Water quality analysis in rivers with non-parametric probability distributions and fuzzy inference systems: Application to the Cauca River,Colombia

The integration of water quality monitoring variables is essential in environmental decision making. Nowadays, advanced techniques to manage subjectivity, imprecision, uncertainty, vagueness, and variability are required in such complex evaluation process. We here propose a probabilistic fuzzy hybrid model to assess river water quality. Fuzzy logic reasoning has been used to compute a water quality integrative index. By applying a Monte Carlo technique, based on non-parametric probability distributions, the randomness of model inputs was estimated. Annual histograms of nine water quality variables were built with monitoring data systematically collected in the Colombian Cauca River, and probability density estimations using the kernel smoothing method were applied to fit data. Several years were assessed, and river sectors upstream and downstream the city of Santiago de Cali, a big city with basic wastewater treatment and high industrial activity, were analyzed. The probabilistic fuzzy water quality index was able to explain the reduction in water quality, as the river receives a larger number of agriculture, domestic, and industrial effluents. The results of the hybrid model were compared to traditional water quality indexes. The main advantage of the proposed method is that it considers flexible boundaries between the linguistic qualifiers used to define the water status, being the belongingness of water quality to the diverse output fuzzy sets or classes provided with percentiles and histograms, which allows classify better the real water condition. The results of this study show that fuzzy inference systems integrated to stochastic non-parametric techniques may be used as complementary tools in water quality indexing methodologies.     

Sustainable supplier selection criteria classification for Indian iron and steel industry: a fuzzy modified Kano model approach

ABSTRACT

The aim of this work is to provide a systematic approach for sustainability criteria clustering into different useful categories. For this purpose, a methodology has been proposed with the following three steps. (i) A comprehensive set of the sustainability criteria in economic, environmental and social dimension has been extracted from the literature and have been customised for the iron and steel industry. (ii) A fuzzy Kano methodology has been used to classify these sustainability criteria into useful Kano cluster like must-be, one-dimensional, and attractive cluster (iii) further, must-be and attractive criteria derived from the second step were further sub-classified into three categories using Type IV Kano model. All steps have been examined in the iron and steel industry of India and findings indicate that quality and delivery criteria are classified as high must be criteria in the economic realm. Further, environmental and energy management system in the environmental dimension and social responsibility and right of stakeholders criteria in the social dimension are classified as high must be criteria. Prioritising must be and attractive criteria enable decision makers of other industries to select the appropriate criteria to adopt sustainability.     

Using fuzzy set theory to address the uncertainty of susceptibility to drought

This paper presents the technical aspects of a new methodology for assessing the susceptibility of society to drought. The methodology consists of a combination of inference modelling and fuzzy logic applications. Four steps are followed: (1) model input variables are selected—these variables reflect the main factors influencing susceptibility in a social group, population or region, (2) fuzzification—the uncertainties of the input variables are made explicit by representing them as ‘fuzzy membership functions’, (3) inference modelling—the input variables are used to construct a model made up of linguistic rules, and (4) defuzzification—results from the model in linguistic form are translated into numerical form, also through the use of fuzzy membership functions. The disadvantages and advantages of this methodology became apparent when it was applied to the assessment of susceptibility from three disciplinary perspectives: Disadvantages include the difficulty in validating results and the subjectivity involved with specifying fuzzy membership functions and the rules of the inference model. Advantages of the methodology are its transparency, because all model assumptions have to be made explicit in the form of inference rules; its flexibility, in that informal and expert knowledge can be incorporated through ‘fuzzy membership functions’ and through the rules in the inference model; and its versatility, since numerical data can be converted to linguistic statements and vice versa through the procedures of ‘fuzzification’ and ‘defuzzification’.     

