模糊因子分析在地下水污染评估中的应用——以河南省洛阳市为例

传统的多元统计法难以定量化表征不同污染源对单个样本点的影响,本文引入了一种新的方法——模糊因子分析法.将该方法应用于洛阳市地下水污染来源解析研究,通过模糊聚类和因子分析对研究区样品进行分类,探明主要的污染源类型及其对整个研究区和单个样品点的污染贡献率.计算结果表明:洛阳市浅层地下水主要有以下四个污染源:基岩风化、加工制...     

模糊逻辑法在云南中甸地区铜矿潜力预测中的应用

模糊逻辑建模应用于矿产预测时分为两步:①变量模糊化,应用隶属函数计算变量的模糊隶属度;②模糊综合,应用模糊算子(模糊与、模糊或、模糊代数和、模糊代数积和伽马算子)对模糊化后的变量进行综合,生成最终的模糊有利度图.在介绍了模糊逻辑的基本原理和详细分析云南中甸铜成矿规律的基础上,应用ArcView GIS及其扩展模块ArcSDM对研究区地质、地球化学、线性构造等方面的数据进行了处理,提取了预测变量.模型应用于云南中甸普朗地区斑岩铜矿的区域成矿预测(1:20万)结果显示,预测出的成矿潜力区包含了81%以上的已知矿点,可以用于指导进一步的大比例勘查工作.     

模糊逻辑法在秦岭-松潘成矿区金矿潜力预测中的应用

在介绍模糊逻辑的基本理论、详细分析秦岭-松潘地区金成矿规律的基础上,应用ArcView GIS及其扩展模块Arc-SDM对研究区地质、地球化学、地球物理等数据进行处理,提取预测变量。已知的金矿（点）被用来构造研究区隶属度函数,确定各预测变量的隶属度大小。根据不同预测变量与金矿的相关性大小,选择不同的模糊算子进行综合,生成控矿因子。最后应用伽马算子,综合控矿因子,得到最终的秦岭-松潘金矿潜力图。根据金矿潜力图和模糊逻辑模型的检验结果,说明模糊逻辑可以对空间数据进行有效的综合,预测潜力图件中圈出的有利矿化区,可用于进一步勘查研究。     

基于博弈论综合权重模糊优选模型在地下水环境风险评价中的应用

地下水环境风险评价是地下水可持续利用的前提.目前,评价方法比较单一,主要为突变理论和单因素模糊理论,它们的控制变量数有限,不适用于多目标决策,同时也没有综合考虑主客观权重,评价结果不科学.本文针对以往评价方法的不足,应用基于主客观综合权重的多层多目标模糊可变优选模型评价.模型采用熵权法计算客观权重,二元对比法确定主观权重,并利用博弈论集结模型推导计算了综合权重,并以海河流域地下水环境为例进行了风险评价.计算实例表明,该模型能较好地考虑评价指标的主客观权重,适用于多层多目标评价系统.     

哈尔滨地区浅层地下水质量与污染评价

为查明哈尔滨地区浅层地下水水质现状及污染情况,利用松嫩平原（黑龙江）地下水污染调查评价项目的数据,对浅层地下水主要化学特征进行了描述.在此基础上采用模糊综合评价法进行了地下水质量评价,采用污染指数法进行了地下水污染现状评价.结果表明：研究区浅层地下水水化学类型以HCO₃-Ca型为主;受原生环境下水化学条件控制的Fe、Mn指标含量对水质影响较大;地下水污染属于区域性污染,污染范围广、污染程度重,主要污染物为NH₄⁺及NO₃^-、NO₂^-,来源于生活污水及农业生产所施用的化肥.根据分析数据,研究区地下水污染以无机污染为特征.     

