Groundwater quality assessment and its correlation with gastroenteritis using GIS: a case study of Rawal Town,Rawalpindi, Pakistan

Majority of the people of Pakistan get drinking water from groundwater source. Nearly 40 % of the total ailments reported in Pakistan are the result of dirty drinking water. Every summer, thousands of patients suffer from acute gastroenteritis in the Rawal Town. Therefore, a study was designed to generate a water quality index map of the Rawal Town and identify the relationship between bacteriological water quality and socio-economic indicators with gastroenteritis in the study area. Water quality and gastroenteritis patient data were collected by surveying the 262 tubewells and the major hospitals in the Rawal Town. The collected spatial data was analyzed by using ArcGIS spatial analyst (Moran’s I spatial autocorrelation) and geostatistical analysis tools (inverse distance weighted, radial basis function, kriging, and cokriging). The water quality index (WQI) for the study area was computed using pH, turbidity, total dissolved solids, calcium, hardness, alkalinity, and chloride values of the 262 tubewells. The results of Moran’s I spatial autocorrelation showed that the groundwater physicochemical parameters were clustered. Among IDW, radial basis function, and kriging and cokriging interpolation techniques, cokriging showed the lowest root mean square error. Cokriging was used to make the spatial distribution maps of water quality parameters. The WQI results showed that more than half of the tubewells in the Rawal Town were providing “poor” to “unfit” drinking water. The Pearson’s coefficient of correlation for gastroenteritis with fecal coliform was found significant (P?P?P?相似文献   

Classification of moisture and aeration regimes in sub-boreal forest soils

One hundred and two white spruce (Picea glauca (Moench) Voss) stands were studied in the Sub-boreal Spruce zone of British Columbia and were quantitatively classified into seven soil moisture regimes (moderately dry, slightly dry, fresh, moist, very moist, wet, and very wet) according to actual/potential evapotranspiration ratio, depth to gleyed layer or prominent mottling, and depth to groundwater table. The delineated soil moisture regimes demonstrated strong relationships with the composition of understory vegetation and white spruce foliar nutrients and site index. These relationships implied that the three differentiating characteristics used in the classification provided a good estimation of growing-season soil water supply. In addition to soil moisture regimes, three soil aeration regimes (adequate, restricted, and deficient) were delineated according to presence or absence of gleyed horizons and groundwater table, slope gradient, and soil texture. These soil aeration regimes helped in explaining the variation in white spruce site index, especially on water-surplus sites. Thus, an integrated classification of soil moisture-aeration regimes was proposed to explain the effect of soil moisture and aeration on white spruce productivity.The results of this study gave further evidence that soil moisture and aeration regimes, differentiated on the basis of climatic data and soil morphological properties, are useful measures of soil moisture and aeration conditions in sub-boreal forest soils.     

Spatiotemporal variation of groundwater quality using integrated multivariate statistical and geostatistical approaches in Amol–Babol Plain,Iran

In recent years, groundwater quality has become a global concern due to its effect on human life and natural ecosystems. To assess the groundwater quality in the Amol–Babol Plain, a total of 308 water samples were collected during wet and dry seasons in 2009. The samples were analysed for their physico-chemical and biological constituents. Multivariate statistical analysis and geostatistical techniques were applied to assess the spatial and temporal variabilities of groundwater quality and to identify the main factors and sources of contamination. Principal component analysis (PCA) revealed that seven factors explained around 75 % of the total variance, which highlighted salinity, hardness and biological pollution as the dominant factors affecting the groundwater quality in the Plain. Two-way analysis of variance (ANOVA) was conducted on the dataset to evaluate the spatio-temporal variation. The results showed that there were no significant temporal variations between the two seasons, which explained the similarity between six component factors in dry and wet seasons based on the PCA results. There are also significant spatial differences (p?>?0.05) of the parameters under study, including salinity, potassium, sulphate and dissolved oxygen in the plain. The least significant difference (LSD) test revealed that groundwater salinity in the eastern region is significantly different to the central and western side of the study area. Finally, multivariate analysis and geostatistical techniques were combined as an effective method for demonstrating the spatial structure of multivariate spatial data. It was concluded that multiple natural processes and anthropogenic activities were the main sources of groundwater salinization, hardness and microbiological contamination of the study area.     

