Risk assessment of groundwater pollution using sensitivity analysis and a worst-case scenario analysis

This paper illustrates how sensitivity analysis and a worst-case scenario analysis can be useful tools in risk assessment of groundwater pollution. The approach is applied to a study area in Hungary with several known groundwater pollution sources and nearby drinking water production wells. The main concern is whether the contamination sources threaten the drinking water wells of the area. A groundwater flow and transport model is set up to answer this question. Due to limited data availability, the results of this model are associated with large uncertainty. Sensitivity analysis and a worst-case scenario analysis are applied to estimate this uncertainty and build confidence in the model results.     

Prediction of agriculture derived groundwater nitrate distribution in North China Plain with GIS-based BPNN

In recent years, nitrate contamination of groundwater has become a growing concern for people in rural areas in North China Plain (NCP) where groundwater is used as drinking water. The objective of this study was to simulate agriculture derived groundwater nitrate pollution patterns with artificial neural network (ANN), which has been proved to be an effective tool for prediction in many branches of hydrology when data are not sufficient to understand the physical process of the systems but relative accurate predictions is needed. In our study, a back propagation neural network (BPNN) was developed to simulate spatial distribution of NO₃-N concentrations in groundwater with land use information and site-specific hydrogeological properties in Huantai County, a typical agriculture dominated region of NCP. Geographic information system (GIS) tools were used in preparing and processing input–output vectors data for the BPNN. The circular buffer zones centered on the sampling wells were designated so as to consider the nitrate contamination of groundwater due to neighboring field. The result showed that the GIS-based BPNN simulated groundwater NO₃-N concentration efficiently and captured the general trend of groundwater nitrate pollution patterns. The optimal result was obtained with a learning rate of 0.02, a 4-7-1 architecture and a buffer zone radius of 400 m. Nitrogen budget combined with GIS-based BPNN can serve as a cost-effective tool for prediction and management of groundwater nitrate pollution in an agriculture dominated regions in North China Plain.     

Using of neural networks for the prediction of nitrate groundwater contamination in rural and agricultural areas

As a neural network provides a non-linear function mapping of a set of input variables into the corresponding network output, without the requirement of having to specify the actual mathematical form of the relation between the input and output variables, it has the versatility for modeling a wide range of complex non-linear phenomena. In this study, groundwater contamination by nitrate, the ANNs are applied as a new type of model to estimate the nitrate contamination of the Gaza Strip aquifer. A set of six explanatory variables for 139 sampled wells was used and that have a significant influence were identified by using ANN model. The Multilayer Perceptrons (MLP), Radial Basis Function (RBF), Generalized Regression Neural Network (GRNN), and Linear Networks were used. The best network found to simulate Nitrate was MLP with six input nodes and four hidden nodes. The input variables are: nitrogen load, housing density in 500-m radius area surrounding wells, well depth, screen length, well discharge, and infiltration rate. The best network found had good performance (regression ratio 0.2158, correlation 0.9773, and error 8.4322). Bivariate statistical test also were used and resulting in considerable unexplained variation in nitrate concentration. Based on ANN model, groundwater contamination by nitrate depends not on any single factor but on the combination of them.     

Mapping groundwater contamination risk using GIS and groundwater modelling. A case study from the Gaza Strip, Palestine

Increasing pressure on water resources worldwide has resulted in groundwater contamination, and thus the deterioration of the groundwater resources and a threat to the public health. Risk mapping of groundwater contamination is an important tool for groundwater protection, land use management, and public health. This study presents a new approach for groundwater contamination risk mapping, based on hydrogeological setting, land use, contamination load, and groundwater modelling. The risk map is a product of probability of contamination and impact. This approach was applied on the Gaza Strip area in Palestine as a case study. A spatial analyst tool within Geographical Information System (GIS) was used to interpolate and manipulate data to develop GIS maps of vulnerability, land use, and contamination impact. A groundwater flow model for the area of study was also used to track the flow and to delineate the capture zones of public wells. The results show that areas of highest contamination risk occur in the southern cities of Khan Yunis and Rafah. The majority of public wells are located in an intermediate risk zone and four wells are in a high risk zone.     

Geological impacts on groundwater pollution: a case study in Khuzestan Province

The main aims of this study were to examine the sources of pollution with an emphasis on geogenic sources and to predict the groundwater quality with reasonable accuracy. For this purpose, factor analysis/principal component analysis and partial least squares regression were used to analyze a data set of groundwater quality containing 17 parameters measured at 45 different sampling wells in Andimeshk Aquifer during 2006–2013 time period. Factor analysis identified three factors, which were responsible for the data structure explaining 78.3 % of the total variance of the data set. There were various sources of groundwater contamination, based on factor analysis, in which geological formations next to agricultural activities had the most influential effects. Partial least squares regression could predict the quality of groundwater according to the value of water quality index. The amounts of R-squared (0.79) and MSE (0.21) using seven PLS components showed that this method has been successful in the prediction of water quality in the study area.     

