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Design of Optimal, Reliable Plume Capture Schemes: Application to the Gloucester Landfill Ground‐Water Contamination Problem
Abstract
A ground-water quality management model is applied to the Gloucester Landfill site, located near Ottawa, Canada, to examine the effectiveness of various single-well pumping schemes for the capture of dissolved contaminants. Deterministic and stochastic design analyses are conducted through ground-water solute transport modeling of the site. The purpose of the modeling analysis is to develop contaminant capture designs that both require minimum pumping rates and possess high probabilities of success.
Optimization based upon deterministic simulation indicates that a well located at the front of the plume would effect plume capture and require the lowest pumping rate. However, a smaller total volume of water could be pumped and still effect plume capture if the well were located at the center of the plume and pumped at a higher rate for a shorter time. Stochastic optimization analyses are used to overdesign the pumping rates so that possible design error is overcome. The analyses indicate that design reliability may be increased from 50 to 90 percent by pumping an additional 18 percent at the front or 27 percent at the center of the plume. These pumping overdesign factors are the first such values calculated using the stochastic optimization approach applied to a field site.
... Physical heterogeneities, in terms of spatially variable hydraulic conductivity and porosity, have been incorporated into aquifer remediation design studies (Gailey and Gorelick 1993;Lee and Kitanidis 1996;McKinney and Lin 1996;Wang and Zheng 1997). On a whole Monitored natural attenuation of contaminated groundwater is increasingly being considered as a possible remedial solution, particularly since the alternative remedial options can be very expensive. ...
... In the field, these non-ideal conditions may locally hinder or enhance the transport of contaminants. Physical heterogeneities, in terms of spatially variable hydraulic conductivity and porosity, have been incorporated into aquifer remediation design studies (Wang and Zheng 1997;Lee and Kitanidis, 1996;McKinney and Lin 1996;Gailey and Gorelick 1993). Heterogeneity in chemical properties, such as the distribution coefficient, is also observed at the field scale (Mackay et al. 1986;MacIntyre et al. 1991); yet chemical variability is widely neglected during remediation design. ...
... The most common methods for including uncertainty in the optimal design of groundwater systems include those which incorporate the uncertainty in the optimization model and those which require multiple realizations (Aly and Peralta 1999). Examples of optimization techniques that use knowledge about the probability distributions in the optimization model includes chance constrained optimization (Bear and Sun 1998;Gailey and Gorelick 1993;Sawyer and Lin 1998;Wagner and Gorelick 1987;Wagner 1999) and robust optimization (Watkins and McKinney 1995). The robust GA approach (Chan Hilton and Culver 2000b) that takes into account the uncertainty of hydraulic conductivity values is evaluated for determining the best remediation design possible. ...
Natural attenuation (NA) has recently emerged as a viable groundwater remediation technology at various petroleum contaminated sites in the United States. NA is a passive remedial approach that depends upon natural processes to degrade and dissipate petroleum constituents in soil and groundwater. Such natural processes include advection, sorption, diffusion, dispersion and biodegradation. Due to heterogeneous nature of most contaminated groundwater (GW) sites there exists uncertainty in subsurface system parameters. This study evaluates sensitivities of parameter uncertainty on the performance and design of remediation plans that use natural attenuation with active remediation. This analysis is completed by using an optimization tool combined a GW flow and contaminant transport simulation model. The Enhanced multi-objective Robust Genetic Algorithm (EMRGA) is the optimization tool used here for the simultaneous optimization of multiple conflicting objectives under parameter uncertainty.
The multi-objective optimization problem is to minimize the cost of the natural attenuation-active remediation system and minimize the maximum contaminant concentration at the end of the five-year remediation period under parameter uncertainty and heterogeneity. The optimization model is applied to a problem based on a field site, contaminated with benzene located in Eglin Air Force Base, Florida. The uncertain parameters considered in this study are hydraulic conductivity (K), hydraulic gradient (dH/dx) and first-order benzene decay rate (k) benzene degradation. The optimization problem is solved using fifteen cases with different combinations of uncertain parameters and degrees of uncertainty. In addition, selected designs from the evolved Pareto-optimal sets (trade-off curves) were further evaluated by Monte Carlo analysis.
Results show that as uncertainty in hydraulic conductivity increased there was increased difficulty in lowering contamination levels as fewer wells were used at lower pumping rates. For uncertain parameters hydraulic gradient and decay rate the highly uncertain scenarios produced designs employing more wells at higher pumping rates, thus achieving minimum concentration values. Cases with less uncertainty in hydraulic conductivity produced high performing remedial designs with higher remediation reliability and higher clean up levels. On the other hand, the designs evolved by the EMRGA had lower reliabilities and lower clean up levels for cases having low variations of hydraulic gradient and first-order decay rate. Also, active remediation in the initial stages of the total remediation period emerged as a feasible and most cost-effective solution for the multi-objective optimization problem. Overall, uncertainty in hydraulic conductivity had the most significant impact on remediation reliability of the designs. Results indicate a threshold pumping index value of 430 m3/day/well over which a remediation design was almost certain in achieving 100% reliability. Effects of multiple parameter uncertainty were highly pronounced for cases involving a wider range of hydraulic conductivity values. For these cases the remediation costs dropped to 5.7% and 31.2% with increasing range of hydraulic gradient and heterogeneous decay rate respectively while the Cmax values increased by 217% and 307% for increasing range of hydraulic gradient and heterogeneous decay rate respectively. In general the EMRGA successfully identified Pareto-optimal remedial designs having a wide range of objective values, which satisfied both the conflicting objectives focused in this study. Based on these conflicting objectives (Remediation cost and Maximum residual concentration) seven highly reliable remedial options are identified. In general these designs used just two extraction wells (located just down-gradient from the contaminant plume) at pumping indices between 350 to 450 m3/day/well. These seven remediation plans are embedded in a decision tree to aid the remediation designer in getting an overview of possible groundwater remediation design requirements at the OU-1 site.
... The pollution threat becomes more important in regions where fractures or weak zones are present either just beneath the landfill or in its surrounding area. The impact of landfill sites on groundwater has been attempted by different workers in different perspectives (Baedecker and Apgar 1984; Flyhammar 1995; Gaily and Gorelick 1993; Kjeldsen et al. 1993; Meju 1993; Newell et al. 1990; Robinson et al. 1982; Tejero et al. 1993; Vendrame and Pinho 1997). Most of the works cited above are focused on assessing the pollution risk to groundwater due to landfill by using invasive as well as non-invasive methods. ...
... To assess the impact of leachates on the groundwater , four general approaches/methodologies may be followed: (1) Experimental determination and estimation through mathematical modelling like NETPATH, MODFLOW (Laine et al. 1982; Laaksoharju et al. 1999) (2) Isotopic characterization of leachate and groundwater using 18 O, 3 H and 2 H (Barker et al. 1988; Vendrame and Pinho. 1997); (3) By comparing chemical nature of leachates with groundwater (Gaily and Gorelick 1993; Flyhammar 1995; Loizidon and Fig. 1 MSW generation rates both in terms of per day and per capita basis for the seven most important metro city of India ...
In present study focus has been given on estimating quality and toxicity of waste with respect to heavy metals and its impact on groundwater quality, using statistical and empirical relationships between different hydrochemical data, so that easy monitoring may be possible which in turn help the sustainable management of landfill site and municipal solid waste. Samples of solid waste, leachate and groundwater were analyzed to evaluate the impact of leachates on groundwater through the comparison of their hydrochemical nature. Results suggest the existence of an empirical relationship between some specific indicator parameters like heavy metals of all three above mentioned sample type. Further, K/Mg ratio also indicates three groundwater samples heavily impacted from leachate contamination. A good number of samples are also showing higher values for NO À 3 and Pb than that of World Health Organization (WHO) drinking water regulation. Predominance of Fe and Zn in both groundwater and solid waste samples may be due to metal plating industries in the area. Factor analysis is used as a tool to explain observed relation between numerous variables in term of simpler relation, which may help to deduce the strength of relation. Positive loading of most of the factors for heavy metal clearly shows landfill impact on ground water quality especially along the hydraulic gradient. Cluster analysis, further substantiates the impact of landfill. Two major groups of samples obtained from cluster analysis suggest that one group comprises samples that are severely under the influence of landfill and contaminated leachates along the groundwater flow direction while other assorted with samples without having such influence.
... Leachates from landfills and uncontrolled other is a result of the weathering of soils and base rocks industrial effluents disposal cause significant in the catchment [2]. The transport of aqueous phase deterioration in the water quality of many aquifers contaminants depends on the permeability of in-situ throughout the world [5,6]. rocks, the geological setting of the hydrogeology of the The rapid and growing agricultural, industrial and area. ...
This study investigates the natural and anthropogenic processes that influence the chemistry of groundwater within the Al-Mukalla Aquifer. Seventeen ground water samples were collected during August 2010 from different fields around Al-Mukalla City and analyzed for their physico-chemical constituents.
