Wastewater reuse potential analysis: implications for China's water resources management

It has been recognized that wastewater reuse or reclamation serves as an efficient and valuable way to cope with the scarcity of water resources and severity of water pollution. This paper presents the systematic framework of wastewater reuse potential estimation. Based on the regional disparities in China, a linear programming optimization model is developed to explore the potential wastewater reuse quantities, under physical and economic constraints. Sensitivity analysis and Robust Counterpart (RC) optimization are performed to discuss the influences of key parameters and the reuse quantity's decision making under uncertainty. Based on the model, effectiveness of different policy scenarios of water price changes are simulated and evaluated, providing information regarding China's water and wastewater management.     

Assessment of water quality management with a systematic qualitative uncertainty analysis

Uncertainty is an inevitable source of noise in water quality management and will weaken the adequacy of decisions. Uncertainty is derived from imperfect information, natural variability, and knowledge-based inconsistency. To make better decisions, it is necessary to reduce uncertainty. Conventional uncertainty analyses have focused on quantifying the uncertainty of parameters and variables in a probabilistic framework. However, the foundational properties and basic constraints might influence the entire system more than the quantifiable elements and have to be considered in initial analysis steps. According to binary classification, uncertainty includes quantitative uncertainty and non-quantitative uncertainty, which is also called qualitative uncertainty. Qualitative uncertainty originates from human subjective and biased beliefs. This study provides an understanding of qualitative uncertainty in terms of its conceptual definitions and practical applications. A systematic process of qualitative uncertainty analysis is developed for assisting complete uncertainty analysis, in which a qualitative network could then be built with qualitative relationship and quantifiable functions. In the proposed framework, a knowledge elicitation procedure is required to identify influential factors and their interrelationship. To limit biased information, a checklist is helpful to construct the qualitative network. The checklist helps one to ponder arbitrary assumptions that have often been taken for granted and may yield an incomplete or inappropriate decision analysis. The total maximum daily loads (TMDL) program is used as a surrogate for water quality management in this study. 15 uncertainty causes of TMDL programs are elicited by reviewing an influence diagram, and a checklist is formed with tabular interrogations corresponding to each uncertainty cause. The checklist enables decision makers to gain insight on the uncertainty level of the system at early steps as a convenient tool to review the adequacy of a TMDL program. Following the instruction of the checklist, an appropriate algorithm in a form of probability, possibility, or belief may then be assigned for the network. Consequently, the risk or evidence of the success of outcomes will be obtained. The incorporation of the systematic consideration of qualitative uncertainty into water quality management is expected to refine the decision-making process.     

An interval-based possibilistic programming method for waste management with cost minimization and environmental-impact abatement under uncertainty

Considerable public concerns have been raised in the past decades since a large amount of pollutant emissions from municipal solid waste (MSW) disposal of processes pose risks on surrounding environment and human health. Moreover, in MSW management, various uncertainties exist in the related costs, impact factors and objectives, which can affect the optimization processes and the decision schemes generated. In this study, an interval-based possibilistic programming (IBPP) method is developed for planning the MSW management with minimized system cost and environmental impact under uncertainty. The developed method can deal with uncertainties expressed as interval values and fuzzy sets in the left- and right-hand sides of constraints and objective function. An interactive algorithm is provided for solving the IBPP problem, which does not lead to more complicated intermediate submodels and has a relatively low computational requirement. The developed model is applied to a case study of planning a MSW management system, where mixed integer linear programming (MILP) technique is introduced into the IBPP framework to facilitate dynamic analysis for decisions of timing, sizing and siting in terms of capacity expansion for waste-management facilities. Three cases based on different waste-management policies are examined. The results obtained indicate that inclusion of environmental impacts in the optimization model can change the traditional waste-allocation pattern merely based on the economic-oriented planning approach. The results obtained can help identify desired alternatives for managing MSW, which has advantages in providing compromised schemes under an integrated consideration of economic efficiency and environmental impact under uncertainty.     

