Groundwater contamination and its effect on health in Turkey

The sources of groundwater pollution in Turkey are identified, and pathways of contaminants to groundwater are first described. Then, the effects of groundwater quality on health in Turkey are evaluated. In general, sources of groundwater contamination fall into two main categories: natural and anthropogenic sources. Important sources of natural groundwater pollution in Turkey include geological formations, seawater intrusion, and geothermal fluid(s). The major sources of anthropogenic groundwater contamination are agricultural activities, mining waste, industrial waste, on-site septic tank systems, and pollution from imperfect well constructions. The analysis results revealed that natural contamination due to salt and gypsum are mostly found in Central and Mediterranean regions and arsenic in Aegean region. Geothermal fluids which contain fluoride poses a danger for skeleton, dental, and bone problems, especially in the areas of Denizli, Isparta, and Ayd?n. Discharges from surface water bodies contaminate groundwater by infiltration. Evidence of such contamination is found in Upper K?z?l?rmak basin, Gediz basin, and Büyük Melen river basin and some drinking water reservoirs in ?stanbul. Additionally, seawater intrusion causes groundwater quality problems in coastal regions, especially in the Aegean coast. Industrial wastes are also polluting surface and groundwater in industrialized regions of Turkey. Deterioration of water quality as a result of fertilizers and pesticides is another major problem especially in the regions of Mediterranean, Aegean, Central Anatolia, and Marmara. Abandoned mercury mines in the western regions of Turkey, especially in ?anakkale, ?zmir, Mu?la, Kütahya, and Bal?kesir, cause serious groundwater quality problems.     

Water quality trend analysis for the Karoon River in Iran

The Karoon River basin, with a basin area of 67,000 km², is located in the southern part of Iran. Monthly measurements of the discharge and the water quality variables have been monitored at the Gatvand and Khorramshahr stations of the Karoon River on a monthly basis for the period 1967–2005 and 1969–2005 for Gatvand and Khorramshahr stations, respectively. In this paper the time series of monthly values of water quality parameters and the discharge were analyzed using statistical methods and the existence of trends and the evaluation of the best fitted models were performed. The Kolmogorov–Smirnov test was used to select the theoretical distribution which best fitted the data. Simple regression was used to examine the concentration-time relationships. The concentration-time relationships showed better correlation in Khorramshahr station than that of Gatvand station. The exponential model expresses better concentration – time relationships in Khorramshahr station, but in Gatvand station the logarithmic model is more fitted. The correlation coefficients are positive for all of the variables in Khorramshahr station also in Gatvand station all of the variables are positive except magnesium (Mg²⁺), bicarbonates () and temporary hardness which shows a decreasing relationship. The logarithmic and the exponential models describe better the concentration-time relationships for two stations.     

Optimization models for siting water quality monitoring stations in a catchment

A water quality monitoring network (WQMN) must be designed so as to adequately protect the water quality in a catchment. Although a simulated annealing (SA) method was previously applied to design a WQMN, the SA method cannot ensure the solution it obtained is the global optimum. Therefore, two new linear optimization models are proposed in this study to minimize the deviation of the cost values expected to identify the possible pollution sources based on uniform cost (UC) and coverage elimination uniform cost (CEUC) schemes. The UC model determines the expected cost values by considering each sub-catchment being covered by which station, while the CEUC model determines the coverage of each station by eliminating the area covered by any upstream station. The proposed models are applied to the Derchi reservoir catchment in Taiwan. Results show that the global optimal WQMN can be effectively determined by using the UC or CEUC model, for which both results are better than those from the SA method, especially when the number of stations becomes large.     

A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

There are several deficiencies in the statistical approaches proposed in the literature for the assessment and redesign of surface water-quality-monitoring locations. These deficiencies vary from one approach to another, but generally include: (i) ignoring the attributes of the basin being monitored; (ii) handling multivariate water quality data sequentially rather than simultaneously; (iii) focusing mainly on locations to be discontinued; and (iv) ignoring the reconstitution of information at discontinued locations. In this paper, a methodology that overcomes these deficiencies is proposed. In the proposed methodology, the basin being monitored is divided into sub-basins, and a hybrid-cluster analysis is employed to identify groups of sub-basins with similar attributes. A stratified optimum sampling strategy is then employed to identify the optimum number of monitoring locations at each of the sub-basin groups. An aggregate information index is employed to identify the optimal combination of locations to be discontinued. The proposed approach is applied for the assessment and redesign of the Nile Delta drainage water quality monitoring locations in Egypt. Results indicate that the proposed methodology allows the identification of (i) the optimal combination of locations to be discontinued, (ii) the locations to be continuously measured and (iii) the sub-basins where monitoring locations should be added. To reconstitute information about the water quality variables at discontinued locations, regression, artificial neural network (ANN) and maintenance of variance extension (MOVE) techniques are employed. The MOVE record extension technique is shown to result in a better performance than regression or ANN for the estimation of information about water quality variables at discontinued locations.     

