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.     

Sediment fluxes and the littoral drift along northeast Andhra Pradesh Coast, India: estimation by remote sensing

The littoral drift regime along the northeastern coast of India was investigated by analyzing coastal drift indicators and shoreline changes based on multitemporal satellite images. The study of offshore turbidity patterns and quantitative estimation of suspended sediments was undertaken to understand the magnitude and direction of movement of sediment fluxes. The study revealed that: (1) the character of coastal landforms and sedimentation processes indicate that the sediment transport is bidirectional and monsoon dependent; (2) multidate, multitemporal analysis of satellite images helps to show the nature of sediment transport along the coast. The dominant net sediment transport is in a NE direction along the eastern coast of India. Finally, this assessment demonstrates the potential of remote sensing technology in understanding the coastal morphometric changes, long-term sediment transport, shoreline changes, and offshore turbidity distribution pattern and the implications for the transport of sediment-associated pollutants.     

Estimation of chlorpyriphos and cypermethrin residues in chilli (Capsicum annuum L.) by gas–liquid chromatography

Dissipation of chlorpyriphos and cypermethrin in chilli was studied following three applications of a combination formulation of Nurelle-D 505 (chlorpyriphos 50 %?+?cypermethrin 5 %) at 1 and 2 L?ha^?1 at an interval of 15 days. Residues of chlorpyriphos and cypermethrin in chilli were estimated by gas–liquid chromatography and confirmed by gas chromatography–mass spectrometry. Half-life periods for chlorpyriphos were found to be 4.43 and 2.01 days, whereas for cypermethrin these values were observed to be 2.51 and 2.64 days at single and double the application rates, respectively. Residues of chlorpyriphos dissipated to more than 80 % after 10 days at both the dosages. However, residues of cypermethrin dissipated to the extent of more than 70 % in 7 days. Soil samples collected after 15 days of the last application did not show the presence of chlorpyriphos and cypermethrin at their respective determination limit of 0.01 mg?kg^?1. The use of chlorpyriphos and cypermethrin mixture at the recommended dosage does not seem to pose any hazards to the consumers, and a waiting period of 1 day is suggested to reduce the risk before consumption of green chilli.     

Alteration of antioxidant enzymes and impairment of DNA in the SiO2 nanoparticles exposed zebra fish (Danio rerio)

The incorporation of nanoparticles in industrial and biomedical applications has increased significantly in recent years, yet their hazardous and toxic effects have not been studied extensively. While standard toxicological test methods are generally capable of detecting the toxic effects, the choice of relevant methods for nanomaterials is still discussed. Among the various oxide nanomaterials, silica nanoparticles are widely used in biological applications that include nano-medicine. But studies on adverse effects of silica nanoparticle exposure to fish remain unclear. Therefore, the present study was designed to investigate the oxidative toxic effects of silicon dioxide nanoparticles using fish model. The size of the SiO₂ nanoparticles was between 68 and 100 nm which was confirmed by X-ray diffractometer, dynamic light scattering, scanning electron microscope and transmission electron microscope. The zebra fish were exposed to sub-lethal concentrations (5 and 2.5 mg/L) of characterized SiO₂ nanoparticles for a period of 7 days. After 7 days, SiO₂ nanoparticle-treated fishes were sacrificed, and tissues such as liver, muscle and gill were dissected out for the analysis of antioxidant enzymes and DNA fragmentation. The DNA profiles were analysed in the tissues of zebra fish that treated with SiO₂ nanoparticles. Tissues of fish from clean water were used as control, and DNA profiles were analysed. It is found that DNA from control tissues was intact, whereas the tissues treated with SiO₂ were all fragmented. SiO₂ nanoparticle-mediated antioxidant enzymes activities, such as catalase, superoxide dismutase, glutathione (GSH)-S-transferase, glutathione reductase and GSH, in the tissues of zebra fish were measured. The results revealed that alteration of antioxidant enzymes due to SiO₂ nanoparticle can be considered as a biomarker to SiO₂-mediated oxidative stress in biological samples.     

