Dynamic Modeling of Ground‐Water Quality Using Bayesian Techniques1

Abstract: Water industry experts have been arguing that the traditional techniques are not an accurate means of measuring water contamination. This is mainly because these techniques emphasize neither the stochastic nature of the water contamination process nor the precision and the accuracy of the tested methods used by environmental laboratories. In this work, we describe the development and application of prototype Dynamic Bayesian Networks (DBNs) that model ground‐water quality to determine the impact of chemical contaminants on ground‐water quality in the Salalah area, which is allocated to the south of Oman. We also present a new technique for data pre‐processing because it is needed for the treatment of ground‐water datasets that are used as the data source to learn the probabilities for dynamic decision models. Among more than 20 wells in area, only four wells were selected to be analyzed and the results show that we achieved an acceptable level of efficiency.     

浙江省废旧金属再生利用的经验、问题及对策

文章分析了浙江省在废旧有色金属资源再生利用方面的几个典型模式的经验、存在问题及发展对策。     

Applicability of a Septic Tank/Engineered Wetland Coupled System in the Treatment and Recycling of Wastewater from a Small Community

A septic tank (ST)/engineered wetland coupled system used to treat and recycle wastewater from a small community in Dar es Salaam, Tanzania was monitored to assess its performance. The engineered wetland system (EWS) had two parallel units each with two serial beds packed with different sizes of media and vegetated differently. The larger-sized medium bed was upstream and was planted with Phragmites (reeds) and the smaller-sized medium bed was downstream and was planted with Typha (cattails). The ST/EWS coupled system was able to remove ammonia by an average of 60%, nitrate by 71%, sulfate by 55%, chemical oxygen demand by 91%, and fecal coliform as well as total coliform by almost 100%. The effluent from the ST/EWS coupled system is used for irrigation. Notably, users of the recycled irrigation water do not harbor any negative feelings about it. This study demonstrates that it is possible to treat and recycle domestic wastewater using ST/EWS coupled systems. The study also brings attention to the fact that an ST/EWS coupled system has operation and maintenance (O&M) needs that must be fulfilled for its effectiveness and acceptability. These include removal of unwanted weeds, harvesting of wetland plants when the EWS becomes unappealingly bushy, and routine repair.     

用窄点原理进行节水分析

简要地对窄点原理进行了介绍。用窄点原理对工程设计进行了具体分析，在排污量相同的情况下，分别采用洁净水接纳污染物、采用满足进水浓度要求但无回用的废水接纳污染物和采用窄点技术且可回用废水但无水处理过程的废水接纳污染物三种供水方式。比较不同的供水方式所需的不同耗水量。从而得出窄点分析原理对节水，节能和降污保护环境具有的重大意义。     

MODELING DRINKING WATER QUALITY VIOLATIONS WITH BAYESIAN NETWORKS1

ABSTRACT: Compliance violations at community water systems are rare but represent significant human health risks. These risks are mediated by the decision schema of human operators at water treatment facilities. However, causal uncertainty among physical and human factors involved in water quality problems complicates assessment of their probability and severity. This study uses a probabilistic Bayesian network modeling approach to explore the causes of compliance violations in a sample of water treatment systems in Pennsylvania. The model presented here is one of several created by treatment system operators during an expert elicitation process. The expert model alone predicts violations poorly, suggesting that experts make inaccurate quantitative estimates. However, Bayesian networks are capable of combining the subjective expertise of treatment system operators with the objective compliance histories of the facilities they manage, and the expert model accurately predicts violations when trained with historical compliance data. Analysis of the trained network reveals those components of the treatment process, including environmental and system characteristics as well as operator decisions, that play the greatest role in determining the likelihood of major violation types. Among operator decisions, coagulant dosing and filter backwash frequency are the most important determinants of violation likelihood.     