Spatiotemporal classification of environmental monitoring data in the Yeongsan River basin, Korea, using self-organizing maps

Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Evaluation of surface water quality characteristics by using multivariate statistical techniques: A case study of the Euphrates river basin, Turkey

The surface water quality of the Euphrates river basin in Turkey are evaluated by using the multivariate statistical techniques known as factor analysis (FA) and multidimensional scaling (MDS) analysis. When FA was applied to the water quality data obtained from the 15 different surface water quality monitoring stations, two factors were identified, which were responsible from the 86.02% of the total variance of the water quality in the Euphrates river basin. The first factor called the urban land use factor explained 44.20% of the total variance and the second factor called the agricultural use factor explained 41.81% of the total variance. MDS technique showed that electrical conductivity (EC), percent sodium (Na%) and total salt are the most important variables causing difference in the water quality analysis.     

2015年新疆阿克苏市沙尘污染与气象因素关系的分析

应用阿克苏市国家基准站及2个环保局监测站2015年大风沙尘天气过程前后PM10浓度变化及其与污染源、NECP全球再分析资料、风、监测站周边环境等关系进行分析.结果表明,阿克苏市春季沙尘天气的首要污染物均为PM10,PM10的变化曲线呈正态分布,春季中度及以上污染日均出现在污染日当日或次日.造成阿克苏市沙尘天气污染源分本地型、外来型以及二者共同影响型三种.本地型沙尘污染强度取决于北风风速大小及强风持续时间,PM10浓度变化与风速呈正相关.而外来型污染多发生在本地型沙尘天气之后,"东灌"冷空气裹挟沙尘进入南疆盆地,造成地面加压,浮尘天气造成PM10浓度增大,并持续数天.总结出沙尘天气污染预警的几个必要条件,后续在地区环保局、县局监测站建立的情况下,为分析阿克苏地区"八县一市"污染物与气象因素的关系提供借鉴,同时为实际的空气质量预警提供参考.     

应用物种DNA条形码识别太湖流域部分底栖无脊椎动物种类

将物种DNA条形码实际应用于太湖流域底栖无脊椎动物分类,并与形态学分类结果比对,结果表明,DNA条形码技术可应用于本流域底栖无脊椎动物分类,但现阶段无法替代形态学鉴定,主要原因是太湖流域底栖无脊椎动物的绝大多数物种COⅠ基因特征序列是未知的或是BLAST所拥有的分类程度不够,提出在今后的研究中应探索建立太湖流域底栖无脊椎动物COⅠ基因数据库。     

Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.     

太湖流域水生态监控系统平台构建研究

从太湖流域水生态监控管理需求出发,研究太湖流域水生态监控系统平台建设目标及建设内容,包括水生态监控数据管理子系统构建、水生态状况评价子系统构建、水生态模拟子系统构建和水生态辅助管理决策子系统构建。集成管理太湖流域水质监测数据、水生生物监测数据、基础地理信息数据,对各类数据进行一体化管理及深度挖掘,自动实现水生态状况评价;构建水生态模拟子系统,对水生态情景、污染物扩散、水生态功能区空间分布及变化趋势进行模拟,并提出水生态辅助决策方案及报告。     

Determination of total Cr in wastewaters of Cr electroplating factories in the I.organize industry region (Kayseri, Turkey) by ICP-AES

The wastewater pollution in industrial areas is one of the most important environmental problems. Heavy metal pollution, especially chromium pollution in the wastewater sources from electroplating, dyeing, and tannery, has affected the life on earth. This pollution can affect on all ecosystems and human health directly or by food chain. Therefore, the determination of total chromium in this study is of great importance. In this study, accurate, rapid, sensitive, selective, simple, and low-cost technique for the direct determination of total Cr in wastewater samples collected from the some Cr electroplating factories in March 2008 by inductively coupled plasma-atomic emission spectrometry has been developed. The analysis of a given sample is completed in about 15 min by this technique applied. As the result of the chromium analysis, the limit of quantification for the total Cr were founded to be over the limit value (0.05 mg L^???1; WHO, EPA, TSE 266, and inland water quality classification) as 1,898.78 ± 0.34 mg/L at station 1 and 3,189.02 ± 0.56 mg/L at station 2. The found concentration of total Cr has been determined to be IV class quality water according to the inland water classification. In order to validate the applied method, recovery studies were performed.     

