A Comparison of Bayesian Methods for Uncertainty Analysis in Hydraulic and Hydrodynamic Modeling

We evaluate and compare the performance of Bayesian Monte Carlo (BMC), Markov chain Monte Carlo (MCMC), and the Generalized Likelihood Uncertainty Estimation (GLUE) for uncertainty analysis in hydraulic and hydrodynamic modeling (HHM) studies. The methods are evaluated in a synthetic 1D wave routing exercise based on the diffusion wave model, and in a multidimensional hydrodynamic study based on the Environmental Fluid Dynamics Code to simulate estuarine circulation processes in Weeks Bay, Alabama. Results show that BMC and MCMC provide similar estimates of uncertainty. The posterior parameter densities computed by both methods are highly consistent, as well as the calibrated parameter estimates and uncertainty bounds. Although some studies suggest that MCMC is more efficient than BMC, our results did not show a clear difference between the performance of the two methods. This seems to be due to the low number of model parameters typically involved in HHM studies, and the use of the same likelihood function. In fact, for these studies, the implementation of BMC results simpler and provides similar results to MCMC. The results of GLUE are, on the other hand, less consistent to the results of BMC and MCMC in both applications. The posterior probability densities tend to be flat and similar to the uniform priors, which can result in calibrated parameter estimates centered in the parametric space.     

基于MonteCarlo模拟的土壤重金属综合风险评价与案例分析

基于不确定性理论,将Monte Carlo模拟计算应用到土壤重金属风险评价中,构建了生态风险和健康风险的随机不确定模型,结合多元统计方法进行实例研究.结果表明,研究区土壤Cd、Co和Cr污染水平较高,主要富集在建矿时间较长的工业园区;综合单因子指数和综合风险因子指数评价显示土壤重金属主要为轻度污染(相应概率分别为53.2%和55.6%);手-口摄入是研究区土壤重金属暴露的主要途径,Cr为主要致癌因子;儿童承担的健康风险较高,其非致癌风险指数分别为成人的5.0倍(手-口摄入途径)和8.2倍(皮肤暴露途径),两种暴露途径下其致癌风险指数均高于USEPA推荐的安全水平.     

Life cycle assessment of active and passive groundwater remediation technologies

Groundwater remediation technologies, such as pump-and-treat (PTS) and funnel-and-gate systems (FGS), aim at reducing locally appearing contaminations. Therefore, these methodologies are basically evaluated with respect to their capability to yield local improvements of an environmental situation, commonly neglecting that their application is also associated with secondary impacts. Life cycle assessment (LCA) represents a widely accepted method of assessing the environmental aspects and potential impacts related to a product, process or service. This study presents the set-up of a LCA framework in order to compare the secondary impacts caused by two conceptually different technologies at the site of a former manufactured gas plant in the city of Karlsruhe, Germany. As a FGS is already operating at this site, a hypothetical PTS of the same functionality is adopted. During the LCA, the remediation systems are evaluated by focusing on the main technical elements and their significance with respect to resource depletion and potential adverse effects on ecological quality, as well as on human health. Seven impact categories are distinguished to address a broad spectrum of possible environmental loads. A main point of discussion is the reliability of technical assumptions and performance predictions for the future. It is obvious that a high uncertainty exists when estimating impact specific indicator values over operation times of decades. An uncertainty analysis is conducted to include the imprecision of the underlying emission and consumption data and a scenario analysis is utilised to contrast various possible technological variants. Though the results of the study are highly site-specific, a generalised relative evaluation of potential impacts and their main sources is the principle objective rather than a discussion of the calculated absolute impacts. A crucial finding that can be applied to any other site is the central role of steel, which particularly derogates the valuation of FGS due to the associated emissions that are harmful to human health. In view of that, environmental credits can be achieved by selecting a mineral-based wall instead of sheet piles for the funnel construction and by minimising the steel consumption for the gate construction. Granular activated carbon (GAC) is exclusively considered as the treatment material, both in-situ and on-site. Here it is identified as an additional main determinant of the relative assessment of the technologies since it is continuously consumed.     