PC-1500A计算机在地下水水质模糊综合评判中的应用

模糊集理论应用于地下水污染综合评价,是现阶段国内比较先进的方法之一。该方法用隶属函数描述水质分级,使本来具有模糊性的水质级别有了比较清晰的数量标准,从而使地下水污染的水平分带和垂向分带更趋于合理。本文从建立地下水污染通用线性隶属函数数学模型出发,以长春市东郊地下水污染的模糊综合评判为例,并应用PC—1500A计算机进行模糊综合评判,比较系统地介绍了该方法的应用。     

综合指数法和模糊综合法在地下水质量评价中的对比——以遵义市为例

综合指数法和模糊综合评价法在地下水质量评价中被广泛应用。岩溶地区地下水环境脆弱,潜在污染来源复杂。为了更好地了解综合指数法和模糊综合法在岩溶地下水评价中的应用效果,本文以贵州省遵义市为例,利用这两种方法分别对该市具有代表性的9个地下水点水质进行评价和对比分析。结果显示:遵义市浅层地下水水质总体较好,Ⅲ类及Ⅲ类以上水占33 %,但个别区域地下水水质很差,主要为NO2-、NH4+、Mn、Na+、Cl-、SO42-、溶解性总固体、总硬度(CaCO3)和Se等超标;两种方法评价结果一致的共有6个水点,均属Ⅱ类水质,结果不一致的3个水点,在综合指数法中全为Ⅳ类水,而在模糊综合评价中则是Ⅲ类水1个,Ⅴ类水两个。出现差异的主要原因是综合指数法在综合分值计算中过于强调单项指标最大值的作用和未考虑参评指标的权重,而模糊综合法则很好地克服了这些不足,精细地刻画出指标值对水质分级界限的接近程度并量化了所有指标对地下水水质的影响权重。可见,地下水水质评价中,模糊综合法要明显优于综合指数法。      

棕地地下水污染修复技术筛选方法研究——以某废弃化工厂污染场地为例

科学合理的地下水污染修复技术筛选方法对于有效修复受污染地下水体、节约修复工程成本、保护地下水资源、维护生态系统安全和人体健康具有重要意义。以某化工厂遗址早期排污渗坑为目标污染源,在结合水文地质勘查和地下水人体健康风险评价的基础上确定场地受污染地下水修复目标污染物,根据污染物迁移性、降解性、人体健康风险等指标及抽出处理、化学修复、生物修复、渗透反应格栅等地下水污染修复技术特点,使用偏好顺序结构评估法(PROMETHEE)进行修复技术筛选。结果显示,该场地地下水中主要污染物为1,2-二氯乙烷、1,4-二氯苯等有机污染物,其中1,2-二氯乙烷在呼吸吸入条件下的最大致癌风险达9.54×10-7。化学清除、监测自然衰减等四项技术适用于该场地地下水1,2-二氯乙烷修复,化学清除法综合排序分值最高,而在成本优先控制条件下,监测自然衰减技术更为适宜。研究对于我国场地地下水污染调查评估及修复工作具有积极的参考意义。     

包头市地下水质量评价

地下水质量评价为保护和开发地下水资源,防止和控制地下水污染,保障人民身体健康提供科学依据。结合相关地下水调查资料采用单指标评价、内梅罗指数和模糊综合评价三种方法,对包头市地下水水质分别进行评价,通过对评价结果综合分析认为:模糊综合评价结果更符合区域地下水总体特征,包头市潜水Ⅳ类、Ⅴ类占到取样点总数的36%,质量整体较差;承压水Ⅰ—Ⅲ类遍及包头市全区,质量整体较好。     

下辽河平原区辽阳-鞍山地段浅层地下水污染评价

随着城市规模和城市化进程的扩大与加快,工业化程度的不断提高,区域地表水和地下水受到不同程度的污染,人类赖以生存的淡水资源面临威胁.20世纪90年代以来,我国开始关注农业污染和有机污染的研究工作.结合研究区研究情况,本次评价主要应用单因子污染指数法及综合污染指数法.综合分析了地下水评价的各种方法后,本次评价选择了单指标污染指数评价法和地下水污染综合评价法对该区进行评价.在研究区展开了野外调查,采集了浅层地下水样品110组（其中包括平行样、加标样和监控样合计20组）,每个样品测试了35项指标.评价结果表明,研究区67.4%浅层地下水受到不同程度的污染.根据本次评价,基本上反映了研究区地下水污染状况,并为有针对性的治理提供依据.     

