Partitioned multiobjective risk modeling of carcinogenic compounds in groundwater

Quantifying human cancer risk arising from exposure to contaminated groundwater is complicated by the many hydrogeological, environmental, and toxicological uncertainties involved. In this study, we used Monte Carlo simulation to estimate cancer risk associated with tetrachloroethene (PCE) dissolved in groundwater by linking three separate models for: (1) reactive contaminant transport; (2) human exposure pathways; and (3) the PCE cancer potency factor. The hydrogeologic model incorporates an analytical solution for a one-dimensional advective–dispersive–reactive transport equation to determine the PCE concentration in a water supply well located at a fixed distance from a continuous source. The pathway model incorporates PCE exposure through ingestion, inhalation, and dermal contact. The toxicological model combines epidemiological data from eight rodent bioassays of PCE exposure in the form of a composite cumulative distribution frequency curve for the human PCE cancer potency factor. We assessed the relative importance of individual model variables through their correlation with expected cancer risk calculated in an ensemble of Monte Carlo simulations with 20,000 trials. For the scenarios evaluated, three factors were most highly correlated with cancer risk: (1) the microbiological decay constant for PCE in groundwater, (2) the linear groundwater pore velocity, and (3) the cancer potency factor. We then extended our analysis beyond conventional expected value risk assessment using the partitioned multiobjective risk method (PMRM) to generate expected-value functions conditional to a 1 in 100,000 increased cancer risk threshold. This approach accounts for low probability/high impact outcomes separately from the conventional unconditional expected values. Thus, information on potential worst-case outcomes can be quantified for decision makers. Using PMRM, we evaluated the cost-benefit relationship of implementing several postulated risk management alternatives intended to mitigate the expected and conditional cancer risk. Our results emphasize the importance of hydrogeologic models in risk assessment, but also illustrate the importance of integrating environmental and toxicological uncertainty. When coupled with the PMRM, models integrating uncertainty in transport, exposure, and potency constitute an effective risk assessment tool for use within a risk-based corrective action (RBCA) framework.     

Sensitivity-guided reduction of parametric dimensionality for multi-objective calibration of watershed models

Problem complexity for watershed model calibration is heavily dependent on the number of parameters that can be identified during model calibration. This study investigates the use of global sensitivity analysis as a screening tool to reduce the parametric dimensionality of multi-objective hydrological model calibration problems while maximizing the information extracted from hydrological response data. This study shows that by expanding calibration problem formulations beyond traditional, statistical error metrics to also include metrics that capture indices or signatures of hydrological function, it is possible to reduce the complexity of calibration while maintaining high quality model predictions. The sensitivity-guided calibration is demonstrated using the Sacramento Soil Moisture Accounting (SAC-SMA) conceptual rainfall–runoff model of moderate complexity (i.e., up to 14 freely varying parameters). Using both statistical and hydrological metrics, optimization results demonstrate that parameters controlling at least 20% of the model output variance (through individual effects and interactions) should be included in the calibration process. This threshold generally yields 30–40% reductions in the number of SAC-SMA parameters requiring calibration – setting the others to a priori values – while maintaining high quality predictions. Two parameters are recommended to be calibrated in all cases (percent impervious area and lower zone tension water storage), three parameters are needed in drier watersheds (additional impervious area, riparian zone vegetation, and percent of percolation going to tension storage), and the lower zone parameters are crucial unless the watershed is very dry. Overall, this study demonstrates that a coupled, multi-objective sensitivity and calibration analysis better captures differences between watersheds during model calibration and serves to maximize the value of available watershed response time series. These contributions are particularly important given the ongoing development of more complex integrated models, which will require new tools to address the growing discrepancy between the information content of hydrological data and the number of model parameters that have to be estimated.     