Towards quantification of uncertainty in predicting water quality failures in integrated catchment model studies

This paper describes the development and application of a method for estimating uncertainty in the prediction of sewer flow quantity and quality and how this may impact on the prediction of water quality failures in integrated catchment modelling (ICM) studies. The method is generic and readily adaptable for use with different flow quality prediction models that are used in ICM studies. Use is made of the elicitation concept, whereby expert knowledge combined with a limited amount of data are translated into probability distributions describing the level of uncertainty of various input and model variables. This type of approach can be used even if little or no site specific data is available. Integrated catchment modelling studies often use complex deterministic models. To apply the results of elicitation in a case study, a computational reduction method has been developed in order to determine levels of uncertainty in model outputs with a reasonably practical level of computational effort. This approach was applied to determine the level of uncertainty in the number of water quality failures predicted by an ICM study, due to uncertainty associated with input and model parameters of the urban drainage model component of the ICM. For a small case study catchment in the UK, it was shown that the predicted number of water quality failures in the receiving water could vary by around 45% of the number predicted without consideration of model uncertainty for dissolved oxygen and around 32% for unionised ammonia. It was concluded that the potential overall levels of uncertainty in the ICM outputs could be significant. Any solutions designed using modelling approaches that do not consider uncertainty associated with model input and model parameters may be significantly over-dimensioned or under-dimensioned. With changing external inputs, such as rainfall and river flows due to climate change, better accounting for uncertainty is required.     

Quantification and relative comparison of different types of uncertainties in sewer water quality modeling

Quantifiable sources of uncertainty have been identified for a case study of integrated modeling of a sewer system with a more downstream wastewater treatment plant and storage sedimentation tank. The different sources were classified in model input and model-structure-related uncertainties. They were quantified and propagated towards the uncertainty in the event-based prediction of sewer emissions (flow, and physico-chemical water quality concentrations and loads). Based on the concept of variance decomposition, the total prediction uncertainty was split into the contributions of the various uncertainty sources and the different submodels. Although the results strongly depend on the water quality variable considered, it is in most general terms concluded that the uncertainty contribution by the water quality submodels is an order of magnitude higher than that for the flow submodels. Future model improvement should therefore mainly focus on water quality data collection, which would reduce current problems of spurious model calibration and verification, but also of knowledge gaps in in-sewer processes.     

天津滨海新区响螺湾商务区城市设计

文章概述了天津滨海新区响螺湾商务区的规划及城市设计。作为天津滨海新区于家堡中心商务区的启动区,响螺湾商务区的规划设计工作以国内外商务区规划建设的成功经验为基础,结合地域文化与环境特点,进行了城市设计及导则的研究与编制工作,并在该导则的指导下实施建筑单体设计。     

Hydrochemical characteristics and water quality assessment of surface water and groundwater in Songnen plain, Northeast China

Water quality is the critical factor that influence on human health and quantity and quality of grain production in semi-humid and semi-arid area. Songnen plain is one of the grain bases in China, as well as one of the three major distribution regions of soda saline-alkali soil in the world. To assess the water quality, surface water and groundwater were sampled and analyzed by fuzzy membership analysis and multivariate statistics. The surface water were gather into class I, IV and V, while groundwater were grouped as class I, II, III and V by fuzzy membership analysis. The water samples were grouped into four categories according to irrigation water quality assessment diagrams of USDA. Most water samples distributed in category C1-S1, C2-S2 and C3-S3. Three groups were generated from hierarchical cluster analysis. Four principal components were extracted from principal component analysis. The indicators to water quality assessment were Na, HCO₃, NO₃, Fe, Mn and EC from principal component analysis. We conclude that surface water and shallow groundwater are suitable for irrigation, the reservoir and deep groundwater in upstream are the resources for drinking. The water for drinking should remove of the naturally occurring ions of Fe and Mn. The control of sodium and salinity hazard is required for irrigation. The integrated management of surface water and groundwater for drinking and irrigation is to solve the water issues.     

天津滨海新区于家堡金融区起步区地下工程防水设计

天津滨海新区于家堡金融区起步区地下工程采用了混凝土结构自防水,以及水泥基渗透结晶型防水涂料和自粘聚合物改性沥青防水卷材的全包防水设计;各种施工缝、诱导缝、地下空间接口处以及桩头等都做了细部加强防水处理.     