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.     

Geostatistical Analysis of Spatial and Temporal Variations of Groundwater Level

Groundwater and water resources management plays a key role in conserving the sustainable conditions in arid and semi-arid regions. Applying management tools which can reveal the critical and hot conditions seems necessary due to some limitations such as labor and funding. In this study, spatial and temporal analysis of monthly groundwater level fluctuations of 39 piezometric wells monitored during 12 years was carried out. Geostatistics which has been introduced as a management and decision tool by many researchers has been applied to reveal the spatial and temporal structure of groundwater level fluctuation. Results showed that a strong spatial and temporal structure existed for groundwater level fluctuations due to very low nugget effects. Spatial analysis showed a strong structure of groundwater level drop across the study area and temporal analysis showed that groundwater level fluctuations have temporal structure. On average, the range of variograms for spatial and temporal analysis was about 9.7 km and 7.2 months, respectively. Ordinary and universal kriging methods with cross-validation were applied to assess the accuracy of the chosen variograms in estimation of the groundwater level drop and groundwater level fluctuations for spatial and temporal scales, respectively. Results of ordinary and universal krigings revealed that groundwater level drop and groundwater level fluctuations were underestimated by 3% and 6% for spatial and temporal analysis, respectively, which are very low and acceptable errors and support the unbiasedness hypothesis of kriging. Although, our results demonstrated that spatial structure was a little bit stronger than temporal structure, however, estimation of groundwater level drop and groundwater level fluctuations could be performed with low uncertainty in both space and time scales. Moreover, the results showed that kriging is a beneficial and capable tool for detecting those critical regions where need more attentions for sustainable use of groundwater. Regions in which were detected as critical areas need to be much more managed for using the current water resources efficiently. Conducting water harvesting systems especially in critical and hot areas in order to recharge the groundwater, and altering the current cropping pattern to another one that need less water requirement and applying modern irrigation techniques are highly recommended; otherwise, it is most likely that in a few years no more crop would be cultivated.     

Assessment of groundwater pollution in West Delhi, India using geostatistical approach

The exploration, exploitation, and unscientific management of groundwater resources in the National Capital Territory (NCT) of Delhi, India have posed a serious threat of reduction in quantity and deterioration of quality. The objective of the study is to determine the groundwater quality and to assess the risk of groundwater pollution at Najafgarh, NCT of Delhi. The groundwater quality parameters were analyzed from the existing wells of the Najafgarh and the thematic maps were generated using geostatistical concepts. Ordinary kriging and indicator kriging methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality parameters such as bicarbonate, calcium, chloride, electrical conductivity (EC), magnesium, nitrate, sodium, and sulphate with concentrations equal or greater than their respective groundwater pollution cutoff value. Experimental semivariogram values were fitted well in spherical model for the water quality parameters, such as bicarbonate, chloride, EC, magnesium, sodium, and sulphate and in exponential model for calcium and nitrate. The thematic maps of all the groundwater quality parameters exhibited an increasing trend of pollution from the northern and western part of the study area towards the southern and eastern part. The concentration was highest at the southernmost part of the study area but it could not reflect correctly the groundwater pollution status. The indicator kriging method is useful to assess the risk of groundwater pollution by giving the conditional probability of concentrations of different chemical parameters exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful for proper management of groundwater resources and minimizing the pollution threat.     

