieved using a web query function of Microsoft Excel and stored in Excel spreadsheets. Locations of surface water features, such as major streams, lakes, wetlands, and springs were obtained from the USGS National Hydrography Dataset (NHD) and used to indicate where the DTW approximates 0 (Snyder, 2008). ArcGIS was used to randomly plot 1000 points (where the DTWs are 0) on these surface water features.…”

“…ArcGIS was used to randomly plot 1000 points (where the DTWs are 0) on these surface water features. The DTW surface was estimated based on an integration of interpolated water table depth and water table elevation, a method proposed by Snyder (2008).…”

Uncertainties Monitoring Groundwater Levels in Exploratory Wells

“…The groundwater level is defined as the upper surface of a saturated zone in an assumed unconfined aquifer. This definition excludes partially saturated or perched zones, horizons, such as the capillary fringe above the water table, ground water lying beneath paleosols, which create semi‐confined water conditions, or ground water perched on or against low‐permeability horizons (Bates and Jackson 1987; Snyder 2008). All these situations are common to riverine floodplains, yet the discrepancies they engender are often ignored in regional GIS (geographic information systems)‐based studies, where any manner of “well” with a “reported water depth” are generally included in large geodatabases (Aldrich and Lambrechts 1986; Holzer 2010).…”

“…Natural fluctuations in groundwater levels also depend on the quantity and timing of precipitation, which can occur on timescales ranging from hours to years, depending on changes in climate or land use (Snyder 2008). For example, groundwater levels in the Mississippi River alluvial valley near St. Louis area fluctuated as much as 3 m between 1980 and 1985, and again from 2002 to 2009.…”

Use of Nested Flow Models and Interpolation Techniques for Science‐Based Management of the Sheyenne National Grassland, North Dakota, USA

“…Alternatively, one could directly interpolate groundwater levels between monitoring wells, which would result in a perfect or nearly perfect match at these monitoring wells, but may not yield sufficiently accurate groundwater heads in between these wells. Although kriging seems to be used the most for depth‐to‐groundwater calculations (Knotters and Bierkens 2001; Hillenbrand and Friedman 2005; Theodossiou and Latinopoulos 2006; Sun et al 2009; Nikroo et al 2010), both the inverse distance weighting (IDW) and artificial neural network (ANN) methods have also been used for this purpose (ASCE 2000b; Knotters and Bierkens 2001; Sepulveda 2002; Lin and Chen 2004; Hillenbrand and Friedman 2005; Snyder 2008; Sun et al 2009; Hoogland et al 2010;). These interpolation methods do not rely on hydrogeological data; all that is needed are data sets of groundwater levels at monitoring wells and ground surface topography (Snyder 2008).…”