Precipitable water modelling using artificial neural network in Çukurova region

Precipitable water (PW) is an important atmospheric variable for climate system calculation. Local monthly mean PW values were measured by daily radiosonde observations for the time period from 1990 to 2006. Artificial neural network (ANN) method was applied for modeling and prediction of mean precipitable water data in Çukurova region, south of Turkey. We applied Levenberg–Marquardt (LM) learning algorithm and logistic sigmoid transfer function in the network. In order to train our neural network we used data of Adana station, which are assumed to give a general idea about the precipitable water of Çukurova region. Thus, meteorological and geographical data (altitude, temperature, pressure, and humidity) were used in the input layer of the network for Çukurova region. Precipitable water was the output. Correlation coefficient (R²) between the predicted and measured values for monthly mean daily sum with LM method values was found to be 94.00% (training), 91.84% (testing), respectively. The findings revealed that the ANN-based prediction technique for estimating PW values is as effective as meteorological radiosonde observations. In addition, the results suggest that ANN method values be used so as to predict the precipitable water.     

Estimation of nonpoint source loadings with data obtained from limited sampling programs

The feasibility of estimating nonpoint source loadings with data obtained from limited sampling programs was analyzed in conjunction with a study of sediment and nutrient loadings in a Swedish river basin. The study showed that different loading estimation methods can yield significantly different results, even if sampling during events (e.g. peak flows) occurs. This was particularly true for the temporal distribution of the estimated loadings. The estimated spatial distribution of loadings in the monitored subbasins was more independent of the applied estimation technique. Theoretical calculations showed that sampling strategies with evenly spaced sampling intervals may systematically over- or underestimate the true loading.The study basin was characterized by a pronounced snowmelt period and partly erosion-controlled nutrient loadings. Guidelines for the estimation of nonpoint loadings in such basins are summarized in a matrix. Factors influencing the choice of estimation method include the characteristics of the collected data, the relative influence of point sources, and the desired detail of loading estimates. Possible correlations between flow and concentration, and the presence of extreme events (and whether or not the events were sampled), also determine the appropriateness of the different methods.     

Spatial properties of nutrient concentrations in the Baltic Sea

Using existing monitoring data, the present study attempts to characterize spatial patterns of surface water nutrients in the Baltic Sea. The analysis was made for two different spatial scales, differences between and within sub-basins.Non-parametric methods were chosen to reduce problems with the distributional properties of the data. By dividing the data into four seasons care was taken as to seasonality. To avoid bias due to different laboratory analysis, only data from Nordic countries were used, whose results did not apparently depart from each other. Bias due to different sampling frequency was another problem. This was reduced by using only the last observation in each season for every station and year.The results suggested differences in the nutrient concentrations between basins. The two northernmost basins (Bothnian Bay and Bothnian Sea) had lower phosphate concentrations and higher silicate concentrations compared to the rest of the Sea. Bothnian Bay and the Gulf of Finland had higher nitrate concentrations.The concentration structure within basins was studied using transects in both latitudinal and longitudinal direction. A gradient for phosphate and nitrate was found in the Gulf of Finland, with lower concentrations at the mouth. The Bothnian Sea showed lower concentrations in the middle of the basin compared to the coasts. The highest concentrations of phosphate were found close to the Finnish coast and for silicate the highest concentrations were located near the Swedish coast. It was not possible to study variation in the west-east direction within the Baltic proper, due to data shortage. For the transects in the north-south direction no differences were detected for nitrate and silicate. Phosphate gave one significant result during autumn for the transect in the eastern part of the Baltic proper.This study revealed several problems associated with the data available. Uneven sampling in space and time put severe constraints on the study. A better design of the monitoring program is suggested, where spatial properties are considered explicitly. Revision of the program in this direction is needed for reasonable calculation of total amounts and concentrations representative for a basin.     

Distribution of heavy metals in water, particulate matter and sediments of Gediz River (Eastern Aegean)

The present paper is the first document of heavy metal levels in surficial sediment, water and particulate matter of the Gediz River collected from five different sites in August, October 1998, February, June 1999. The present work attempts to establish the status of distribution and environmental implications of metals in the sediment, water and particulate matter and their possible sources of derivation. The concentrations of mercury ranged 0.037–0.81, 120–430; lead 0.59–1.5, 190–8,100; copper 0.24–1.6, 30–180; zinc 0.19–2.9, 10–80; manganese 30–170, 20–490; nickel 0.39–9.0, 100–510; iron 1.3–687, 100–6,200 μg/l in water and particulate matter, respectively. The maximum values in water were generally obtained in summer periods due to industrial and agricultural activities at Muradiye. The particulate metal concentrations also generally showed increased levels from the upper Gediz to the mouth of the river. Calculation of metal partition coefficients shows that the relative importance of the particulate and the water phases varies in response to water hydrochemistry and suspended solid content, but that most elements achieve a conditional equilibrium in the Gediz River. The metals ranged between Hg: 0.25–0.49, Cr: 59–814, Pb: 38–198, Cu: 15–148, Zn: 34–196, Mn: 235–1,371, Ni: 35–175, and Fe: 10,629–72,387 mg/kg in sediment. The significant increase of metals found in Muradiye suggested a pollution effect, related to anthropogenic wastes. Also, relatively high concentrations of Ni and Mn occurred in sampling site upstream, due to geochemical composition of the sediments. Maximum values of contamination factor for metals were noticed for sediment of Muradiye. The sampling stations have very high degree of contamination indicating serious anthropogenic pollution.     

