Augmenting Groundwater Monitoring Networks near Landfills with Slurry Cutoff Walls

This study investigated the use of slurry cutoff walls in conjunction with monitoring wells to detect contaminant releases from a solid waste landfill. The 50 m wide by 75 m long landfill was oriented oblique to regional groundwater flow in a shallow sand aquifer. Computer models calculated flow fields and the detection capability of six monitoring networks, four including a 1 m wide by 50 m long cutoff wall at various positions along the landfill's downgradient boundaries and upgradient of the landfill. Wells were positioned to take advantage of convergent flow induced downgradient of the cutoff walls. A five-well network with no cutoff wall detected 81% of contaminant plumes originating within the landfill's footprint before they reached a buffer zone boundary located 50 m from the landfill's downgradient corner. By comparison, detection efficiencies of networks augmented with cutoff walls ranged from 81 to 100%. The most efficient network detected 100% of contaminant releases with four wells, with a centrally located, downgradient cutoff wall. In general, cutoff walls increased detection efficiency by delaying transport of contaminant plumes to the buffer zone boundary, thereby allowing them to increase in size, and by inducing convergent flow at downgradient areas, thereby funneling contaminant plumes toward monitoring wells. However, increases in detection efficiency were too small to offset construction costs for cutoff walls. A 100% detection efficiency was also attained by an eight-well network with no cutoff wall, at approximately one-third the cost of the most efficient wall-augmented network.     

Groundwater Monitoring Strategies for Variable Versus Constant Contaminant Loading Functions

Contaminant plumes were derived for constant and variable loading functions at locations within a landfill. Annually, the alternative loading functions injected the same volume of contaminated water. Mass transport modeling was used to evaluate the detection efficiencies of 25 monitoring transects, spaced evenly between the landfill and a downgradient compliance boundary. Respectively, the most efficient transects (requiring the fewest monitoring wells) for constant and variable loading were located at 60–64 and 40 percent of the distance to the compliance boundary. The mean detection efficiency was 29 percent higher for variable loading, but the variation in detection efficiency was similar for constant and variable loading. At the most efficient transects, the minimum number of detection wells was 20 percent lower for variable loading. Given the influence of source loading on monitoring efficiency, alternative loading functions should be considered when designing detection monitoring networks in aquifers.     

Uncertainty based optimal monitoring network design for a chlorinated hydrocarbon contaminated site

An application of a newly developed optimal monitoring network for the delineation of contaminants in groundwater is demonstrated in this study. Designing a monitoring network in an optimal manner helps to delineate the contaminant plume with a minimum number of monitoring wells at optimal locations at a contaminated site. The basic principle used in this study is that the wells are installed where the measurement uncertainties are minimum at the potential monitoring locations. The development of the optimal monitoring network is based on the utilization of contaminant concentration data from an existing initial arbitrary monitoring network. The concentrations at the locations that were not sampled in the study area are estimated using geostatistical tools. The uncertainty in estimating the contaminant concentrations at such locations is used as design criteria for the optimal monitoring network. The uncertainty in the study area was quantified by using the concentration estimation variances at all the potential monitoring locations. The objective function for the monitoring network design minimizes the spatial concentration estimation variances at all potential monitoring well locations where a monitoring well is not to be installed as per the design criteria. In the proposed methodology, the optimal monitoring network is designed for the current management period and the contaminant concentration data estimated at the potential observation locations are then used as the input to the network design model. The optimal monitoring network is designed for the consideration of two different cases by assuming different initial arbitrary existing data. Three different scenarios depending on the limit of the maximum number of monitoring wells that can be allowed at any period are considered for each case. In order to estimate the efficiency of the developed optimal monitoring networks, mass estimation errors are compared for all the three different scenarios of the two different cases. The developed methodology is useful in coming up with an optimal number of monitoring wells within the budgetary limitations. The methodology also addresses the issue of redundancy, as it refines the existing monitoring network without losing much information of the network. The concept of uncertainty-based network design model is useful in various stages of a potentially contaminated site management such as delineation of contaminant plume and long-term monitoring of the remediation process.     