Uncertainty assessment for watershed water quality modeling: A Probabilistic Collocation Method based approach

Watershed water quality models are increasingly used in management. However, simulations by such complex models often involve significant uncertainty, especially those for non-conventional pollutants which are often poorly monitored. This study first proposed an integrated framework for watershed water quality modeling. Within this framework, Probabilistic Collocation Method (PCM) was then applied to a WARMF model of diazinon pollution to assess the modeling uncertainty. Based on PCM, a global sensitivity analysis method named PCM-VD (VD stands for variance decomposition) was also developed, which quantifies variance contribution of all uncertain parameters. The study results validated the applicability of PCM and PCM-VD to the WARMF model. The PCM-based approach is much more efficient, regarding computational time, than conventional Monte Carlo methods. It has also been demonstrated that analysis using the PCM-based approach could provide insights into data collection, model structure improvement and management practices. It was concluded that the PCM-based approach could play an important role in watershed water quality modeling, as an alternative to conventional Monte Carlo methods to account for parametric uncertainty and uncertainty propagation.     

Combination of sensitivity and uncertainty analyses for sediment transport modeling in sewer pipes

Mitigation of sediment deposition in lined open channels is an essential issue in hydraulic engineering practice.Hence,the limiting velocity should be determined to keep the channel bottom clean from sediment deposits.Recently,sediment transport modeling using various artificial intelligence(AI) techniques has attracted the interest of many researchers.The current integrated study highlights unique insight for modeling of sediment transport in sewer and urban drainage systems.A novel methodology...     

Simulation-based risk assessment of contaminated sites under remediation scenarios, planning periods, and land-use patterns—a Canadian case study

Risk assessment of contaminated sites is crucial for quantifying adverse impacts on human health and the environment. It also provides effective decision support for remediation and management of such sites. This study presents an integrated approach for environmental and health risk assessment of subsurface contamination through the incorporation of a multiphase multicomponent modeling system within a general risk assessment framework. The method is applied to a petroleum-contaminated site in western Canada. Three remediation scenarios with different efficiencies (0, 60, and 90%) and planning periods (10, 20, 40, 60, and 80 years later) are examined for each of the five potential land-use plans of the study site. Then three risky zones with different temporal and spatial distributions are identified based on the local environmental guidelines and the excess lifetime cancer risk criteria. The obtained results are useful for assessing potential human health effects when the groundwater is used for drinking water supply. They are also critical for evaluating environmental impacts when the groundwater is used for irrigation, stockbreeding, fish culture, or when the site remains the status quo. Moreover, the results indicate that the proposed method can effectively identify risky zones with different risk levels under various remediation actions, planning periods, and land-use patterns.     

Deduction of groundwater flow regime in a basaltic aquifer using geochemical and isotopic data: The Golan Heights, Israel case study

Groundwater flow-paths through shallow-perch and deep-regional basaltic aquifers at the Golan Heights, Israel, are reconstructed by using groundwater chemical and isotopic compositions. Groundwater chemical composition, which changes gradually along flow-paths due to mineral dissolution and water–rock interaction, is used to distinguish between shallow-perched and deep-regional aquifers. Groundwater replenishment areas of several springs are identified based on the regional depletion in rainwater δ¹⁸O values as a function of elevation (−0.25‰ per 100 m). Tritium concentrations assist in distinguishing between pre-bomb and post-bomb recharged rainwater.

It was found that waters emerging through the larger springs are lower in δ¹⁸O than surrounding meteoric water and poor in tritium; thus, they are inferred to originate in high-elevation regions up to 20 km away from their discharge points and at least several decades ago. These results verify the numerically simulated groundwater flow field proposed in a previous study, which considered the geological configuration, water mass balance and hydraulic head spatial distribution.     

同震重力变化对震源滑动参数的敏感性研究：以2004年苏门答腊地震为例

在地震孕育和发生过程中,常伴有地表重力变化.通过同震重力变化反演震源参数,可以为认识地震活动特征奠定基础.为了有效提高同震重力变化反演滑动参数的精度,本文设计了一套定量化表征同震重力变化对震源不同滑动参数敏感性的方法.首先,基于位错理论,通过正演得到震源不同滑动参数下的同震重力变化;随后,利用无量纲化的敏感性分析方法,计算同震重力变化对不同滑动参数的敏感度因子.以2004年苏门答腊地震的断层模型为参考,定量评估了该地震同震重力变化对断层深度、断层倾角、滑移量和滑动角四个独立震源滑动参数的敏感性.评估结果显示,2004年苏门答腊地震同震重力变化对滑移量、滑动角、断层深度和断层倾角这四个独立震源滑动参数的敏感性依次降低.因对滑移量的敏感性远高于对断层倾角的敏感性,滑移量较小的反演偏差可以造成断层倾角较大的反演偏差.所以,在反演过程中,需要更加重视排序靠前的滑移量和滑动角.本文设计的方法虽然适用于其他震例,但在不同震例中,同震重力变化对各滑动参数的敏感性将有所差别.

