Use of USLE/GIS Methodology for Predicting Soil Loss in a Semiarid Agricultural Watershed

The Universal Soil Loss Equation (USLE) is an erosion model to estimate average soil loss that would generally result from splash, sheet, and rill erosion from agricultural plots. Recently, use of USLE has been extended as a useful tool predicting soil losses and planning control practices in agricultural watersheds by the effective integration of the GIS-based procedures to estimate the factor values in a grid cell basis. This study was performed in the Kazan Watershed located in the central Anatolia, Turkey, to predict soil erosion risk by the USLE/GIS methodology for planning conservation measures in the site. Rain erosivity (R), soil erodibility (K), and cover management factor (C) values of the model were calculated from erosivity map, soil map, and land use map of Turkey, respectively. R values were site-specifically corrected using DEM and climatic data. The topographical and hydrological effects on the soil loss were characterized by LS factor evaluated by the flow accumulation tool using DEM and watershed delineation techniques. From resulting soil loss map of the watershed, the magnitude of the soil erosion was estimated in terms of the different soil units and land uses and the most erosion-prone areas where irreversible soil losses occurred were reasonably located in the Kazan watershed. This could be very useful for deciding restoration practices to control the soil erosion of the sites to be severely influenced.     

Protective effects of melatonin and vitamin E in acetamiprid-induced nephrotoxicity

Environmental Science and Pollution Research - Investigation of probable toxic effects of acetamiprid (ACMP) on kidney and comparative analysis of the probable protective effects of vitamin E and...     

Interactions between metals accumulated in the narrow-clawed crayfish Astacus leptodactylus (Eschscholtz, 1823) in Dikilitaş Lake,Turkey

The accumulations of Al, Cd, Cr, Cu, Fe, Ni, Pb and Zn in the exoskeleton, gills, hepatopancreas and abdominal muscles of crayfish Astacus leptodactylus (Eschscholtz, 1823) were determined. The strongest correlation observed was between Cr and Ni in the gills (r?=?0.904); moderate to strong correlations between Al, Cr, Fe, Ni and Cu were also observed in gill tissue. Disregarding the gills, the strongest correlation was found between Cu and Zn in the hepatopancreas (r?=?0.808); the correlation between these two metals might have been a result of metallothionein activity. The accumulation of Pb was found to correlate with that of Cd in the exoskeleton, Cd and Zn in the gills, Zn and Cu in the hepatopancreas and Cu in the abdominal muscle. None of these correlations were present in lakewater and sediment samples, suggesting that the crayfish metabolism may be responsible for the co-accumulation of metal–metal pairs. As all correlations in non-gill tissues are observed between divalent metals, a shared transporter such as divalent metal transporter 1 might be involved in the accumulation of these metals.     

Effects of spacing and post-planting treatments on survival and growth of Fraxinus angustifolia seedlings

This study was conducted at a bottomland hardwood site with heavy textured soil in Akyazi, Turkey to determine the effect of initial spacing (3.0 x 3.0, 3.0 x 2.0, 2.5 x 1.6 and 2.5 x 1.2 m) and post-planting treatments (untreated check, moving, hoeing, disking, and hoeing plus disking) on early survival and growth of Fraxinus angustifolia Vahl. One-year old bare-root seedlings (70 +/- 5 cm in height) were hand-planted in December 2004. Through three years survival was perfect with a rate of 98% in all treatments. Spacing and the interaction between spacing and post-planting treatment did not significantly affect seedling growth through three years. However height and diameter growth increased overtime and differed significantly among post-planting treatments. The hoeing and hoeing plus disking treatments gave the highest growth, and resulted in about 31% increase in diameter and height increment, and in total diameter and height about 20%. These results suggest that post-planting treatments on bottomland sites with heavy textured soil give promising results.     

The influence of biomass energy consumption on CO<Subscript>2</Subscript> emissions: a wavelet coherence approach

In terms of today, one may argue, throughout observations from energy literature papers, that (i) one of the main contributors of the global warming is carbon dioxide emissions, (ii) the fossil fuel energy usage greatly contributes to the carbon dioxide emissions, and (iii) the simulations from energy models attract the attention of policy makers to renewable energy as alternative energy source to mitigate the carbon dioxide emissions. Although there appears to be intensive renewable energy works in the related literature regarding renewables’ efficiency/impact on environmental quality, a researcher might still need to follow further studies to review the significance of renewables in the environment since (i) the existing seminal papers employ time series models and/or panel data models or some other statistical observation to detect the role of renewables in the environment and (ii) existing papers consider mostly aggregated renewable energy source rather than examining the major component(s) of aggregated renewables. This paper attempted to examine clearly the impact of biomass on carbon dioxide emissions in detail through time series and frequency analyses. Hence, the paper follows wavelet coherence analyses. The data covers the US monthly observations ranging from 1984:1 to 2015 for the variables of total energy carbon dioxide emissions, biomass energy consumption, coal consumption, petroleum consumption, and natural gas consumption. The paper thus, throughout wavelet coherence and wavelet partial coherence analyses, observes frequency properties as well as time series properties of relevant variables to reveal the possible significant influence of biomass usage on the emissions in the USA in both the short-term and the long-term cycles. The paper also reveals, finally, that the biomass consumption mitigates CO₂ emissions in the long run cycles after the year 2005 in the USA.     

