Using multivariate statistical methods to assess the groundwater quality in an arsenic-contaminated area of Southwestern Taiwan

Groundwater is a major water resource in Southwestern Taiwan; hence, long-term monitoring of water quality is essential. The study aims to assess the hydrochemical characteristics of water in the arsenic-contaminated aquifers of Choushui River alluvial fan and Chianan Plain, Taiwan using multivariate statistical methods, namely, factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA). Factor analysis is applied to reveal the processes controlling the hydrochemistry of groundwater. Cluster analysis is applied to spatially categorize the collected water samples based on the water quality. Discriminant analysis is then applied to elucidate key parameters associated with the occurrence of elevated As concentration (>10 μg L(-1)) in groundwater. Major water types are characterized as Na-Ca-Cl and Na-Mg-Cl in the Choushui River alluvial fan and Chianan Plain, respectively. Inorganic species of arsenic (As), particularly As(III), prevail in these two groundwater catchments, and their levels are higher in the Chianan Plain than in the Choushui River alluvial fan. Through FA, three factors, namely, the degree of salination, As reduction, and iron (Fe) reduction, are determined and denoted irrespective of some differences between the factorial compositions. Spatial distribution patterns of factors As reduction and Fe reduction imply that the redox zonation is delineated by As- and Fe-dominance zones separately. The results of CA demonstrate that three main groups can be properly explained by the factors extracted via FA. Three- (Fe(2+), Fe(3+), and NH (4) (+) ) and four-parameters (Fe(2+), Fe(3+), NH (4) (+) , and Ca(2+)) derived from discriminant analysis for Choushui River alluvial fan and Chianan Plain are elucidated as key parameters affecting the distribution of As-contained groundwater. The analytical results indicate that the reductive dissolution of Fe minerals is prerequisite for the mobilization of As, whereas the shift of redox condition from Fe- to As-reducing leads to the accumulation of dissolved As in this area.     

Hydrochemical profile for assessing the groundwater quality of Sambhar lake City and its Adjoining area

Quality assessment of water is essential to ensure sustainable safe use of it for drinking, agricultural, and industrial purposes. For the same purpose the study was conducted for the samples of water of Sambhar lake city and its adjoining areas. The standard methods of APHA were used to analysis 15 samples collected from hand pumps and tube wells of the specified area. The analytical results show higher concentration of total dissolved solids, electrical conductivity sodium, nitrate, sulfate, and fluoride, which indicate signs of deterioration but values of pH, calcium, magnesium, total hardness, and carbonate are within permissible limits as per WHO standards. From the Hill-piper trilinear diagram, it is observed that the majority of groundwater from sampling stations are sodium?Cpotassium?Cchloride?Csulfate type water. The values of sodium absorption ratio and electrical conductivity of the groundwater were plotted in the US salinity laboratory diagram for irrigation water. Only the one sample fall in C₃S₁ quality with high salinity hazard and low sodium hazard. Other samples fall in high salinity hazard and high sodium hazard. Chemical analysis of groundwater shows that mean concentration of cation is in order sodium > magnesium > calcium > potassium while for the anion it is chloride > bicarbonate > nitrate > sulfate.     

Use of multivariate indicator kriging methods for assessing groundwater contamination extents for irrigation

Multivariate geostatistical approaches have been applied extensively in characterizing risks and uncertainty of pollutant concentrations exceeding anthropogenic regulatory limits. Spatially delineating an extent of contamination potential is considerably critical for regional groundwater resources protection and utilization. This study used multivariate indicator kriging (MVIK) to determine spatial patterns of contamination extents in groundwater for irrigation and made a predicted comparison between two types of MVIK, including MVIK of multiplying indicator variables (MVIK-M) and of averaging indicator variables (MVIK-A). A cross-validation procedure was adopted to examine the performance of predicted errors, and various probability thresholds used to calculate ratios of declared pollution area to total area were explored for the two MVIK methods. The assessed results reveal that the northern and central aquifers have excellent groundwater quality for irrigation use. Results obtained through a cross-validation procedure indicate that MVIK-M is more robust than MVIK-A. Furthermore, a low ratio of declared pollution area to total area in MVIK-A may result in an unrealistic and unreliable probability used to determine extents of pollutants. Therefore, this study suggests using MVIK-M to probabilistically determine extents of pollutants in groundwater.     