An optimization model for water quantity and quality integrated management of an urban lake in a water deficient city

This paper presents an optimization model for water quantity and quality integrated management of an urban lake in a water deficient city. A representative water quantity and quality safeguard system served urban lake, including multi-source water supply facilities, recirculating water purification facilities and surplus water discharge facilities, is widely used in Chinese water deficient cities. Because it is complicated, any mismanagement will result in water quality deterioration, water waste and high operation cost. The presented model attempts to achieve the objectives of controlling water pollution, reducing economic cost and improving water utilization efficiency through an optimized operating water safeguard system. The model is applied to Qingjing Lake in Tianjin, China. Results show that the model plays a more positive role for water quantity and quality integrated management.     

量化可持续——天津市滨海新区北塘地区发展规划初探

该文主要阐明可持续系统整合模型的创建及实地应用,探索出一条将模型与国内城市规划过程相互协调应用的道路。以滨海新区北塘地区为试点,利用当地基础规划数据,校核模型,使其适用于当地的实际情况,从而为整个区域建立一套切实可行的可持续城市指标体系,以及一系列可持续实施措施,以实现政府在一定时期内可接受的可持续发展目标。     

天津滨海新区西外环盐池段桥梁耐久性设计

天津滨海新区盐场分布较广,西外环的部分桥梁工程(桩号K32+337~K32+882)位于塘沽盐场的盐池内。根据详勘报告的腐蚀性评价结果,该场地地表水对钢筋混凝土的结晶类腐蚀等级为严重腐蚀、结晶分解类复合腐蚀等级为严重腐蚀。气候上天津属于寒冷地区,会产生冻融腐蚀作用,故需要对桩基、承台、立柱等采取特殊防护措施。通过原材料、结构设计、防腐涂装、外加剂等途径进行耐久性设计,保证桥梁在设计基准期内满足使用要求。     

Assessment of the surface water quality in Northern Greece

The application of different multivariate statistical approaches for the interpretation of a large and complex data matrix obtained during a monitoring program of surface waters in Northern Greece is presented in this study. The dataset consists of analytical results from a 3-yr survey conducted in the major river systems (Aliakmon, Axios, Gallikos, Loudias and Strymon) as well as streams, tributaries and ditches. Twenty-seven parameters have been monitored on 25 key sampling sites on monthly basis (total of 22,350 observations). The dataset was treated using cluster analysis (CA), principal component analysis and multiple regression analysis on principal components. CA showed four different groups of similarity between the sampling sites reflecting the different physicochemical characteristics and pollution levels of the studied water systems. Six latent factors were identified as responsible for the data structure explaining 90% of the total variance of the dataset and are conditionally named organic, nutrient, physicochemical, weathering, soil-leaching and toxic-anthropogenic factors. A multivariate receptor model was also applied for source apportionment estimating the contribution of identified sources to the concentration of the physicochemical parameters. This study presents the necessity and usefulness of multivariate statistical assessment of large and complex databases in order to get better information about the quality of surface water, the design of sampling and analytical protocols and the effective pollution control/management of the surface waters.     

A decision support system for water quality issues in the Manzanares River (Madrid, Spain)

The Manzanares River, located in Madrid (Spain), is the main water supplier of a highly populated region, and it also receives wastewater from the same area. The effluents of eight Waste Water Treatment Plants (WWTPs) downstream of the river, which represent 90% of the flow in the middle and lower parts of the river, are the primary sources of water pollution. Although the situation has improved slightly in the last two years, the water in the river is highly polluted, making it uninhabitable for aquatic life. Water quality modelling is typically used to assess the effect of treatment improvements in water bodies. In this work, the GESCAL module of the Aquatool Decision Support System Shell was used to simulate water quality in the Manzanares River. GESCAL is appropriate for modelling in an integrated way water quality for whole water resources systems, including reservoirs and rivers. A model was built that simulates conductivity, phosphorous, carbonaceous organic matter, dissolved oxygen, organic nitrogen, ammonia, and nitrates. The period from October 2006 to September 2008 was selected for calibration due to the many treatment modifications that occurred during this time. An earlier and longer period, from October 2000 to September 2006, was used for validation. In addition, a daily model was used to analyse the robustness of the GESCAL model. Once the GESCAL model was validated, different scenarios were considered and simulated. First, different combinations of nutrient elimination among the different WWTPs were simulated, leading to the conclusion that investments have to focus on three of the proposed WWTPs. Moreover, these treatments will not be sufficient to maintain fish habitat conditions at all times. Additional measures, such as the increment of the flow in the river or oxygen injection, were simulated. Incrementing the flow of the Manzanares River has been shown to be an efficient means of increasing water quality, but this implies an increment in the risk of water scarcity situations in the Madrid water supply system.     