Using the Sediment Quality Triad to characterize baseline conditions in the Anacostia River, Washington, DC, USA

The Sediment Quality Triad (SQT) consists of complementary measures of sediment chemistry, benthic community structure, and sediment toxicity. We applied the SQT at 20 stations in the tidal portion of the Anacostia River from Bladensburg, MD to Washington, DC to establish a baseline of conditions to evaluate the effects of management actions. Sediment toxicity was assessed using 10-day survival and growth tests with the freshwater amphipod, Hyalella azteca and the midge, Chironomus dilutus. Triplicate grabs were taken at each station for benthic community analysis and the Benthic Index of Biotic Integrity (B-IBI) was used to interpret the data. Only one station, #92, exhibited toxicity related to sediment contamination. Sediments from this station significantly inhibited growth of both test species, had the highest concentrations of contaminants, and had a degraded benthic community, indicated by a B-IBI of less than 3. Additional sediment from this station was tested and sediment toxicity identification evaluation (TIE) procedures tentatively characterized organic compounds as the cause of toxicity. Overall, forty percent of the stations were classified as degraded by the B-IBI. However, qualitative and quantitative comparisons with sediment quality benchmarks indicated no clear relationship between benthic community health and contaminant concentrations. This study provides a baseline for assessing the effectiveness of management actions in the Anacostia River.     

Landsat and limnologically derived water quality data: A perspective

Fixed station sampling is the conventional method used to obtain data on the median water quality of reservoirs. A major source of uncertainty associated with this technique is that water quality at the fixed stations may not be representative of the ambient water quality in the reservoir at the time of sampling. This problem is particularly relevant for water quality variables such as chlorophyll, which have a markedly patchy spatial distribution. The use of Landsat reflectance data to estimate median chlorophyll concentrations in Roodeplaat Dam was investigated. A linear polynomial regression model for estimating chlorophyll concentrations from Landsat reflectance data, was firstly calibrated with chlorophyll concentration data obtained by sampling seven fixed stations on the reservoir at the time of the satellite overflight to produce an individual calibration. Secondly, the model was calibrated with a pooled set of sampled data obtained from five separate overflights, to obtain a generalised calibration.It was found that median chlorophyll concentrations determined from Landsat-derived data were similar to median chlorophyll concentrations estimated from fixed station data. However, the range of chlorophyll concentrations in the reservoir estimated from Landsat data was considerably larger than that estimated from fixed station data. Landsat derived estimates of chlorophyll concentrations have the added advantage of providing information on the spatial distribution of chlorophyll in the reservoir.     

Integrating data-driven ecological models in an expert-based decision support system for water management in the Du river basin (Vietnam)

In this study, classification trees were combined with the Water Framework Directive (WFD)-Explorer, a modular toolbox that supports integrated water management in a river basin to evaluate the impact of different restoration measures on river ecology. First, the WFD-Explorer toolbox analysed the effect of different restoration options on the abiotic river characteristics based on the water and substance balance embedded in the simulation environment. Based on these abiotic characteristics, the biological index Biological Monitoring Working Party for Vietnam was then predicted by classification trees that were trained on biological and abiotic data collected in the Du river basin in northern Vietnam. The ecological status of streams in the basin ranged from nearly pristine headwaters to severely impacted river stretches. Elimination of point sources from ore extraction and decentralised domestic wastewater treatment proved to be the most effective measures to improve the ecological condition of the Du river basin. The combination of the WFD-Explorer results with data-driven models enabled model application in a situation where expert knowledge was lacking. Consequently, this approach appeared promising for decision support in the context of river restoration and conservation management.     

平顶山市湛河水水质预报模型研究

运用随机理论－－马尔科夫过程预报平顶山市湛河水质,并通过平顶山市湛河近十年的水质监测数据验证了模型的可靠性,对2000年前后湛河水质进行预报,为使2000年淮河流域水质变清,给平顶山市的管理层提供了一定的理论依据。