Statistical approaches for hydrogeochemical characterization of groundwater in West Delhi, India

Parametric statistical approaches, correlations and multiple linear regressions were used to develop models for the interpretation of hydrogeochemical parameters in the Western part of Delhi state, India. The hydrogeochemical parameters indicated that the groundwater quality is not safe for consumption. The water is moderately saline and the salinity level is increasing over time. There is also the problem of nitrate pollution. The correlation between electrical conductivity (EC) and other water quality parameters except potassium (K(+)), nitrate (NO(3)(-)) and bicarbonate (HCO(3)(-)) is significantly positive and Ca(++)+ Mg(++)/Na(+)+ K(+) is significantly negative. In predicting EC, the multiple R(2) values of 0.996 and 0.985 indicate that 99.6% and 98.5% variability in the observed EC could be ascribed to the combined effect of Na(+), HCO(3)(-), Cl(-), SO(4)(--), NO(3)(-) and Ca(++)+ Mg(++) for the year of 2005 and 2006 respectively. Out of 99.6% of the variability in EC in 2005, 51.2% was due to Cl(-) alone, and 8.5%, 12.5%, 6.1%, 14.7% and 6.7% were due to Na(+), HCO(3)(-), SO(4)(--), NO(3)(-) and Ca(++) + Mg(++). Similarly in 2006, out of 98.5% of the variability in EC, 48.5% was due to Cl(-) alone, and 10.4%, 12.7%, 5.3%, 17.2% and 4.4% were due to Na(+), HCO(3)(-), SO(4)(--), NO(3)(-) and Ca(++)+ Mg(++). The analysis shows that a good correlation exists between EC, Cl(-) and SO(4)(--) either individually or in combination with other ions and the multiple regression models can predict EC at 5% level of significance.     

Application of an environmental impact assessment methodology to a site discharging low levels of radioactivity to a freshwater environment in Norway

Significant shifts in opinion regarding environmental protection from ionising radiation have resulted in the development and availability of bespoke approaches for the assessment of impacts on wildlife from radioactive contaminants. The application of such assessment methodologies to actual situations, however, remains relatively limited. This paper describes the implementation of the ERICA Integrated Approach and associated tools within the context of routine discharges of radioactive materials to a freshwater environment. The article follows the implementation through its relevant stages and discusses strengths and weaknesses of the approach in relation to the case study. For current discharge levels, ¹³⁷Cs and ⁶⁰Co constitute the main dose contributors to the majority of reference organisms studied, although ²⁴¹Am and ³H are the main contributors for the phyto- and zooplankton categories. Patterns are observed depending on whether the reference organism is sediment-associated or not. At current discharge levels, none of the reference organisms exceeded or approached the selected screening level, and impacts on biota could be regarded as negligible.     

Joint application of an empirical and mechanistic model for regional lake acidification

The empirical direct distribution model for lake acidification is calibrated for use in an integrated assessment model which predicts the regional impact of an acid deposition control strategy. The calibration is based on the mechanistic Model of Acidification of Groundwater in Catchments (MAGIC). The models are applied jointly to a set of 33 statistically-selected lakes in the Adirondack region of New York. Calibration of the direct distribution model is based on a step-function application of acid deposition to MAGIC. Comparative evaluations of the resulting model predictions are made using historic deposition estimates and two alternative future deposition scenarios. The predictions of the direct distribution model match well the shapes and patterns of change of the regional distributions of ANC and pH predicted by MAGIC, the short- and medium-term dynamics of these changes, and the effect of including organic acids. However, small, long-term decreases in the fraction of incoming acid deposition neutralized by lakes and their watersheds predicted by MAGIC are not reproduced.     

The range fraction: an applied method to characterize regional groundwater responses to climate inputs

An important component of ongoing water-resource investigations in the eastern Great Basin, USA, has been to ascertain the impact of future predicted climate change on groundwater availability. As a first step in that analysis, it was hypothesized that potentiometric fluctuations at certain wells would reflect annual-scale precipitation variation. Potentiometric behavior at a well depends on local hydrologic conditions, well construction, and human activities, in addition to natural recharge and regional water levels. Moreover, measurement data are limited for many wells. After preliminarily screening, a large body of well and climate station data, short-term potentiometric responses to annual-scale climate inputs, were identified at 18 wells using a simple visualization methodology developed during the study. For water levels displaying multi-annual trends, the signals were measured as deviations from a linear trendline. Groundwater responses lagged precipitation signals by less than 1 year to as much as 3 years, with most wells showing at most a 1- to 2-year delay. Response amplitude was variable and strongly depended on the hydrologic setting of each well.     