An investigation of heavy metal and migration through groundwater from the landfill area of Eskisehir in Turkey

This paper was conducted in order to determine the groundwater and soil pollution within and around the landfill of Eskisehir, Turkey. In this paper, mud, leachate and groundwater samples were collected seasonally a year from near Eskisehir landfill-site to investigate the possible impact of leachate which affects soil and groundwater quality. Concentrations of various heavy metals (Fe, Cu, Zn, Mn, Co, Pb, Cr, Ni and Mo) were determined in mud, leachate and groundwater samples. In addition, the heavy metal transportation infiltrated from landfill through a porous medium into the groundwater was modelled in order to determine the potential groundwater pollution caused by the leachate of the landfill. The modelling of the contaminant transportation was carried out by using a multiflow computer programme which simulates the distribution of heavy metal concentrations. As a result of this study, the distribution of the contaminant concentration was modelled and determined with respect to time and distance. Hence, the contaminant concentrations were determined at any time interval according to distance. The heavy metal contamination in groundwater does not affect the wells found at far points from the source in a short time, e.g. 10, 20 and 30 days according to the obtained experimental results. When the time intervals extended more than 1 year, heavy metal concentrations decrease with distance but the concentration of the contamination increases when it gets closer to the pollution source. In this study, the potential contamination of groundwater was effectively estimated.     

Conjunctive Vadose and Saturated Zone Monitoring for Subsurface Contamination

A comprehensive subsurface monitoring program should include contaminant detectors in both the vadose and saturated zones. Vadose zone detectors can provide an early warning of an impending groundwater contamination problem, and also yield information relevant to placing groundwater monitoring wells. Moisture probes, gas monitoring wells, and pore-liquid samplers deployed in the vadose zone complement groundwater detection wells. The objective(s) of a monitoring program, spatial-scales, and hydrogeology are important considerations for designing subsurface monitoring networks. Often, these networks are used to detect potential releases or characterize existing contamination beneath land-based waste storage facilities. A case study in Santa Barbara, California, U.S.A., illustrates the utility of vadose zone monitoring in characterizing a gasoline contamination problem and guiding the placement of groundwater monitoring wells.     

Estimating contaminant attenuation half-lives in alluvial groundwater systems

One aspect of describing contamination in an alluvial aquifer is estimating changes in concentrations over time. A variety of statistical methods are available for assessing trends in contaminant concentrations. We present a method that extends trend analysis to include estimating the coefficients for the exponential decay equation and calculating contaminant attenuation half-lives. The conceptual model for this approach assumes that the rate of decline is proportional to the contaminant concentration in an aquifer. Consequently, the amount of time to remove a unit quantity of the contaminant inventory from an aquifer lengthens as the concentration decreases. Support for this conceptual model is demonstrated empirically with log-transformed time series of contaminant data. Equations are provided for calculating system attenuation half-lives for non-radioactive contaminants. For radioactive contaminants, the system attenuation half-life is partitioned into the intrinsic radioactive decay and the concentration reduction caused by aquifer processes. Examples are presented that provide the details of this approach. In addition to gaining an understanding of aquifer characteristics and changes in constituent concentrations, this method can be used to assess compliance with regulatory standards and to estimate the time to compliance when natural attenuation is being considered as a remediation strategy. A special application of this method is also provided that estimates the half-life of the residence time for groundwater in the aquifer by estimating the half life for a conservative contaminant that is no longer being released into the aquifer. Finally, the ratio of the half-life for groundwater residence time to the attenuation half-life for a contaminant is discussed as a system-scale retardation factor which can be used in analytical and numerical modeling.     

A novel high-frequency groundwater quality monitoring system

High-frequency, long-term monitoring of water quality has revolutionized the study of surface waters in recent years. However, application of these techniques to groundwater has been limited by the ability to remotely pump and analyze groundwater. This paper describes a novel autonomous groundwater quality monitoring system which samples multiple wells to evaluate temporal changes and identify trends in groundwater chemistry. The system, deployed near Fresno, California, USA, collects and transmits high-frequency data, including water temperature, specific conductance, pH, dissolved oxygen, and nitrate, from supply and monitoring wells, in real-time. The system consists of a water quality sonde and optical nitrate sensor, manifold, submersible three-phase pump, variable frequency drive, data collection platform, solar panels, and rechargeable battery bank. The manifold directs water from three wells to a single set of sensors, thereby reducing setup and operation costs associated with multi-sensor networks. Sampling multiple wells at high frequency for several years provided a means of monitoring the vertical distribution and transport of solutes in the aquifer. Initial results show short period variability of nitrate, specific conductivity, and dissolved oxygen in the shallow aquifer, while the deeper portion of the aquifer remains unchanged—observations that may be missed with traditional discrete sampling approaches. In this aquifer system, nitrate and specific conductance are increasing in the shallow aquifer, while invariant changes in deep groundwater chemistry likely reflect relatively slow groundwater flow. In contrast, systems with high groundwater velocity, such as karst aquifers, have been shown to exhibit higher-frequency groundwater chemistry changes. The stability of the deeper aquifer over the monitoring period was leveraged to develop estimates of measurement system uncertainty, which were typically lower than the manufacturer’s stated specifications, enabling the identification of subtle variability in water chemistry that may have otherwise been missed.     