A graphic expression of salinization and pollution of groundwater The case of Israel's groundwater

 Anthropogenic activities create various contaminated leachate, which can migrate downward from the vadose zone to groundwater, transferring contaminants, including some hazardous ones. When these various sources of contamination influence the groundwater aquifer simultaneously, the effects of contamination are enhanced. The major concern of this study has been to determine whether the shape of a groundwater chlorograph might be the result of such deterministic effects as accumulation of one or more particular processes of groundwater contamination, and how this might relate to specific hydrological situations. This study proposes a classification of groundwater contamination on the basis of properties of the main components of groundwater quality graphs and the corresponding hydrogeological/environmental situation. The study further suggests that contamination of groundwater in any hydrogeological situation (e.g. sea water) may be graphically expressed. A variety of chlorographs and nitrographs, representative of various groundwater aquifers sampled from a number of wells throughout Israel attest to this. The study thus indicates that groundwater quality graphs may be considered as a complementary tool for groundwater quality control and better understanding aquifer situations.     

基于信息熵技术对地下水观测网的层次分类--以河北平原地下水观测网为例

针对目前地下水观测网存在的层次不清问题，提出了基于信息熵技术的新的分类方法。列举了观测网层次混乱问题的表现、原因和可能造成的后果，提出地下水观测网具有层次性，而且这种层次性必须与地下水流动系统的层次性对应；认为地下水观测网就是一种信号通讯网，水位信号具有可传递性、差异性以及衰减性等特征，可以运用信息熵理论中的互信息概念定量刻画观测孔之间的信息联系，并以这种信息联系程度作为观测孔层次分类的主要依据；以河北平原地下水观测网为例，研究了区域尺度和局部尺度观测网的分类，结果表明信息熵方法可以很好地解决此类问题。     

应用信息熵方法对地下水观测网的层次分类——以河北平原地下水观测网为例

本文主要针对目前地下水观测网存在的层次不清问题，提出了基于信息熵理论新的分类方法。文章列举了观测网层次问题的表现，原因和可能造成的后果，提出地下水观测网的层次性应该对应地下水流动系统的层次性。认为地下水观测网就是一种信号通讯网，水位信号具有可传递性、差异性以及衰减性等特征，可以运用信息熵理论中的互信息概念，定量刻画观测孔之间的信息联系，并以这种信息联系程度作为观测孔层次分类的主要依据。作者以河北平原地下水观测网为实例，研究了区域尺度观测网的分类，结果表明信息熵方法可以很好地解决此类问题。     

Visual Modflow在石家庄市地下水硝酸盐污染模拟中的应用

利用Visual Modflow软件建立了石家庄市长达42 a的二维潜水水流模型和硝酸盐运移模型.收集整理大量地下水监测报告和研究报告提供的数据用于模型的建立,详细的地下水位和硝酸盐浓度监测数据以及不同时期的等水位线图用于模型校正.敏感度分析显示面状硝酸盐补给浓度是引起地下水NO3-浓度变化最敏感因子.利用校正的模型分3种管理方案预测了未来30 a内地下水硝酸盐浓度的变化.拟合、验证和预测结果显示该模型可作为石家庄市地下水管理的有效工具.     

全国地下水质分布及变化特征

以2013—2017年地下水监测站点水质监测数据为基础,统计地下水质监测指标的变化特征,筛查影响地下水质的主要指标,研究地下水质变化规律。选取2013—2017年具备连续监测数据的地下水监测井,对常规20项监测指标进行分析。研究发现:就监测站点水质指标而言,总硬度、铁、锰、“三氮”等超标率均达到了10%及以上,是导致地下水水质恶化的主要指标。总硬度超标集中在华北、东北、西南和西北地区的监测井,超标率在各省市间差别较大。氨氮超标率在各省市地区的监测井中差别较大,超标较为严重的省份是黑龙江、江苏、广东和宁夏。硝酸盐氮超标率年际变化稳定,华北、东北和西北地区的监测井中硝酸盐氮超标较为严重。亚硝酸盐氮超标在华北、东北和西北,以及上海、江苏、湖北、广西和贵州的监测井中较为严重。铁、锰超标主要集中在华北、华东、中南地区的监测井中,东三省、安徽、湖北、四川、宁夏等省份尤其严重。基于地下水监测井统计数据,在全国尺度上对地下水质量进行了综合分析评价,总结出了地下水监测中需要着重关注的指标,如“三氮”总硬度,铁、锰等。     

Assessing the vulnerability of over-exploited volcanic aquifer systems using multi-parameter analysis,Toluca Basin,Mexico