Efficacy of electrical resistivity and induced polarization methods for revealing fluoride contaminated groundwater in granite terrain

The accumulation of fluoride (F) in groundwater is a common phenomenon in India and worldwide. Its location can be identified through a direct hydrochemical analysis, which was carried out in Kurmapalli watershed (located 60 km SE of Hyderabad city), Nalgonda district, Andhra Pradesh, India affected by F contamination. The results of the hydrochemical analysis showed that F varied from 0.71 to 19.01 mg/l and its concentration exceeded the permissible limit (i.e., 1.5 mg/l) in 78% of the total 32 samples analyzed. The highest F value (19.01 mg/l) was found near Madnapur village, which is located in the central part of the watershed. Resistivity and induced polarization (IP) surveys were also carried out to reveal the zones where elevated F-contaminated groundwater exists. The objective of this paper was to highlight the utility of resistivity and IP surveys, using hydrochemical constituents as constraint, for the successful delineation of such contaminated/polluted groundwater zones in the granite area.     

Comparison of stochastic and deterministic methods for mapping groundwater level spatial variability in sparsely monitored basins

In sparsely monitored basins, accurate mapping of the spatial variability of groundwater level requires the interpolation of scattered data. This paper presents a comparison of deterministic interpolation methods, i.e. inverse distance weight (IDW) and minimum curvature (MC), with stochastic methods, i.e. ordinary kriging (OK), universal kriging (UK) and kriging with Delaunay triangulation (DK). The study area is the Mires Basin of Mesara Valley in Crete (Greece). This sparsely sampled basin has limited groundwater resources which are vital for the island’s economy; spatial variations of the groundwater level are important for developing management and monitoring strategies. We evaluate the performance of the interpolation methods with respect to different statistical measures. The Spartan variogram family is applied for the first time to hydrological data and is shown to be optimal with respect to stochastic interpolation of this dataset. The three stochastic methods (OK, DK and UK) perform overall better than the deterministic counterparts (IDW and MC). DK, which is herein for the first time applied to hydrological data, yields the most accurate cross-validation estimate for the lowest value in the dataset. OK and UK lead to smooth isolevel contours, whilst DK and IDW generate more edges. The stochastic methods deliver estimates of prediction uncertainty which becomes highest near the southeastern border of the basin.     

An innovative technique for lake management with reference to aeration unit installed at lower lake, Bhopal, India

Water is key element in human life. All forms of life upon the earth depend upon water for their mere existence. Life & water may be aptly said to be two facets of the same coin. Most of the water bodies are getting polluted due to domestic waste, sewage, industrial waste and agricultural effluent. The present study is designed to ascertain the effectiveness of artificial aeration cum Ozonizer unit installed at Lower Lake, Bhopal for assessment of water quality. Various physico- chemical parameters like pH, Dissolved oxygen, Biochemical Oxygen demand, Chemical oxygen demand, nitrate, phosphate and bacteriological status were studied to assess the extent of deterioration in water quality of Lower lake and at the same time to assess the performance of the dual aeration system in improvement of water quality.     

Application of multivariate statistical methods for groundwater physicochemical and biological quality assessment in the context of public health

Three representative areas (lowland, semi-mountainous, and coastal) have been selected for the collection of drinking water samples, and a total number of 28 physical, chemical, and biological parameters per water sample have been determined and analyzed. The mean values of the physical and chemical parameters were found to be within the limits mentioned in the 98/83/EEC directive. The analysis of biological parameters shows that many of the water samples are inadequate for human consumption because of the presence of bacteria. Cluster analysis (CA) first was used to classify sample sites with similar properties and results in three groups of sites; discriminant analysis (DA) was used to construct the best discriminant functions to confirm the clusters determined by CA and evaluate the spatial variations in water quality. The standard mode discriminant functions, using 17 parameters, yielded classification matrix correctly assigning 96.97% of the cases. In the stepwise mode, the DA produced a classification matrix with 96.36% correct assignments using only ten parameters (EC, Cl^???, NO₃ ^???, HCO₃ ^???, CO₃ ^???2, Ca^?+?2, Na^?+?, Zn, Mn, and Pb). CA and factor analysis (FA) are used to characterize water quality and assist in water quality monitoring planning. CA proved that two major groups of similarity (six subclusters) between 17 physicochemical parameters are formed, and FA extracts six factors that account for 66.478% of the total water quality variation, when all samples’ physicochemical data set is considered. It is noteworthy that the classification scheme obtained by CA is completely confirmed by principal component analysis.     