The groundwater in the study area falls under brackish water type (TDS > 1000 mg/l). The order of major cations are Ca > Mg > Na > K. The total hardness (TH) as CaCO3 ranges from 623 to 1168 mg/l. Water with TH greater than 80 mg/l cannot be used for domestic purposes. In the study area there are two groundwater facies: earth alkaline type water in the first nine wells and alkalis in the other wells. These groundwater types in the study
area is predominately indicative of the lithology of aquifer and the role of evaporation in the water composition as the loss by evaporation results in the transfer of salts from soil water to the soils. The saturation Indices of groundwater lie under saturation degrees except saturation Indices of dolomite. The study area has high to very high salinity with low sodium water types, which need adequate drainage to overcome salinity problems for
irrigation purposes.
Key words: Groundwater Quality (GWQ) Groundwater Al-Mukalla Yemen
... The interaction of groundwater with leachates results in formation of the solution that can effect on the organism of the particular ecosystem (Christensen et al., 2001). The influence of landfills on groundwater quality has been attempted to clarify by many researchers from different points of view (Robinson et al., 1982;Baedecker and Apgar, 1984;Newell et al., 1990;Kjeldsen et al., 1993;Meju, 1993;Gailey and Gorelick, 1993;Tejero et al., 1993;Flyhammar, 1995;Vendrame and Pinho, 1997;Christensen et al., 2001). The most frequent risk is analyzed by various experimental methods and/or are calculated through different mathematical models (Mor et al., 2006). ...
Waste landfills represent a global problem, which is more pronounced in developing countries because of the lack of resources to implement procedures that include separation and waste processing. The aim of this research was to analyze leachate and ground waters samples at the site, upstream and downstream from the landfill during different year seasons on a registered non-hazardous waste dump and to conduct physico-chemical and biological assays to determine potential risk for the ecosystem. Potential cytotoxic, prooxidative and mutagenic effects of leachates and water samples were evaluated on human laryngeal cell line (HEp2). Leachates collected at landfill site caused genotoxic effect and had a higher pH, chemical oxygen demand (COD), biochemical oxygen demand (BOD) and elevated concentrations of phosphorus, chloride, nitrogen compounds and sulphate. Genotoxicity of the leachate was increased in samples collected in dry and warm period of the year. These results are in accordance to the physico-chemical analysis which revealed that during summer period, because of intense degradation process at high temperatures increased concentrations of different chemicals can be found in leachate. Groundwater collected downstream and upstream from landfill did not show statistically significant (geno)toxic effect, irrespective of the sampling season. Chemical analysis revealed that all compounds in groundwater were below permitted values. Purification process at landfill is effective and compounds that reach groundwater do not represent a toxicological threat.
... Morgan et al. [1993] developed a mixed-integer chance-constrained programming and demonstrated its applicability to groundwater remediation problems. Chanceconstrained groundwater management models have also been applied to design groundwater hydraulics [Tiedman and and quality management strategies [Gailey and Gorelick, 1993]. Chan [1994] developed a partial infeasibility method for aquifer management. ...
Approximately 70% of the world's population lives in coastal areas, and the majority of these people depend on coastal aquifers for freshwater. The fragility of these aquifers and their sensitivity to human activity demand informed, competent management to guarantee their survival. Significant knowledge and new technologies related to the subject have accumulated in the last two decades, and a need has emerged for a comprehensive reference that gathers and disseminates crucial information to engineering practitioners and policymakers. Coastal Aquifer Management-Monitoring, Modeling, and Case Studies provides the most advanced and up-to-date methods and tools for the study and protection of coastal aquifers. This "how-to" volume presents a worldwide perspective with contributions from an international panel of experts. They address topics such as geohydrology, optimization, uncertainty analysis, and GIS as they relate to geographically-specific case studies; knowledge from these examples can be applied to aquifer issues in other regions. A companion CD-ROM supplements the text with programs and graphics, making this overview an indispensable reference and tool for the analysis of critical freshwater resources.
... Morgan et al. [1993] developed a mixed-integer chance-constrained programming and demonstrated its applicability to groundwater remediation problems. Chanceconstrained groundwater management models have also been applied to design groundwater hydraulics [Tiedman and and quality management strategies [Gailey and Gorelick, 1993]. Chan [1994] developed a partial infeasibility method for aquifer management. ...
... Quality of groundwater is affected by several factors such as climate, landscape, parent material of the area, land use and management at field or farm level. Other significant sources of groundwater contamination include uncontrolled hazardous waste sites, uncontrolled industrial effluents disposal and leachates from landfills ( Gailey and Gorelick, 1993;Kjeldsen et al., 1993). The fact that Dhamar city has been witnessing a substantial growth in agricultural, industrial and municipal activities imposes equivalent governmental and social efforts to protect groundwater against contamination. ...
p>Chemical and statistical regression analysis on groundwater at five fields (17 sampling wells) located in Dhamar city, the central highlands of Yemen, was carried out. Samples were collected from the ground water supplies (tube wells) during the year 2015. Physical parameters studied include (values between bracket s represents the measured mean values) temperature (T, 25°), total dissolved solids (TDS, 271.47), pH (7.5), and electrical conductivity (EC, 424.18). The chemical parameters investigated include total hardness (TH, 127.45), calcium (Ca2+, 32.89), magnesium (Mg2+, 11.03), bicarbonate (HCO3̶, 143.84), sulphate (SO42-, 143.84), sodium (Na+, 35.11), potassium (K+, 6.28) and Chloride (Cl ̵, 22.69). The results were compared with drinking water quality standards issued by Yemen standards for drinking water. Except for T° and pH, all other measured parameters fall below the minimum permissible limits. The correlation between various physio-chemical parameters of the studied water wells was performed using Principal Component Analysis (PCA) method. The obtained results show that all water samples are potable and can be safely used for both drinking and irrigation purposes. This comes in agreement with the public notion about groundwater of Dhamar Governorate. Sodium Absorption Ratio (SAR) values were calculated and found below 3 except for one drill. The results revealed that systematic calculations of correlation coefficients between water parameters and regression analysis provide a useful means for rapid monitoring of water quality.
International Journal of Environment
Volume-6, Issue-4, Sep-Nov 2017, page: 56-71</p
... Flyhammer (1995) examined leachate quality in several Swedish landfills and Sanchez et al. (1993) in Madrid. Similar studies were undertaken on leachate quality by Zheng et al. (1991) in New Jersey, Gailey and Gorelick (1993) in Canada and Blight (1995) in South Africa. ...
The fast development of field, data processing equipment and software has allowed the use of geophysical methods to an ever increasing range of applications. Hence nowadays it is much easier to conduct massive field surveys combining different methods, to obtain more accurate and denser data, so that complex modeling and interpretation at limited costs can be carried out. Landfills have been targeted by geophysical methods in order to investigate their environmental impacts. In fact, landfills have been the classic way to deposit domestic and industrial waste and have generated a large range of negative environmental impacts in groundwater and soils. These problems often persist even after the effective use of the landfills and subsequent recovery processes. Owing to their characteristics, landfills are difficult to access and because of the general lack of accurate information regarding the shape, nature of the refuse, history and development of the landfill, non-invasive, nondestructive methods and sometimes autonomous data acquisition devices must be used to monitor impacts and to investigate and prevent groundwater and soil contamination. Geophysical methods can be applied to investigate a wide range of aspects related with the assessment of the environmental impact of landfills. Problems such as geometry definition, geological settings, contamination plume location and monitoring investigation of internal structure and refuse zoning, determination of fluid flow direction and paths or the determination of sealing conditions and leakage may be more successfully evaluated if a carefully chosen geophysical survey is part of any investigation program. Because of the nature and complexity of the problems to investigate, only multidisciplinary approaches, involving geophysics, hydrochemical, hydrogeological and geological information, can provide meaningful results for a thorough assessment of the landfills impact on the environment. This work intends to demonstrate the application of geophysical methods in the investigation of the environmental impacts, as described above, of industrial and domestic landfills during their life time and after closure. Thus, several examples will be discussed illustrating the use of 2D, 3D and time lapse resistivity, electromagnetic, ground probing radar, self-potential, magnetic, gravity surveys and airborne thermal mapping. Most of the geophysical data will be presented and shortly discussed together with information from boreholes, geology, hydrogeology and hydrochemical data. As it will be shown, it is clear that only a judicious combination of methods and information from different nature can provide tools for the diagnosis and assessment of the impact of landfills in the environment, for the investigation of the best engineering solutions to remediate them and for the possible recovery of refuse with economic interest.
... Flyhammer (1995) examined leachate quality in several Swedish landfills and Sanchez et al. (1993) in Madrid. Similar studies were undertaken on leachate quality by Zheng et al. (1991) in New Jersey, Gailey and Gorelick (1993) in Canada and Blight (1995) in South Africa. ...
Landfill capping is a part of the post closure management protocol to minimise environmental problems such as leachate generation from landfills. The costs of conventional caps (e.g. clay caps, HDPE) and remediation of landfills have escalated over the last decade due to increase in the cost of capping material and with the introduction of stringent environmental laws. Research is therefore required to identify alternative capping systems that will not only minimise the costs, but also demonstrate increased environmental performance and community benefits. An alternative landfill capping technique known as 'Phytocapping' (establishment of plants on a layer of soil placed over the waste) was trialled at Lakes Creek Landfill, Rockhampton, Australia. This particular system checks on the seepage as well as allows preferential amount of water to promote biodegradation. In this technique, trees were used as 'bio-pumps' and soil cover as ?water storage?. The trees and soil together help minimise percolation of water into the landfill. Phytocaps also know as Evapotranspiration (ET) covers have been very successful in the US. This study is the first of its kind in Australia to evaluate the performance of 21 different tree species over two soil thicknesses (1400 mm and 700 mm). This paper reviews the critical points of the current knowledge and study conducted on phytocapping till date. The paper also reports the progress done on phytocapping till date; identifies the missing links and recommends further research that needs to be done to make this system more sustainable.