基于可变模糊集理论及其模型的水利规划环境影响综合评价

地区水利规划环评处于起步阶段，存在评价形式化、方法单一化以及指标权重确定的主观性较强等问题。针对以往评价中的不足，提出了运用可变模糊集理论及其模型进行综合评价的方法。以江苏省水利发展规划作为研究实例，建立指标体系，采用模糊聚类循环迭代模型进行主客观综合指标权重的计算；从重点工程空间布局角度出发，运用调整后的可变模糊识别模型进行各市环境影响的相对优属度计算。结果表明，全省规划方案的环境影响相对优属度大于现状和零方案，南通市的相对优属度最大，其次是苏州和无锡。与层次分析法进行对比，该理论及其模型适用于地区水利规划环境影响综合评价     

区域水环境系统脆弱性指标体系及综合决策模型研究

目前水环境系统脆弱性研究主要局限于水环境系统的单方面脆弱性研究，过于片面化，需要综合考虑水资源、水环境质量、旱涝灾害、社会经济以及生态环境等方面的脆弱性。根据水环境系统脆弱性是系统状态受到系统压力引起的敏感性以及系统状态对系统压力的适应性响应的观点，采用“压力-状态-响应”模式构建区域水环境系统脆弱性指标体系。区域水环境系统脆弱性研究中客观存在诸多不确定性，利用联系数描述上述不确定性过程中差异度系数在［-1,1］上取值仍存在不确定性，为此，构造三角模糊数刻画差异度系数取值的不确定性，给出三角模糊联系数的基本形式，取置信水平得出置信区间联系数，采用期望-方差排序法对置信区间联系数进行决策分析，建立基于三角模糊联系数的系统综合决策模型。此模型用于安徽省水环境系统脆弱性评价的结果表明，安徽省区域水环境系统脆弱等级介于［2.731 3.620］之间，脆弱性状况不容乐观，应采取相应措施改善区域水环境质量，降低区域水环境系统脆弱性，保障区域社会经济及生态环境的可持续发展     

基于灰色模糊理论的流域水电规划环境影响综合评价

结合模糊优选理论和灰色关联分析方法,提出灰色模糊综合评价法,该方法将灰色关联分析作为优属度确定的隶属度计算方法;提出理想环境序列建立遵循的原则,引入梯形模糊数实现定性指标量化并采用变异系数法确定评价指标权重.应用灰色模糊综合评价法对黄河流域河段水电规划的高坝方案和多级开发方案进行了比选研究,计算了两个方案的优属度及其开发性因子、稳定性因子、保护性因子、经济活力因子、社会可接受因子、环境风险因子等6个指标层优属度,结果表明,多级开发方案总体优于高坝方案;多级开发方案的保护性远好于高坝开发方案,而高坝方案的开发性略好于多级开发方案,稳定性、经济活力、社会可接受、环境风险等因子两种方案比较接近.评价结果与流域实际情况比较符合,证明该方法是一种有效的方法.     

九江市地下水易污性评价——基于DPASTIC指标的模糊综合评价模型

从污染物入渗土壤-包气带-含水层的过程出发，以地质、地貌、水文地质条件为主控因素，选取地下水埋深〖WTBX〗(D)、降雨入渗补给量(P)、含水层岩性(A)、土壤类型(S)、地形坡度(T)、非饱和带介质(I)及含水层渗透系数(C)〖WTBZ〗7个指标，建立了九江市地下水易污性评价DPASTIC指标体系。结合模糊数学理论和方法，建立了基于DPASTIC指标的模糊综合评价模型。该模型克服了指标参数级别划分定额差异和指标值不连续性变化的缺陷，寻求出最优的级别定额划分状态和指标值的连续性变化情况；在指标级别定额划分上，引用了指标标准特征值的概念，根据实测参数数据资料，建立了10个级别的指标标准特征值矩阵，确定指标参数的最优相对隶属度。结合MAPGIS软件得出最后的地下水易污性分区，评价结果与规划区的实测及预测的水环境质量相吻合。     