Spatial evaluation of the risk of groundwater quality degradation. A comparison between disjunctive kriging and geostatistical simulation

In some previous papers a probabilistic methodology was introduced to estimate a spatial index of risk of groundwater quality degradation, defined as the conditional probability of exceeding assigned thresholds of concentration of a generic chemical sampled in the studied water system. A crucial stage of this methodology was the use of geostatistical techniques to provide an estimation of the above-mentioned probability in a number of selected points by crossing spatial and temporal information. In this work, spatial risk values were obtained using alternatively stochastic conditional simulation and disjunctive kriging. A comparison between the resulting two sets of spatial risks, based on global and local statistical tests, showed that they do not come from the same statistical population and, consequently, they cannot be viewed as equivalent in a statistical sense. At a first glance, geostatistical conditional simulation may appear to represent the spatial variability of the phenomenon more effectively, as the latter tends to be smoothed by DK. However, a close examination of real case study results suggests that disjunctive kriging is more effective than simulation in estimating the spatial risk of groundwater quality degradation. In the study case, the potentially ‘harmful event’ considered, threatening a natural ‘vulnerable groundwater system,’ is fertilizer and manure application.     

Groundwater depth and elevation interpolation by kriging methods in Mohr Basin of Fars province in Iran

Prediction of groundwater depth and elevation is important in quantitative water management especially in arid areas. There are several basins in southwest of Iran, in Zagross Mountain, in which the water wells are distributed along a narrow elliptic ring band around the region. To find the most applicable interpolation method, both of the groundwater depth and elevation are predicted by different kriging methods. It is found that the groundwater elevation and depth can be predicted by different methods. Furthermore, it is found that the methods in which the trend is eliminated predicted the groundwater elevation and depth in central part of the region is with less standard error. Furthermore, the methods with no trend elimination, predicted the groundwater depths with less error near the water wells. Dividing the area to hydro-geologically homogeneous sub-areas improved the interpolation precision.     

Comparison of Groundwater Level Estimation Using Neuro-fuzzy and Ordinary Kriging

Water level in aquifer plays the main role in groundwater modeling as one of the input data. In practice, due to aspects of time and cost, data monitoring of water levels is conducted at a limited number of sites, and interpolation technique such as kriging is widely used for estimation of this variable in unsampled sites. In this study, the efficiency of the ordinary kriging (OK) and adaptive network-based fuzzy inference system (ANFIS) was investigated in interpolation of groundwater level in an unconfined aquifer in the north of Iran. The results showed that ANFIS model is more efficient in estimating the groundwater level than OK.     

Mapping Soil Gas Radon Concentration: A Comparative Study of Geostatistical Methods

Understanding soil gas radon spatial variations can allow the constructor of a new house to prevent radon gas flowing from the ground. Indoor radon concentration distribution depends on many parameters and it is difficult to use its spatial variation to assess radon potential. Many scientists use to measure outdoor soil gas radon concentrations to assess the radon potential. Geostatistical methods provide us a valuable tool to study spatial structure of radon concentration and mapping. To explore the structure of soil gas radon concentration within an area in south Italy and choice a kriging algorithm, we compared the prediction performances of four different kriging algorithms: ordinary kriging, lognormal kriging, ordinary multi-Gaussian kriging, and ordinary indicator cokriging. Their results were compared using an independent validation data set. The comparison of predictions was based on three measures of accuracy: (1) the mean absolute error, (2) the mean-squared error of prediction; (3) the mean relative error, and a measure of effectiveness: the goodness-of-prediction estimate. The results obtained in this case study showed that the multi-Gaussian kriging was the most accurate approach among those considered. Comparing radon anomalies with lithology and fault locations, no evidence of a strict correlation between type of outcropping terrain and radon anomalies was found, except in the western sector where there were granitic and gneissic terrain. Moreover, there was a clear correlation between radon anomalies and fault systems.     

Seasonal and spatial variation of arsenic in groundwater in a rhyolithic volcanic area of Lesvos Island,Greece

A survey conducted in water wells located in the rhyolithic volcanic area of Mandamados, Lesvos Island, Greece, indicated that significant seasonal variation of arsenic concentration in groundwater exists mainly in wells near the coastal zone. However, there were differences among those coastal wells with regard to the processes and factors responsible for the observed seasonal variability of the element, although they are all located in a small homogeneous area. These processes and factors include (a) a higher rate of silicate weathering and ion exchange during the dry period followed by the dilution by the recharge water during the wet period, (b) enhanced desorption promoted by higher pH in summer and subsequent dilution of As by rainwater infiltration during the wet period, and (c) reductive dissolution of Mn during the wet period and by desorption under high pH values during the dry period. On the other hand, in wells located in higher-relief regions, the concentration of As in groundwater followed a fairly constant pattern throughout the year, which is probably related to the faster flow of groundwater in this part of the area due to a higher hydraulic gradient. In general, seasonal variation of As in groundwater in the study area was found to be related to geology, recharge rate, topography—distance from coast, and well depth.     