... With the development of computers, numerical approaches are appropriately used to simulate complex systems and flow field; numerical methods can also be used to delineate capture zones. Furthermore, numerical methods have been extensively used to delineate WHPAs (Ahlfeld and Sawyer 1990;Bair and Roadcap 1992;Ratzlaff et al.1992;Springer and Bair 1992;Gailey and Gorelick 1993;Gorelick et al. 1993;Tiedeman and Goreick 1993). ...
Karstic limestone formation in Lancun spring area is one of the most important drinking water resources for Taiyuan City in Shanxi Province. The mapping of drinking water-protected areas is an effective way to protect drinking water sources. In this study, Lancun spring area in Taiyuan City was considered as a case study. Considering geological deposition and hydrogeological characteristics of this area, the
stochastic idea was introduced to structural model establishment to determine the heterogeneity of karst groundwater system and clarify medium parameters. To analyze the influence of heterogeneity on groundwater flow simulation and wellhead-protected area delineation, homogeneous and stochastic hydrogeological parameter models were established and coupled with groundwater flow simulation models. Particle tracer analysis could be performed to determine capture zone. Results showed that stochastic methods could be used to generate a series of possible flow head field distributions and delineate a series of capture zones compared with homogeneous methods; thus, probability distribution was observed instead of a deterministic area. This result could provide a more scientific basis for the design and assessment of protective measures for wellhead areas in karst groundwater systems.
... Although hydraulic gradient control approaches using linear response matrices with linear or quadratic objective functions were in place by the mid-1980s [Atwood and Gorelick, 1985;Lefkoff and Gorelick, 1986; also see Gorelick et al., 1993], it was recognized that treating concentrations as constrained variables in optimized remediation schemes required solute transport simulations combined with nonlinear programming, NLP [Gorelick et al., 1984;Ahlfeld et al., 1988aAhlfeld et al., , 1988b. Optimization methods then addressed model uncertainty using chance constraints and the multiple realization approach as well as optimal tradeoff between data collection and remediation costs Gorelick, 1987, 1989;Tucciarelli and Pinder, 1991;Wagner et al., 1992;Chan, 1993] with applications to field problems in the U.S. and Canada [Tiedeman and Gorelick, 1993;Gailey and Gorelick, 1993]. ...
With rivers in critical regions already exploited to capacity throughout the world and groundwater overdraft as well as large-scale contamination occurring in many areas, we have entered an era in which multiple simultaneous stresses will drive water management. Increasingly, groundwater resources are taking a more prominent role in providing freshwater supplies. We discuss the competing fresh groundwater needs for human consumption, food production, energy, and the environment, as well as physical hazards, and conflicts due to transboundary overexploitation. During the past 50 years, groundwater management modeling has focused on combining simulation with optimization methods to inspect important problems ranging from contaminant remediation to agricultural irrigation management. The compound challenges now faced by water planners require a new generation of aquifer management models that address the broad impacts of global change on aquifer storage and depletion trajectory management, land subsidence, groundwater-dependent ecosystems, seawater intrusion, anthropogenic and geogenic contamination, supply vulnerability, and long-term sustainability. The scope of research efforts is only beginning to address complex interactions using multi-agent system models that are not readily formulated as optimization problems and that consider a suite of human behavioral responses. This article is protected by copyright. All rights reserved.
... CC programming determines the optimal decision variables that ensure maintaining the management constraints at a prescribed level of probability. In the groundwater community, CC programming is usually used to cope with model prediction uncertainty arising from uncertain model parameters (Tung 1986;Wagner and Gorelick 1987;Gailey and Gorelick 1993;Morgan et al. 1993;Chan 1994;Datta and Dhiman 1996;Sawyer and Lin 1998;Wagner 1999). In this study, the BMA method is applied to CC programming, and the BMA-CC framework is proposed to account for model parameter and geological structure uncertainties in the remediation design. ...
The groundwater community has widely recognized the model structure uncertainty as the major source of model uncertainty in groundwater modeling. Previous studies in the aquifer remediation design, however, rarely discuss the impact of the model structure uncertainty. This study combines the chance-constrained (CC) programming with the Bayesian model averaging (BMA) as a BMA-CC framework to assess the effect of model structure uncertainty in the remediation design. To investigate the impact of the model structure uncertainty on the remediation design, we compare the BMA-CC method with the traditional CC programming that only considers the model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from saltwater intrusion in the “1,500-foot” sand and the “1-700-foot” sand of the Baton Rouge area, southeastern Louisiana. To address the model structure uncertainty, we develop three conceptual groundwater models based on three different hydrostratigraphy structures. The results show that using the traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from connector wells is higher than the total pumpage of the protected public supply wells. While reducing injection rate can be achieved by reducing reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station is not economically attractive.
... This issue has attracted the attention of many researchers, which conducted research on the effect of leachate on the soil and groundwater quality (Loizidou and Kapetanios 1993, Fatta et al. 1997, Lee et al. 1997, Gailey and Gorelick 1993, Freyberg 1986, MacKay et al. 1986, and Sudicky et al. 1983. ...
The effect of the leachate migrating from the open dump solid waste landfill in Urmia City, Iran, on the surrounding soil and groundwater quality was investigated. Leachate samples were collected and analyzed for their physical and chemical properties and the results were compared with the reported values from other landfills in different countries. The comparison indicated that the values of pH, Electrical Conductance (EC), Sulphate, Zinc, Ammonium Nitrogen, Potassium, and Total Nitrogen, in Urmia landfill leachate exceed the reported values from other landfills. Soil samples were collected from two hand-excavated boreholes and were analyzed for their physical and chemical properties. Results showed that the soil samples have been contaminated due to the leachate migration downgradient of the landfill. Similar soil samples collected from the upgradient of the landfill, did not show any contamination due to leachate. Groundwater samples were collected from 16 wells located downstream of the landfill site, downgradient of the groundwater flow path. The samples were then analyzed for their physical and chemical properties and the results did not show any contamination due to leachate migration.
... Steward (1999) a horizontal well oriented perpendicularly to the direction of uniform flow required the smallest pumping rate to capture contaminated leachate. Many researchers have used numerical methods for the capture zone delineation and optimization (Ahlfeld and Sawyer, 1990;Bair and Roadcap, 1992;Ratzlaff et al., 1992;Springer and Bair, 1992;Gailey and Gorelick, 1993;Gorelick et al., 1993;Hoffman, 1993;Tiedeman and Goreick, 1993). Compared with numerical methods, analytical solutions handle problems in simpler conditions, and can directly calculate the parameters of capture zones. ...
... For both the 10-well and 90-well cases, achieving 90% reliability requires a pumping rate that is about 40% higher than that required for 50% reliability. Gailey and Gorelick' [1993] found that an 18 to 27% higher pumping rate was required to achieve the same level of overdesign for a field site in which both hydraulic head and contaminant concentration data were used for model calibration. ...
... CC programming determines the optimal decision variables that ensure maintaining the management constraints at a prescribed level of probability. In the groundwater community, CC programming is usually used to cope with model prediction uncertainty arising from uncertain model parameters (Tung 1986;Wagner and Gorelick 1987;Gailey and Gorelick 1993;Morgan et al. 1993;Chan 1994;Datta and Dhiman 1996;Sawyer and Lin 1998;Wagner 1999). In this study, the BMA method is applied to CC programming, and the BMA-CC framework is proposed to account for model parameter and geological structure uncertainties in the remediation design. ...
The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance-constrained (CC) programming with Bayesian model averaging (BMA) as a BMA-CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA-CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the ‘‘1500-foot’’ sand and the ‘‘1700-foot’’ sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive.
... The method of optimization can be employed in the capture zone analysis to find the best solution for determining the pumping rates and well locations [318,319], the minimum number of wells [320], or the number of wells and total pumping rates [307]. In addition, the optimization approaches can also be used in the analysis of capture zone delineation to examine the effectiveness of various single-well pumping scheme [321] or the most cost-effective strategies for hydraulic control of groundwater contamination [322,323]. Some studies have devoted to the assessment of the uncertainty about the delineation of well capture zones in heterogeneous aquifers. ...
... They demonstrate the applicability of the technique to groundwater remediation problems. Chanceconstrained ground-water management models have been applied to design ground water hydraulic [Tiedman and and ground-water quality [Gailey and Gorelick, 1993] management strategies. The chance-constrained method for remediation design has been demonstrated in " real world" systems. ...