FRFI model application in groundwater non-point source pollution evaluation: a case study in the Luoyang Basin of North Henan province, China

The traditional non-point source (NPS) pollution models mainly focus on the flow path of NPS pollutants and attenuation during the flow. Extensive data set preparation and complex results analysis for these models are the most common problems encountered by the model user. In this study a new model, fuzzy-rough sets and fuzzy inference (FRFI), was introduced to evaluate groundwater NPS pollution. The proposed model involves two steps: the algorithm of fuzzy-rough sets attribute reduction (FRSAR) was applied to yield minimal decision rules from the fuzzy information system (FIS); the fuzzy inference technique was then used to forecast a groundwater synthesis pollution index based on the minimal decision rules. This model was applied in the Luoyang Basin, examining NPS pollution factors and hydrochemical variables data to validate the effectiveness of this model. The results indicate that it is only required to collect five NPS pollution factors or three hydrochemical variables; the groundwater synthesis pollution index can be predicted using the FRFI model. The prediction error is restricted to 2.9–6.1 % and 0.8–1.6 %, respectively. Therefore, the costs of computation and monitoring can be decreased, and the user is not required to prepare massive model parameters for the FRFI model. According to analyze the correlation between NPS pollution factors and hydrochemical variables, prevention measures are provided for treatment of the endemic disease and eutrophication. The FRFI model can be suitable for groundwater NPS pollution evaluation systems.     

Development of a GIS-based catastrophe theory model (modified DRASTIC model) for groundwater vulnerability assessment

This study developed a new paradigm for groundwater vulnerability assessment by modifying the standard DRASTIC index (DI) model based on catastrophe theory. The developed paradigm was called the catastrophe theory-based DI (CDI) model. The proposed model was applied to assess groundwater vulnerability to pollution index (GVPI) in Perak Province, Malaysia. The area vulnerability index was modeled by considering the DRASTIC multiple vulnerability causative factors (VCFs) obtained from different data sources. The weights and ranking of the VCFs were computed by using the inner fuzzy membership mechanism of the CDI model. The estimated vulnerability index values of the CDI model were processed in a geographic information system (GIS) environment to produce a catastrophe theory–DRASTIC groundwater vulnerability to pollution index (CDGVPI) map, which demarcated the area into five vulnerability zones. The produced CDGVPI map was validated by applying the water quality status–vulnerability zone relationship (WVR) approach and the relative operating characteristic (ROC) curve method. The performance of the developed CDI model was compared with that of the standard DI model. The validation results of the WVR approach exhibits 89.29% prediction accuracy for the CDI model compared with 75% for the DI model. Meanwhile, the ROC validation results for the CDI and DI models are 88.8% and 78%, respectively. The GIS-based CDI model demonstrated better performance than the DI model. The GVPI maps produced in this study can be used for precise decision making process in environmental planning and groundwater management.     

An interval fuzzy model for magnetic monitoring: estimation of a pollution index

In this contribution, a methodology is reported in order to build an interval fuzzy model for the pollution index PLI (a composite index using relevant heavy metal concentration) with magnetic parameters as input variables. In general, modelling based on fuzzy set theory is designed to mimic how the human brain tends to classify imprecise information or data. The “interval fuzzy model” reported here, based on fuzzy logic and arithmetic of fuzzy numbers, calculates an “estimation interval” and seems to be an adequate mathematical tool for this nonlinear problem. For this model, fuzzy c-means clustering is used to partition data, hence the membership functions and rules are built. In addition, interval arithmetic is used to obtain the fuzzy intervals. The studied sets are different examples of pollution by different anthropogenic sources, in two different study areas: (a) soil samples collected in Antarctica and (b) road-deposited sediments collected in Argentina. The datasets comprise magnetic and chemical variables, and for both cases, relevant variables were selected: magnetic concentration-dependent variables, magnetic features-dependent variables and one chemical variable. The model output gives an estimation interval; its width depends on the data density, for the measured values. The results show not only satisfactory agreement between the estimation interval and data, but also provide valued information from the rules analysis that allows understanding the magnetic behaviour of the studied variables under different conditions.     

