A new methodology for water resources multicriteria decision making under uncertainty

A multiciteria decision making problem in water resource is addressed through the generation of fuzzy Pareto optimal set. Methodology is using positive and negative ideal solutions (Lai, Y.-J., Liu, T.-Y., Hwang, C.L. (1994). TOPSIS for MODM. European Journal of Operational Research 76, 486-500) and a set of weights assigned to the objective functions in fuzzy triangular form. Solution of the problem is obtained by transforming each objective function into a set of three objective functions. A planning problem of multicriteria waste water treatment from the literature is used as an illustrative example to demonstrate the utility of the proposed methodology. The obtained fuzzy Pareto solution set has been compared with the deterministic solution set. It is shown that the proposed approach can: (a) capture the uncertainty associated with the assignment of weights; and (b) provide the decision makers with a wider range of solutions to select from.     

Estimation of river flow by artificial neural networks and identification of input vectors susceptible to producing unreliable flow estimates

Reliable river flow estimates are crucial for appropriate water resources planning and management. River flow forecasting can be conducted by conceptual or physical models, or data-driven black box models. Development of physically-based models requires an understanding of all the physical processes which impact a natural process and the interactions among them. Since identification of the relationships among these physical processes is very difficult, data-driven approaches have recently been utilized in hydrological modeling. Artificial neural networks are one of the widely used data-driven approaches for modeling hydrological processes. In this study, estimation of future monthly river flows for Guvenc River, Ankara is conducted using various artificial neural network models. Success of artificial neural network models relies on the availability of adequate data sets. A direct mapping from inputs to outputs without consideration of the complex relationships among the dependent and independent variables of the hydrological process is identified. In this study, past precipitation, river flow data, and the associated month are used to predict future river flows for Guvenc River. Impacts of various input patterns, number of training cycles, and initial values assigned to the weights of the connections are investigated. One of the major weaknesses of artificial neural networks is that they may fail to generate good estimates for extreme events, i.e. events that do not occur at all or often enough in the training data set. It is very important to be able to identify such unlikely events. A fuzzy c-means algorithm is used in this study to cluster the training and validation input vectors into regular and extreme events so that the user will have an idea about the risk of the artificial neural network model to generate unreliable results.     

Fuzzy robust process capability indices for risk assessment of air pollution

Air pollution is one of the most important threats for the humanity. It can damage not only human health but also Earth’s ecosystem. Because of the harmful effects of air pollution, it should be controlled very carefully. To do the risk assessment of air pollution in Istanbul, the process capability indices (PCIs) which are very effective statistics to summarize the performance of process are used in this paper. Fuzzy PCIs are used to determine the levels of the air pollutants which are measured in different nine stations in Istanbul. Robust PCIs (RPCIs) are used when air pollutants have correlation. Fuzzy set theory has been applied for both PCIs and RPCIs to have more sensitive results. More flexible PCIs obtained by using fuzzy specification limits and fuzzy standard deviation are used to evaluate the air pollution’s level of Istanbul. Additionally some evaluation criteria have been constructed for fuzzy PCIs to interpret the air pollution.     

Modeling Monthly Mean Flow in a Poorly Gauged Basin by Fuzzy Logic

The estimation of the monthly mean flow is a critical issue in many water resource development projects. However, in practice the mean flow is not easily determined in ungauged and poorly gauged basins. Therefore, in the literature, various flow estimation methods have been developed recently for mountainous regions which are generally ungauged or poorly gauged basins. In this study a fuzzy logic model based on the Mamdani approach was developed to estimate the flow for poorly gauged mountainous basins. This model was applied to the Solakli Basin which is located in the Eastern Black Sea Region of Turkey. Limited rainfall and flow data are available for this basin. In addition to these variables, the stream and time coefficients were introduced and used as variables for modeling. The data was divided into training and testing phases. The model results were compared with the measured data. The comparison depends on seven statistical characteristics, four different error modes and the contour map method. It was observed that the fuzzy model developed in this study yielded reliable results.     

Flow Discharge Modeling in Open Canals Using a New Fuzzy Modeling Technique (SMRGT)

The main goal of this study was to research the answer to two important questions in flow modeling; i) how to optimally design the cross‐section of an open channel for a given flow, and ii) in the case of selecting the fuzzy method for modeling, how to construct the membership functions (MFs) and fuzzy rules (FRs) such that the system yields the best results. The first question is answered in order to minimize difficulties in excavation and related costs by using the appropriate flow velocity. To provide the best answer researchers use several methods. The second question is answered in order to minimize model error. For this aim, there are many algorithms proposed by researchers in the literature. In this paper, the fuzzy logic method was used for open canal flow modeling. Furthermore, a simple membership function and fuzzy rule generation technique (SMRGT) is introduced, and used for fuzzy modeling. Two fuzzy models, each for different cross‐sectional shape, are presented in this study as an application of SMRGT. The comparison depends on various statistics, mean absolute relative error, and contour maps showed that the fuzzy models were successful in open channel flow modeling and SMRGT is useful for MF (membership function) and FR (fuzzy rule) generation.     