     

Inverse modeling for seawater intrusion in coastal aquifers: Insights about parameter sensitivities,variances, correlations and estimation procedures derived from the Henry problem

Inverse modeling studies employing data collected from the classic Henry seawater intrusion problem give insight into several important aspects of inverse modeling of seawater intrusion problems and effective measurement strategies for estimation of parameters for seawater intrusion. Despite the simplicity of the Henry problem, it embodies the behavior of a typical seawater intrusion situation in a single aquifer. Data collected from the numerical problem solution are employed without added noise in order to focus on the aspects of inverse modeling strategies dictated by the physics of variable-density flow and solute transport during seawater intrusion. Covariances of model parameters that can be estimated are strongly dependent on the physics. The insights gained from this type of analysis may be directly applied to field problems in the presence of data errors, using standard inverse modeling approaches to deal with uncertainty in data.     

Analysis and interpretation of anomalous conductivity and magnetic permeability effects in time domain electromagnetic data: Part I: Numerical modeling

Time domain electromagnetic (TDEM) response is usually associated with eddy currents in conductive bodies, since this is the dominant effect. However, other effects, such as displacement currents from dielectric processes and magnetic fields associated with rock magnetization, can contribute to TDEM response. In this paper we analyze the effect of magnetization on TDEM data. We use a 3-D code based on finite-difference method, developed by Wang and Hohmann [Geophysics 58 (1993) 797], to study transient electromagnetic field propagation through a medium containing bodies with both anomalous conductivity and anomalous magnetic permeability. The remarkable result is that the combination of anomalous conductivity and permeability within the same body could increase significantly the anomalous TDEM response in comparison with purely conductive or purely magnetic anomalies. This effect has to be taken into account in interpretation of TDEM data over electrical inhomogeneous structures with potentially anomalous magnetic permeability.     

The impact of freshwater discharges on the ocean circulation in the Skagerrak/northern North Sea area. Part II: energy analysis

We perform eddy-permitting to eddy-resolving simulations of the Skagerrak/northern North Sea with a terrain-following numerical ocean model. We demonstrate that realistic representations of freshwater input are not required when the focus is on modelling mesoscale structures such as meanders and eddies. To arrive at this conclusion, we analyze the results using a recently developed energy diagnostic scheme to study the sensitivity to realistic representations of the lateral freshwater flux provided to the area from the Baltic Sea and by the major rivers. The scheme is suitable for analysis of growth of instabilities, and it has four basic instability processes prominent. We recognize both horizontal and vertical shear instabilities. There are two processes where average potential energy is converted to eddy kinetic energy, and they are related to the mean gradient in surface elevation and the mean lateral density gradient, respectively. The latter process is known as frontal instability. We demonstrate that the change in the eddy kinetic energy field is small, despite the large variations in the hydrographic properties from experiment to experiment. Moreover, generation of eddy activity appears at the same locations and with approximately the same strength regardless of actual representations of freshwater input. Furthermore, we find that vertical shear instability dominates the energy conversion processes in the Norwegian Coastal Current. Finally, we find that the areas off the northwest coast of Denmark recognized with enhanced eddy kinetic energy level is not caused by instability processes but eddy–eddy interaction rooted in variations in the sea level.     

Uncertainty and importance assessment using differential analysis: an illustration of corrosion depth of spent nuclear fuel canister

Uncertainty of NRC proposed performance assessment for the corrosion depth of storage canister of nuclear spent fuel in time history is preformed using the differential analysis. The method is demonstrated to evaluate uncertainty propagation of a system with incomplete and insufficient data in the preliminary phase of assessment. The result shows that mean corrosion depth presents a non-linear regression while variance demonstrates a first-order linear increase through 1,000-year time history. By incorporating correlation into pitting factor, uniform corrosion factor, oxygen concentration and chlorine concentration, it is found that the covariance of pitting factor and chlorine concentration has the most significant contribution in the variance of total loss. Incorporating assumed covariance into the system, the analytical form of uncertainty and importance for the corrosion depth evaluation can be well demonstrated from the input parameters.     