Hydrogeochemical characterization and quality assessment of groundwater using self-organizing maps in the Hangjinqi gasfield area,Ordos Basin,NW China

Water resources are scarce in arid or semiarid areas,which not only limits economic development,but also threatens the survival of mankind.The local communities around the Hangjinqi gasfield depend on groundwater sources for water supply.A clear understanding of the groundwater hydrogeochemical characteristics and the groundwater quality and its seasonal cycle is invaluable and indispensable for groundwater protection and management.In this study,self-organizing maps were used in combination with the quantization and topographic errors and K-means clustering method to investigate groundwater chemistry datasets.The Piper and Gibbs diagrams and saturation index were systematically applied to investigate the hydrogeochemical characteristics of groundwater from both rainy and dry seasons.Further,the entropy-weighted theory was used to characterize groundwater quality and assess its seasonal variability and suitability for drinking purposes.Our hydrochemical groundwater dataset,consisting of 10 parameters measured during both dry and rainy seasons,was classified into 6 clusters,and the Piper diagram revealed three hydrochemical facies:Cl-Na type(clusters 1,2 and 3),mixed type(clusters 4 and 5),and HCO3-Ca type(cluster 6).The Gibbs diagram and saturation index suggested thatweathering of rock-forming mineralswere the primary process controlling groundwater chemical composition and validated the credibility and practicality of the clustering results.Two-thirds of 45 groundwater samples were categorized as excellent-or good-quality and were suitable as drinking water.Cluster changes within the same and different clusters from the dry season to the rainy season were detected in approximately 78%of the collected samples.The main factors affecting the groundwater quality were hydrogeochemical characteristics,and dry season groundwater quality was better than rainy season groundwater quality.Based on this work,such results can be used to investigate the seasonal variation of hydrogeochemical characteristics and assess water quality accurately in the others similar area.     

招远金矿区水体中硫同位素特征及其对污染来源的指示

稳定同位素因其指纹效应已成为分析矿区污染来源的重要技术手段。文章以招远金矿区为例,应用硫同位素联合水化学分析、聚类分析及氢氧同位素分析招远金矿区水污染特征和成因。通过分析可知,矿区内地表水和地下水主要接受大气降水补给,水力联系密切。水化学类型以SO₄—Ca和SO₄—Na型为主,阴离子以SO₄2-为主,地表水和地下水的NO₃-和Cl-在空间上变异性较大。地表水硫酸盐含量普遍偏高,硫酸盐污染较为严重,高值区出现在玲珑金矿、金翅岭金矿和张星镇附近;而地下水高值区都出现在玲珑金矿附近,且SO₄2-浓度沿着径流方向逐渐降低。地表水中硫酸盐δ34S值介于1.8‰~9.8‰,地下水中硫酸盐δ34S值介于2.7‰~9.6‰,地表水和地下水硫酸盐含量受玲珑金矿硫化、玲珑花岗岩和胶东岩群影响明显。在地下水径流途中,有地表水入渗污染地下水的现象。另外,工业废水的排放也是硫酸盐含量升高的主要原因。研究表明:硫同位素在金矿区硫酸盐污染的来源和特征方面有很好的指示作用,是评价矿山开采对地下水污染的有效工具。     