Integrated Protected Area Selection in Australian Biogeographic Regions

/ This paper reports on the development of abiogeographic-based protected area selection procedure (PASP) that addresseslimitations of current reserve selection methods such as inflexibility,restrictive criteria structures, and disregard of social criteria. We arguethat selection criteria are legitimately identified through the politicalprocess and can therefore have both social and biological content. PASPprovides a systematic, flexible and efficient procedure for identifying anetwork of protected areas that satisfies a given set of selection criteria.PASP has 11 steps divided into three main stages: compilation, selection, andvalidation. A selection algorithm is used into which criteria specific to thebiogeographic region under study can be incorporated. The procedure is ableto accommodate both nominal and ranking criteria and gives the analyst theopportunity to specify thresholds and targets for each criterion. Otherfeatures of PASP include the minimization of data collection effort,consideration of reserve design principles, and inclusion of a networkevaluation as a check to ensure that politically determined objectives havebeen met.KEY WORDS: Land use; Protected area networks; Selection algorithms     

Modeling Flow and Sediment Transport in a River System Using an Artificial Neural Network

A river system is a network of intertwining channels and tributaries, where interacting flow and sediment transport processes are complex and floods may frequently occur. In water resources management of a complex system of rivers, it is important that instream discharges and sediments being carried by streamflow are correctly predicted. In this study, a model for predicting flow and sediment transport in a river system is developed by incorporating flow and sediment mass conservation equations into an artificial neural network (ANN), using actual river network to design the ANN architecture, and expanding hydrological applications of the ANN modeling technique to sediment yield predictions. The ANN river system model is applied to modeling daily discharges and annual sediment discharges in the Jingjiang reach of the Yangtze River and Dongting Lake, China. By the comparison of calculated and observed data, it is demonstrated that the ANN technique is a powerful tool for real-time prediction of flow and sediment transport in a complex network of rivers. A significant advantage of applying the ANN technique to model flow and sediment phenomena is the minimum data requirements for topographical and morphometric information without significant loss of model accuracy. The methodology and results presented show that it is possible to integrate fundamental physical principles into a data-driven modeling technique and to use a natural system for ANN construction. This approach may increase model performance and interpretability while at the same time making the model more understandable to the engineering community.     

辅助驾驶中的换道决策安全研究

换道是驾驶员达到快速通行目标的一种常用手段,但换道会带来很多公路交通事故。为有效避免交通事故,需给驾驶员提供换道安全预警。构建了安全换道决策模型,将换道决策分为换道意图识别和换道条件判断分别建立模型以提高预测精确度。通过神经网络方法SOM(Self-Organization-Map)聚类及BP(Back Propagation)建立换道意图识别模型,基于贝叶斯理论建立最小风险贝叶斯换道条件判别模型。模型开发和测试采用车辆轨迹数据集(NGSIM),提取数据中的换道行为特征参数作为模型的输入,将驾驶员换道决策预测视为输入变量的函数。通过对比最小贝叶斯和最小风险贝叶斯方法发现,由后者构建的换道条件判别模型效果较好,对于不换道行为的预测精度为90.4%,换道行为的预测精度为73.8%。鉴于错误的换道决策可能导致交通事故,而错误的不换道决策只会导致失去一次换道的机会,在换道辅助系统中,不换道决策的精确度要求需高于换道决策的精度。最后,在微观交通仿真系统中加入换道决策模型,其结果验证换道决策安全。最小风险贝叶斯换道条件判别模型的引入,使得换道决策系统能够通过修正风险系数,进一步提高换道判别精度,减少不安全的换道概率。     

应用遗传神经网络方法分析我国降水化学数据

收集了１１１组包含Ｃａ＾２＋、Ｍｇ＾２＋等８种离子浓度和ＰＨ值的我国降水化学数据，并用遗传神经网络（Ｇｅｎｅｔｉｃ Ｎｅｕｒａｌ Ｎｅｔ－ｗｏｒｋｓ，ＧＮＮ）方法建立了这些离子浓度和ＰＨ值绵ＢＰ网络模式，运用这些模式计算了各离子浓度对ＰＨ值的贡献，结果表明，我国各地降水ＰＨ值与各地区酸性离子与碱性离子相互用途相关，其中生离子的中和作用起着主导作用。     

产品责任制在废弃物管理中的应用

从消费者，销售者，生产者的角度阐明产品责任制的概念，并分析了其实现形式——自发回收和强制回收。提出了在废弃物管理中应用产品责任制的范围和实施步骤。