The potential for contamination of groundwater in an over-exploited system led to this investigation on aspects of aquifer vulnerability in the Toluca Basin, Mexico. This study involved the use of various hydrogeological, geochemical and isotopic tools to better understand the susceptibility to contamination where heavy groundwater extraction along with industrial extensive development is concentrated. Geochemical and isotopic analyses of groundwater from production wells along the mountain boundary show little evidence of contamination at present time. Radiocarbon and tritium data collected in piezometers and wells penetrating the Lower basalt aquifer indicate that the groundwater is of varying age and quality. These data, in addition to stable isotope and chemical data also indicate evidence of contamination in the Lower aquifer; which could be associated with fast recharge in the mountains or injection of waste water by illegal wells. Evidence found in this study of low downward gradients in the valley fill sediments and the presence of low permeability aquitard deposits suggest that the aquifer system is currently not highly threatened by surface sources of contamination. However, where urban and industrial development occurs, in the centre of the valley and along the flanks of the Basin, the vulnerability of the aquifer system increases significantly.     

Integrating an artificial intelligence approach with k-means clustering to model groundwater salinity: the case of Gaza coastal aquifer (Palestine)

Artificial intelligence (AI) techniques have increasingly become efficient alternative modeling tools in the water resources field, particularly when the modeled process is influenced by complex and interrelated variables. In this study, two AI techniques—artificial neural networks (ANNs) and support vector machine (SVM)—were employed to achieve deeper understanding of the salinization process (represented by chloride concentration) in complex coastal aquifers influenced by various salinity sources. Both models were trained using 11 years of groundwater quality data from 22 municipal wells in Khan Younis Governorate, Gaza, Palestine. Both techniques showed satisfactory prediction performance, where the mean absolute percentage error (MAPE) and correlation coefficient (R) for the test data set were, respectively, about 4.5 and 99.8% for the ANNs model, and 4.6 and 99.7% for SVM model. The performances of the developed models were further noticeably improved through preprocessing the wells data set using a k-means clustering method, then conducting AI techniques separately for each cluster. The developed models with clustered data were associated with higher performance, easiness and simplicity. They can be employed as an analytical tool to investigate the influence of input variables on coastal aquifer salinity, which is of great importance for understanding salinization processes, leading to more effective water-resources-related planning and decision making.     

开采条件下河北平原中部咸淡水界面下移

河北平原中部上层咸水入侵下层淡水已造成局部地下水污染,本文调查统计了地下水质监测资料和2700多眼深井孔的测井物探资料。以水化学方法和数理统计方法,从水文地质条件和地下水开采利用状况入手,对研究区咸淡水界面下移的机理进行了分析。结果认为,咸淡水界面从20世纪70年代以来年均下移约0.4m,开采地下水造成上下层水头压力变化,加大上部浅层水向下越流是其主要原因之一。     

A comprehensive study of the spread of radioactive contamination in the geological medium near Lake Karachai,Chelyabinsk oblast

The spread of radioactive contamination in the subsurface medium near Lake Karachai is considered. The complexity of this process requires a comprehensive approach to its study. The source of radioactive contamination is overviewed. The map of faults in subsurface medium is considered in order to determine the prevailing direction of contaminated groundwater flow. Photometry in observation wells has been used for structural geological estimation of transport properties of the shallow aquifer, where contaminated groundwater is moving. This study was carried out along with hydrochemical logging, which makes it possible to estimate the dynamics of contamination of subsurface medium and vertical distribution of groundwater contamination. Special attention is paid to transport of radionuclides in the form of radiocolloid particles. Groundwater samples were taken from various depths corresponding to different contamination levels near Lake Karachai. The depth intervals of sampling were determined from the data of hydrochemical logging. Ultrafiltration through membranes with a specific pore size in combination with gamma spectrometry was used to characterize radionuclide transfer with colloidal particles differing in size. The local elemental composition of the radiocolloid surface was studied by Auger spectroscopy. The chemical composition and structure of radiocolloid particles were determined by X-ray photoelectron spectroscopy with consecutive etching of the particle surface by argon ions for a certain depth. The data obtained indicate that radiocolloid particles are heterogeneous and an organic shell consisting of humic and fulvic acids and technogenic organic compounds coat their surface.     

Use of discriminant statistical analysis to determine the origin of an industrial pollution type in the aquiferous system of the area of Berrahal, Algeria

The continuous increase of industrial activities in the area of Berrahal (northeast of Algeria) resulted in an increase of waste disposal, inducing environmental pollution and contamination of groundwater. Available data on groundwater contamination were used to develop a statistical study for contaminated regions and to identify exposure scenarios of pollution. Chemical analysis of the samples shows that water of most wells and drillings is in bad quality or not drinkable, whereas statistical processing of these data by principal component analysis and discriminant factorial analysis suggests that wastewater coming from companies of the industrial park of Berrahal is very rich in organic pollutants (high percentages of BOD₅ and NO₂ ^?) and has high mineralization (has strong concentration in major elements and high electric conductivity); these constitute the main factors of the deterioration of the quality of this water. The considered exposure pathways were drinking water exploited from wells and drillings implanted in this area and its contact with soil (ingestion and dermal contact) that could threaten either humans or wildlife, on site or off site. In addition, groundwater was considered to be a potential risk pathway, especially for the ecosystem of Lake Fetzara and for the aquiferous system.     