河流综合水质评价方法比较研究

为探讨综合水质评价结论的科学合理性,对典型的7种河流综合水质评价方法,包括单因子评价法、污染指数法、模糊评价法、灰色系统评价法、层次分析法、人工神经网络法、水质标识指数法,在归类分析其特性的基础上,针对代表性的评价样本,进行了综合水质评价比较研究。主要结论为：①单因子评价法以最差水质指标所属类别作为综合水质类别,评价结论表现为过保护;②污染指数法能够直观判断综合水质是否达到功能区目标,但是不能判断综合水质类别;③对模糊数学法、灰色系统评价法、层次分析法、BP人工神经网络法和水质标识指数法等5种典型评价方法,当综合水质为Ⅰ~Ⅴ类水情形时,这几种方法评价结论基本一致,证明这5种典型评价方法对Ⅰ~Ⅴ类水的评价结论具有科学合理性;④当综合水质为劣Ⅴ类水时,模糊数学法、灰色系统评价法、层次分析法、BP人工神经网络法的评价结论偏保守,而水质标识指数法解决了劣Ⅴ类水质的连续性描述问题,能够对劣Ⅴ类水进行科学合理评价,并对Ⅰ~Ⅴ类水、劣Ⅴ类水不黑臭、劣Ⅴ类水黑臭进行全面、科学合理的定性与定量评价.     

Impacts of climate change on lakes and reservoirs dynamics and restoration policies

Meteorological-driven processes exert large and diverse impacts on lakes and their water quality; these impacts can be hydrologic, thermal, hydraulic, chemical, biochemical, or ecological. The impact of climate change on Lake Tahoe (California–Nevada) was investigated here as a case study of climate change effects on the physical processes occurring within lakes. The already published trends of meteorological variables were used to assess the effects of global warming on Lake Tahoe dynamics. Records from the period 1969–2002 show that Lake Tahoe has became warmer and more stable. A series of simulation years into the future (i.e., 2000–2040) was established using flows, loads, and meteorology data sets for the period 1994–2004. Results of 40-year simulations show that the lake continues to become warmer and more stable, and mixing is reduced. Possible changes in water quality because of global warming are discussed through inference, although these are not specifically simulated. Many existing problems may be exacerbated due to climate change, yet extreme uncertainty depends on the rate and magnitude of climate change. Therefore, shifts in water quality and quantity due to climate change should be integrated into contemporary planning and management in an adaptive manner, and the research and development of impact assessment methodology should focus on approaches that can handle extreme uncertainty. The general alternatives for lake management due to climate change are discussed. Depending on the specific case, further intensive research is suggested to restore lake water quality.     

A new approach to quantifying and comparing vulnerability to drought

In this study we develop an “inference modeling” approach to compare and analyze how different disciplines (economics, political science, and behavioral science/environmental psychology) estimate vulnerability to drought. It is thought that a better understanding of these differences can lead to a synthesis of insights from the different disciplines and eventually to more comprehensive assessments of vulnerability. The new methodology consists of (1) developing inference models whose variables and assertions incorporate qualitative knowledge about vulnerability, (2) converting qualitative model variables into quantitative indicators by using fuzzy set theory, (3) collecting data on the values of the indicators from case study regions, (4) inputting the regional data to the models and computing quantitative values for susceptibility. The methodology was applied to three case study regions (in India, Portugal and Russia) having a range of socio-economic and water stress conditions. In some cases the estimates of susceptibility were surprisingly similar, in others not, depending on the factors included in the disciplinary models and their relative weights. A new approach was also taken to testing vulnerability parameters by comparing estimated water stress against a data set of drought occurrences based on media analysis. The new methodologies developed in this paper provide a consistent basis for comparing differences between disciplinary perspectives, and for identifying the importance of the differences.

九江市地下水易污性评价——基于DPASTIC指标的模糊综合评价模型

从污染物入渗土壤-包气带-含水层的过程出发,以地质、地貌、水文地质条件为主控因素,选取地下水埋深(D)、降雨入渗补给量(P)、含水层岩性(A)、土壤类型(S)、地形坡度(T)、非饱和带介质(I)及含水层渗透系数(C)7个指标,建立了九江市地下水易污性评价DPASTIC指标体系.结合模糊数学理论和方法,建立了基于DPASTIC指标的模糊综合评价模型.该模型克服了指标参数级别划分定额差异和指标值不连续性变化的缺陷,寻求出最优的级别定额划分状态和指标值的连续性变化情况;在指标级别定额划分上,引用了指标标准特征值的概念,根据实测参数数据资料,建立了10个级别的指标标准特征值矩阵,确定指标参数的最优相对隶属度.结合MAPGIS软件得出最后的地下水易污性分区,评价结果与规划区的实测及预测的水环境质量相吻合.     

