Spatial assessment of soil salinity in the Harran Plain using multiple kriging techniques

The Harran Plain is located in the southeastern part of Turkey and has recently been developed for irrigation agriculture. It already faces soil salinity problems causing major yield losses. Management of the problem is hindered by the lack of information on the extent and geography of the salinization problem. A survey was carried out to delineate the spatial distribution of salt-affected areas by randomly selecting 140 locations that were sampled at two depths (0 to 30 and 30 to 60 cm) and analyzed for soil salinity variables: soil electrical conductivity (EC), soluble cations (Ca^2+, Mg²⁺, Na⁺, and K⁺), soluble anions (SO ₄ ^2? , Cl^?), exchangeable Na⁺ (me 100 g^?1) and exchangeable sodium percentage. Terrain attributes (slope, topographical wetness index) were extracted from the digital elevation model of the study area. Variogram analyses after log transformation and ordinary kriging (OK) were applied to map spatial patterns of soil salinity variables. Multivariate geostatistical methods—regression kriging (RK) and kriging with external drift (KED)—were used using elevation and soil electrical conductivity data as covariates. Performances of the three estimation methods (OK, RK, and KED) were compared using independent validation samples randomly selected from the main dataset. Soils were categorized into salinity classes using disjunctive kriging (DK) and ArcGIS, and classification accuracy was tested using the kappa statistic. Results showed that soil salinity variables all have skewed distribution and are poorly correlated with terrain indices but have strong correlations among each other. Up to 65 % improvement was obtained in the estimations of soil salinity variables using hybrid methods over OK with the best estimations obtained with RK using EC_0–30 as covariate. DK–ArcGIS successfully classified soil samples into different salinity groups with overall accuracy of 75 % and kappa of 0.55 (p?<?0.001).     

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.     

Assessment of long-term wastewater irrigation impacts on the soil geochemical properties and the bioaccumulation of heavy metals to the agricultural products

An extensive field survey was employed for assessing the impacts of long-term wastewater irrigation of forage crops and orange orchards in three suburban agricultural areas in Cyprus (areas I, II, and III), as compared to rainfed agriculture, on the soil geochemical properties and the bioaccumulation of heavy metals (Zn, Ni, Mn, Cu, Co) to the agricultural products. Both ryegrass fields and orange orchards in areas I and II were continuously wastewater irrigated for 10 years, whereas clover fields in area III for 0.5, 4, and 8 years. The results revealed that wastewater reuse for irrigation caused a slight increase in soil salinity and Cl^? content in areas I and II, and a remarkable increase, having strong correlation with the period in which wastewater irrigation was practiced, in area III. Soil salinization in area III was due to the high electrical conductivity (EC) of the wastewater applied for irrigation, attributed to the influx of seawater to the sewage collection network in area III. In addition, the wastewater irrigation practice resulted in a slight decrease of the soil pH values in area III, while a subtle impact was identified regarding the CaCO₃, Fe, and heavy metal content in the three areas surveyed. The heavy metal content quantified in the forage plants’ above-ground parts was below the critical levels of phytotoxicity and the maximum acceptable concentration in dairy feed, whereas heavy metals quantified in orange fruit pulp were below the maximum permissible levels (MPLs). Heavy metal phytoavailability was confined due to soil properties (high pH and clay content), as evidenced by the calculated low transfer factor (TF).     

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.     

Modeling of Cr contamination in the agricultural lands of three villages near the leather industry in Kasur,Pakistan, using statistical and GIS techniques

Kasur is one of the hubs of leather industry in the Punjab, Pakistan, where chrome tanning method of leather processing is extensively being used. Chromium (Cr) accumulation levels in the irrigation water, soil, and seasonal vegetables were studied in three villages located in the vicinity of wastewater treatment plant and solid waste dumping site operated by the Kasur Tanneries Waste Management Agency (KTWMA). The data was interpreted using analysis of variance (ANOVA), clustering analysis (CA), and principal component analysis (PCA). Interpolated surface maps for Cr were generated using the actual data obtained for the 30 sampling sites in each of the three villages for irrigation water, soil, and seasonal vegetables. The level of contamination in the three villages was directly proportional to their distance from KTWMA wastewater treatment plant and the direction of water runoff. The highest level of Cr contamination in soil (mg kg^?1) was observed at Faqeeria Wala (37.67), intermediate at Dollay Wala (30.33), and the least in Maan (25.16). A gradational variation in Cr accumulation was observed in the three villages from contaminated wastewater having the least contamination level (2.02–4.40 mg L^?1), to soil (25.16–37.67 mg kg^?1), and ultimately in the seasonal vegetable crops (156.67–248.33 mg kg^?1) cultivated in the region, having the highest level of Cr contamination above the permissible limit. The model used not only predicted the current situation of Cr contamination in the three villages but also indicated the trend of magnification of Cr contamination from irrigation water to soil and to the base of the food chain. Among the multiple causes of Cr contamination of vegetables, soil irrigation with contaminated groundwater was observed to be the dominant one.     