应用模糊综合评判方法对青海省水资源承载力评价研究

应用模糊综合评判方法对青海省水资源承载能力进行了分析评价。探讨了水资源承载能力模糊综合评价的方法,在对青海省水资源特征及开发利用等对承载能力影响的主要因素分析基础上,在评价因素选取、权重分配方面对水生态环境、生态用水因素给予重点考虑。结果表明,青海省水资源有较大开发容量,水资源承载能力的潜力相对较大。青海省水资源开发利用条件和程度不平衡,西宁市出现工程和水质型缺水,内陆河流域共和盆地和黄河一级支流湟水河流域水资源开发利用已达到极限水平。内陆河流域的格尔木河、巴音河的社会用水量和缺水量较大,资源性缺水严重。     

Valuation of in-stream water quality improvement via fuzzy contingent valuation method

Society benefits from rivers in many aspects. To the extent of water resources management, one of the salient issues is that the social benefit of in-stream water quality improvements is often difficult to be quantified for possible cost justification in many water pollution control programs. The difficulties arise from that many service flows of water quality are not channelled through the market system to consumers and producers. With different socio-economic structures, such valuation could be even more challenging when taking river basins with low-income level into account. Recent advances in fuzzy set theory provide a germain insight to viewing the in-stream water quality as a kind of fuzzy resource due to varying awareness of the quality of life. This paper provides a technical analysis using the fuzzy contingent valuation mothod (FCVM) to value in-stream water quality improvements in terms of three fuzzy resources from aesthetic to recreational, and to ecological aspects. Traditional CVM may allow interest groups or affected parties to join and present a more flexible asset assessment with respect to the prescribed environmental features in the river corridor. Yet the FCVM provides a mechanism that lies in providing a mapping (via fuzzy set theory) from a survey of respondents valuation of subjective assessments of water quality into objective economic measures in terms of water quality parameters that management can more directly manipulate. With this new tool, the traditional CVM assessment outputs in a well-developed river basin may even lead to derive a simular valuaton function in a form of a regression equation in a developing river basin where the incme level is relatively low. As part of the sustainablity analysis basin wide, a case study in Taiwan showed that such effort may provide supportive information for cost benefit analysis in many water pollution control programs corresponding to different temporal and spatial scales.     

Distinguishing climatic from direct anthropogenic influences during the past 400 years in varved sediments from Lake Holzmaar (Eifel,Germany)

A 336-year floating varve chronology from Lake Holzmaar (Eifel, Western-Germany) covering the recent period has been established by microfacies analysis of thin sections. This sequence terminates 23 cm below the core top. In the top 23 cm, the varves are disturbed. By means of linear regression, the varve sequence was dated to the period AD 1607–1942. The influences of climatic variability and anthropogenic activities in the lakes catchment (e.g., forestry, agriculture) on lithology, fabric, and microfossil content of the varve sublaminae could be discriminated by applying statistical analyses (ordination and clustering) to the combination of the sublaminae in the varves and their thickness. Four clusters are obtained. Cluster 1 indicates cold springs, and shorter, cooler summers reflected primarily in below-average varve thickness (VT) for two stable phases: from AD 1650–1700 (during the Maunder Minimum) and from AD 1750–1785. Cluster 2 indicates years with conditions transitional to that indicated by cluster 1, characterized by vigorous and prolonged spring circulation with massive blooms of the nordic-alpine Aulacoseira subarctica. The samples assigned to Cluster 3 and Cluster 4 show the imprint of anthropogenic influences. Cluster 3 (AD 1795–1815 and AD 1825–1885) is characterized by above-average VT due to high detritus input throughout the year. The increased soil erosion can be linked to anthropogenic deforestation as a consequence of the production increase of the Eifelian iron industry at the end of the 18th century. This input dampens the climatic signal of a colder Dalton Minimum, which is reflected in a short drop in VT centered around AD 1810. At about AD 1885, Cluster 4 conditions, characterized by increased nutrient concentrations, low detritus input, and longer periods of stable summer stratification, become the stable state in Lake Holzmaar. They indicate the response of the lake to natural reforestation and the use of artificial fertilizers in the catchment, which began, according to historical records, in the 1850s in the Eifel region. The prolonged, stable summer stratification periods may be the first indication of the modern warming trend. A drop in VT centered around AD 1890 and recurring cluster-1 conditions may indicate the Damon Minimum.     

成都市居民夏季舒适度的评判及分析

本文通过成都市1960～1984年夏季(7月)居民舒适度的模糊综合评判,论证了成都市因城市发展所带来的气候变化而引起的人体舒适度各级指标的变化规律,并应用主成份回归分析讨论了在城市发展各类指标中影响居民夏季舒适度的主要因子是:城市植树造林、房屋密度等,从而为成都市的规划建设等方面提供了具有实际参考价值的依据。