Spatial and temporal characterization of standard duration-maximum precipitation over Black Sea Region in Turkey

Natural Hazards - This study characterises the spatial and temporal behaviours of maximum precipitation over the Black Sea Region in northern Turkey. Maximum precipitation data of 14 standard...     

Seismic stratigraphy of Late Quaternary sediments of western Mersin Bay shelf, (NE Mediterranean Sea)

High-resolution shallow seismic-reflection profiles obtained from the western Mersin Bay have revealed the existence of the two distinct depositional sequences (C and B) lying on a narrow and relatively steeply-sloping continental shelf which mainly receives its sediments from the ephemeral rivers. The upper Holocene sedimentary sequence (C) is characterized by stratified (simple to complex) to chaotic reflection configurations produced by the development of a prograding wedge of terrigenous sediment. Particular occurrences of slope- and front-fill facies and the lack of a sharp boundary, which has, however, been observed on the western shelf of this bay, between the Early Holocene and latest Pleistocene deposits are related to possible movement of underlying deposits due to local gravity mass movements or synsedimentary tectonics due to adjustment of the underlying evaporites in adjacent basin. The maximum thickness of the topmost sequence C is associated with the Tarsus–Seyhan delta, which lies to the northeast of the area and is prograding along the shelf. Other variations in thickness (5–40 m) of this topmost sequence are related to the variable sediment discharge along the coast, and the distance from the coast. It is at a maximum (40 m) in the nearshore area just west of the Lamas river mouth and at a minimum (5–15 m) in the offshore area.

The lower depositional pre-Holocene sequence (B) is characterized by continuous to wavy reflection configurations and how some cyclicity, suggesting coarse, heterogeneous sediments deposited under high energy conditions (fan-deltas) of Plio-Pleistocene age.

The combined interpretation of seismic reflection profiles with the available bore-hole data reveals the existence of a widespread Miocene acoustic basement (A) off the Susanoğlu–Tırtar coasts and Karapınar–Gilindirez rivers mouths. Unusual features in some profiles suggest the escape of coastal freshwater into the accumulating sediment.     

Prediction of ground vibrations resulting from the blasting operations in an open-pit mine by adaptive neuro-fuzzy inference system

The aim of this study is to predict the peak particle velocity (PPV) values from both presently constructed simple regression model and fuzzy-based model. For this purpose, vibrations induced by bench blasting operations were measured in an open-pit mine operated by the most important magnesite producing company (MAS) in Turkey. After gathering the ordered pairs of distance and PPV values, the site-specific parameters were determined using traditional regression method. Also, an attempt has been made to investigate the applicability of a relatively new soft computing method called as the adaptive neuro-fuzzy inference system (ANFIS) to predict PPV. To achieve this objective, data obtained from the blasting measurements were evaluated by constructing an ANFIS-based prediction model. The distance from the blasting site to the monitoring stations and the charge weight per delay were selected as the input parameters of the constructed model, the output parameter being the PPV. Valid for the site, the PPV prediction capability of the constructed ANFIS-based model has proved to be successful in terms of statistical performance indices such as variance account for (VAF), root mean square error (RMSE), standard error of estimation, and correlation between predicted and measured PPV values. Also, using these statistical performance indices, a prediction performance comparison has been made between the presently constructed ANFIS-based model and the classical regression-based prediction method, which has been widely used in the literature. Although the prediction performance of the regression-based model was high, the comparison has indicated that the proposed ANFIS-based model exhibited better prediction performance than the classical regression-based model.     

Equilibrium data and process design for adsorption of disperse dyes onto Alunite

Adsorption of disperse dyes from aqueous solutions onto calcined alunite has been investigated to assess the possibility of using alunite for removing disperse dyes from aqueous solutions. The effects of particle size, adsorbent mass, initial pH and temperature of the dye solution on the adsorption capacities have been evaluated. Acidic pH was favorable for the adsorption of all dyes: Disperse Blue 56 (DB56), Disperse Red 74 (DR74) and Disperse Yellow 119 (DY119). The experimental data were correlated reasonably well by the Langmuir isotherm and the isotherm parameters (K_L and a_L) have been calculated. The adsorption capacities were found to be 498, 525 and 500 mg of dye per g of calcined alunite for DB56, DR74 and DY119, respectively. The single-stage batch adsorber design of the adsorption of disperse dyes onto alunite has been studied based on the Langmuir isotherm equation.     

DDT,DDE, and PCB residues in fish,crustaceans and sediments from the eastern Mediterranean coast of Turkey

Residues of DDE, DDT and PCBs were determined in four different commercial bony fishes: grey mullet, red mullet, striped mullet and gold bandgoat fish, as well as in shrimps, limpets and sediments obtained from the eastern Mediterranean coast of Turkey. The PCB levels in living organisms and sediments were found to be very low, and in most cases below the detection limits. The DDE and DDT values were relatively high compared to PCBs and there was a linear correlation between the organochlorine residue concentrations and the extractable organic material of the analysed samples.     