Design of automobile engines for remanufacture with quality function deployment

Parallel with the increase in environmental problems, the importance of design of environmentally friendly products has become more important together with the design for remanufacture. This paper presents the application of quality function deployment (QFD) methodology in the design of products for remanufacture. The main goal of this paper is to determine the engineering characteristics of automobile engines that firms have to focus on, in order to design automobile engines for remanufacture. In this paper, how a product can be designed for remanufacture using QFD and house of quality (HOQ) has been highlighted. A questionnaire survey was conducted on automobile engine refurbishing & remanufacturing facilities in order to find out what is required of the products which are remanufactured. With the establishment of the HOQ, the engineering characteristics that firms should focus on for designing automobile engines for remanufacture have been found as ‘position of the parts’ and ‘ types of parts used’.     

基于线性变换的水质综合评价方法

对于多个因子的水质综合评价存在很多不同方法,尚未形成公认的权威评价方法。因而,对水质综合评价方法进行探索有利于积累研究经验,丰富方法手段。在把数据向[0 1]区间标准化的基础上,通过线性空间变换,把水质样本数据与《地表水环境质量标准》(GB3838-2002)数据转换到同一线性空间。计算水质样本数据向量与5类水质划分等级标准数据向量的欧式距离,把欧式距离的最小值作为水质类别辨别的依据,最终得到水质的综合评价结果。借由已经公开发表的19个断面水质监测数据,运用大型工程计算软件Matlab 2010b进行计算,并与变权欧式距离模型、灰色聚类法、模糊综合指数法和BP神经网络法的评价结果相比较,符合性较好,验证了线性空间变换法应用于水质综合评价的科学性和合理性。方法可用于水质综合评价。在不对污染因子进行加权的情况下,基于线性变换的水质综合评价方法,获得的评价结果较轻。对于被评价为同一类水质的不同监测断面,可以借助"评价单元与5级水质标准的欧式距离矩阵",对评价单元水质差异进一步辨识。     

基于贝叶斯公式的湖泊富营养化随机评价方法及其验证

为了准确评价湖泊所处的营养状态,进而为湖泊富营养化的防治提供科学依据,提出了基于贝叶斯公式的湖泊富营养化随机评价方法。该法通过计算单个水质指标属于某个评价级别的概率,由最大似然分类原则确定单个水质指标的评价级别,并采用加权平均法推求湖泊富营养化多个水质指标的综合评价级别,具有方法简单、计算工作量小的特点。经全国30个湖泊实测水质资料的验证,随机评价方法与模糊评价方法和灰色评价方法相比较,有29个湖泊评价结果的差异小于等于一个级别,其比例为96.6％,说明这三种富营养化评价方法的计算精度相当。根据各项评价指标与叶绿素的相关系数,计算各项水质指标在富营养化评价中所占权重的方法,适用于浮游植物型湖泊,如果采取等权重方法,则适用于任何类型的湖泊。确定湖泊富营养化评价的水质指标个数和种类的选择具有不确定性,确定湖泊富营养化的评价级别和各个级别对应的水质标准浓度也具有不确定性,因此湖泊富营养化的评价方法具有不确定性。应采用多种途径对湖泊富营养化的评价方法进行研究,并取长补短,使评价结果更趋合理。     

The Fuzzy Synthesizing Evaluation of City''''s Environmental Quality Based on GIOWA Operator:A Case of 13 Cities of Jiangsu Province

1 INTRODUCTION In China, cities have been undergoing a rapid development in recent years. On the one hand, the level of urbanization rises continuously and a large population gathers in a city. The number and the scale of city increase and enlarge continuously. On the other hand, large population gathering in a city brings a huge pressure to the ecological environment of the city. The environmental pollution of the city is becoming more serious. This is a terrible and heavy cost for city…     