Speciation of selected heavy metals geochemistry in surface sediments from Tirumalairajan river estuary, east coast of India

Surface sediment samples from the Tirumalairajan river estuary were studied for grain size pattern, organic matter, and heavy metals (Fe, Mn, Zn, and Pb) using the sequential and bulk metal extraction methods to evaluate metal behavior. Ten surface sediment samples were collected during the monsoon and summer seasons of the year 2009. The observed orders of concentrations of heavy metals in the sediments were as follows: Fe?>?Mn?>?Zn?>?Pb. The results obtained from sequential extraction showed that, among the metals studied, a larger portion of the metals were associated with the residual phase, although they are available in other fractions. The low concentration of metals available in bioavailable phases indicated that the sediments of Tirumalairajan river estuary were relatively unpolluted. Correlation analysis was also carried out to understand the associations of metals in different phases with sand, silt, clay, and organic matter. To understand the risk of heavy metals to sediment-dwelling organisms, the data were compared with risk assessment code and sediment quality values using the screening quick reference table. The main source of metals to the estuary is from the irrigation field and its associated activities in the study area.     

An assessment of the optimal scale for monitoring of MODIS and FIA NPP across the eastern USA

Robust monitoring of carbon sequestration by forests requires the use of multiple data sources analyzed at a common scale. To that end, model-based Moderate Resolution Imaging Spectroradiometer (MODIS) and field-based Forest Inventory and Analysis (FIA) data of net primary productivity (NPP) were compared at increasing levels of spatial aggregation across the eastern USA. A total of 52,167 FIA plots and colocated MODIS forest cover NPP pixels were analyzed using a hexagonal tiling system. A protocol was developed to assess the optimal scale as an optimal size of landscape patches at which to map spatially explicit estimates of MODIS and FIA NPP. The optimal mapping resolution (hereafter referred to as optimal scale) is determined using spatially scaled z-statistics as the tradeoff between increased spatial agreement as measured by Pearson’s correlation coefficient and decreased details of coverage as measured by the number of hexagons. Spatial sensitivity was also assessed using land cover assessment and forest homogeneity using spatially scaled z-statistics. Pearson correlations indicate that MODIS and FIA NPP are most highly correlated when using large hexagons, while z-statistics indicate an optimal scale at an intermediate hexagon size of 390 km². This optimal scale had more spatial detail than was obtained for larger hexagons and greater spatial agreement than was obtained for smaller hexagons. The z-statistics for land cover assessment and forest homogeneity also indicated an optimal scale of 390 km².     

Automated riverine landscape characterization: GIS-based tools for watershed-scale research, assessment, and management

River systems consist of hydrogeomorphic patches (HPs) that emerge at multiple spatiotemporal scales. Functional process zones (FPZs) are HPs that exist at the river valley scale and are important strata for framing whole-watershed research questions and management plans. Hierarchical classification procedures aid in HP identification by grouping sections of river based on their hydrogeomorphic character; however, collecting data required for such procedures with field-based methods is often impractical. We developed a set of GIS-based tools that facilitate rapid, low cost riverine landscape characterization and FPZ classification. Our tools, termed RESonate, consist of a custom toolbox designed for ESRI ArcGIS®. RESonate automatically extracts 13 hydrogeomorphic variables from readily available geospatial datasets and datasets derived from modeling procedures. An advanced 2D flood model, FLDPLN, designed for MATLAB® is used to determine valley morphology by systematically flooding river networks. When used in conjunction with other modeling procedures, RESonate and FLDPLN can assess the character of large river networks quickly and at very low costs. Here we describe tool and model functions in addition to their benefits, limitations, and applications.     