Evaluation of water quality in an agricultural watershed as affected by almond pest management practices

In the last decade, the detection of organophosphate (OP) pesticides in the San Joaquin River watershed has raised concerns about water quality. This study examined the influences of almond pest management practices (PMPs) on water quality. The Soil and Water Assessment Tool (SWAT) model was employed to simulate pesticide concentration in water as affected by different PMPs. California Pesticide Use Reporting (PUR) data were used to investigate PMP use trends. Stepwise regression analysis was performed to test the correlation between specific PMP use and pesticide concentrations in surface water and sediment. Our results showed an increasing use of reduced risk pesticides and pyrethroids on almonds. SWAT simulation over the period of 1992-2005 showed decreases in OP concentrations in surface water. High OP and pyrethroid use in dormant sprays was associated with high pesticide concentrations in water and sediment. Almond pesticide use was proved to have significant impacts on the pesticide load in the San Joaquin River watershed. The PMP which combines the use of reduced risk pesticides with no dormant spray was recommended for almond orchard use. This paper presented a novel method of studying the environmental impacts of different agricultural PMPs. By combining pesticide use surveys with watershed modeling, we provided a quantitative foundation for the selection of PMPs to reduce pesticide pollution in surface water.     

Long-term water quality monitoring of the Sejnane reservoir in northeast Tunisia

The Sejnane reservoir in northeast Tunisia provides drinking and irrigation water. Long-term water quality monitoring data including precipitation, evaporation, temperature, pH, conductivity, dissolved oxygen, turbidity, total suspended solids, major anions and cations, fluoride, BOD₅, NO₃ ⁻, NO₂ ⁻, NH₄ ⁺, P _tot, fecal coliform bacteria, boron and heavy metals (Fe, Zn, Cu, Ni, Pb, Cr and Cd) are reported. The appropriateness for irrigation was estimated by the SAR and Na percentage and the water quality assessed using the Canadian Water Quality Index as good to excellent, which confirmed its suitability for drinking, aquatic life and irrigation purposes.      

Spatial analysis of water quality trends in the Han River basin, South Korea

Spatial patterns of water quality trends for 118 sites in the Han River basin of South Korea were examined for eight parameters-temperature, pH, dissolved oxygen (DO), biochemical oxygen demand (BOD), chemical oxygen demand (COD), suspended sediment (SS), total phosphorus (TP), and total nitrogen (TN). A non-parametric seasonal Mann-Kendall's test determined the significance of trends for each parameter for each site between 1993 and 2002. There are no significant trends in temperature, but TN concentrations increased for the majority of the monitoring stations. DO, BOD, COD, pH, SS, and TP show increasing or decreasing trends with approximately half of the stations exhibiting no trends. Urban land cover is positively associated with increases in water pollution and included as an important explanatory variable for the variations in all water quality parameters except pH. Topography and soil factors further explain the spatial variations in pH, COD, BOD, and SS. BOD, COD, SS, and TP variations are consistently better explained by 100m buffer scale analysis, but DO are better explained by the whole basin scale analysis. Local water quality management or geology could further explain some variations of water quality. Non-point-source pollution exhibits strong positive spatial autocorrelation as measured by Moran's I, indicating that the incorporation of spatial dimensions into water quality assessment enhances our understanding of spatial patterns of water quality. The spatial regression models, compared to ordinary least square (OLS) models, always better explain the variations in water quality. This study suggests that spatial analysis of watershed data at different scales should be a vital part of identifying the fundamental spatio-temporal distribution of water quality.     