中国69个城市地下水挥发性卤代烃污染检测与特征研究

为了初步掌握中国主要城市地下水挥发性卤代烃污染状况和特征,在中国69个城市开展了地下水挥发性卤代烃污染检测与特征研究,采集地下水样品791组,采样井均为工农业生产和生活饮用水水井;依据USEPA8260B检测方法,采用气相色谱／质谱联用分析仪器（P＆T—GC／MS）,分析和测试了氯仿、四氯化碳、1,1,1-三氯乙烷、三氯乙烯、四氯乙烯和二氯甲烷等15种挥发性卤代烃的质量浓度。结果表明：在791组地下水样品中,有406组样品至少有一种挥发性卤代烃组分被检出,检出率为51．33％;各组分中,氯仿的检出率最高,为20．35％,其他组分的检出率为0．25％～5．06％;氯乙烯在所有样品中均未检出;有13组样品的单项组分超标,超标率为1．64％;超标率由高到低分别为四氯化碳（0．76％）、氯仿（0．25％）、1,2-二氯乙烷（0．25％）、三氯乙烯（0．13％）、1,1,2-三氯乙烷（0．13％）、1,2-二氯丙烷（0．13oA）;超标井均为非供水水源地水井。检测与研究结果表明：中国主要城市地下水挥发性卤代烃污染物检出率较高,检测的69个城市中719／6的城市至少有一种挥发性卤代烃被检出,且潜水的检出率高于承压水,但总体超标率较低。     

The effect of vertical aquifer heterogeneity on the results of the simulation of contaminant migration in lateral groundwater flows

This study provides a solution for groundwater contamination problems. High anthopogenic loading on the water intake area makes it difficult to predict the migration of a contaminant to water supply wells, despite the known source location. Predictions were made using finite-difference grid models. The study provides an evaluation of the effects of the aquifer heterogeneity on the simulation results.     

Groundwater quality in the Niva River basin, Chittoor district, Andhra Pradesh, India

 This study was made to assess the groundwater quality in relation to agricultural and domestic uses in a part of the Peninsular Archean granite and gneissic complex of India. Water samples were collected from the existing wells in the Niva River basin, Chittoor district, Andhra Pradesh, India and analysed for major ions. The analytical data, processed and interpreted acoording to the WHO standards, reveal that, in general, the groundwater is suitable for both agricultural and domestic uses, exept in a few locations. High concentration of nitrates were observed in some of the wells (both agricultural and domestic) that are affected by the impact of industrial effluents. Multiple regression analysis was performed and used as a positive predictive tool in understanding the chemistry of the groundwater. Received: 2 May 1996 / Accepted: 14 October 1996     

Using geographical information systems to assess groundwater contamination from arsenic and related diseases based on survey data in Lahore,Pakistan

The present study was aimed at assessing the groundwater contamination from arsenic (As) and its impact on health from survey data in Lahore, Pakistan. OK (ordinary kriging) technique was used to create As and pH surfaces for samples from 380 groundwater wells at different locations and depths in the study area. Geographic information systems (GIS) was applied to delineate areas for safe, risk, and dangerous zones of As in drinking water from groundwater wells at 640 to 850 ft depths. To analyze effects of high As on public health, GIS-based field surveys were conducted to link health data along location of respondents to As contamination levels in the delineated safe, risk, and dangerous zones. Moreover, various pH levels and their effectiveness were studied to suggest cost-effective As treatment in the study area. Our results show that As contaminated strata varies with depth of groundwater wells, i.e., 44.50% areas comprising safe zone of drinking water from deep wells at 850 ft depth compared to 26% areas of shallow water at 640 ft depth. About 35% area with pH range (7 to 7.5) is marked in the risk and danger zones of As that can be initially targeted for treatment. Surveys confirm that people living in the risk and danger zones have some kind of As-related diseases.     

Application of Visual MODFLOW to simulation of migration in Cr6+ contaminated site

On the basis of site investigation and data collection of a certain electro plating factory, the groundwater flow and solute transport coupled models were established by applying Visual MODFLOW 4.1 software, which was used to conduct a numerical simulation that forecast the transport process of Cr6+ in groundwater. The results show that contamination plume of Cr6+ transports with groundwater flow direction. Without control measures, in 3 650 days, 19 wells for drinking would be contaminated, and the range of transport would be 52 172 m2, the maximum contamination would be 35.8 mg/L