Sensitivity of groundwater monitoring networks to contaminant source width for various seepage velocities

Abstract

[1] This study evaluated the effect of contaminant source width on the detection efficiency of five, six, and seven well monitoring networks for a range of groundwater seepage velocities. Wells were positioned downgradient of a rectangular landfill oriented obliquely to groundwater flow. A buffer zone boundary, establishing a distance limit within which contaminant plumes should be detected, was located 100 m from the landfill's downgradient corner. Various combinations of seepage velocity, from 0.01 to 10.0 m/d, and contaminant source width, from 0.1 to 5.0 m, were input to a computer model, which computed the detection capability of alternative monitoring networks. Smaller networks were more sensitive to changes in contaminant source width and seepage velocity. The smallest network showed a 21.6% greater range in detection efficiency than the largest network over the range of input values. Each network was considerably more sensitive to contaminant source width than seepage velocity, suggesting uncertainty in contaminant source width warrants attention in field applications. The type of analysis illustrated in this study may be useful for identifying appropriate monitoring networks given uncertainty in contaminant source width and seepage velocity at field settings.

Enhanced detection of groundwater contamination from a leaking waste disposal site by microbial community profiles

“…Unfortunately, the variability of leachate composition and its associated water quality impacts [ Gibbons et al , 1999; Kjeldsen et al , 2002] necessitate the monitoring of dozens of parameters during this time. In addition, detection efficiency is lower if numbers of sentinel wells or their spatial distribution are insufficient relative to site hydrogeologic characteristics [ Hudak , 1999, 2005]. As a result, contamination may spread over a larger area prior to its detection or characterization, reducing remediation efficiency and increasing remedial and long‐term monitoring costs [ Massmann and Freeze , 1987].…”

Contaminant detection probability in heterogeneous aquifers and corrected risk analysis for remedial response delay

“…In addition, at several waste disposal facilities with natural clay bottom barriers, leakages may be caused by deposition of fluid containers over cracks or failure zones of small areal extent. Consequently, we have assumed that the size of the leakage source is a single point inside the landfill area, representing a worst case scenario in terms of detection because the plume to be formed will be very narrow and difficult to detect [ Meyer et al , 1994; Allen , 2001; Hudak , 2005].…”

“…In the unsaturated zone, flows are gravity driven and thus are primarily vertical, with the saturated‐zone transport presenting perhaps the greatest opportunity for a contaminant to travel large distances [ National Academies , 1994]. Cases where ignoring the influence of the unsaturated zone may be a valid approximation include those when the water table is relatively close to the bottom of the facility and contaminants move vertically toward the aquifer [ Meyer et al , 1994; Çelik et al , 2009]; when there is a highly permeable vadose zone or nonstratified deposits between a point source and the aquifer [ Hudak , 2005], or when there is fingered flow, which significantly increases the vertical pore water velocity leading to rapid discharge of contaminant into the saturated zone [ Selker et al , 1996].…”

Strategies for Designing Ground Water Monitoring Networks at Waste Storage Facilities with Multiple Source Areas

“…Relative to purely subjective approaches, structured methods for configuring wells may increase the probability of contaminant detection, while reducing monitoring costs, elapsed time to detection, and polluted volume of ground water. Most published approaches for configuring detection wells in ground water or evaluating alternative design methods were applied to single contaminant source areas, as opposed to multiple source areas within a larger waste storage facility (Meyer and Brill 1988; Morisawa and Inoue 1991; Meyer et al 1994; Cieniawski et al 1995; Hudak 1998, 2005; Angulo and Tang 1999; Yenigul et al 2005). Storck et al (1997) applied a computationally intensive optimization approach to multiple hazardous waste trenches, taking into account contaminant advection, and allocating wells among predefined candidate locations.…”