A chance-constrained management model with an economic objective of coastal aquifers threatened by saltwater intrusion is developed. The model explicitly considers that the toe location of saltwater intrusion is a function of random variables such as physical parameters and boundary conditions. This model incorporates the quantity, quality and economic aspects of groundwater for sustainable use of the coastal aquifers and extends the existing deterministic model to stochastic one. The management objective allows for a plausible scenario for economic planned withdrawal and salinity control in coastal aquifers. The steady-state model simulates groundwater flow on a horizontal plane using sharp-interface analytical approach. This model is incorporated into a simple genetic algorithm (SGA) and chance constrained optimization. The chance constraint is divided into an expected value component and a stochastic one. Both the expected value and stochastic component were evaluated using the perturbation technique based on the second order Taylor series approximation. When the input physical parameters and boundary conditions are given as mean and standard deviation, the solutions, either the toe location of the saltwater wedge or the entire interface location, are predicted as a mean and standard deviation. The chance constrained programming method transforms the probabilistic model to a deterministic one and therefore facilitate the solution and reduces memory requirements and computational time. The management model is illustrated through a hypothetical unconfined coastal aquifer system. The results show that incorporating uncertainty into coastal aquifer optimization model using chance constraint programming coupled to SGA could be a practical method for making decisions on optimal pumping rates and scenario exploitation schemes.
... Morgan, et al. [1993] developed a mixed-integer chance-constrained programming and demonstrated its applicability to groundwater remediation problems. Chance-constrained groundwater management models have been applied to design groundwater hydraulics [Tiedman and Gorelick, 1993] and groundwater quality management strategies [Gailey and Gorelick, 1993]. Chan [1994] developed a partial infeasibility method for chance-constrained aquifer management that uses heuristic methods requiring the design reliability level to be satisfied for a training set consisting of multiple realizations of uncertain transmissivity. ...
EXTENDED ABSTRACT This paper develops a management model with the economic objective of maximizing the benefit from pumped freshwater volume and minimizing the utility cost in coastal aquifers threatened by saltwater intrusion. In a previous paper, "Pumping optimization in saltwater intruded aquifers by simple genetic algorithm—deterministic model" we assumed that the aquifer parameters, such as the hydraulic conductivity, the recharge rate, the freshwater outflow rate, etc., were known with certainty. In reality, however, information about aquifer parameters is often uncertain. The aquifer management model then needs to address the uncertainty issues and to provide solutions with respect to different reliability requirements. In the optimization model, the uncertainty is handled using chance-constrained optimization. Cases presented in the previous paper, particularly the Miami Beach (Spain) case, are re-examined. It is shown that the allowable pumping rate is decreased with increasing uncertainty level in the input and higher demand of confidence level in the prediction.
... Steward (1999) a horizontal well oriented perpendicularly to the direction of uniform flow required the smallest pumping rate to capture contaminated leachate. Many researchers have used numerical methods for the capture zone delineation and optimization (Ahlfeld and Sawyer, 1990;Bair and Roadcap, 1992;Ratzlaff et al., 1992;Springer and Bair, 1992;Gailey and Gorelick, 1993;Gorelick et al., 1993;Hoffman, 1993;Tiedeman and Goreick, 1993). Compared with numerical methods, analytical solutions handle problems in simpler conditions, and can directly calculate the parameters of capture zones. ...
We have presented analytical solutions for the capture zones of infinitely long horizontal wells in a homogeneous, confined aquifer with uniform flow. We find that the capture width enlarges and the bisector line of the capture zone moves toward the centerline of the aquifer when moving away from the well in the upstream direction for an arbitrary well location. The capture width and bisector line approach their ultimate width and position, respectively, after a distance of about 1.5 times the aquifer thickness. The ultimate capture width depends on the well discharge but not on the well location. We have plotted the ultimate bisector line position versus discharge for different well locations. Compared to the capture zone of a fully penetrating vertical well in an isotropic and laterally infinite aquifer, the ultimate capture width of a horizontal well is smaller than that of a vertical well given the same discharge rate per unit length. Furthermore, the relationship between the ultimate capture width and the well discharge rate is non-linear, in contrast to the linear behavior often observed in the vertical well capture zone.
... [3] Significant progress has been made in the development of simulation-optimization models for a wide variety of applications (e.g., see reviews of Gorelick [1983], Yeh [1992], and Ahlfeld and Heidari [1994]), and model uncertainty has been considered in the context of aquifer remediation design (e.g., see reviews of Wagner [1995] and Gorelick [1990Gorelick [ , 1997). Examples of stochastic simulation-optimization formulations for cases primarily involving aquifer remediation are the studies reported by Tung [1986], Wagner and Gorelick [1987], Gaily and Gorelick [1993], and Tiedeman and Gorelick [1993]. Stochastic optimization that includes a comprehensive sensitivity analysis has yet to be applied to groundwater resource allocation in hydroecologically sensitive regions. ...
A stochastic groundwater management model is formulated to account for prediction uncertainty when maximizing regionally distributed groundwater production yet obeying regulations to maintain the hydroecological balance in wetland areas. The water table elevation in sensitive wetland areas is lowered by the withdrawal of groundwater at supply wells. Substantial uncertainty exists because drawdowns depend on both the unknown spatial distribution of hydraulic conductivity and regional boundary conditions. Planning in the face of uncertain predictions of water table changes means that optimal production must be prudently reduced. A stochastic simulation-optimization formulation is developed that provides a robust water production plan. Prediction uncertainty is dealt with through stochastic simulation-optimization using a multiple-realization approach. On the basis of analyses involving solution of over 8 million aquifer models and 36,000 stochastic-optimization solutions, the nature and reliability of the optimal groundwater production scheme are inspected to determine the effects of uncertainty in spatially variable hydraulic conductivity, conditioning on local measurements, and the type of boundary conditions imposed in the nonlinear aquifer model. We propose a new measure to predict the expected reliability of meeting water level constraints in wetland areas. Monte Carlo simulations based on numerous optimal groundwater production schemes confirm that the expected reliability is a quantifiable function of the number of hydraulic conductivity realizations included in the stochastic-optimization formulation and the variance of log hydraulic conductivity.
... Models including concentrations in the regression have been developed by Strecker & Chu (1986), Wagner & Gorelick (1987), Gailey et al. (1991), Keidser & Rosbjerg (1991), and Weiss & Smith (1993), but, because of high computation time, applications mainly involve two-dimensional hypothetical cases. The few two-dimensional applications to field cases show, however, that including concentration data can help make the model calibration more certain (Gailey & Gorelick, 1993). The purpose of this paper is to (1) present a three-dimensional inverse model that can include concentrations of non-reactive solutes in the regression and (2) study how the concentrations affect parameter sensitivity, correlation and estimates, and measures of prediction uncertainty in a landfill case. ...
A three-dimensional inverse model using hydraulic heads and concentrations of non-reactive solutes is presented. Application to the Danish Grindsted Old Landfill is used to investigate how the concentration data affects estimates of horizontal and vertical hydraulic conductivity and longitudinal dispersivity as well as prediction uncertainty.
... These lowlying disposal sites, being devoid of a Leachate collection system, landfill gas monitoring and collection equipment, can hardly be called sanitary landfills and are the potential threat for water resources, especially groundwater. The pollution threat becomes more important in regions where fractures or weak zones are present either just beneath the landfill or in its surrounding area.The impact of landfill sites on groundwater has been attempted by different workers in different perspectives [17] [18] [19] [20] [21] [22] [23] [24] [25]. Most of the works cited above are focused on assessing the pollution risk to groundwater due to landfill by using invasive as well as non-invasive methods. ...
Physico-chemical and microbiological parameters were analyzed in leachate affected groundwater samples obtained at different locations viz. Bhanpor District, Union Carbide Area, Shivnagar, Mohali village, Peoples Group Colony and Nishatpora. during December, 2008 to May 2009 in order to assess the impact of leachate percolation on groundwater quality in District, Bhopal (M.P). Different physico-chemical parameters (pH, Total Dissolved Solids, Electrical Conductivity, Dissolved Oxygen, Free Carbon dioxide, Alkalinity, Chloride, Total Hardness and Biological Oxygen Demand) and bacteriological parameters (Total Coli form, Fecal Coli forms and Fecal Streptococci) were analyzed using standard methodology in each of the collected samples. Total dissolved solids (TDS), electrical conductivity (EC), and Na + exceeded the World Health Organization (WHO) tolerance levels for drinking water in 62.5%, 100%, and 37.5% of the groundwater samples respectively with pH and Fe exceeding WHO limits in 75% of the samples. Our results suggest the altered Physico-chemical and bacteriological parameters compared to the drinking water standards laid by Indian Council of Medical Research (ICMR) and World Health Organization (WHO). For example the electrical conductance was in the range of 980 – 1490 simens. A good number of samples are also showing significant amount of organic matter that provides nutrition for the growth and multiplication of microorganisms, thus not fit for drinking purpose. Thus it was concluded that most of the water samples were non-portable for human beings due to high concentration of one or the other parameter and some remedial measures are suggested to reduce further groundwater contamination via Leachate percolation, hence the present study demands for proper management of wastes in Bhopal.
... These lowlying disposal sites, being devoid of a Leachate collection system, landfill gas monitoring and collection equipment, can hardly be called sanitary landfills and are the potential threat for water resources, especially groundwater. The pollution threat becomes more important in regions where fractures or weak zones are present either just beneath the landfill or in its surrounding area.The impact of landfill sites on groundwater has been attempted by different workers in different perspectives [17] [18] [19] [20] [21] [22] [23] [24] [25]. Most of the works cited above are focused on assessing the pollution risk to groundwater due to landfill by using invasive as well as non-invasive methods. ...