基于可拓学的尾矿库安全评价

为综合评价尾矿库的安全状态,基于尾矿库灾变机理和大量工程实践构建了一套包括3级指标、22个因素的评价指标体系,并确定了评价指标的等级量值区间。采用EAHP和熵权法结合的方式确定指标权重,基于可拓理论评价尾矿库的安全等级。以湖南黄金集团责任有限公司旗下的7座尾矿库为案例,评价其安全状态,根据蒙特卡洛模拟基本理论,基于Crystal Ball对案例进行敏感性分析,找出具体敏感因素,为后期尾矿库安全管理提供简单有效的控制方法。     

MODIFIED WATER QUANTITY RECEIVING MODEL FOR FLORIDA CONSERVATION AREAS1

ABSTRACT: The Conservation Areas in South Florida have been considered as one of the major water storage areas to provide a water supply for the Everglades National Park and Lower East Coast (LEC). Due to the increasing water demands of the area, additional backpumping of the surplus runoff from the LEC area into the Conservation Areas has been considered as one of several alternative plans. The Receiving Water Quantity (EPA, 1971) model has been adapted and modified to be applicable in the Conservation Areas to investigate the possible impact of additional inflow under various backpumping cases. The modification of the model included Manning's roughness coefficient, depth of flow, width of hypothetical channels through marsh areas, rainfall input, seepage rate, etc. The use of the Monte Carlo technique for area computations was found to be easy and time saving both in area and weighting rainfall input to each node. Comparison of results generated by this modified model with the recorded values in Conservation Areas 1 and 2A indicated that the model not only can be a very good evaluation tool to simulate the hydraulic regime of the Conservation Areas system but also a proper tool for investigating the impact of additional inflow resulting from the backpumping related to the water use planning and management.     

PROBABILISTIC METHODS IN STREAM QUALITY MANAGEMENT1

ABSTRACT. Recent advances in water quality modelling have pointed out the need for stochastic models to simulate the probabilistic nature of water quality. However, often all that is needed is an estimate of the uncertainty in predicting water quality variables. First order analysis is a simple method of providing an estimate in the uncertainty in a deterministic model due to uncertain parameters. The method is applied to the simplified Streeter-Phelps equations for DO and BOD; a more complete Monte Carlo simulation is used to check the accuracy of the results. The first order analysis is found to give accurate estimates of means and variances of DO and BOD up to travel times exceeding the critical time. Uncertainty in travel time and the BOD decay constant are found to be most important for small travel times; uncertainty in the reaeration coefficient dominates near the critical time. Uncertainty in temperature was found to be a negligible source of uncertainty in DO for all travel times.     

Uncertainty Analysis In Dissolved Oxygen Modeling in Streams

Uncertainty analysis in surface water quality modeling is an important issue. This paper presents a method based on the first-order reliability method (FORM) to assess the exceedance probability of a target dissolved oxygen concentration in a stream, using a Streeter–Phelps prototype model. Basic uncertainty in the input parameters is considered by representing them as random variables with prescribed probability distributions. Results obtained from FORM analysis compared well with those of the Monte Carlo simulation method. The analysis also presents the stochastic sensitivity of the probabilistic outcome in the form of uncertainty importance factors, and shows how they change with changing simulation time. Furthermore, a parametric sensitivity analysis was conducted to show the effect of selection of different probability distribution functions for the three most important parameters on the design point, exceedance probability, and importance factors. Note: This version was published online in June 2005 with the cover date of August 2004.     

Ecological Impact Assessment in Data-Poor Systems: A Case Study on Metapopulation Persistence

Legislation on the protection of biodiversity (e.g., European Union Habitat and Bird Directives) increasingly requires ecological impact assessment of human activities. However, knowledge and understanding of relevant ecological processes and species responses to different types of impact are often incomplete. In this paper we demonstrate with a case study how impact assessment can be carried out for situations where data are scarce but some expert knowledge is available. The case study involves two amphibian species, the great crested newt (Triturus cristatus) and the natterjack toad (Bufo calamita) in the nature reserve the Meinweg in the Netherlands, for which plans are being developed to reopen an old railway track called the Iron Rhine. We assess the effects of this railway track and its proposed alternatives (scenarios) on the metapopulation extinction time and the occupancy times of the patches for both species using a discrete-time stochastic metapopulation model. We quantify the model parameters using expert knowledge and extrapolated data. Because of our uncertainty about these parameter values, we perform a Monte Carlo uncertainty analysis. This yields an estimate of the probability distribution of the model predictions and insight into the contribution of each distinguished source of uncertainty to this probability distribution. We show that with a simple metapopulation model and an extensive uncertainty analysis it is possible to detect the least harmful scenario. The ranking of the different scenarios is consistent. Thus, uncertainty analysis can enhance the role of ecological impact assessment in decision making by making explicit to what extent incomplete knowledge affects predictions.     

BOD5容量计算的不确定性分析

应用蒙特卡罗方法对BODs容量计算的不确定性,作出定量估计。结合算例,讨论了主要参数的统计检验,随机变量生成等。给出了以容量——概率曲线估计不确定性的定量结果。