基于云推理和模糊逻辑关系模型的干旱等级预测方法研究

针对月平均降水量时间序列存在模糊性和随机性的特点,给出一种结合云推理和模糊逻辑关系的干旱等级预测方法。采用徐州站1951~2014年逐月降水量数据,通过计算标准化降水指数(SPI),得到实测干旱等级序列,以1952~2013年SPI指数数据作为样本数据,并提取样本模糊时间序列的52条模糊逻辑推理规则,将某月份的SPI指数数据作为输入变量,利用云发生器进行云推理,得到未来相应月份的干旱等级预测结果。结果表明,研究方法对干旱发生具有一定预测能力,尤其是对无旱的预测比较准确,但是对于干旱状态突变的预测能力较弱,主要是由于发生严重旱灾的可能性较少,导致模糊推理规则较少。因此,对于江苏省以轻旱为主的苏北地区,可以作为早期干旱预警的参考。     

基于区间直觉模糊集的水资源配置群决策研究

水资源问题是我国面临的重要资源与环境问题。流域水资源配置的有效性缺失也使水资源问题进一步恶化，而水资源配置过程中大量不确定信息也使高效决策问题更加困难。基于区间直觉模糊群决策的水资源配置方案优化方法，分析了水资源系统作为复杂系统的特殊性和区间直觉模糊理论在群决策中应用的优势，利用区间模糊数来表达专家判断信息，提高了流域水资源配置方案的合理性。通过多个水资源领域专家的群体决策，从流域水资源可持续利用评价视角出发，针对流域的社会、经济、资源、环境等多个因素进行判断，利用IIWAA算子进行群体意见集成，最后根据流域指标与理想点逼近点的距离对流域水资源配置方案排序。通过赣抚平原灌区内的用水区域在不同方案情景下的水资源可持续利用实例分析表明，该方法能够比较准确地评估出流域水资源配置方案的可持续性，为流域的水资源配置方案制定提供有效合理的决策支持     

中国环境质量的时空格局及影响因素研究——基于污染和吸收两个视角

提升环境质量是经济高质量发展的重要内涵和必然要求。基于环境污染和环境吸收两个视角，在综合大气、土壤、水体三大环境要素测算环境污染指数和吸收指数的基础上，结合环境质量影响因素的地域差异性，采用SDM模型分析全国及各地区环境质量的影响因素和空间效应。研究表明：（1）环境质量的空间集聚特征明显，地域不平衡问题突出，环境恶化的趋势没有得到根本性扭转；（2）重工业比重偏高是造成环境质量低的最主要原因；（3）东部地区环境质量与经济发展逐渐趋于协调，但人口集聚给环境带来较大负面影响。中、西部地区“高投入、高耗能、高污染、低效率”的发展模式成为提升环境质量的掣肘。最后，针对不同地区发展特点提出“硬治理”与“软治理”融合的差异化环境治理路径。     

群链产业合作模式下“京津冀”区域水资源优化配置研究

产业间的合作在不同区域中呈现出不同的形式,这会导致基于其建立的水资源合作联盟形式各异,进而会影响区域内合作水资源的整体收益。为优化"京津冀"区域内的水资源配置,本文基于产业合作的群链模式机理和模糊联盟博弈思想,提出了一种具有三阶段结构的"京津冀"区域水资源配置模式。在第一阶段,以满足"京津冀"区域居民生活用水需求并兼顾产业间的水资源配置公平为目标,通过构建水资源一次配置模型,进行区域内各用水主体间的一次配置;在第二阶段,针对"京津冀"区域内产业间合作的群链结构,分析产业间进行水资源模糊合作博弈可能出现的模糊联盟形式,进而构建出水资源二次配置模型以实现水资源收益(效率)最大化,二次配置模型采用"优先规则"建立各水资源合作模糊联盟的支付函数,将"京津冀"区域内所有产业用水主体在第一阶段配置中获得的水资源按一定比率配置到各联盟中;在第三阶段,考虑模糊联盟的稳定性,采用模糊shapley值法对第二阶段配置后各模糊联盟的收益分配给产业用水主体。本文运用算例对上述水资源配置模式的有效性进行了验证。算例分析结果显示:(1)"京津冀"区域内各产业间合作关系为群链模式时,各产业通过形成多种形式的水资源合作模糊联盟,获得比其单独利用水资源时更高的用水收益;(2)京津冀区域内各产业的总体用水收益也高于各产业单独利用水资源时的总用水收益。即本研究中的水资源配置模式有效。因此,该水资源配置模式可为产业合作关系为群链模式的区域,在进行产业间水资源优化配置时提供决策参考。