Physico-chemical and microbiological parameters were analyzed in leachate affected groundwater samples
obtained at different locations viz. Bhanpor District, Union Carbide Area, Shivnagar, Mohali village, Peoples
Group Colony and Nishatpora. during December, 2008 to May 2009 in order to assess the impact of leachate
percolation on groundwater quality in District, Bhopal (M.P). Different physico-chemical parameters (pH, Total
Dissolved Solids, Electrical Conductivity, Dissolved Oxygen, Free Carbon dioxide, Alkalinity, Chloride, Total
Hardness and Biological Oxygen Demand) and bacteriological parameters (Total Coli form, Fecal Coli forms and
Fecal Streptococci) were analyzed using standard methodology in each of the collected samples. Total dissolved
solids (TDS), electrical conductivity (EC), and Na+ exceeded the World Health Organization (WHO) tolerance
levels for drinking water in 62.5%, 100%, and 37.5% of the groundwater samples respectively with pH and Fe
exceeding WHO limits in 75% of the samples. Our results suggest the altered Physico-chemical and bacteriological
parameters compared to the drinking water standards laid by Indian Council of Medical Research (ICMR) and
World Health Organization (WHO). For example the electrical conductance was in the range of 980 – 1490 simens.
A good number of samples are also showing significant amount of organic matter that provides nutrition for the
growth and multiplication of microorganisms, thus not fit for drinking purpose. Thus it was concluded that most of
the water samples were non-portable for human beings due to high concentration of one or the other parameter and
some remedial measures are suggested to reduce further groundwater contamination via Leachate percolation,
hence the present study demands for proper management of wastes in Bhopal.
Key Words: Landfill site, Leachate, Ground water Quality, Physiochemical characteristics, Bacteriological
parameters, Health risk.
... In spite of the work that has been done in this area and the huge number of theoretical studies available, its acceptance is, in practice, rather low. Still, scientific objectives are at the forefront of most real world applications [e.g., Marryott et al., 1993;Gailey and Gorelick, 1993;Zheng and Wang, 2002]. However, the use of mathematical optimization methods, rather than common trial-and-error approaches, for the selection of preferable management solutions has demonstrated an enormous potential to save costs by facilitating better technical system design. ...
The uniqueness and mathematical complexity of typical groundwater remediation or control problems involving numerical models necessitate appropriate solvers that find optimal solutions reliably and within reasonable computational time. The aim of this paper is to introduce an innovative evolutionary algorithm, the evolution strategies with covariance matrix adaptation and rank mu update (CMA-ES), used as an external solver in combination with groundwater transport models. A broad range of hypothetical pump-and-treat design problems is set up to derive recommendations for a robust CMA-ES configuration. One- and five-well cases are distinguished, for which both extraction rates and well positions have to be optimized in order to partly capture a contaminant plume. Intrinsic natural attenuation of the contaminant that emanates from a continuous source is considered. During this study, it is revealed that when pumping rates are minimized, well positions should be focused close to the source. In contrast, when contaminant mass extraction is minimized, positions distant from the source close to the plume fringes prove to be preferable.
Large quantities of waste from urban, municipal and industrial sectors are generated worldwide and disposed of in landfill sites. This can cause significant problems for groundwater as contamination can occur by infiltration recharge. The present research addresses a concern through an assessment of the pollution risk to the aquifer system at the Al-Akeeder site based on hydrogeological data and solid waste management. We consider the following risk elements: potential rates of waste input, leachate collection system, type of refuse, physical state of the refuse and its water content, monitoring system, disposal criteria and final cover. The environmental compatibility is estimated by applying an integrated method based on the depth of the water, which is the depth of the piezometric level relative to the ground surface (the SINTACS ratings relative to this parameter decreases with increasing depth), the effective infiltration, the unsaturated zone attenuation capacity, the soil attenuation capacity, the hydrological characteristics of the aquifer system, the hydraulic conductivity range of the aquifer, and the hydrologic role of the topographic surface average slope. The intrinsic vulnerability of the aquifer system within and around the study area is at a medium level. We suggest remediation measures to overcome the risks in the study area.
Based on groundwater, surface water quality standards, water environmental quality evaluation criteria suitable for landfill was established and the water quality index method was used for water quality evaluation of the landfill area through investigating the water environment and sampling in the study area. By analyzing the sub-division of the basin, the water quality features, the hydrogen and oxygen stability isotope characteristics, combined with the geological environment, three ways to water pollution caused by landfill were determined. By comparing massive components, micro components and organic micro components (polycyclic aromatic hydrocarbons, phthalate esters, BTEX), according to the degree of water quality higher than the background value for the leachate and the contaminated water points, a landfill groundwater pollution index system was tried to be established, as indicative choices for landfill groundwater pollution source identification and water pollution assessment.
During the twentieth century, the science of hydrogeology focused on establishing and refi ning fundamental principles and developing tools to study groundwater flow, well hydraulics, hydrogeochemistry, and contaminant hydrogeology. By the end of the century, the science evolved to assimilate principles and expertise from other disciplines, including surface water hydrology, chemistry, microbiology, geophysics, and ecology. In this chapter, we review seminal achievements in hydrogeology from 1963 to 2013, focusing on work by recipients of the Hydrogeology Division's O.E. Meinzer Award, one of the most prestigious and coveted awards in hydrogeology. The canon of 116 Meinzer Award papers, reports, and books refl ects the trends in hydrogeological research since the early 1960s. We also discuss other contributory papers by Meinzer awardees and related work by other scientists, and cover some research areas that have not been recognized by the Meinzer Award. We anticipate that the contributions of future Meinzer awardees will continue to document leadership in hydrogeology, perhaps in areas that have not yet been recognized by the award, including hydrogeoecology and hyporheic processes, submarine groundwater discharge, multilevel slug tests and hydraulic tomography, heat as a groundwater tracer, hydrogeophysics including remote sensing, and regional groundwater hydrology applied to issues of climate change.
The RCRA/Superfund GroundWater Forum is a group of scientists representing EPA's Regional Superfund Offices, committed to the identification and resolution of groundwater issues affecting the remediation of Superfund sites. Design of conventional groundwater extraction and injection (i.e., pump-and-treat) systems has been identified by the Forum as an issue of concern to decision makers. This issue paper focuses on design of conventional groundwater extraction and injection systems used in subsurface remediation. For further information contact Steve Acree (405) 436-8609 or Randall Ross (405) 436-8611 at the Subsurface Remediation and Protection
The groundwater community has widely recognized geological structure uncertainty as a major source of model structure uncertainty. Previous studies in aquifer remediation design, however, rarely discuss the impact of geological structure uncertainty. This study combines chance-constrained (CC) programming with Bayesian model averaging (BMA) as a BMA-CC framework to assess the impact of geological structure uncertainty in remediation design. To pursue this goal, the BMA-CC method is compared with traditional CC programming that only considers model parameter uncertainty. The BMA-CC method is employed to design a hydraulic barrier to protect public supply wells of the Government St. pump station from salt water intrusion in the “1500-foot” sand and the “1700-foot” sand of the Baton Rouge area, southeastern Louisiana. To address geological structure uncertainty, three groundwater models based on three different hydrostratigraphic architectures are developed. The results show that using traditional CC programming overestimates design reliability. The results also show that at least five additional connector wells are needed to achieve more than 90% design reliability level. The total amount of injected water from the connector wells is higher than the total pumpage of the protected public supply wells. While reducing the injection rate can be achieved by reducing the reliability level, the study finds that the hydraulic barrier design to protect the Government St. pump station may not be economically attractive.
A new simulation optimization model for groundwater-surface water
management identifies efficient strategies for meeting water demand and
controlling a regional water quality problem, while accounting for
varying availability of surface water supplies. Optimal values of model
variables are computed for ranges of surface water availability.
Expected groundwater levels are computed using a response function
approach, which incorporates a probability for each hydraulic stress.
Three objective functions are considered: (1) minimize need for
supplemental water, (2) minimize imposed water use reductions, and (3)
minimize changes from current pumping patterns. The model imposes
constraints on expected groundwater levels, expected hydraulic gradients
(surrogates for controlling contaminant transport), capacities of
pipeline and recharge facilities, and water demand requirements.
Capacity and demand constraints must be met every year for all possible
surface water conditions. Application to the Santa Clara-Calleguas Basin
in southern California indicates that a large quantity of supplemental
water or significant pumpage reductions, particularly in the lower
aquifer, may be required to control seawater intrusion with current
facilities. Supplemental water would be delivered directly to users
through pipelines and artificially recharged. Results also indicate that
the current artificial-recharge program has been valuable and that
construction of new artificial-recharge facilities might be beneficial.
It should be noted that local agencies are currently developing several
potential sources of supplemental water. Monte Carlo simulations yield
estimates of the reliability of gradient constraints in controlling
advective transport and the likelihood that water level constraints will
be violated.