Evaluation of Monod kinetic parameters in the subsurface using moment analysis: Theory and numerical testing

The spatial moments of a contaminant plume undergoing bio-attenuation are coupled to the moments of microbial populations effecting that attenuation. In this paper, a scalable inverse method is developed for estimating field-scale Monod parameters such as the maximum microbial growth rate (μ^max), the contaminant half saturation coefficient (K_s), and the contaminant yield coefficient (Y_s). The method uses spatial moments that characterize the distribution of dissolved contaminant and active microbial biomass in the aquifer. A finite element model is used to generate hypothetical field-scale data to test the method under both homogeneous and heterogeneous aquifer conditions. Two general cases are examined. In the first, Monod parameters are estimated where it is assumed a microbial population comprised of a single bacterial species is attenuating one contaminant (e.g., an electron donor and an electron acceptor). In a second case, contaminant attenuation is attributed to a microbial consortium comprised of two microbial species, and Monod parameters for both species are estimated. Results indicate the inverse method is only slightly sensitive to aquifer heterogeneity and that estimation errors decrease as the sampling time interval decreases with respect to the groundwater travel time between sample locations. Optimum conditions for applying the scalable inverse method in both space and time are investigated under both homogeneous and heterogeneous aquifer conditions.     

An empirical function to estimate the depths of linear hot sources: Laboratory modeling and field measurements of lava tubes

Estimating depths of buried lava tubes is important for determining the thermal budgets and effusion rates of basaltic volcanic systems. This research used a laboratory experiment scaled to a lava tube system to measure the 3D temperature field surrounding a hot viscous fluid flowing through a buried glass tube while varying conditions such as flow rate and temperature. The depth of the glass tube was changed for different experimental runs. Numerical techniques were applied to model the laboratory experiment. The surface thermal distributions from 166 thermal traverses, constrained to a depth to width ratio of 0.6 to 1.6, were analyzed to empirically derive a depth estimation function using regression techniques. This “Linear Anomaly Surface Transect (LAST)” depth function is a scaleable depth estimation technique which can be solved with thermal imaging data alone. The minimum temperature, maximum temperature and width of a Lorentzian distribution fit to a surface thermal transect, are the only inputs required for the LAST function to estimate the depths of the hot source. The input parameters were then applied to non-laboratory situations including the Kuhio lava tube system in Hawai’i. The LAST function produced depth estimates of ∼ 0.3 m for the Kuhio lava tube in Hawai’i, which did not agree with observations on the ground. This is the result of the complex composition and geometry of an actual lava tube where heat transfer is controlled by more than a simple fluid filling a tube, but also by convection of gasses and fluids in a partially filled passage. Though not effective for lava tubes at this time, the model provides promising results for simple cases applied to engineering and underground coal fires.     

Blooms of the toxic dinoflagellate Alexandrium fundyense in the western Gulf of Maine in 1993 and 1994: A comparative modeling study

Blooms of the toxic dinoflagellate Alexandrium fundyense commonly occur in the western Gulf of Maine but the amount of toxin observed in coastal shellfish is highly variable. In this study, a coupled physical–biological model is used to investigate the dynamics underlying the observed A. fundyense abundance and shellfish toxicity in 1993 (a high toxicity year) and 1994 (low toxicity year). The physical model simulates the spring circulation, while the biological model estimates the germination and population dynamics of A. fundyense based on laboratory and field data. The model captures the large-scale aspects of the initiation and development of A. fundyense blooms during both years, but small-scale patchiness and the dynamics of bloom termination remain problematic. In both cases, the germination of resting cysts accounts for the magnitude of A. fundyense populations early in the spring. Simulations with low net A. fundyense growth rates capture the mean observed concentration during the bloom peak, which is of similar magnitude during both years. There is little evidence that large-scale changes in biological dynamics between 1993 and 1994 were a primary driver of the differences in shellfish toxicity. Results instead suggest that the persistent southwesterly flow of the western Maine Coastal Current led to A. fundyense populations of similar alongshore extent by late May of both years. This period coincides with peak cell abundance in the region. Variations in wind forcing (downwelling favorable in 1993, upwelling favorable in 1994) and subsequent cell transport (inshore in 1993, offshore in 1994) in early June then provides a plausible explanation for the dramatic mid-June differences in shellfish toxicity throughout the western Gulf of Maine.     