黄土梁峁地貌矿井水水质时空变异评估与关键控制因子水源识别

针对黄土梁峁地区砂岩-泥岩互层覆岩突水水源难以准确判别以及不同水源所占比例无法定量化问题,在系统采集了陕北朱家峁煤矿地表水、地下水水样基础上,采用数理统计、Piper三线图、Gibbs图、常规水化学特征比值法,揭示了不同含水系统水化学演化规律和水源补给关系。通过分析水体稳定同位素组成演变特征,明确了不同环境背景下各类水源水质时空变异性。在此基础上,以常规、同位素特征比因子作为判别指标,构建了基于T-球型模糊聚集算子TOPSIS法(T-TOPSIS)、粗糙集理论(RST)、D-S证据理论(DSET)与单指标未知测度函数(SIUMF)的突水水源混合比例计算模型。结果表明,研究区地表水、地下水水化学类型虽均以Na-SO4·Cl为主,但两者受控因素有着明显差别,即地表水水化学成分受硅酸盐岩风化和蒸发结晶共同控制;地下水成分则主要受控于蒸发结晶作用。此外,经历了强烈蒸发作用的地表水对地下水存在一定程度的补给作用。T-TOPSISRST-DSET-SIUMF突水水源混合比例判别模型表明,陕北朱家峁煤矿50%以上的突水水源为顶板砂岩水和地表沙空沟水。三维高密度电法探测结果验证了该模型的准确性。     

Application of multivariate statistical procedures on major ions and trace elements in a multilayered coastal aquifer: the case of the south Rhodope coastal aquifer

Multivariate statistical techniques including cluster analysis and principal components analysis were applied on 22 variables consisted of 3 physicochemical parameters, 8 major ions and 11 trace elements. Samples were collected from the south Rhodope multilayered coastal aquifer in north Greece which is facing saltwater intrusion and anthropogenic contamination over the last 35 years. Cluster analysis grouped the variables into five main groups while principal components analysis revealed four distinct hydrochemical processes in the aquifer system, explaining 84.5 % of the total variance between the variables. The identified processes correspond to, saltwater intrusion and subsequent reverse cation exchange, the presence of deep connate groundwater masses, application of fertilizers in shallow wells and anthropogenic contamination with heavy metals nearby an improperly constructed landfill. The wells categorized with the above techniques were grouped and five constituent ratios Na/Cl, (Mg + Ca)/Cl, Ca/(HCO₃ + SO₄), Ca/SO₄ and Ca/Mg were utilized to identify the ones which enable the more accurate distinction between the group cases. The results of stepwise discriminant analysis showed that the calculated classification function can distinguish almost 80 % of groundwater samples with the Na/Cl ratio being the most statistically significant grouping variable. All the aforementioned statistical models managed to successfully identify numerous hydrochemical processes in a complex multilayered aquifer system and to explicitly attribute them for every investigated well, allowing a deeper insight into groundwater chemical characteristics with the use of an optimized smaller number of variables.     

Assessment of natural and anthropogenic impacts in groundwater,utilizing multivariate statistical analysis and inverse distance weighted interpolation modeling: the case of a Scopia basin (Central Greece)

In Scopia basin, central Greece, a hydrochemical investigation was completed. Groundwater samples from 41 sites were used to assess the natural and anthropogenic impacts in groundwater, utilizing the principal component analysis (PCA) involved with the inverse distance weighted (IDW) interpolation modeling and hierarchical cluster analysis (HCA). Best fit model to explain the spatial distribution of both hydrochemical parameters and PCA was chosen by optimizing the IDW interpolator’s parameters. Precision of the model was picked based on less root-mean-squared prediction error (RMSPE) amongst predicted and actual values measured at the same locations. Groundwater exhibit Ca–Mg–HCO₃ as the dominant hydrochemical type and their greater part are mixed waters with non-dominant ion. Interpolation models demonstrate high estimations of nitrates in zones with agricultural activities and high estimations of nickel and chromium in regions with the strong presence of ultrabasic rocks. Dominant part of the groundwater samples surpasses in many cases the European Community (EC) drinking water permissible limits. Thus, they are unsuitable for human consumption. PCA illustrated four factors, which clarified 80.62% of the aggregate variance of data and HCA classified two statistically significant clusters of sampling sites. Results show natural procedures ascribed to the weathering of the minerals contained in the ultrabasic rocks and anthropogenic influences related to the use of fertilizers and wastewater leak. In light of FAO standards and Richards’s classification, the groundwaters are reasonable for irrigation purposes, featuring waters with low sodium hazard and moderate salinity hazard.