Estimation of total sediment load concentration obtained by experimental study using artificial neural networks

Estimation of sediment concentration in rivers is very important for water resources projects planning and managements. The sediment concentration is generally determined from the direct measurement of sediment concentration of river or from sediment transport equations. Direct measurement is very expensive and cannot be conducted for all river gauge stations. However, sediment transport equations do not agree with each other and require many detailed data on the flow and sediment characteristics. The main purpose of the study is to establish an effective model which includes nonlinear relations between dependent (total sediment load concentration) and independent (bed slope, flow discharge, and sediment particle size) variables. In the present study, by performing 60 experiments for various independent data, dependent variables were obtained, because of the complexity of the phenomena, as a soft computing method artificial neural networks (ANNs) which is the powerful tool for input–output mapping is used. However, ANN model was compared with total sediment transport equations. The results show that ANN model is found to be significantly superior to total sediment transport equations.     

A study of a sustainable greenway approach for a part of the Silk Road in Turkey

The article describes different steps and methodologies to create an alternative greenway with recreational, scenic, historical and cultural values in Hamsiköy-Zigana, part of Trabzon-Gümü?hane former state highway. As a first step, inventory studies and analyses were carried out to determine the cultural and natural values of the area. As the second step, area analyses studies were carried out. Depending on results of expert-based visual assessment and suitability analyses for determining the suitability of greenway planning in the study area; recreational, scenic, historical–cultural and multifunctional status of the greenway having all these three functions at the same time were mapped using suitability rank in GIS and the plan square technique. As a result, the plan squares having high suitability for the above functions were dense in the determined study, in terms of old highway and neighbourhood. In the whole area (4385.25 ha), 598.00 ha were ranked as good (A), 770.27 ha as medium (B) and 3016.98 ha as poor (C), in terms of suitability value. Seasonal assessments for recreation and scenery functions of A, B and C indicate that the area has opportunities for all seasons. As a third step, the results are discussed and some proposals suggested.     

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation. Many of the water quality variables (chemical oxygen demand, temperature, dissolved oxygen, water flow, chlorophyll a and nutrients, ammonia, nitrite, nitrate) that affect biological oxygen demand concentrations were collected at 11 sampling sites in the Melen River Basin during 2001-2002. To develop an ANN model for estimating BOD, the available data set was partitioned into a training set and a test set according to station. In order to reach an optimum amount of hidden layer nodes, nodes 2, 3, 5, 10 were tested. Within this range, the ANN architecture having 8 inputs and 1 hidden layer with 3 nodes gives the best choice. Comparison of results reveals that the ANN model gives reasonable estimates for the BOD prediction.     

Genotoxicity study of high aspect ratio silver nanowires

The genotoxicity potential of silver nanowires synthesized via the solution-based polyol method has been investigated. They were found to be non-mutagenic in three Salmonella strains and were not genotoxic in a clastogenicity assay in mice. Residual surfactant was found to have an effect on the toxicological properties of the nanowires by increasing the rate of Ag⁺ release. Residual surfactant can be easily degraded via a UV treatment.     

Bacterial community composition of sediments from Artificial Lake Maslak, Istanbul, Turkey

Small artificial lakes are ubiquitous in various natural environments. Small impoundments increase the residence time of water, thereby increasing the potential for retention of nutrients through biological and physical processes. We examined bacterial community structure of Lake Maslak, a small freshwater impoundment located in a densely populated region. The objective of our study was to investigate bacterial communities of the lake sediment which has not been determined and to elucidate the factors controlling bacterial diversity and the biogeochemical processes within the lake. For these purposes, surface water, lake bed sediments, and one core sample were collected. Microbiological characteristic of the lake bed and core sediments was determined by denaturing gradient gel electrophoresis targeting the 16S rRNA gene. Along with the microbiological studies, physicochemical (O(2), pH, temperature) and geochemical properties of the surface (NO (3) (-) , NO (2) (-) , NH (4) (+) ,PO (4) (-) ,SO (4) (2-) , K(+), Mg(2+), Ca(2+)) and pore water (K(+), Mg(2+), Ca(2+)) were determined in addition to heavy metals contents (Co Cu, Fe, Zn, Pb, Cd). Eight lake bed and one core sediments were also collected and analyzed for heavy metals and elemental compositions. Nitrate concentration in the surface water ranges from 0.27-1.8 mg/L, and ammonium (0.0-0.83 mg/L) appears to follow nitrate concentration. Sulfate concentration in the surface water (mean 60 mg/L) is greater than those measured in the pore water (mean, 37.5 mg/L). Fe, Zn, Pb, and Cd were not determined in the surface water, whereas Co was significantly higher both in the surface and pore water. Unlike Co, Pb, Zn, and Cd were not measured in the pore water. Lakebed and core sediments show significant enrichment in Pb, Zn, and Cu, indicating anthropogenic pollution. Consistent with geochemical parameters, microbiological analysis suggests a diverse bacterial community in the lake sediments and influence of anthropogenic pollution (e.g., atmospheric emission) on bacterial community.