采用BP神经网络模型对东北地区水库水水质的预测研究

采用BP神经网络建立了东北地区某水库水的浊度预测模型,同时针对该水库的地域特点,重点研究了冰封期对水源水水质预测的影响。结果表明,以浊度为预测对象,将水库的水质数据按照是否进入冰封期进行划分后建模,预测效果比划分之前有较明显的提高。     

Influence of water and sediment quality on benthic biota in an acidified river

Water and sediment quality and benthic biota were investigated in all seasons during three years in the River Akagawa that receives the effluent from a mine drainage treatment plant at its upstream site. The upper reaches kept the low pH, the comparatively high concentrations of metals and a large amount of iron deposited on the riverbed. The predominant macroinvertebrates were Protonemura sp., Capnidae, Nemoura sp. and Chironomidae in the upper and middle reaches. In the lowest reaches, the community structure of the macroinvertebrate changed into Chironomidae, Trichoptera (Hydropsychidae) and Ephemeroptera (Baetis sp.) as the pH was increased. From the results of multivariate analyses, it was found that the restoration of pH and attached algae and the increase in the concentrations of nutrients and organic matter promoted the inhabitation of Chironomidae and Hydropsychidae, whereas the dissolved metals in the river water inhibited the inhabitation of these families. Moreover, the sedimentation of metals would cause a severe damage to the inhabitation of Hydropsychidae compared with that of Chironomidae.     

Analysis of the QUESTOR water quality model using a Fourier amplitude sensitivity test (FAST) for two UK rivers

This paper presents the sensitivity analysis of a well-known in-stream water quality model, QUESTOR (QUality Evaluation and Simulation TOol for River systems) as applied to two rivers of contrasting land-use in the northeast of England: the 'rural' Ouse and the 'urban' Aire. The analysis employed a version of the Fourier Amplitude Sensitivity Test (FAST) that quantifies the contribution of changes in individual parameters and combination of parameters to the variance of the model output (here the Nash-Sutcliffe) in an efficient way. The quantification of the sensitivity of the model output to the parameters led to the identification of the most influential parameters. Differences between the Aire and the Ouse were found, reflecting their different water quality regime. Results highlighted the importance of interactions between two, or more, parameters on the model output. It led to question the one-at-a-time calibration method currently applied with QUESTOR and underlined the importance of including interactions between parameters in sensitivity analyses. Comparison of the relative influence of parameters versus input data showed contrasting results. In the urban system, the inputs from discharges (sewage treatment works and industrial effluents) were highly influential on model outputs and generally more important than the model parameters. For the rural river, the tributary discharges were most influential, but only at a similar or a lower level than the model parameters.     

Simulating the impacts of future land use and climate changes on surface water quality in the Des Plaines River watershed, Chicago Metropolitan Statistical Area, Illinois

Modeling the effects of past and current land use composition and climatic patterns on surface water quality provides valuable information for environmental and land planning. This study predicts the future impacts of urban land use and climate changes on surface water quality within Des Plaines River watershed, Illinois, between 2010 and 2030. Land Change Modeler (LCM) was used to characterize three future land use/planning scenarios. Each scenario encourages low density residential growth, normal urban growth, and commercial growth, respectively. Future climate patterns examined include the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenario (SRES) B1 and A1B groups. The Soil and Water Assessment Tool (SWAT) was employed to estimate total suspended solids and phosphorus concentration generated at a 10 year interval. The predicted results indicate that for a large portion of the watershed, the concentration of total suspended solids (TSS) would be higher under B1 and A1B climate scenarios during late winter and early spring compared to the same period in 2010; while the summer period largely demonstrates a reverse trend. Model results further suggest that by 2020, phosphorus concentration would be higher during the summer under B1 climate scenario compared to 2010, and is expected to wane by 2030. The projected phosphorus concentrations during the late winter and early spring periods vary across climate and land use scenarios. The analysis also denotes that middle and high density residential development can reduce excess TSS concentration, while the establishment of dense commercial and industrial development might help ameliorate high phosphorus levels. The combined land use and climate change analysis revealed land use development schemes that can be adopted to mitigate potential future water quality impairment. This research provides important insights into possible adverse consequences on surface water quality and resources under certain climate change and land use scenarios.