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.     

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.     

The geostatistic-based spatial distribution variations of soil salts under long-term wastewater irrigation

The purpose of this study was to determine and evaluate the spatial changes in soil salinity by using geostatistical methods. The study focused on the suburb area of Beijing, where urban development led to water shortage and accelerated wastewater reuse to farm irrigation for more than 30 years. The data were then processed by GIS using three different interpolation techniques of ordinary kriging (OK), disjunctive kriging (DK), and universal kriging (UK). The normality test and overall trend analysis were applied for each interpolation technique to select the best fitted model for soil parameters. Results showed that OK was suitable for soil sodium adsorption ratio (SAR) and Na⁺ interpolation; UK was suitable for soil Cl^? and pH; DK was suitable for soil Ca²⁺. The nugget-to-sill ratio was applied to evaluate the effects of structural and stochastic factors. The maps showed that the areas of non-saline soil and slight salinity soil accounted for 6.39 and 93.61 %, respectively. The spatial distribution and accumulation of soil salt were significantly affected by the irrigation probabilities and drainage situation under long-term wastewater irrigation.     

Can juvenile corals be surveyed effectively using digital photography?: implications for rapid assessment techniques

Seasonal variations in the concentrations of groundwater with respect to arsenic, lead, cadmium and aluminium has been studied in Dhemaji district of Assam, India. The water samples were collected from 20 different sites in both dry and wet seasons. The metals were analysed by using atomic absorption spectrometer, Perkin Elmer AAnalyst 200 model. The concentrations of aluminium, lead and cadmium in groundwater were found to be significantly elevated. High concentrations of all the metals were recorded in the dry season than in the wet season. Univariate statistics along with skewness, kurtosis and confidence limit have been calculated for both the seasons to test the distribution normality for each metal. Statistical analyses of the data reveal non-uniform distribution of the metals in the area. The metal contamination of groundwater in the district follows the trend Al > Pb > Cd > As in both the seasons.     

Water use sources of desert riparian Populus euphratica forests

Desert riparian forests are the main body of natural oases in the lower reaches of inland rivers; its growth and distribution are closely related to water use sources. However, how does the desert riparian forest obtains a stable water source and which water sources it uses to effectively avoid or overcome water stress to survive? This paper describes an analysis of the water sources, using the stable oxygen isotope technique and the linear mixed model of the isotopic values and of desert riparian Populus euphratica forests growing at sites with different groundwater depths and conditions. The results showed that the main water source of Populus euphratica changes from water in a single soil layer or groundwater to deep subsoil water and groundwater as the depth of groundwater increases. This appears to be an adaptive selection to arid and water-deficient conditions and is a primary reason for the long-term survival of P. euphratica in the desert riparian forest of an extremely arid region. Water contributions from the various soil layers and from groundwater differed and the desert riparian P. euphratica forests in different habitats had dissimilar water use strategies.     

Estimation of spatial distrubition of groundwater level and risky areas of seawater intrusion on the coastal region in Çarşamba Plain,Turkey, using different interpolation methods