The leachate composition of an old waste dump connected to groundwater: Influence of the reclamation works

This study has been carried out in an uncontrolled dump in the suburbs of Buenos Aires, Argentina. This dump still contains solid wastes of different types in direct contact with the human consumption aquifer. After 18 years of overturning the dump was closed in 1992, and the reclamation works started.Three leachate samplings were carried out in three different zones of the dump, selected according to the topography, the age of residues and the degree of water contact. These samplings were done before the reclamation works, at the end, and four months after they were finished. Several chemical parameters, including heavy metals in solid and dissolved fractions, were analyzed.Multivariate analysis (PCA) was performed to help to understand the effects of the labors on leachate composition. The works could be responsible for a temporal increase of dissolved heavy metals and several chemical variables in the leachate. At the sites of the dump where the modifications were carried out, the levels of some elements analyzed recovered their former values a few months after the reclamations works. At the farthest site, the impact and recovery effects of the works on leachate composition, were delayed.     

Numerical modelling of the groundwater inflow to an advancing open pit mine: Kolahdarvazeh pit,Central Iran

The groundwater inflow into a mine during its life and after ceasing operations is one of the most important concerns of the mining industry. This paper presents a hydrogeological assessment of the Irankuh Zn-Pb mine at 20 km south of Esfahan and 1 km northeast of Abnil in west-Central Iran. During mine excavation, the upper impervious bed of a confined aquifer was broken and water at high-pressure flowed into an open pit mine associated with the Kolahdarvazeh deposit. The inflow rates were 6.7 and 1.4 m³/s at the maximum and minimum quantities, respectively. Permeability, storage coefficient, thickness and initial head of the fully saturated confined aquifer were 3.5?×?10^?4 m/s, 0.2, 30 m and 60 m, respectively. The hydraulic heads as a function of time were monitored at four observation wells in the vicinity of the pit over 19 weeks and at an observation well near a test well over 21 h. In addition, by measuring the rate of pumping out from the pit sump, at a constant head (usually equal to height of the pit floor), the real inflow rates to the pit were monitored. The main innovations of this work were to make comparison between numerical modelling using a finite element software called SEEP/W and actual data related to inflow and extend the applicability of the numerical model. This model was further used to estimate the hydraulic heads at the observation wells around the pit over 19 weeks during mining operations. Data from a pump-out test and observation wells were used for model calibration and verification. In order to evaluate the model efficiency, the modelling results of inflow quantity and hydraulic heads were compared to those from analytical solutions, as well as the field data. The mean percent error in relation to field data for the inflow quantity was 0.108. It varied between 1.16 and 1.46 for hydraulic head predictions, which are much lower values than the mean percent errors resulted from the analytical solutions (from 1.8 to 5.3 for inflow and from 2.16 to 3.5 for hydraulic head predictions). The analytical solutions underestimated the inflow compared to the numerical model for the time period of 2–19 weeks. The results presented in this paper can be used for developing an effective dewatering program.     

Indicator and probability kriging methods for delineating Cu, Fe, and Mn contamination in groundwater of Najafgarh Block, Delhi, India

Two non-parametric kriging methods such as indicator kriging and probability kriging were compared and used to estimate the probability of concentrations of Cu, Fe, and Mn higher than a threshold value in groundwater. In indicator kriging, experimental semivariogram values were fitted well in spherical model for Fe and Mn. Exponential model was found to be best for all the metals in probability kriging and for Cu in indicator kriging. The probability maps of all the metals exhibited an increasing risk of pollution over the entire study area. Probability kriging estimator incorporates the information about order relations which the indicator kriging does not, has improved the accuracy of estimating the probability of metal concentrations in groundwater being higher than a threshold value. Evaluation of these two spatial interpolation methods through mean error (ME), mean square error (MSE), kriged reduced mean error (KRME), and kriged reduced mean square error (KRMSE) showed 3.52% better performance of probability kriging over indicator kriging. The combined result of these two kriging method indicated that on an average 26.34%, 65.36%, and 99.55% area for Cu, Fe, and Mn, respectively, are coming under the risk zone with probability of exceedance from a cutoff value is 0.6 or more. The groundwater quality map pictorially represents groundwater zones as ??desirable?? or ??undesirable?? for drinking. Thus the geostatistical approach is very much helpful for the planners and decision makers to devise policy guidelines for efficient management of the groundwater resources so as to enhance groundwater recharge and minimize the pollution level.     