Identifying drivers for fishing pressure. A multidisciplinary study of trawl and sea snail fisheries in Samsun,Black Sea coast of Turkey

This study aims to investigate and model driving forces that lead to increased fishing pressure and an altered state of the environment in the coastal areas near Samsun on the Turkish Black Sea coast. We have applied a modified DPSIR model to structure our investigation and analysis and have investigated the drivers that generate fishing pressure in the Samsun fisheries. The overall health of the ecosystem is declining, and there is a consistent trend of deterioration in the condition of the three major species targeted by the trawl fisheries. Although introduced invasive species have brought significant changes to the Black Sea, it is clear that the state of the environment is significantly and negatively affected by the pressure exerted by fisheries. Fishing pressure has to a certain extent been redirected to pelagic trawling as bottom trawling has become less profitable and a rise in catch capacity has levelled off. This reduction is, however, offset by an increase in illegal trawling and dredging by a very rapidly growing sector of multi-purpose small boats, resulting in a considerable increase in the overall accumulated engine power of fishing boats in Samsun during 2000–2005. Fisheries in Samsun, in particular sea snail fisheries, have constituted a frontier of sorts open to the poorer populations of Samsun during the last 20 years, and, thereby, constitute one of the major drivers for fishing pressure. We identify eight drivers of importance for the period 2000–2005. Although the authorities can impact all or most of those drivers, most of them are beyond the scope of conventional ‘fisheries management’.     

Hydrological time‐series modelling using an adaptive neuro‐fuzzy inference system

Accurate forecasting of hydrological time‐series is a quite important issue for a wise and sustainable use of water resources. In this study, an adaptive neuro‐fuzzy inference system (ANFIS) approach is used to construct a time‐series forecasting system. In particular, the applicability of an ANFIS to the forecasting of the time‐series is investigated. To illustrate the applicability and capability of an ANFIS, the River Great Menderes, located in western Turkey, is chosen as a case study area. The advantage of this method is that it uses the input–output data sets. A total of 5844 daily data sets collected from 1985 to 2000 are used for the time‐series forecasting. Models having various input structures were constructed and the best structure was investigated. In addition, four various training/testing data sets were built by cross‐validation methods and the best data set was obtained. The performance of the ANFIS models in training and testing sets was compared with observations and also evaluated. In order to get an accurate and reliable comparison, the best‐fit model structure was also trained and tested by artificial neural networks and traditional time‐series analysis techniques and the results compared. The results indicate that the ANFIS can be applied successfully and provide high accuracy and reliability for time‐series modelling. Copyright © 2007 John Wiley & Sons, Ltd.     

Development of a GIS-based monitoring and management system for underground coal mining safety

Coal mine safety is of paramount concern to mining industry. Mine accidents have various causes and consequences including catastrophic failure of mine, substantial economic losses and most notably loss of lives. Therefore, any initiative in mine monitoring is of vital importance for progressing safety surveillance and maintenance.This paper presents the development of a geographic information system (GIS)-based monitoring and management system for underground mine safety in three levels as constructive safety, surveillance and maintenance, and emergency. The developed model integrates the database design and management to the monitoring system implementation which encompasses query and analysis operations with the help of web and desktop applications. Interactive object-oriented graphical user interfaces (GUIs) were developed to visualize information about the entities gathered from the model and also to provide analysis operations based on the graphical representations and demonstrations using data tables and map objects.The research methodology essentially encompasses five main stages: (i) designing a conceptual database model; (ii) development of a logical model in terms of entity-relationship (ER) diagrams; (iii) development of a physical model based on physical constraints and requirements; (iv) development of GUIs and implementation of the developed model, analysis and queries; (v) verification and validation of the created model for Ömerler underground coal mine in Turkey. The proposed system is expected to be an efficient tool for improving and maintaining healthy standards in underground coal mines which can possibly be extended to a national GIS infrastructure.     

Monitoring of coal mining subsidence in peri-urban area of Zonguldak city (NW Turkey) with persistent scatterer interferometry using ALOS-PALSAR

This paper presents the results of spatiotemporal monitoring of surface subsidence over a mining area in Zonguldak Province of Turkey using Synthetic Aperture Radar (SAR) data, providing maps of subsidence rates in the radar line of sight direction. A total of 18 SAR images, acquired between January 2007 and June 2010 by the Japanese Advanced Land Observing Satellite, have been used to map the surface displacements using the Persistent Scatterer Interferometry technique. The use of Phased Array Type L-band Synthetic Aperture Radar data has proved useful for avoiding signal decorrelation and estimating surface deformation in the heavily vegetated study region. The technique enables the monitoring of continuous small displacements over a large area. Our findings present that many Persistent Scatterers were located on the vegetation cover. The results reveal areas of ground surface subsidence up to 44 mm/year that are well correlated with the underground coal mining galleries particularly in the Gelik region where the Karadon mining galleries are present.