An approach for land suitability evaluation using geostatistics, remote sensing, and geographic information system in arid and semiarid ecosystems

This study was undertaken to incorporate geostatistics, remote sensing, and geographic information system (GIS) technologies to improve the qualitative land suitability assessment in arid and semiarid ecosystems of Arsanjan plain, southern Iran. The primary data were obtained from 85 soil samples collected from tree depths (0–30, 30–60, and 60–90 cm); the secondary information was acquired from the remotely sensed data from the linear imaging self-scanner (LISS-III) receiver of the IRS-P6 satellite. Ordinary kriging and simple kriging with varying local means (SKVLM) methods were used to identify the spatial dependency of soil important parameters. It was observed that using the data collected from the spectral values of band 1 of the LISS-III receiver as the secondary variable applying the SKVLM method resulted in the lowest mean square error for mapping the pH and electrical conductivity (ECe) in the 0–30-cm depth. On the other hand, the ordinary kriging method resulted in a reliable accuracy for the other soil properties with moderate to strong spatial dependency in the study area for interpolation in the unstamped points. The parametric land suitability evaluation method was applied on the density points (150 × 150 m²) instead of applying on the limited representative profiles conventionally, which were obtained by the kriging or SKVLM methods. Overlaying the information layers of the data was used with the GIS for preparing the final land suitability evaluation. Therefore, changes in land characteristics could be identified in the same soil uniform mapping units over a very short distance. In general, this new method can easily present the squares and limitation factors of the different land suitability classes with considerable accuracy in arbitrary land indices.     

Assessing environmental impacts of treated wastewater through monitoring of fecal indicator bacteria and salinity in irrigated soils

To assess the potential for treated wastewater irrigation to impact levels of fecal indicator bacteria (FIB) and salinity in irrigated soils, levels of Escherichia coli, Enterococcus, and environmental covariates were measured in a treated wastewater holding pond (irrigation source water), water leaving the irrigation system, and in irrigated soils over 2 years in a municipal parkland in Arizona. Higher E. coli levels were measured in the pond in winter (56 CFU 100 mL⁻¹) than in summer (17 CFU 100 mL⁻¹); however, in the irrigation system, levels of FIB decreased from summer (26 CFU 100 mL⁻¹) to winter (4 CFU 100 mL⁻¹), possibly related to low winter water use and corresponding death of residual bacteria within the system. For over 2 years, no increase in FIB was found in irrigated soils, though highest E. coli levels (700 CFU g⁻¹ soil) were measured in deeper (20–25 cm) soils during summer. Measurements of water inputs vs. potential evapotranspiration indicate that irrigation levels may have been sufficient to generate bacterial percolation to deeper soil layers during summer. No overall increase in soil salinity resulting from treated wastewater irrigation was detected, but distinct seasonal peaks as high as 4 ds m⁻¹ occurred during both summers. The peaks significantly declined in winter when surface ET abated and more favorable water balances could be maintained. Monitoring of seasonal shifts in irrigation water quality and/or factors correlated with increases and decreases in FIB will aid in identification of any public health or environmental risks that could arise from the use of treated wastewater for irrigation.     

Temporal-spatial variability and fractal characteristics of soil nitrogen and phosphorus in Xinji District, Hebei Province, China

