Investigating evidential reasoning for the interpretation of microbial water quality in a distribution network

Total coliforms are used as indicators for evaluating microbial water quality in distribution networks. However, total coliform provides only a weak “evidence” of possible fecal contamination because pathogens are subset of total coliform and therefore their presence in drinking water is not necessarily associated with fecal contamination. Heterotrophic plate counts are also commonly used to evaluate microbial water quality in the distribution networks, but they cover even a wider range of organisms. As a result, both of these indicators can provide incomplete and highly uncertain bodies of evidence when used individually. In this paper, it is shown that combing these two sources of information by an appropriate data fusion technique can provide improved insight into microbial water quality within distribution networks. Approximate reasoning methods like fuzzy logic and probabilistic reasoning are commonly used for data fusion where knowledge is uncertain (i.e., ambiguous, incomplete, and/or vague). Traditional probabilistic frameworks like Bayesian analysis, reasons through conditioning based on prior probabilities (which are hardly ever available). The Dempster–Shafer (DS) theory generalizes the Bayesian analysis without requiring prior probabilities. The DS theory can efficiently deal with the difficulties related to the interpretation of overall water quality where the redundancy of information is routinely observed and the credibility of available data continuously changes. In this paper, the DS rule of combination and its modifications including Yager’s modified rule, Dubois–Prade disjunctive rule and Dezert–Smarandache rule are described using an example of microbial water quality in a distribution network.     

Comparative analysis of two approaches to the assessment of water quality by biological indices: Case Study Of Dnieper tributaries

Water quality in several tributaries of the Dnepr in the southeastern part of its basin in the territory of the Republic of Belarus was estimated by six biotic indices and by the comparison with reference sites as accepted in the European Water Framework Directive. Water quality estimates obtained by different indices for the same sites are significantly different. The most adequate estimates were obtained from the British and Belgian indices for the assessment of the state of flowing waters. The comparative analysis of the two approaches showed that the method based on reference sites yields a more stringent estimate of river water quality than biotic indices.     

Earthquake hazard assessment in the Zagros Orogenic Belt of Iran using a fuzzy rule-based model

Producing accurate seismic hazard map and predicting hazardous areas is necessary for risk mitigation strategies. In this paper, a fuzzy logic inference system is utilized to estimate the earthquake potential and seismic zoning of Zagros Orogenic Belt. In addition to the interpretability, fuzzy predictors can capture both nonlinearity and chaotic behavior of data, where the number of data is limited. In this paper, earthquake pattern in the Zagros has been assessed for the intervals of 10 and 50 years using fuzzy rule-based model. The Molchan statistical procedure has been used to show that our forecasting model is reliable. The earthquake hazard maps for this area reveal some remarkable features that cannot be observed on the conventional maps. Regarding our achievements, some areas in the southern (Bandar Abbas), southwestern (Bandar Kangan) and western (Kermanshah) parts of Iran display high earthquake severity even though they are geographically far apart.     

Deriving reservoir operational strategies considering water quantity and quality objectives by stochastic fuzzy neural networks

By taking advantage of the close relationship between quality and quantity of water, we investigated the potential improvements of the in-reservoir water quality through the optimization of reservoir operational strategies. However, the few available techniques for optimization of reservoir operational strategies present some limitations, such as restrictions on the number of state/decision variables, the impossibility considering stochastic characteristics and difficulties for considering simulation/prediction models. One technique which presents great potential for overcoming some of these limitations is applied here and investigated for the first time in such complex system. The method, named stochastic fuzzy neural network (SFNN), can be defined as a fuzzy neural network (FNN) model stochastically trained by a genetic algorithm (GA) based model to yield a quasi optimal solution. The term “stochastically trained” refers to the introduction of a new loop within the training process which accounts for the stochastic variable of the system and its probabilities of occurrence. The SFNN was successfully applied to the optimization of the monthly operational strategies considering maximum water utilization and improvements on water quality simultaneous. Results showed the potential improvements on the water quality through means of hydraulic control.     