Groundwater level plays a significant role in coastal plains. Heavy pumping and excessive use of near-coast groundwater can increase the intrusion of seawater into the aquifers. In the present study, groundwater levels were measured at 59 groundwater wells at different times during pre- and post-irrigation seasons (April and September of the year 2012) in Çar?amba Plain, Turkey. To select the best method, two deterministic interpolation methods (inverse distance weighing (IDW) with the weights of 1, 2, and 3 and radial basis function (RBF) with spline with tension (SPT) and completely regularized spline (CRS)) and two stochastic methods (ordinary kriging (OK) with spherical, exponential, and Gaussian variograms) and cokriging (COK)) were compared and then the best interpolation method was used to evaluate the spatial distribution of groundwater levels in different seasons and seasonal changes. A total of nine different techniques were tested. Also, risky areas of seawater intrusion in coastal area were determined using the best methods for two periods. The performance of these interpolation methods is evaluated by using a validation test method. Statistical indices of correlation (R ²), mean absolute error (MAE), and root-mean-square error (RMSE) were used to select and validate the best methods. Comparisons between predicted and observed values indicated RBF as the optimal method for groundwater level estimation in April and September. When the best method RBF and the worst method IDW were compared, significant differences were observed in the spatial distribution of groundwater. Results of the study also revealed that excessive groundwater withdrawals during the post-irrigation season dropped the groundwater levels up to 2.0 m in some sections. With regard to seawater intrusion, 9,103 ha of land area was determined to be highly risky and risky.     

Time-lapse resistivity investigation of salinity changes at an ex-promontory land: a case study of Carey Island, Selangor, Malaysia

Time-lapse resistivity measurements and groundwater geochemistry were used to study salinity effect on groundwater aquifer at the ex-promontory-land of Carey Island in Malaysia. Resistivity was measured by ABEM Terrameter SAS4000 and ES10-64 electrode selector. Relationship between earth resistivity and total dissolved solids (TDS) was derived, and with resistivity images, used to identify water types: fresh (ρ ( e ) > 6.5 Ω m), brackish (3 Ω m < ρ ( e ) < 6.5 Ω m), or saline (ρ ( e ) < 3 Ω m). Long-term monitoring of the studied area's groundwater quality via measurements of its time-lapse resistivity showed salinity changes in the island's groundwater aquifers not conforming to seawater-freshwater hydraulic gradient. In some aquifers far from the coast, saline water was dominant, while in some others, freshwater 30 m thick showed groundwater potential. Land transformation is believed to have changed the island's hydrogeology, which receives saltwater pressure all the time, limiting freshwater recharge to the groundwater system. The time-lapse resistivity measurements showed active salinity changes at resistivity-image bottom moving up the image for two seasons' (wet and dry) conditions. The salinity changes are believed to have been caused by incremental tide passing through highly porous material in the active-salinity-change area. The study's results were used to plan a strategy for sustainable groundwater exploration of the island.     

Groundwater quality assessment in semi-arid regions using integrated approaches: the case of Grombalia aquifer (NE Tunisia)

As many arid and semi-arid regions in the Mediterranean Basin, the Grombalia coastal aquifer (NE Tunisia) is affected by severe groundwater exploitation and contamination. Therefore, quality assessments are becoming increasingly important as the long-term protection of water resources is at stake. Multidisciplinary investigations, like the one presented in this paper, are particularly effective in identifying the different origins of mineralization within an aquifer and investigating the impact of anthropogenic activities on groundwater quality. An integrated assessment, focused on the combined use of geostatistical, geochemical and isotopic (δ¹⁸O, δ²H and ³H) tools, was performed in the Grombalia aquifer between February and March 2014. The overall goal was to study the main processes controlling aquifer salinization, with special focus to nitrate contamination. Results indicate a persisting deterioration of water quality over the whole basin except the south-eastern zone juxtaposing the recharge area of the aquifer. Nitrate contents exceed the drinking water standard (50 mg/l) in 70% of groundwater samples, mainly due to the excessive use of fertilizers and urban activities. Stable isotope measurements showed the contribution of modern rainwater to aquifer recharge and proved the presence of evaporation contributing to the salinity increase. Tritium values of groundwater samples suggested two hypotheses: the existence of mixture between old and recent water or/and the existence of two recharge periods of the aquifer, pre- and post-nuclear weapons test. Principal component analysis confirmed the geochemical interpretation, highlighting that water-rock interaction evaporation effect and intensive anthropogenic activities constitute the main processes controlling the regional groundwater mineralization.