Uncertainty propagation of hydrodispersive transfer in an aquifer: an illustration of one-dimensional contaminant transport with slug injection

It is evident that the hydrodynamic dispersion coefficient and linear flow velocity dominate solute transport in aquifers. Both of them play important roles characterizing contaminant transport. However, by definition, the parameter of contaminant transport cannot be measured directly. For most problems of contaminant transport, a conceptual model for solute transport generally is established to fit the breakthrough curve obtained from field testing, and then suitable curve matching or the inverse solution of a theoretical model is used to determine the parameter. This study presents a one-dimensional solute transport problem for slug injection. Differential analysis is used to analyze uncertainty propagation, which is described by the variance and mean. The uncertainties of linear velocity and hydrodynamic dispersion coefficient are, respectively, characterized by the second-power and fourth-power of the length scale multiplied by a lumped relationship of variance and covariance of system parameters, i.e. the Peclet number and arrival time of maximum concentration. To validate the applicability for evaluating variance propagation in one-dimensional solute transport, two cases using field data are presented to demonstrate how parametric uncertainty can be caught depending on the manner of sampling.     

Joint inversion of Rayleigh‐wave dispersion data and vertical electric sounding data: synthetic tests on characteristic sub‐surface models

In the traditional inversion of the Rayleigh dispersion curve, layer thickness, which is the second most sensitive parameter of modelling the Rayleigh dispersion curve, is usually assumed as correct and is used as fixed a priori information. Because the knowledge of the layer thickness is typically not precise, the use of such a priori information may result in the traditional Rayleigh dispersion curve inversions getting trapped in some local minima and may show results that are far from the real solution. In this study, we try to avoid this issue by using a joint inversion of the Rayleigh dispersion curve data with vertical electric sounding data, where we use the common‐layer thickness to couple the two methods. The key idea of the proposed joint inversion scheme is to combine methods in one joint Jacobian matrix and to invert for layer S‐wave velocity, resistivity, and layer thickness as an additional parameter, in contrast with a traditional Rayleigh dispersion curve inversion. The proposed joint inversion approach is tested with noise‐free and Gaussian noise data on six characteristic, synthetic sub‐surface models: a model with a typical dispersion; a low‐velocity, half‐space model; a model with particularly stiff and soft layers, respectively; and a model reproduced from the stiff and soft layers for different layer‐resistivity propagation. In the joint inversion process, the non‐linear damped least squares method is used together with the singular value decomposition approach to find a proper damping value for each iteration. The proposed joint inversion scheme tests many damping values, and it chooses the one that best approximates the observed data in the current iteration. The quality of the joint inversion is checked with the relative distance measure. In addition, a sensitivity analysis is performed for the typical dispersive sub‐surface model to illustrate the benefits of the proposed joint scheme. The results of synthetic models revealed that the combination of the Rayleigh dispersion curve and vertical electric sounding methods in a joint scheme allows to provide reliable sub‐surface models even in complex and challenging situations and without using any a priori information.     

Use of statistical analysis to formulate conceptual models of geochemical behavior: water chemical data from the Botucatu aquifer in São Paulo state, Brazil

Water chemical data from the Botucatu Sandstone aquifer in the São Paulo State part of the Paraná Basin, Brazil, was evaluated using geochemical methods and two statistical analyses: cluster analysis and factor analysis. The results were used to develop a conceptual geochemical model, in which three geochemical regions were identified, and their chemical behavior was modeled. The characteristic chemicals, changing from the recharge area to the center of the basin, are: SiO₂—(HCO₃⁻ and Ca²⁺)—(Na⁺, CO₃²⁻, and SO₄²⁻). The distribution of the chemicals is interpreted as controlled by different water–rock interaction processes in the different regions. In the recharge area, dissolution of alkali–feldspar minerals in the sandstone is the main reaction observed; in the mid-section of the basin, calcite dissolution results in high calcium and bicarbonate concentration; in the center of the basin, leakage from underlying layers becomes the governing factor.