Traditional statistics, geostatistics, fractal dimensions, and geographic information systems (GIS) were employed to study the temporal?Cspatial variability of soil total nitrogen (TN) and total phosphorus (TP) levels in Xinji District, Hebei Province area of the North China Plain from 1980 to 2007. The results indicate that nutrient levels follow normal or lognormal distributions. The TN content was 0.59 ±0.155 g kg^???1 in 2007, an increase of 0.44 g kg^???1 compared with that of 1980. In 2007, the TP content was 1.21 ±0.227 g kg^???1, an increase of 0.01 g kg^???1 from 1980. The geostatistical analysis showed that the distribution of these soil nutrients in the study area exhibits a trend and anisotropy. The range and [C ₀/(C ₀?+?C)] of TN and TP in 1980 were all less than in 2007. The ordinary kriging interpolation method was used to analyze the nutrient contents differences between 1980 and 2007. The results indicate that soil TN levels have increased over the 27-year period, and the area where the TN level had increased by at least 0.4 g kg^???1 was about 61.7% of the district. The area where the TP content increased covered about 58.4% of the district. The variance analysis indicated that land-use type had a clear influence on the distribution and change in TN and TP content. Using the 3-D box-counting dimension method combined with GIS, the fractal dimension of soil nutrient spatial distribution over the two periods showed that in 27 years, the fractal dimension of TN increased from 1.95 to 2.02, and the fractal dimension of TP increased from 1.89 to 2.01, indicating that the complexity of the spatial distribution of all nutrient contents had increased. This study can provide a basis for accurate fertilizing and to enhance the conversion of soil characteristics under different spatial scales.     

Spatial variability of depth and salinity of groundwater under irrigated ustifluvents in the Middle Black Sea Region of Turkey

Information on the potential risk for soil salinity buildup can be very helpful for soil salinity management in irrigated areas. We evaluated the spatial and temporal variability of groundwater salinity (GWS) and groundwater depth (GWD), which are two of the most important indicators of soil salinity, by indicator kriging technique in a large irrigated area in northern Turkey. GWS and GWD were measured on a monthly basis from irrigation season (August 2003) to rainy season (April 2004) at 60 observation wells in the 8,187-ha irrigated area. Five indicator thresholds were used for GWS and GWD. The semivariogram for each of the thresholds for both variables was analyzed then used together with experimental data to interpolate and map the corresponding conditional cumulative distribution functions (CCDF). Risk for soil salinity buildup was greater in the irrigation season compared to that in the rainy season. The greatest risk for soil salinity buildup occurred in the eastern part of the study area, suffering from poor drainage problem due to malfunctioning drainage infrastructure, as indicated by the CCDF of GWS and GWD obtained in both seasons. It was concluded that a combination of mechanical and cultural measures should be taken in high-risk locations to avoid further salinity problems.     

Does irrigation with reclaimed water significantly pollute shallow aquifer with nitrate and salinity? An assay in a perurban area in North Tunisia

In Tunisia, reclaimed water is increasingly used for irrigation in order to mitigate water shortage. However, few studies have addressed the effect of such practice on the environment. Thus, we attempted in this paper to assess the impact of irrigation with reclaimed water on the nitrate content and salinity in the Nabeul shallow aquifer on the basis of satellite images and data from 53 sampled wells. Ordinary and indicator kriging were used to map the spatial variability of these groundwater chemical parameters and to locate the areas where water is suitable for drinking and irrigation. The results of this study have shown that reclaimed water is not an influential factor on groundwater contamination by nitrate and salinity. Cropping density is the main factor contributing to nitrate groundwater pollution, whereas salinity pollution is affected by a conjunction of factors such as seawater interaction and lithology. The predictive maps show that nitrate content in the groundwater ranges from 9.2 to 206 mg/L while the electric conductivity ranges from 2.2 to 8.5 dS/m. The high-nitrate concentration areas underlie sites with high annual crop density, whereas salinity decreases gradually moving away from the coastline. The probability maps reveal that almost the entire study area is unsuitable for drinking with regard to nitrate and salinity levels. Appropriate measures, such as the elaboration of codes of good agricultural practices and action programs, should be undertaken in order to prevent and/or remediate the contamination of the Nabeul shallow aquifer.     

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.     

Deposition and storage of solid-bound heavy metals in the floodplains of the River Geul (the Netherlands)

Because of past mining activities, the floodplains of the River Geul are polluted with heavy metals. The continuous supply of fresh sediments during floods has caused the floodplain soils to exhibit large quality variations in time. By measurements of ¹³⁷Cs deposition rates in part of the floodplain area were determined at 0.4 to 2.7 cm yr^–1. Analysis of soil metal concentrations at various depths at 65 locations, revealed that the upper 40 cm of the soil profile deposited during the past 30–45 yr, exhibit the highest metal levels. The geostatistical interpolation technique kriging was used to map actual and past pollution patterns. It was shown that, as a result of variable deposition rates, the spatial correlation structure of soil metal concentrations becomes less clear with increasing depth/age. Kriged maps of average metal concentrations in the upper 100 cm of the soil profile provided the basis for the calculation of the mass storage of heavy metals.     

