Abstract:Trace metal clean sampling and analysis techniques were used to examine the temporal patterns of Hg, Cu, and Zn concentrations in shallow ground water, and the relationships between metal concentrations in ground water and in a hydrologically connected river. Hg, Cu, and Zn concentrations in ground water ranged from 0.07 to 4.6 ng L-1, 0.07 to 3.10 micrograms L-1, and 0.17 to 2.18 micrograms L-1, respectively. There was no apparent seasonal pattern in any of the metal concentrations. Filtrable Hg, Cu, and Zn c… Show more
“…These results indicate minimum seasonal variability of data. The lack of a seasonal pattern in heavy metal concentrations in other aquifers has also been noted in previous studies (Zelewski et al 2001).…”
Section: Data Preparationsupporting
confidence: 83%
“…Although data for heavy metals are available from 1975 through 2000, >95% of the samples are in the period between 1989 and 2000. Unreliability of heavy metal data collected prior to 1990 across the United States has been well studied and explained by Zelewski et al (2001). The major reason for this conclusion is the lack of adherence to clean sampling techniques prior to 1990.…”
A methodology using ordinal logistic regression is proposed to predict the probability of occurrence of heavy metals in ground water. The predicted probabilities are defined with reference to the background concentration and the maximum contaminant level. The model is able to predict the occurrence due to different influencing variables such as the land use, soil hydrologic group (SHG), and surface elevation. The methodology was applied to the Sumas-Blaine Aquifer located in Washington State to predict the occurrence of five heavy metals. The influencing variables considered were (1) SHG; (2) land use; (3) elevation; (4) clay content; (5) hydraulic conductivity; and (6) well depth. The predicted probabilities were in agreement with the observed probabilities under existing conditions. The results showed that aquifer vulnerability to each heavy metal was related to different sets of influencing variables. However, all heavy metals had a strong influence from land use and SHG. The model results also provided good insight into the influence of various hydrogeochemical factors and land uses on the presence of each heavy metal. A simple economic analysis was proposed and demonstrated to evaluate the cost effects of changing the land use on heavy metal occurrence.
“…These results indicate minimum seasonal variability of data. The lack of a seasonal pattern in heavy metal concentrations in other aquifers has also been noted in previous studies (Zelewski et al 2001).…”
Section: Data Preparationsupporting
confidence: 83%
“…Although data for heavy metals are available from 1975 through 2000, >95% of the samples are in the period between 1989 and 2000. Unreliability of heavy metal data collected prior to 1990 across the United States has been well studied and explained by Zelewski et al (2001). The major reason for this conclusion is the lack of adherence to clean sampling techniques prior to 1990.…”
A methodology using ordinal logistic regression is proposed to predict the probability of occurrence of heavy metals in ground water. The predicted probabilities are defined with reference to the background concentration and the maximum contaminant level. The model is able to predict the occurrence due to different influencing variables such as the land use, soil hydrologic group (SHG), and surface elevation. The methodology was applied to the Sumas-Blaine Aquifer located in Washington State to predict the occurrence of five heavy metals. The influencing variables considered were (1) SHG; (2) land use; (3) elevation; (4) clay content; (5) hydraulic conductivity; and (6) well depth. The predicted probabilities were in agreement with the observed probabilities under existing conditions. The results showed that aquifer vulnerability to each heavy metal was related to different sets of influencing variables. However, all heavy metals had a strong influence from land use and SHG. The model results also provided good insight into the influence of various hydrogeochemical factors and land uses on the presence of each heavy metal. A simple economic analysis was proposed and demonstrated to evaluate the cost effects of changing the land use on heavy metal occurrence.
“…These transition zones react very sensitive due to a change of geochemical conditions, which can effect a remobilization of trace elements with a risk for surface water and groundwater contamination (e.g. Balistrieri et al 1994;Caetano et al 2003;Kelly et al 2005;Selim and Sparks 2001;Zelewski et al 2001).…”
The occurrence of trace metals was studied at the interface between groundwater and the drainage system of a large floodplain in NE Germany, the Oderbruch region. Depending on the predominant hydraulic connectivity between groundwater and the drainage channels, the geochemical environment creates a high variability in the accumulation of Fe, Mn, Cd, Zn, Cu, and As. The mobility of the trace metals depends on spatial variable redox transition zones which act as geochemical barriers between the anaerobe aquifer and the oxic surface waters. In drainage ditches with high exchange flow between groundwater and surface water the transition zone is small and unstable with a low retention potential for trace metals. Decreasing hydraulic gradients and respectively decreasing base flow cause the change for an extensive transition zone with increasing trace metal accumulation in the channel sediments. The accumulation is mainly controlled by oxidation and degassing of CO 2 . In the streambed sediments of channels which periodically run dry an effective chemical barrier can be observed. This Fe dominated oxic horizon controls the accumulation of Mn [ Cu [ As [ Zn [ Cd, which are mainly associated with fresh, amorphous Fe oxyhydroxides. The chemical barriers can be instable and reversible. Therefore, water management decisions are discussed which stabilize the barriers by controlling aquifer-channel exchange rates, channel oxygen content and surface water levels.
“…Moreover, groundwater sampling normally takes only 10 -15 min, during which any contamination of the water sample by released metal ions is probably very small with respect to the groundwater composition; in addition the sampler is flushed, as it is lowered open, to the sampling depth. Trace metal clean sampling and analysis techniques are described in detail in Zelewski et al (2001). Given these guidelines and the low concentrations recorded by the test, it is concluded that despite some metal release, these concentrations are insignificant compared with the observed concentrations in the groundwater.…”
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