Soil water, salt, and groundwater characteristics in shelterbelts with no irrigation for several years in an extremely arid area

This paper is based on long-term monitoring data for soil water, salt content, and groundwater characteristics taken from shelterbelts where there has been no irrigation for at least 5 years. This study investigated the distribution characteristics of soil water and salt content in soils with different textures. The relationships between soil moisture, soil salinity, and groundwater level were analyzed using 3 years of monitoring data from a typical oasis located in an extremely arid area in northwest China. The results showed that (1) the variation trend in soil moisture with soil depth in the shelterbelts varied depending on soil texture. The soil moisture was lower in sandy and loamy shelterbelts and higher in clay shelterbelts. (2) Salinity was higher (about 3.0 mS cm^?1) in clay shelterbelts and lower (about 0.8 mS cm^?1) in sandy shelterbelts. (3) There was a negative correlation between soil moisture in the shelterbelts and groundwater level. Soil moisture decreased gradually as the depth of groundwater table declined. (4) There was a positive correlation between soil salinity in the shelterbelts and the depth of groundwater table. Salinity increased gradually as groundwater levels declined.     

Choosing how to choose: Comparing amalgamation methods for environmental impact assessment

Amalgamation, in which disparate impacts are combined so that alternatives can be ranked, has become an important part of many impact assessments. Such methods can help make decisions more rational by systematically combining great amounts of information into more digestible forms. They can also facilitate public participation and ease documentation of decisions. The intent of this article is to give an overview of amalgamation methods and to propose four criteria for choosing among them: the purpose to be served, ease of use, validity, and results compared to other methods. Because experiments have repeatedly shown that the method chosen can significantly affect what decision is made, EIA practitioners should place more emphasis on the last two criteria than they have in the past. Finally, recent results in psychology and management science are discussed for practitioners facing the question “how do we choose how to choose?”     

Molecular-level methods for monitoring soil organic matter responses to global climate change

Soil organic matter (SOM) is one of the most complex natural mixtures on earth. It plays a critical role in many ecosystem functions and is directly responsible for sustaining life on our planet. However, due to its chemical heterogeneity, SOM composition at molecular-level is still not completely clear. Consequently, the response of SOM to global climate change is difficult to predict. Here we highlight applications of two complementary molecular-level methods (biomarkers and nuclear magnetic resonance (NMR)) for ascertaining SOM responses to various environmental changes. Biomarker methods that measure highly specific molecules determine the source and decomposition stage of SOM components. However, biomarkers only make up a small fraction of SOM components because much of SOM is non-extractable. By comparison, (13)C solid-state NMR allows measurement of SOM in its entirety with little or no pretreatment but suffers from poor resolution (due to overlapping of SOM components) and insensitivity, and thus subtle changes in SOM composition may not always be detected. Alternatively, (1)H solution-state NMR methods offer an added benefit of improved resolution and sensitivity but can only analyze SOM components that are fully soluble (humic type molecules) in an NMR compatible solvent. We discuss how these complementary methods have been employed to monitor SOM responses to: soil warming in a temperate forest, elevated atmospheric CO(2) and nitrogen fertilization in a temperate forest, and permafrost thawing in the Canadian High Arctic. These molecular-level methods allow some novel and important observations of soil dynamics and ecosystem function in a changing climate.     

Future groundwater extraction scenarios for an aquifer in a semiarid environment: case study of Guadalupe Valley Aquifer,Baja California,Northwest Mexico

Semiarid northwestern Mexico presents a growing water demand produced by agricultural and domestic requirements during the last two decades. The community of Guadalupe Valley and the city of Ensenada rely on groundwater pumping from the local aquifer as its sole source of water supply. This dependency has resulted in an imbalance between groundwater pumpage and natural recharge. A two-dimensional groundwater flow model was applied to the Guadalupe Valley Aquifer, which was calibrated and validated for the period 1984–2005. The model analysis verified that groundwater levels in the region are subject to steep declines due to decades of intensive groundwater exploitation for agricultural and domestic purposes. The calibrated model was used to assess the effects of different water management scenarios for the period 2007–2025. If the base case (status quo) scenario continues, groundwater levels are in a continuous drawdown trend. Some wells would run dry by August 2017, and water demand may not be met without incurring in an overdraft. The optimistic scenario implies the achievement of the mean groundwater recharge and discharge. Groundwater level depletion could be stopped and restored. The sustainable scenario implies the reduction of current extraction (up to about 50 %), when groundwater level depletion could be stopped. A reduction in current extraction mitigates water stress in the aquifer but cannot solely reverse declining water tables across the region. The combination of reduced current extraction and an implemented alternative solution (such as groundwater artificial recharge), provides the most effective measure to stabilize and reverse declining groundwater levels while meeting water demands in the region.