Comparison of spatial interpolation methods for soil moisture and its application for monitoring drought

Soil moisture data can reflect valuable information on soil properties, terrain features, and drought condition. The current study compared and assessed the performance of different interpolation methods for estimating soil moisture in an area with complex topography in southwest China. The approaches were inverse distance weighting, multifarious forms of kriging, regularized spline with tension, and thin plate spline. The 5-day soil moisture observed at 167 stations and daily temperature recorded at 33 stations during the period of 2010–2014 were used in the current work. Model performance was tested with accuracy indicators of determination coefficient (R ²), mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and modeling efficiency (ME). The results indicated that inverse distance weighting had the best performance with R ², MAPE, RMSE, RRMSE, and ME of 0.32, 14.37, 13.02%, 0.16, and 0.30, respectively. Based on the best method, a spatial database of soil moisture was developed and used to investigate drought condition over the study area. The results showed that the distribution of drought was characterized by evidently regional difference. Besides, drought mainly occurred in August and September in the 5 years and was prone to happening in the western and central parts rather than in the northeastern and southeastern areas.     

Accuracy and uncertainty assessment on geostatistical simulation of soil salinity in a coastal farmland using auxiliary variable

Understanding the spatial soil salinity aids farmers and researchers in identifying areas in the field where special management practices are required. Apparent electrical conductivity measured by electromagnetic induction instrument in a fairly quick manner has been widely used to estimate spatial soil salinity. However, methods used for this purpose are mostly a series of interpolation algorithms. In this study, sequential Gaussian simulation (SGS) and sequential Gaussian co-simulation (SGCS) algorithms were applied for assessing the prediction accuracy and uncertainty of soil salinity with apparent electrical conductivity as auxiliary variable. Results showed that the spatial patterns of soil salinity generated by SGS and SGCS algorithms showed consistency with the measured values. The profile distribution of soil salinity was characterized by increasing with depth with medium salinization (EC_e 4–8 dS/m) as the predominant salinization class. SGCS algorithm privileged SGS algorithm with smaller root mean square error according to the generated realizations. In addition, SGCS algorithm had larger proportions of true values falling within probability intervals and narrower range of probability intervals than SGS algorithm. We concluded that SGCS algorithm had better performance in modeling local uncertainty and propagating spatial uncertainty. The inclusion of auxiliary variable contributed to prediction capability and uncertainty modeling when using densely auxiliary variable as the covariate to predict the sparse target variable.     

The assessment of spatial distribution of soil salinity risk using neural network

Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km²) results were used to upscale soil salinity to a district area (∼300 km²). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m⁻¹). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70–90% of locations were correctly estimated.     

SPATIAL ANALYSIS AND EUTROPHICATION ASSESSMENT FOR CHLOROPHYLL a IN TAIHU LAKE

Spatial structure analysis and kriging analysis have been identified to be useful tools in illustrating the spatial patterns of variables. Taihu Lake is one of the largest fresh water lakes in China, and has suffered serious eutrophication in recent years due to the rapid economic development and growing environmental pollution in the Taihu Catchment. In this paper, spatial structural analysis, kriging interpolation and eutrophication assessment were carried out for chlorophyll a in the lake. Studies show that spherical model could be applied to fit all experimental variograms. Positive nuggets were observed for three directions except NE–SW direction. The variograms show some anisotropy with anisotropic ratio falling within 1.76. The spatial structural patterns of chlorophyll a in the lake were affected by factors such as distribution of pollution sources, water flow and wind. Two-dimensional ordinary block kriging was applied for interpolation process. An eutrophication assessment map was also made based on a water-quality evaluation standard. Results show that the content of chlorophyll a in Taihu Lake was quite high. The whole lake has suffered serious eutrophication. However, the eutrophic situation varied in space. Higher contents of chlorophyll a appeared mainly in the northern part of the lake.     

Fractionation and mobility of cadmium and zinc in urban vegetable gardens of Kano, Northern Nigeria

Metal fractionation provides information on mobility and stability of various metal species which can be used to evaluate the movement of such metals in soils. The effect of wastewater irrigation on the fractions, spatial distribution, and mobility of cadmium (Cd) and zinc (Zn) was investigated in five urban gardens in Kano, Nigeria. Concentration of total Zn in the surface soils (0–20 cm) ranged from 121 to 207 mg kg^− 1 while Cd concentration was 0.3–2.0 mg kg^− 1. Speciation of both heavy metals into seven operationally defined fractions indicated that the most reactive forms extracted with ammonium nitrate and ammonium acetate, also considered as the bioavailable fractions, accounted for 29–42% of total Cd and 22–54% of total Zn, respectively. The weakly bound fractions of Cd and Zn reached up to 50% of the total Cd and Zn concentrations in the soils. Such high proportions of labile Cd and Zn fractions are indicative of anthropogenic origins, arising from the application of wastewater for irrigation and municipal biosolids for soil fertility improvement. Thus, given the predominance of sandy soil textures, high concentrations of labile Cd and Zn in these garden soils represent a potential hazard for the redistribution and translocation of these metals into the food chain and aquifer.     

