Delineation Of Contaminant Plumes Research Articles

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 integrative method to quantify contaminant fluxes in the groundwater of urban areas

Groundwater in urban areas is often contaminated and emission sources can be located close to groundwater wells. The delineation of contaminant plumes is difficult because of the various potential emission sources. Thus, detection, quantification and remediation of contaminated sites in a city need more integrative approaches. A method has been developed which allows quantification of mass fluxes of contaminants in groundwater between control planes. Budget zones along the flow path are defined to calculate a contaminant balance and to quantitatively reveal input areas. Concentrations and water budgets are used to calculate mass balances for each contaminant. The city of Darmstadt (Germany) was chosen to evaluate the method. The groundwater monitoring wells (GMWs) upstream of the city showed anthropogenically superposed background values for all naturally occurring inorganic species. The contaminant concentrations increased in the city (probably influenced by road traffic, gas stations, leaking sewers, etc.). Downstream from the city, concentrations usually decreased. Organic compounds typical for urban environments, such as polycyclic aromatic hydrocarbons (PAH), locally exceeded drinking water regulations. In GMWs with high concentrations of organic contaminants in the city or downstream from industrial areas, a significant increase in Fe2+ and Mn2+ could be observed, in some cases coinciding with a decrease in NO3, SO4 and an increase in NH4. For typical urban contaminants, a positive budget was calculated in several zones, which shows that emissions from urban sources are reaching the groundwater. Negative budgets can be mainly explained with diving plumes and degradation. The input calculated from the individual budget zones is usually higher than the input estimated from urban emissions. Differences between the calculated and the estimated input can be explained with additional sources or (bio)degradation processes. It was confirmed that high concentrations of contaminants do not necessarily correlate with high fluxes. Integrative approaches can reveal areas of high contaminant mass input. The results obtained with the new method are plausible compared to the land use and the estimated urban input. The concentration pattern of Fe2+, Mn2+, SO4 and NO3 is partly due to natural processes, triggered by the degradation of organic matter and organic contaminants. Since this method includes mass balances and flux calculations, avoiding an overestimation of single point contaminant concentration, it is recommended to use this approach to quantify groundwater contamination in cities. Further research is focusing on the role of urban soils as natural reservoirs for the input of contaminants.

Imaging lateral groundwater flow in the shallow subsurface using stochastic temperature fields

Although temperature has often been used as an indication of vertical groundwater movement, its usefulness for identifying horizontal fluid flow has been limited by the difficulty of obtaining sufficient data to draw defensible conclusions. Here we use stochastic simulation to develop a high-resolution image of fluid temperatures in the shallow subsurface at Borax Lake, Oregon. The temperature field inferred from the geostatistical simulations clearly shows geothermal fluids discharging from a group of fault-controlled hydrothermal springs, moving laterally through the subsurface, and mixing with shallow subsurface flow originating from nearby Borax Lake. This interpretation of the data is supported by independent geochemical and isotopic evidence, which show a simple mixing trend between Borax Lake water and discharge from the thermal springs. It is generally agreed that stochastic simulation can be a useful tool for extracting information from complex and/or noisy data and, although not appropriate in all situations, geostatistical analysis may provide good definition of flow paths in the shallow subsurface. Although stochastic imaging techniques are well known in problems involving transport of species, e.g. delineation of contaminant plumes from soil gas survey data, we are unaware of previous applications to the transport of thermal energy for the purpose of inferring shallow groundwater flow.