Intentional contamination of water distribution networks: developing indicators for sensitivity and vulnerability assessments

Performing a comprehensive risk analysis is primordial to ensure a reliable and sustainable water supply. Though the general framework of risk analysis is well established, specific adaptation seems needed for systems such as water distribution networks (WDN). Understanding of vulnerabilities of WDN against deliberate contamination and consumers’ sensitivity against contaminated water use is very vital to inform decision-maker. This paper presents an innovative step-by-step methodology for developing comprehensive indicators to perform sensitivity, vulnerability and criticality analyses in case of absence of early warning system (EWS). The assessment and the aggregation of these indicators with specific fuzzy operators allow identifying the most critical points in a WDN. Intentional intrusion of contaminants at these points can potentially harm both the consumers as well as water infrastructure. The implementation of the developed methodology has been demonstrated through a case study of a French WDN unequipped with sensors.     

Developing methods for bioidentification of xenobiotics for water quality assessment

The role of bioassay in the pollution control system for water bodies is considered. Studies of the mechanisms of toxic impact of various chemical compounds on aquatic organisms were used to develop a bioindication method to give an integral estimate of water toxicity and determine some classes of chemical pollutants. The results of application of such methods to assessing water quality in Lake Ladoga are given.     

Comparative analysis of fuzzy inference systems for water consumption time series prediction

Two types of fuzzy inference systems (FIS) are used for predicting municipal water consumption time series. The FISs used include an adaptive neuro-fuzzy inference system (ANFIS) and a Mamdani fuzzy inference systems (MFIS). The prediction models are constructed based on the combination of the antecedent values of water consumptions. The performance of ANFIS and MFIS models in training and testing phases are compared with the observations and the best fit model is identified according to the selected performance criteria. The results demonstrated that the ANFIS model is superior to MFIS models and can be successfully applied for prediction of water consumption time series.     

吡虫啉的本土物种敏感性分布及水质基准研究

吡虫啉是一种新烟碱类杀虫剂,环境中吡虫啉的残留会对水生生物产生潜在的慢性毒害作用,然而我国目前尚缺乏吡虫啉的淡水水生生物基准。为了构建吡虫啉的水质基准以及评估其对本土水生物种的生态风险,搜集筛选了吡虫啉对我国本土淡水水生生物的急慢性毒性数据,获得了来自5门14科的共21种急性毒性数据和来自5门11科的共15种慢性毒性数据。选取Log-normal和Log-logistic两种分布模型分别对毒性数据进行拟合以得到吡虫啉的物种敏感性分布。拟合优度检验结果表明Log-normal分布对急性和慢性数据均有更好的拟合效果。吡虫啉对我国本土水生物种的短期水质基准为6.95 μg/L,长期水质基准为0.47 μg/L,可作为保护我国水生生物的水质基准。采用风险商值法评估了吡虫啉在我国主要流域地表水的生态风险,结果显示研究区所包括流域地表水中78.95%的水体为低风险水体,15.79%的水体为中风险水体。本研究结论可为吡虫啉水质标准制定、水生生物保护和水生态环境管理提供科学依据。     

Grey fuzzy optimization model for water quality management of a river system

A grey fuzzy optimization model is developed for water quality management of river system to address uncertainty involved in fixing the membership functions for different goals of Pollution Control Agency (PCA) and dischargers. The present model, Grey Fuzzy Waste Load Allocation Model (GFWLAM), has the capability to incorporate the conflicting goals of PCA and dischargers in a deterministic framework. The imprecision associated with specifying the water quality criteria and fractional removal levels are modeled in a fuzzy mathematical framework. To address the imprecision in fixing the lower and upper bounds of membership functions, the membership functions themselves are treated as fuzzy in the model and the membership parameters are expressed as interval grey numbers, a closed and bounded interval with known lower and upper bounds but unknown distribution information. The model provides flexibility for PCA and dischargers to specify their aspirations independently, as the membership parameters for different membership functions, specified for different imprecise goals are interval grey numbers in place of a deterministic real number. In the final solution optimal fractional removal levels of the pollutants are obtained in the form of interval grey numbers. This enhances the flexibility and applicability in decision-making, as the decision-maker gets a range of optimal solutions for fixing the final decision scheme considering technical and economic feasibility of the pollutant treatment levels. Application of the GFWLAM is illustrated with case study of the Tunga–Bhadra river system in India.     