Assessment of methane emission and oxidation at Air Hitam Landfill site cover soil in wet tropical climate

Methane (CH₄) emissions and oxidation were measured at the Air Hitam sanitary landfill in Malaysia and were modeled using the Intergovernmental Panel on Climate Change waste model to estimate the CH₄ generation rate constant, k. The emissions were measured at several locations using a fabricated static flux chamber. A combination of gas concentrations in soil profiles and surface CH₄ and carbon dioxide (CO₂) emissions at four monitoring locations were used to estimate the CH₄ oxidation capacity. The temporal variations in CH₄ and CO₂ emissions were also investigated in this study. Geospatial means using point kriging and inverse distance weight (IDW), as well as arithmetic and geometric means, were used to estimate total CH₄ emissions. The point kriging, IDW, and arithmetic means were almost identical and were two times higher than the geometric mean. The CH₄ emission geospatial means estimated using the kriging and IDW methods were 30.81 and 30.49 g m^?2 day^?1, respectively. The total CH₄ emissions from the studied area were 53.8 kg day^?1. The mean of the CH₄ oxidation capacity was 27.5 %. The estimated value of k is 0.138 year^?1. Special consideration must be given to the CH₄ oxidation in the wet tropical climate for enhancing CH₄ emission reduction.     

Three-dimensional data interpolation for environmental purpose: lead in contaminated soils in southern Brazil

Monitoring of heavy metal contamination plume in soils can be helpful in establishing strategies to minimize its hazardous impacts to the environment. The objective of this study was to apply a new approach of visualization, based on tridimensional (3D) images, of pseudo-total (extracted with concentrated acids) and exchangeable (extracted with 0.5 mol L^?1 Ca(NO₃)₂) lead (Pb) concentrations in soils of a mining and metallurgy area to determine the spatial distribution of this pollutant and to estimate the most contaminated soil volumes. Tridimensional images were obtained after interpolation of Pb concentrations of 171 soil samples (57 points × 3 depths) with regularized spline with tension in a 3D function version. The tridimensional visualization showed great potential of use in environmental studies and allowed to determine the spatial 3D distribution of Pb contamination plume in the area and to establish relationships with soil characteristics, landscape, and pollution sources. The most contaminated soil volumes (10,001 to 52,000 mg Pb kg^?1) occurred near the metallurgy factory. The main contamination sources were attributed to atmospheric emissions of particulate Pb through chimneys. The large soil volume estimated to be removed to industrial landfills or co-processing evidenced the difficulties related to this practice as a remediation strategy.     

Incidence of metal and antibiotic resistance in Pseudomonas spp. from the river water, agricultural soil irrigated with wastewater and groundwater

A total of 144 isolates of Pseudomonas spp. (48 each from the Yamuna River water, wastewater irrigated soil and groundwater irrigated soil) were tested for their resistance against certain heavy metals and antibiotics. Minimum inhibitory concentrations (MICs) of Hg^2?+?, Cd^2?+?, Cu^2?+?, Zn^2?+?, Ni^2?+?, Pb^2?+?, Cr^3?+? and Cr^6?+? for each isolate were also determined. A maximum MIC of 200 ??g/ml for mercury and 3,200 ??g/ml for other metals were observed. The incidences of metal resistance and MICs of metals for Pseudomonas isolates from the Yamuna water and wastewater irrigated soil were significantly different to those of groundwater irrigated soil. A high level of resistance against tetracycline and polymyxin B (81.2%) was observed in river water isolates. However, 87.5% of Pseudomonas isolates from soil irrigated with wastewater showed resistance to sulphadiazine, whereas 79.1% were resistant to both ampicillin and erythromycin. Isolates from soil irrigated with groundwater exhibited less resistance towards heavy metals and antibiotics as compared to those of river water and wastewater irrigated soil. Majority of the Pseudomonas isolates from water and soil exhibited resistance to multiple metals and antibiotics. Resistance was transferable to recipient Escherichia coli AB2200 strains by conjugation. Plasmids were cured with the curing agent ethidium bromide and acridine orange at sub-MIC concentration.