A new optimization formulation for designing groundwater plume control systems is presented. The new formulation uses particle-tracking techniques in a two-step solution process. The two-step procedure is motivated by numerical and computational considerations; particle representation is defined to take advantage of specific properties and improve model convergence. The optimization formulation seeks the least cost control system that satisfies the two equivalent requirements that the contaminant plume be located within the capture zone (step 1) and that all particles representing contaminant solute travel to an extraction well (step 2). To date, optimization formulations for plume capture design have emphasized either hydraulic or concentration control; however, these formulations provide indirect representation of the plume control and containment problem. The model presented here explicitly represents the capture zone design problem using particle tracking and formalizes the design procedures used by many practitioners. Two example problems representing two- and three-dimensional flow systems are used to demonstrate the new advective control model. Hydraulic control formulations for the two problems are also developed, and designs are compared with those of the advective control model. Control systems resulting from the hydraulic control model are sensitive to constraint magnitude and location, highlighting the need for constraint calibration in order to best achieve design goals. Conversely, constraints in the new model directly represent the plume capture problem, and the model provides more efficient capture zone designs than the hydraulic control formulation.
The MultiScale ThermoHydrologic Model (MSTHM) is used in the total system performance assessment (TSPA) for the proposed nuclear-waste repository at Yucca Mountain. The MSTHM uses the Nonisothermal Unsaturated Flow and Transport (NUFT) code to represent thermal-hydrologic (TH) processes occurring at scales from a few tens of centimeters around individual waste packages and emplacement drifts (tunnels) all the way to the kilometer scale for heat flow through the mountain. The MSTHM is computationally more efficient than a monolithic 3-D TH model because it breaks the problem into smaller tractable pieces. An MSTHM simulation is constructed with NUFT-submodel calculations of various levels of coupled-process detail and scale, by superposing results of 3-D mountain- and drift-scale thermal submodels onto those of 2-D drift-scale TH submodels. The MSTHM was previously validated against an alternative (monolithic) 3-D TH model for a test problem at a scale smaller than the Yucca Mountain repository. Good agreement with the alternative model was obtained for temperature, relative humidity, and liquid saturation. A parallel-CPU version of NUFT handles much larger and more computationally demanding problems. This version is applied to an alternative (monolithic) 3-D "pillar-scale" TH model to simulate near-field and in-drift TH behavior along a full-scale (~1000-m long) emplacement drift. Results from the alternative model are compared to corresponding MSTHM results. Agreement with the alternative model builds confidence in the MSTHM applied at the scale of the Yucca Mountain repository. This study justifies key assumptions used in the MSTHM, such as that of negligible vapor flow along emplacement drifts. The pillar-scale model is also used to conduct a sensitivity study of parameters that control the magnitude of vapor flow and condensation along emplacement drifts. This work was performed under the auspices of the U.S. Department of Energy by University of California Lawrence Livermore National Laboratory under contract No. W-7405-Eng-48. Sandia is a multi-program laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.
This study was performed in order to evaluate the effect of the leachate from a landfill, in the Athens region (Greece), on the underground water of the surrounding area. A field study was performed and various samples were taken from various wells in a way that an area up to 3 km from the landfill was covered. The physical chemical characteristics of the underground water were measured. The experimental results indicate that the underground water has been greatly affected by the leachate, since most of the parameters examined show increased concentrations which are very much related to the leachate characteristics.
Computational cost is a critical issue for large-scale water-resource optimization under uncertainty, since time-intensive Monte Carlo simulations are often required to evaluate over multiple parameter realizations. This paper presents an efficient approach for replacing most Monte Carlo simulations with surrogate models within a noisy genetic algorithm (GA). The surrogates are trained to predict the posterior expectations online on the basis of stochastic decision theory, using Monte Carlo simulation results created during the GA run. The surrogates, which in this application are neural networks, are adaptively updated to improve their prediction performance as the search progresses. A Latin hypercube sampling method is used to efficiently sample parameters for the Monte Carlo simulation, and the sampling results are archived so that the estimate of posterior expectation can be iteratively improved in an efficient manner. In addition, the GA is modified to incorporate hypothesis tests in its selection operator to account for sampling noise. The method is applied to a field-scale groundwater remediation design case study, whereas the primary source of uncertainty stems from hydraulic conductivity values in the aquifers. The results show that the method identified more reliable and cost-effective solutions with 86-90% less computational effort than the purely physically based noisy GA approach.
Given the inherent uncertainty in groundwater management problems uncertainty in determining aquifer parameter values, identifying an optimal remediation strategy based on a deterministic description of the system may not yield an optimal and feasible design. This work builds on the robust genetic algorithm (GA) developed by Chan Hilton and Culver. The robust GA is a simulation-optimization approach which combines a GA with a contaminant fate and transport simulation model and a spatially correlated random field generator to identify tradeoffs between design cost and reliability while considering uncertainty of hydraulic conductivity values. This work evaluates the application of the robust GA to two formulations of a groundwater remediation design problem. In this problem, the objectives are to minimize the cost of the remediation design while satisfying water quality constraints and indirectly maximizing the reliability of the designs. This is done by identifying the location and pumping rates of a set of extraction well used for pump-and-treat remediation. The results show that the robust GA can successfully identify cost-effective and reliable designs in a computationally efficient manner. Future work involving the robust GA and planned modifications also are discussed in this paper.
The impacts of physical and chemical aquifer heterogeneities on optimal remediation design, costs, and time to compliance are investigated by linking a genetic algorithm with a contaminant transport simulation model. Physical and chemical aquifer heterogeneities were grouped into three levels as follows: (1) hydraulic conductivity (K) heterogeneity only; (2) combined heterogeneity of K and the distribution coefficient (Kd); and (3) combined heterogeneity of K, Kd, and the mass transfer rate (α). Various degrees of heterogeneity were considered, ranging from slightly heterogeneous to strongly heterogeneous. Impacts were evaluated using two different optimization models: the optimal design model and the time-to-compliance model. The first model focused on finding optimal aquifer remediation designs and costs under various heterogeneity conditions, and the second model optimized the time needed to meet the water quality goals for a fixed pumping schedule. Results show that the variability in the remediation costs and time to compliance for different realizations of a heterogeneous K-field increases as K-heterogeneity increases. Consideration of Kd- and α-heterogeneities results in different policies and costs compared to cases where sorption heterogeneity is neglected. In general, time to compliance increases for systems with both chemical and physical heterogeneity as compared to systems with only physical heterogeneity. The impact of α-heterogeneity on remediation strategies is most apparent when Kd-heterogeneity is high. Although an increase in K-heterogeneity decreases the impact of Kd- and α-heterogeneities on remediation costs and time to compliance, sorption heterogeneity could still significantly impact the performance of a remediation system, especially when sorption heterogeneity is high.
A decision framework is presented for assessing the value of ground-water sampling within the context of ground-water management under uncertainty. The framework couples two optimization models-a chance-constrained ground-water management model and an integer-programing sampling network design model-to identify optimal pumping and sampling strategies. The methodology consists of four steps: (1) The optimal ground-water management strategy for the present level of model uncertainty is determined using the chance-constrained management model; (2) for a specified data collection budget, the monitoring network design model identifies, prior to data collection, the sampling strategy that will minimize model uncertainty; (3) the optimal ground-water management strategy is recalculated on the basis of the projected model uncertainty after sampling; and (4) the worth of the monitoring strategy is assessed by comparing the value of the sample information-i.e., the projected reduction in management costs-with the cost of data collection. Steps 2-4 are repeated for a series of data collection budgets, producing a suite of management/monitoring alternatives, from which the best alternative can be selected. A hypothetical example demonstrates the methodology's ability to identify the ground-water sampling strategy with greatest net economic benefit for ground-water management.
This work explores the sensitivity of optimal remedial design policies and their associated costs to the residual constraint violation, which is the sum of any small violations in constraints that may occur over all points of interest. To evaluate the sensitivity, a genetic algorithm is used to solve two different groundwater remediation design problems: pump-and-treat using granular activated carbon and enhanced in situ bioremediation. The sensitivity to the residual violation is tested given a range of water quality goals and for static and dynamic cases. The range of residual constraint violations tested was small, so that in all cases greater than 98% of the remediation goal was reached. Nevertheless, it was found that the cost sensitivity to these small constraint relaxations was of the same magnitude as the cost sensitivity to changes in the ultimate water quality goal. The greatest sensitivity was seen for the lowest water quality goals. This work indicates that a remediation designer using optimization tools should consider the trade-offs in cost and performance that will occur depending upon one's approach to constraint enforcement.
Groundwater remediation optimization models were formulated using a statistical optimization methodology, chance-constrained programming (CCP), to account for uncertainty in the coefficients in the coefficients of the models. Several models were formulated that depended on which set of coefficients were considered uncertain. Such models were either mixed-integer linear programming models or mixed-integer nonlinear programming models. The CCP method transformed the probabilistic models to deterministic models. The deterministic models are easier to solve and use less computer memory and less storage space than probabilistic models. Results are presented that demonstrate the models formulated. The results showed that incorporating uncertainty into a groundwater optimization model using CCP could be a practical method for making decisions on well locations and pumping rates in groundwater remediation.
A capture zone of pumping well(s) in an aquifer with regional groundwater flow has been widely used to help design a pump-and-treat system for groundwater containment and remediation. Based on the theorem of potential and the principle of superposition, an analytical solution is derived in this study to calculate the capture zone for two arbitrarily located wells that pump water from a confined aquifer at an equal flow rate. The general two-well capture zone is composed of two sub-capture zones, one for each well. The shapes of the two sub-capture zones and their relative locations change with variations of the orientation and the separation of the two wells. The solution can be useful in verifying available numerical codes, as well as in solving practical field problems.