Methodical approach to distribution of epilithic and drifting algae communities in a French subalpine river: Inferences on water quality assessment

In a sub-alpine river, the Asse, with an unpredictable discharge regime, chlorophyll, density and taxonomic diversity of both drifting and periphytic communities were studied from a methodical approach. The investigations based on stamping two close cross-sections to know their spatial distributions in a heterogeneous bed substrate showed a heterogeneous pattern of colonization mainly influenced by hydrological variables as the current velocity, the size of the substrata (gravel-pebble-boulder). For the drifting algae, mainly composed with benthic species temporarily unhooked to the substrata, the heterogeneity of the distribution was reduced in fast flow which induced a mixing of the whole mass of water. For the periphyton, some results indicated that the greatest diversity and the highest chlorophyll concentration were found on pebble substratum where the current velocity was moderate. These results have also shown that the classical methods used to day for investigations were inadequate for most Mediterranean rivers. It was really difficult to estimate the water quality from classical index created for use in regular large plain rivers.     

Water quality and Cryptosporidium distribution in an upland water supply catchment,Cumbria, UK

Four micro‐catchment (MC) areas were identified to represent the main terrain types of a remote, sparsely populated upland valley catchment of 18 km² in Cumbria, UK. These were improved land with good grazing (IB), steeply sloping land with rough grazing (SG), wet moorland with sparse grazing (WM) and enclosed woodland that excluded livestock and deer (EW). Each MC contained the origin of a small stream that flowed into Swindale Beck, the river draining the valley. The water quality during the 14‐month study, as judged by chemical and physical parameters, was excellent, but it could not be regarded as pristine because of the frequent presence of Cryptosporidium oocysts arising from livestock and wild mammal faeces. Oocysts (0·2–5·6 l^?1) detected by genus‐specific immunofluorescent antibody were found in 32% of 188 water samples tested: ranking order EW 44%, IB 34%, Beck 30%, SG and WM 26%. Similarly, oocysts were identified in 9·5% of 1730 faecal samples. Small wild mammals (28%), calves (15·7%) and lambs (8·1%) were the dominant sources, whereas adult livestock (1·8%) and large wild mammals (4·8%) were less important. Autumn showed the highest occurrence of oocysts for both water and faecal samples. No hydrological controls were found to have a significant impact on the occurrence or concentration of oocysts in the main river or in the MCs, suggesting that their presence is controlled by seasonal changes in pathogen prevalence in the animal reservoir. Copyright © 2006 John Wiley & Sons, Ltd.     

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.     

Assessment of reliability in water distribution networks using entropy based measures

Entropy based expressions for measurement of reliability and redundancy have recently been reported. These measures approach assessment of the reliability of the distribution network from the intrinsic redundancy of the network layout. The paper extends earlier work on entropy functions by including a more explicit statement of the alternate paths available in the network and by recognizing that under certain circumstances, e.g., failure of some part of the network work, an outflow link from a node under normal working condition may become an inflow link to the same node. The measures are assessed by comparison with parameters measuring Nodal Pair Reliability and percentage of flow supplied at adequate pressure for a range of networks and link failure conditions in this networks. The entropy measures are shown to reflect changes in the network reliability, as measured by these two comparative parameters, very well.     

Comparative assessment of water treatment using polymeric and inorganic coagulants

Portable water plays a vital role in improving human life, particularly in controlling the spread of diseases. However, problems associated with lack of potable water are still common especially in developing countries including Malawi. Until now little information exists on the effectiveness of available commercial coagulants used by national water boards in Malawi. Therefore, this study was undertaken in Southern Region Water Board (SRWB) to investigate the efficiency of polymeric coagulants (sufdfloc 3850 and algaefloc 19s) in turbidity reduction comparative with inorganic coagulant (aluminium sulphate) at Zomba, Liwonde, Mangochi, Chikwawa and Mulanje Treatment plants. The jar test method was used to determine the effectiveness of the water coagulants. The results revealed that sudfloc 3850 was most effective in reducing turbidity at Mangochi (99.4 ± 0.06%) and Liwonde (97.2 ± 0.04%) using 0.4 mg L⁻¹ flocculant dose. The Zomba, Mulanje and Chikwawa plants gave 19.56 ± 0.03%, 29.23 ± 0.02% and 9.43 ± 0.02% total reductions respectively. Algaefloc 19s afforded the highest turbidity reduction at Liwonde and Mangochi plants (98.66 ± 0.06 and 97.48 ± 0.05% at a dose of 0.4 and 0.6 mg L⁻¹ respectively), while Chikwawa provided the lowest (9.52 ± 0.01%). At the Zomba and Mulanje plants 20.5 ± 0.03% and 28.4 ± 0.04% reductions were obtained respectively. The inorganic flocculant, alum provided a 99.0 ± 0.05% and 98.6 ± 0.04% reduction at a dose of 4.0 mg L⁻¹ and 6.0 mg L⁻¹ at Zomba and Liwonde plants respectively. The lowest reductions in turbidity were achieved at Chikwawa (7.50 ± 0.01%), Mangochi (12.97 ± 0.02%) and Mulanje (25.00 ± 0.02). The best and optimum pH ranges for polymeric and inorganic coagulants were 7.20–7.80 and 7.35 to 7.57 respectively. The results further revealed that sudfloc 3850 and algaefloc 19s achieved faster formation of heavy flocs than alum. At 0.4 mg L⁻¹ flocculant dosage sudfloc 3850 and algaefloc 19s required ten times lower dosages than alum. Therefore, the polymeric coagulants could be used instead of alum, the choice dependant on the type of water.     