A statistical F test for the natural attenuation of contaminants in groundwater

Natural attenuation (NA) is a catchall explanation for the overall decay and slowed movement of the contaminants in the subsurface. One direct support to NA is to demonstrate that contaminant concentrations from monitoring wells located near the source are decreasing over time. The decrease is summarily expressed in terms of an apparent half-life that is determinedfrom the line best fitting the observed log-transformed concentration data and time. This simple (time-only) decay modelassumes other factors are invariant, and so is flawed when complicating factors – such as a fluctuating water table – are present. A history of the water-table fluctuation can track changes in important NA factors like recharge, groundwater flow direction and velocity, as well as other non-NA factors like volume of water in and purged from the well before a sample is collected. When the trend in the concentrations is better associated with the water table rising or falling, any conclusionabout degradation rate may be premature. We develop simple regressions to predict contaminant concentration (c) by two line models: one involving time (c c(t)), and another involving groundwater elevation (c c(z)). We develop a third model that includesboth factors (c c(t, z)). Using an F-test to compare the fits to the models, we determine which modelis statistically better in explaining the observed concentrations. We applied the test to sites where benzene degradation rates had previously been estimated. The F-testcan be used to determine the suitability of applying non-parametric statistics, like the Mann-Kendall, to the concentration data, because the result from the F-test canindicate instability of the contaminant plume that may bemasked when the water table fluctuates.     

Analysis and evaluation of nitrate levels in groundwater at Al-Hashimiya area, Jordan

Water with high nitrate concentration (NO₃ ⁻) is unfit for human consumption, especially when its concentration exceeded the threshold limit (50 mg/l) recommended by the health authorities such as the World Health Organization (WHO). In Jordan, there is a great concern for determination and monitoring organic and inorganic pollutants that may reach groundwater. Nitrate is highly mobile and present in domestic, agricultural and industrial waste in Jordan, and thus this study focused initially on nitrate as both a contaminant of concern and as an indicator of potential groundwater contamination. The present study determined the extent of nitrate contamination in groundwater in the study area and examined the likely sources of NO₃ ⁻. A total of 248 groundwater samples were collected from 16 wells in different sites of Al-Hashimiya area, Zerqa Governorate, Jordan, and investigated for NO₃ ⁻ concentrations. Moreover, measurements of temperature, electrical conductivity and pH were carried out in the field. Analysis was carried out according to the methods described by the American Public Health Association (APHA). Results showed that there was a dramatic increasing in NO₃ ⁻ concentrations from the year 2001 to 2006 for some selected wells in the present study. NO₃ ⁻ concentration in 2006 was ranged from 10 to 330 mg/l with an average of 77 mg/l. Overall, groundwater had elevated nitrate concentration with 92% of the samples containing more than 20 mg/l NO₃ ⁻, indicating the influence of human activities. This study has shown that there is a strong correlation between the nitrate concentration and the wastewater effluents as a source of pollution.     

A Method for Designing Upgradient Groundwater Monitoring Networks

A graphical heuristic was devised for locating upgradient groundwater monitoring wells near landfills. Utilizing computer-simulated contaminant plumes, the heuristic considers the direction of groundwater flow relative to the shape of a landfill, the location of the downgradient migration boundary used for configuring detection wells, and uniformity of spatial coverage. The heuristic positions upgradient wells far enough from a landfill to avoid contamination, but close enough to measure ambient water quality near the landfill. It can be adapted to nonuniform flow fields, nonlinear migration boundaries, and irregularly shaped landfills. An application to a rectangular landfill, oriented at various angles to the direction of groundwater flow, demonstrates the utility of the approach.