This paper is included in the Special Publication entitled 'Faulting, fault sealing and fluid flow in hydrocarbon reservoirs', edited by G.Jones, Q.J. Fisher and R.J. Knipe. Field measurements constrain the fluid flow characteristics of an analogue hydrocarbon reservoir in the faulted Entrada sandstone, Arches National Park, Utah. These data comprise maps of the geometry, inhomogeneous permeability, and porosity of fault zones, joints, and deformation bands in a region where two discontinuous normal faults overlap. Two-dimensional computer simulations of drainage of this analogue reservoir identify normal faults with highly permeable slip planes as the most important reservoir inhomogeneities. These faults compartmentalize fluid pressure over timespans greater than years while fluid can be drained on the kilometre scale along their highly permeable slip planes. Joints induce the second most important distortions of radial drawdown, influencing the timespans over which fault signatures are observed in pressure decline curves. The joints often extend to the boundaries of the reservoir. This also reduces the time before the rate of pressure decline accelerates due to boundary interaction. Zones of deformation bands less than 25 cm wide with a spacing ≥30 m have little effect on radial drawdown in our single phase fluid flow simulations. When drawdown spreads with time over the deformation structures in the analogue reservoir, the different structures simultaneously influence the change of pressure at the wellbore (pressure derivative). This temporal overlap prohibits an analysis of the effects of individual structures. Drawdown does not 'recover' to radial flow after an inhomogeneity is encountered.
In recent years, the aquifer simulation model has been combined with
techniques of optimization to address important groundwater management
problems. The combined simulation and optimization model accounts for
the complex behavior of the groundwater system and identifies the best
management strategy under consideration of the management objectives and
constraints. Simulation-optimization groundwater management models have
been developed for a variety of applications, such as restoration of
contaminated groundwater, control of aquifer hydraulics, allocation of
ground and surface water resources, and evaluation of groundwater
policies [see reviews by Gorelick, 1983, 1990; Yeh, 1992; Ahlfeld and
Heidari, 1994; Bredehoeft et al, 1994].Gorelick [1983] divides
groundwater management models into three categories: groundwater
hydraulic management, groundwater quality management, and groundwater
policy evaluation and allocation. This review focuses in detail on the
recent advances made in groundwater hydraulic and groundwater quality
management modeling, which encompasses most of the aquifer management
work done in the past four years. For a review of recent research in
groundwater policy evaluation and allocation, see Bredehoeft et al.
[1994].
Optimal extraction well locations and pumping rates are compared, based on a limited number of deterministic simulations, for multiple contaminant plumes exhibiting rate-limited, or nonequilibrium, mass transfer from a mobile to an immobile phase. This rate-limited mass transfer results in what we define as rate-limited, or nonequilibrium, transport. Two-dimensional, nonequilibrium solute transport simulation and optimization are used to study the simultaneous remediation of carbon tetrachloride, 1,2-dichloroethane and tetrahydrofuran that have been chromatographically separated during transport by groundwater. Minimum total pumping necessary for cleanup is compared for five different well geometries over remediation periods of 3 and 15 years. The sensitivity of these designs to first-order mass transfer rates is examined for equilibrium and for three levels of nonequilibrium transport. The key results of this particular study are that (1) classic contaminant capture at downgradient wells is a poor design for contaminant cleanup; (2) for effective design of multiple plume remediation, the transport characteristics of each contaminant must be considered; (3) if solute transport is limited by mass transfer from an immobile to a mobile phase, there is a minimum remediation time which cannot be reduced by adjustment of pumping rates or changing well locations; (4) the optimal locations and pumping rates of extraction wells are less sensitive to nonequilibrium transport for long-term remediation than for short-term remediation; and (5) competition between pumping wells may significantly affect the feasibility and efficiency of specific multiple-well cleanup designs. In addition, a method and a measurement are presented for evaluating the importance to remediation of rate-limited mass transfer.
A three-dimensional groundwater management model is developed for a shallow, unconfined sandy aquifer at a Superfund site at which a vinyl chloride plume is migrating toward Lake Michigan. We use nonlinear simulation-regression applied to a transient groundwater flow model to estimate parameter values and their uncertainties and use steady state flow path analyses to confirm the model's consistency with the location of contaminants. Parameter uncertainty is translated into flow model prediction uncertainty using a first-order Taylor series approximation. Optimal minimum-pumping strategies for steady state hydraulic containment of the plume are designed, and model prediction uncertainty is accounted for with stochastic programming. It is impossible to achieve a reliability level higher than 60% using only two pumping wells. For the 10-well case, pumping rates must increase about 40% to extend reliability from 50 to 90%. Monte Carlo analyses indicate that for the I 0-well 90% reliability formulation, the first-order method of propagating uncertainty results in a solution with accurate performance reliabilities. We find that the coefficient of variation in hydraulic gradient dictates whether the probabilistic constraints are obeyed. Comparison of the probabilistic constraint and "safety factor" approaches to overcoming model uncertainty reveals that the ability of probabilistic constraints to accommodate local variations in model prediction uncertainty is highly important. Postoptimization solute transport studies show that increased reliability levels for hydraulic containment do not necessarily translate into faster plume cleanup times.
In the present study, the effect of the leachate from the major landfill in northern Jordan, El-Akader on the ground-water was investigated. Various physical and chemical parameters were estimated, this includes pH, total hardness, electrical conductivity, and total dissolved solids for the physical parameters. The chemical parameters included are major cations, Ca+2, Mg+2, Na+, and K+. Major anions, HCO−3, NO−23, Cl−, and SO−24, major ions PO−34, and heavy metals, Pb, Fe, Mn, Cd, and Zn. The landfill leachate is a result of both solid waste and septage waste. El-Akader dump site receive both solid waste and waste-water, the average septage volume received at El-Akader site is 2305 m3day−1, and almost 217 tankers with the capacity of 11 m3discharge their loads at El-Akader site. The total volume of solid waste dumped into the site was estimated to about 400 tonnes day−1.An area almost 6 km from the landfill site following the ground-water flow direction towards the north-eastern wards was covered. The results showed that the landfill leachates constitute a serious threat to the local aquifers.
This study compares the contrasts stochastic optimization and decision analysis as frameworks for the design of remedial pump-and-treat systems in contaminated aquifers. It is shown that historically, there have been some fundamental philosophical differences in the way that the economic impact of risk is handled in the two frameworks. However, it is also shown that there have been great similarities between the two approaches. Possible ways for the combined use of these techniques are proposed.
To date optimization models for groundwater quality management give no assurance that water quality standards will be met. This is in part because they ignore errors in hydraulic heads, flows, and solute concentrations due to flow and transport model parameter uncertainty. Here parameter estimation and estimate uncertainties are explicitly incorporated into a model for the optimal design of an aquifer remediation scheme. Parameter uncertainty is incorporated into the decision-making process. Results show that remediation requirements can increase dramatically due to parameter uncertainty. Risk-averse design solutions automatically provide insurance by 'overdesigning' the strategy relative to the risk-neutral case. The approach is fairly general and is applicable to a variety of groundwater management problems. The influence on design solutions of the reliability level and verification of the underlying statistical assumptions of the first-order analysis are explored in a sensitivity study and 2000 Monte Carlo simulations, respectively. -from Authors
A simulation nonlinear multiple-regression methodology for estimating parameters that characterize the transport of contaminants is developed and demonstrated. Finite difference contaminant transport simulation is combined with a nonlinear weighted least squares multiple-regression procedure. The technique provides optimal parameter estimates Sand gives statistics for assessing the reliability of these estimates under certain general assumptions about the distributions of the random measurement errors. Monte Carlo analysis is used to estimate parameter reliability for a hypothetical homogeneous soil column for which concentration data contain large random measurement errors. The value of data collected spatially versus data collected temporally was investigated for estimation of velocity, dispersion coefficient, effective porosity, first-order decay rate, and zero-order production. The use of spatial data gave estimates that were 2-3 times more reliable than estimates based on temporal data for all parame-ters except velocity. Comparison of estimated linear and nonlinear confidence intervals based upon Monte Carlo analysis showed that the linear approximation is poor for dispersion coefficient and zero-order production coefficient when data are collected over time. In addition, examples demonstrate transport parameter estimation for two real one-dimensional systems. First, the longitudinal dispersivity and effective porosity of an unsaturated soil are estimated using laboratory column data. We compare the reliability of estimates based upon data from individual laboratory experiments versus estimates based upon pooled data from several experiments. Second, the simulation nonlinear regression procedure is extended to include an additional governing equation that describes delayed storage during contami-nant transport. The model is applied to analyze the trends, variability, and interrelationship of parame-ters in a mouvtain stream in northern California.
A simulation-management methodology is demonstrated for the rehabilitation of aquifers that have been subjected to chemical contamination. Finite element groundwater flow and contaminant transport simulation are combined with nonlinear optimization. The model is capable of determining well lo-cations plus pumping and injection rates for groundwater quality control. Examples demonstrate linear or nonlinear objective functions subject to linear and nonlinear simulation and water management constraints. Restrictions can be placed on hydraulic heads, stresses, and gradients, in addition to con-taminant concentrations and fluxes. These restrictions can be distributed over space and time. Three design strategies are demonstrated for an aquifer that is polluted by a constant contaminant source: they are pumping for contaminant removal, water injection for in-ground dilution, and a pumping, treatment, and injection cycle. A transient model designs either contaminant plume interception or in-ground dilution so that water quality standards are met. The method is not limited to these cases. It is generally applicable to the optimization of many types of distributed parameter systems.