Assessment of reliability in water distribution networks using entropy based measures

Entropy based expressions for measurement of reliability and redundancy have recently been reported. These measures approach assessment of the reliability of the distribution network from the intrinsic redundancy of the network layout. The paper extends earlier work on entropy functions by including a more explicit statement of the alternate paths available in the network and by recognizing that under certain circumstances, e.g., failure of some part of the network work, an outflow link from a node under normal working condition may become an inflow link to the same node. The measures are assessed by comparison with parameters measuring Nodal Pair Reliability and percentage of flow supplied at adequate pressure for a range of networks and link failure conditions in this networks. The entropy measures are shown to reflect changes in the network reliability, as measured by these two comparative parameters, very well.     

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.     

A two-phase grey fuzzy optimization approach for water quality management of a river system

An extension of the Grey Fuzzy Waste Load Allocation Model (GFWLAM) developed in an earlier work is presented here to address the problem of multiple solutions. Formulation of GFWLAM is based on the approach for solving fuzzy multiple objective optimization problems with max–min as the operator, which usually may not result in a unique solution. The multiple solutions of fuzzy multiobjective optimization model should be obtained as parametric equations or equations that represent a subspace. A two-phase optimization technique, two-phase GFWLAM, is developed to capture all alternative or multiple solutions of GFWLAM. The optimization model in Phase 1 is exactly same as the optimization model described in GFWLAM. The optimization model in Phase 2 maximizes the upper bounds of fractional removal levels of pollutants and minimizes the lower bounds of fractional removal levels of pollutants keeping the value of goal fulfillment level same as obtained from Phase 1. The widths of the interval-valued fractional removal levels play an important role in decision-making as these can be adjusted within their intervals by the decision-maker considering technical and economic feasibility in the final decision scheme. Two-phase GFWLAM widens the widths of interval-valued removal levels of pollutants, thus enhancing the flexibility in decision-making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.     

Inexact fuzzy two-stage programming for water resources management in an environment of fuzziness and randomness

A standard lower-side attainment values based inexact fuzzy two-stage programming (SLA-IFTSP) approach is proposed for supporting multi-water resources management under multi-uncertainties. The method improves upon the existing inexact two-stage stochastic programming by the introduction of a standard average lower-side attainment values based fuzzy linear programming. Multi-uncertainties such as intervals, probabilistic and/or possibilistic distributions and their combinations in water resources management can be directly communicated into the water allocation process. The risk of infeasibility caused by the random water availabilities can be analyzed by imposing economic penalties when the designed water allocations would not be satisfied after the occurrence of random seasonal flows. Based on the standard average lower-side attainment index, the fuzzy random relationships representing various subjective judgments in the model can be transformed into corresponding deterministic ones without additional constraints, and thus guarantee a higher computational efficiency. A hypothetical case regarding two-source water resources management is adopted for demonstrating its applicability. Reasonable solutions have been generated. They provide desired water allocations with maximized system benefit under different water availability levels. The solutions of intervals with different probabilities can be used for generating decision alternatives. Comparisons between the solutions from SLA-IFTSP and those from ITSP are also undertaken. They show that SLA-IFTSP can generate more reasonable water allocation patterns with higher net system benefits than ITSP.