Statistical source identification of major and trace elements in groundwater downward the tailings dam of Miduk Copper Complex, Kerman, Iran

Identifying the possible sources of potential harmful metals in groundwater systems plays a crucial role in evaluating the potential risks to residents and local plant cover. An attempt was made to define the origin of Al, Cd, Cu, Fe, Mo, Ni, and Pb in groundwater using multivariate statistic approaches [principal component analysis (PCA), hierarchical cluster analysis], and tailings sequential extraction by the method of Tessier et al. The concentrations of studied elements were measured in 42 samples collected from 15 stations surrounding and downward the tailings dam of Miduk Copper Complex, central province of Kerman, Iran. According to the PCA results, confirmed by cluster dendrogram and metal content measurement of tailings sequential extracts, two components accounting for nearly 73% of the total variance, controlled the heavy metal variability and classified the possible source of groundwater contamination into two categories: (1) upper seepage which controls the variability of Cd, Cu, Fe, Ni, and Pb and (2) toe seepage of tailings dump affecting on Mo and Al concentration in downstream groundwater.     

Geostatistical Evaluation of Spatial Variation Related to Groundwater Quality Database: Case Study for Arak Plain Aquifer,Iran

Geostatistical methods are one of the advanced techniques to interpolate groundwater quality data. Geostatistical interpolation techniques employ both the mathematical and the statistical properties of the measured points. Compiling the data distribution on spatial and temporal domain is of crucial importance in order to evaluate its quality and safety. The main purpose of this paper is to assess groundwater quality of Arak plain, Iran, by an unbiased interpolated method so called Kriging. Therefore, seven quality variables of Arak plain aquifer including TDS, SAR, EC, Na⁺, TH, Cl^?, and SO₄ ^2? have been analyzed, studied, and interpreted statistically and geostatistically. Utilized data in this study were collected from 97 water well samples in Arak plain, in 2012. After normalizing data, variogram as a geostatistical tool for defining spatial regression was calculated and experimental variograms have been plotted by GS⁺ software, then the best theoretical model was fitted to each variogram based on minimum RSS error. Cross validation was used to determine the accuracy of the estimated data. The uncertainty of the method could be well assessed via this method since the method not only gave the average error (around 0 in this study) but also gave the standard deviation of the estimations. Therefore, more than 3800 points were estimated by ordinary Kriging algorithm in places which have not been sampled. Finally, estimation maps of groundwater quality were prepared and map of estimation variance, EV, has been presented to assess the quality of estimation in each estimated point. Results showed that the Kriging method is more accurate than the traditional interpolation algorithms not honoring the spatial properties of the database.     

Adaptation of Iranian farmers to climate variability and change

Climate change poses serious challenges for populations whose livelihoods depend principally on natural resources. Given the increases in extreme weather events projected to adversely affect the arid and semi-arid regions of Iran, adaptation of the agricultural sector is imperative. Few studies have addressed the farmers’ adaptation in Iran, and little is known about ongoing adaptation strategies in use. Adopting principal component analysis/fuzzy logic-based method, this paper considers the agricultural adaptation to climate variability. A survey of 255 farmers of Fars Province, selected through a multistage stratified random sampling method, revealed different levels of adaptation, specifically the low, moderate and high, which are principally distinguished by various degrees of sensitivity and adaptive capacity. The study also identified the main adaptation strategies used by farmers in response to climate-related shocks. Results indicated that although a large percentage of farmers make some adjustments to their farming practices, there are significant differences in choice of adaptation strategies by the adaptation categories. Some conclusions and recommendations are offered to increase the adaptive capacity of farmers and reduce negative impacts of climate variability and change.     

The effect of neglecting spatial variations of the parameters in pollutant transport modeling in rivers

Environmental Fluid Mechanics - For many environmental projects and plans, it is necessary to model pollutant transport in rivers. Pollutant transport modeling is a complex phenomenon with multiple...     

Optimization of a methodology for the simultaneous determination of deltamethrin,permethrin and malathion in stored wheat samples using dispersive liquid–liquid microextraction with solidification of floating organic drop and HPLC-UV

The purpose of this study was to investigate common pesticides in stored wheat at Kermanshah province's silos in Iran. A simple, inexpensive, reliable and environmentally friendly method based on dispersive liquid–liquid microextraction with solidification of floating organic drop was developed. The analytical characteristics of the method were determined. Also, various parameters such as the materials of the silos, types of ownerships of the silos, geographic orientation of silo locations and climatic conditions of silo locations on pesticide residues in studied wheat samples were investigated. Among all the studied parameters, the climatic conditions of silo locations showed the highest influence on pesticide residues in wheat samples. Generally, 61.2% of the samples had pesticide levels below the method detection limits and 38.8% of the total samples had at least one of the understudied pesticides. Also, 13.9% of the samples had deltamethrin residues, 16.7% of the samples had permethrin, 22.2% of the samples had malathion, 11.1% of the samples had both permethrin and malathion and 2.8% of the samples had both deltamethrin and malathion. The results revealed that the residues of deltamethrin and malathion were lower than the standard level announced by European Union regulation and only three samples contained permethrin higher than Europe standard level.     

Fuzzy logic and adaptive neuro-fuzzy inference system for characterization of contaminant exposure through selected biomarkers in African catfish

This study represents a first attempt at applying a fuzzy inference system (FIS) and an adaptive neuro-fuzzy inference system (ANFIS) to the field of aquatic biomonitoring for classification of the dosage and time of benzo[a]pyrene (BaP) injection through selected biomarkers in African catfish (Clarias gariepinus). Fish were injected either intramuscularly (i.m.) or intraperitoneally (i.p.) with BaP. Hepatic glutathione S-transferase (GST) activities, relative visceral fat weights (LSI), and four biliary fluorescent aromatic compounds (FACs) concentrations were used as the inputs in the modeling study. Contradictory rules in FIS and ANFIS models appeared after conversion of bioassay results into human language (rule-based system). A “data trimming” approach was proposed to eliminate the conflicts prior to fuzzification. However, the model produced was relevant only to relatively low exposures to BaP, especially through the i.m. route of exposure. Furthermore, sensitivity analysis was unable to raise the classification rate to an acceptable level. In conclusion, FIS and ANFIS models have limited applications in the field of fish biomarker studies.     

Male Alborz Red Sheep (<Emphasis Type="Italic">Ovis gmelini</Emphasis> × <Emphasis Type="Italic">O. vignei</Emphasis>) migration corridors selection from summer to fall habitats in Jajroud Protected Area Complex,Iran

Jajroud Protected Area Complex is one of the main habitats of Alborz Red Sheep (Ovis gmelini × O. vignei) in Iran. Being close to Tehran, this habitat has been reduced and fragmented due to the human constructions. This study was designed with the aim of identifying the summer and fall habitat patches and the suitability of the matrix by means of Ecological Niche Factor Analysis (ENFA). Cost-distance function was then used to calculate the cost of moving among the patches and the corridors with the least cost was identified using Least-cost path analysis. Results showed that, in both seasons, the species inhabits a narrow niche and is very sensitive to habitat changes. Overall, a suitable habitat for this species is at an elevation of more than 1535 m, with a lower average temperature than average of the habitat, with suitable escape terrain, and away from villages. Military areas, based on their specific use, can have different effects on the habitat suitability. This species selects corridors which are close to escape terrain, with a slope of about 15 percent and low slope fluctuation.     

Numerical and artificial intelligence models for predicting the water advance in border irrigation

Environment, Development and Sustainability - The water advance time (Ta) is needed for designing and evaluating surface irrigation systems. This study employed artificial neural networks (ANNs)...