To date optimization models for groundwater quality management give no assurance that water quality standards will be met. This is in part because they ignore errors in hydraulic heads, flows, and solute concentrations due to flow and transport model parameter uncertainty. Here we explicitly incor-porate parameter estimation and estimate uncertainties into a model for the optimal design of an aquifer remediation scheme. Parameter uncertainty is incorporated into the decision-making process. The objec-tive is to identify the best remediation strategies (well site selection and pumping-recharge rates) so that water quality standards are met at a specified reliability level. The procedure couples three methods: (1) a finite element flow and transport simulation model combined with nonlinear least squares multiple regression for simultaneous flow and transport parameter estimation; (2) first-order first-and second-moment analysis to transfer the information about the effects of parameter uncertainty to the manage-ment model; and (3) nonlinear chance-constrained stochastic optimization combined with flow and transport simulation for optimal decision making. This joint approach enables one to estimate unknown aquifer parameters, quantify the uncertainty of the parameter estimates, simulate flow and transport responses, and automatically account for parameter uncertainty in the decision-making process through the simulation management model. Results show that remediation requirements can increase dramati-cally due to parameter uncertainty. Risk-averse design solutions automatically provide insurance by "overdesigning" the strategy relative to the risk-neutral case. The approach is fairly general and is applicable to a variety of groundwater management problems. The influence on design solutions of the reliability level and verification of the underlying statistical assumptions of the first-order analysis are explored in a sensitivity study and 2000 Monte Carlo simulations, respectively.
Owing to the deterministic nature of most groundwater flow models there
has been a tendency in the past to overlook the strong element of
uncertainty that invariably enters into the problem of parameter
identification. It is shown that because of this uncertainty an approach
based on the minimization of a single error functional does not in
general lead to satisfactory results. A multiple-objective decision
process is postulated taking into account all the available information
on the aquifer flow system as well as the range of environmental
conditions under which the system is expected to operate in the future.
According to this new approach a continuous or discrete set of
alternative solutions to the identification problem is generated with
the aid of mathematical programing techniques, and the decision maker is
asked to apply his own value judgment in selecting a particular model
structure. The method is illustrated by applying parametric linear
programing to a finite element model of steady state flow in a locally
anisotropic aquifer. The reliability of each parameter estimate is
ascertained with the aid of a postoptimal sensitivity analysis.
SUTRA (Saturated-Unsaturated Transport) is a computer program which simulates fluid movement and the transport of either energy or dissolved substances in a subsurface environment. The mathematical model employs a two-dimensional hybrid finite-element and integrated-finite-difference method to approximate the governing equations that describe the two interdependent processes that are simulated by SUTRA: (1) fluid density-dependent saturated or unsaturated ground-water flow, and either; (2a) transport of a solute in the ground water, in which the solute may be subject to: equilibrium adsorption on the porous matrix, and both first-order and zero-order production or decay, or, (2b) transport of thermal energy in the ground water and solid matrix of the aquifer. SUTRA provides, as the primary calculated result, fluid pressures and either solute concentrations or temperatures, as they vary with time, everywhere in the simulated subsurface system. SUTRA may also be used to simulate simpler subsets of the above process. Additional keywords: Fluid flow; Radial flow; FORTRAN. (Author)
This report forms the user's guide for Version 4.0 of NPSOL, a set of Fortran subroutines designed to minimize a smooth function subject to constraints, which may include simple bounds on the variables, linear constraints and smooth nonlinear constraints. (NPSOL may also be used for unconstrained, bound-constrained and linearly constrained optimization.) The user must provide subroutines that define the objective and constraint functions and (optionally) their gradients. All matrices are treated as dense, and hence NPSOL is not intended for large sparse problems. NPSOL uses a sequential quadratic programming (SQP) algorithm, in which the search directions is the solution of a quadratic programming (QP) subproblem. The algorithm treats bounds, linear constraints and nonlinear constraints separately. The Hessian of each QP subproblem is a positive-definite quasi-Newton approximation to the Hessian of the Lagrangian function. The steplength at each iteration is required to produce a sufficient decrease an augmented Lagrangian merit function. Each QP subproblem is solved using a quadratic programming package with several features that improve the efficiency of an SQP algorithm. (Author)
Nonpumping monitoring wells are commonly installed and sampled to delineate the extent of a contaminant plume and its chemical character. Samples from municipal and private pumping wells are frequently collected during ground-water contamination investigations as well. Pumping wells are also employed for remedial actions.
To properly interpret sampling data from monitoring and pumping wells and to estimate their potential effectiveness in remedial actions, it is important to clearly define the geometry of that portion of the aquifer contributing water to the well (the capture zone). Velocity distribution plots by manual and computerized methods are illustrated and shown to be simple and of reasonable accuracy.
A glacial outwash aquifer underlying the Gloucester Landfill near Ottawa, Canada, has become polluted with various organic chemicals following the disposal of laboratory solvents in shallow trenches immediately above the aquifer. Several remedial alternatives have been considered by the government of Canada. Impermeable barrier walls were rejected as being unsuitable given the permeable nature of the underlying bedrock. It appears improbable that pools of liquid organic chemicals (DNAPLs) exist within the aquifer, although ganglia are likely present. Therefore, much of the contaminant plume can be removed hydraulically over a period of five years by the operation of four purge wells discharging to an on-site treatment plant from which the purified water is returned to the aquifer by recharge wells. The residual contamination is anticipated to be cleaned up by in situ biorestoration techniques currently under development.
The most common process for remediating contaminated ground water is extraction and treatment. Data from 19 on‐going and completed ground water extraction systems were collected and analyzed (U.S. EPA 1989b) to evaluate the effectiveness of this process in achieving cleanup concentration goals for ground water. This analysis indicated several trends including (1) containment of ground water plumes was usually achieved; (2) contaminant concentrations dropped significantly initially followed by a leveling out; (3) after the period of initial rapid decline, the continued decreases in concentration were usually slower than anticipated; and (4) certain data important to optimizing system design and operation had often not been collected during the site characterization phase.
Factors limiting the achievement of cleanup concentration goals fell into four basic categories: (1) hydrogeological factors, such as subsurface heterogeneity, low‐permeability units, and presence of fractures; (2) contaminant‐related factors, such as high sorption to soil and presence of non‐aqueous phases (dissolution from a separate non‐aqueous phase or partitioning of contaminants from the residual non‐aqueous phase); (3) continued migration from source areas and the size of the plume itself; and (4) system design factors, such as pumping rates, screened intervals, and extraction well locations.
The findings of this study indicate that ground water extraction is an effective method for preventing additional migration of contaminant plumes and achieving risk reduction. However, the findings indicate that in many situations, it may not be practicable to rely solely on ground water extraction and treatment to achieve health‐based cleanup concentrations throughout the contaminated zone and fulfill the primary goal of returning ground water to beneficial use.
This study suggests several recommendations (U.S. EPA 1989a) for improving ground water response actions including (1) actions to contain contaminant plumes should be initiated early; (2) data on vertical variation of hydraulic conductivity, distribution of the contaminant mass, and partitioning of contaminants to soil or a stationary phase in the saturated zone should generally be collected as part of the site characterization process; (3) remedial actions should be implemented in stages to better utilize information on aquifer response as the system is being designed and implemented; (4) remedial actions should be monitored and modified during operation to optimize system efficiency; and (5) methods to enhance extraction effectiveness and efficiency should be considered.
A regression-based inverse technique for groundwater modelling that exploits coupling between flow and solute transport is applied to the Gloucester Landfill site near Ottawa, Canada, where hydraulic head and solute concentration data are available. The worth of this technique is demonstrated by comparing model parameter estimates and covariances obtained by matching only concentration data with those obtained by simultaneously matching head and concentration data. For the simultaneous match to both heads and concentrations, optimal weighting of the head residuals with respect to the concentration residuals was established through an iterative technique to equalize the variances of the two residual populations. Statistical analyses indicate that the parameter estimates obtained by matching both the head and concentration data are more certain than estimates obtained by matching concentration data alone. The significance of this greater certainty is demonstrated by translating parameter uncertainty into concentration prediction uncertainty for both parameter sets. For this field application, the predicted peak values are about twice as uncertain when regression estimates are derived solely from concentration data versus those based on both heads and concentrations.
Thesis (Ph. D.)--Stanford University, 1985.
Numerical modeling of the special waste plume at the Gloucester landfill
- A S Crowe
- S Shikaze
Contaminant hydrogeology of toxic organic chemicals at a disposal site Gloucester Ontario 1. Chemical concepts and site assessment. NHRI Paper No
- R E R J Jackson
- B W Patterson
- J Graham
- D Bahr
- J Belanger
- Lockwood
Ground Water Issue Performance Evaluations of Pump-and-Treat Remediations
- U S Epa
General Methods for Remedial Operations Performance Evaluations
- U S Epa