Distribution of radionuclides in surface soils, Singhbhum Shear Zone, India and associated dose

Gamma emitters were estimated in surface soils from a mineralized zone in Eastern India using high purity Germanium detector-based high resolution gamma spectrometry system. Activities of ²³⁸U, ²²⁶Ra, ²³²Th, ²³⁵U, ²²⁷Th, ^234mPa, ²¹⁰Pb, ⁴⁰K, and ¹³⁷Cs were 79?±?50, 81?±?53, 65?±?23, 4?±?2, 5?±?4, 92?±?50, 97?±?45, 517?±?201, and 4?±?2 Bq/kg, respectively. Most radionuclides were observed to follow log-normal distribution. The correlation between physicochemical properties of the samples, like pH, organic matter content, particle size, and moisture content were also studied. Activity ratios of ²²⁶Ra/²³⁸U, ²¹⁰Pb/²²⁶Ra, and ²²⁷Th/²³⁵U indicated deviation from secular equilibrium in some samples. The associated annual effective dose ranged from 0.07 to 0.24 mSv and the mean was calculated to be 0.12?±?0.04 mSv for this region, indicating it to be one of normal natural background radiation.     

Sand as a relevant fraction in geochemical studies in intertidal environments

Soil and sediment samples from several intertidal environment exposed to different types of contamination were studied to investigate the importance of grain size in relation to the capacity of the substrates to retain trace metals. The unfractionated samples (referred to as bulk samples) were separated into the following grain/size fractions: fine–coarse sand (2?0.100 mm), very fine sand (0.100?0.050 mm), silt (0.050?0.002 mm), and clay (0.002 mm). The sample into its fractions was carried out was in a glove box under high-purity N₂ atmosphere in order to minimize any alterations to the samples. The bulk samples were characterized in terms of physicochemical properties such as pH, redox potential, and grain size. The total organic carbon (TOC), total sulfur (S), iron (Fe) pyrite, Fe, and manganese (Mn), and trace metals lead (Pb), mercury (Hg), chromium (Cr), and nickel (Ni) were analyzed in the bulk samples and in each fraction. The sand fractions were also examined by scanning electron microscopy (SEM). Comparisons of the above parameters were made between fractions and between each fraction and the corresponding bulk sample. The fine–coarse sand fraction contained high levels of the primary elements of the geochemical processes that occur in marine sedimentary environments such as TOC, total Fe, Mn, and S. The net concentrations of these four elements were higher in the fine-coarse sand fraction than in the very fine sand fraction and were similar to the net concentrations in the silt and clay fractions. Detailed SEM analysis of the sand coarse fraction revealed the presence of Fe and aluminum oxyhydroxide coatings in the oxic layers, whereas the framboidal pyrites and coatings observed in the anoxic layers were Fe sulfides. The presence of the various coatings explains why the trace metal concentrations in the sand fine–coarse fraction were similar to those in the clay fraction and higher than those in the very fine sand fraction. The present results highlight the importance of the sand fraction, which is generally disregarded in geochemical and environmental studies of sedimentary layers.     

Status and effect of pesticide residues in soils under different land uses of Andaman Islands, India

Pesticides are shown to have a great effect on soil organisms, but the effect varies with pesticide group and concentration, and is modified by soil organic carbon content and soil texture. In the humid tropical islands of Andaman, India, no systematic study was carried out on pesticide residues in soils of different land uses. The present study used the modified QuEChERS method for multiresidue extraction from soils and detection with a gas chromatograph. DDT and its various metabolites, α-endosulfan, β-endosulfan, endosulfan sulfate, aldrin, and fenvalerate, were detected from the study area. Among the different pesticide groups detected, endosulfan and DDT accounted for 41.7 % each followed by aldrin (16.7 %) and synthetic pyrethroid (8.3 %). A significantly higher concentration of pesticide residues was detected in rice–vegetable grown in the valley followed by rice–fallow and vegetable–fallow in the coastal plains. Soil microbial biomass carbon is negatively correlated with the total pesticide residues in soils, and it varied from 181.2 to 350.6 mg?kg^?1. Pesticide residues have adversely affected the soil microbial populations, more significantly the bacterial population. The Azotobacter population has decreased to the extent of 51.8 % while actinomycetes were the least affected though accounted for 32 % when compared to the soils with no residue.