Soil gas radon concentrations along the Ganos Fault (GF)

In this study, soil radon levels have been measured for the first time across the Ganos fault (GF), which is known as the western part of the North Anatolian Fault Zone. LR 115 Type 2 Solid State Nuclear Track Detectors (time integrated) have been applied to determine soil gas radon levels, and the survey was performed in 16 stations along the fault line. The results showed that soil gas radon concentrations and variation of concentration levels are comparable high along the fault line. It is also observed that in the middle of the Ganos Fault, fairly elevated radon levels were detected. These can be related to the activity of the fault lines. It is confirmed that the study area has a very active tectonic structure and is great location for analyzing radon variations.     

The measurement of soil gases and shallow temperature for determination of active faults in a geothermal area: a case study from Ömer–Gecek,Afyonkarahisar (West Anatolia)

Afyonkarahisar is a very important geothermal province of western Anatolia and has low and medium enthalpy geothermal areas. This study has been carried out for the preparation of distribution maps of soil gases (radon and carbon dioxide) and shallow soil temperature and the exploration of permeable tectonic regions associated with geothermal systems and reveal the origins of radon and carbon dioxide gases. The western district of the study area is characterized by the high radon concentration (168.30 kBq/m³), carbon dioxide ratio (0.30%), and soil temperature (21.0 °C) values. Fethibey and Demirçevre faults, which allow the circulation of geothermal fluids, have been detected in the distribution maps of radon, carbon dioxide, and shallow depth temperature and the directions of the curves in these maps correspond to the strikes of Demirçevre faults. The effect of the fault plays an important role in the change of carbon dioxide concentration along the W-E directional geological section prepared to determine the change of soil gas and shallow depth temperature values depending on lithological differences, fault existence, and geothermal reservoir depth. On the other hand, it was determined that Rn²²² concentration and soil temperature changed as a function of geothermal reservoir depth or lithological difference. Tuffs in Köprülü volcano-sedimentary units are the main source of radon due to their higher uranium contents. Besides, the carbon dioxide in Ömer–Gecek soils has geothermal origin because of the highest carbon dioxide content (99.3%) in non-condense gas. The similarities in patterns of soil temperature, radon, and carbon dioxide indicate that the variation in soil temperatures is related to radon and carbon dioxide emissions. It is concluded that soil gas and temperature measurements can be used to determine the active faults in the initial stage of geothermal exploration successfully.     

Investigation of the Kumdanlı and surrounding faults on the Eğirdir Lake by conducting ground penetrating radar (GPR) profiles

A ground penetrating radar (GPR) survey was performed on the E?irdir Lake to obtain the structural properties of Kumdanl? and surrounding faults. GPR data was collected along ten profiles in various directions by using 100–200-MHz GPR antennas. The radar sections showed that the Kumdanl? Fault, SW-NE in direction, and also some other neighboring NW-SE normal faults have played an active role in forming the E?irdir-Hoyran Lakes. The deformation and the geometry obtained from the results show that the Kumdanl? Fault is a sinistral strike-slip fault including oblique and segmented displacements. The other faults (Kemerdam? and Akkeçili) have mainly normal fault systems. Their trends are generally NW-SE in direction. It is also observed that they are younger than the Kumdanl? Fault system. These fault properties demonstrate the E?irdir Lake side has an extensional structure trending SW-NE.     

Heavy metals in <Emphasis Type="Italic">Mytilus galloprovincialis</Emphasis>, suspended particulate matter and sediment from offshore submerged longline system,Black Sea

The study was performed between March 2009 and March 2010 at the Sinop Inner Harbor on cultured mussels at the offshore submerged longline system. The samples of mussels, sediment and suspended particulate matter were seasonally taken for the purpose of monitoring differences of metal contents. In addition, burnable organic matter, contamination factors (CF), pollution load index (PLI) in sediment samples, meat yield of mussels were seasonally determined. All metals in suspended particulate matter were found to be above the national limit. Cd concentration in sediment was above the limit according to sediment quality guidelines, and Cd concentration in mussel was above both national and international limit values. According to CF and PLI identified in sediment, it was found that Inner Harbor was under the effect of anthropogenic pollution in terms of Cd accumulation. Provisional tolerable weekly intake calculated in mussel did not exceed the tolerable consumption values. In conclusion, it can be said that this region considered for commercial mussel cultivation is not a suitable area.     

Environmental hazard analysis of a gypsum karst depression area with geophysical methods: a case study in Sivas (Turkey)

Because the mixture of seawater and freshwater in the Gyeongin-Ara Waterway in South Korea can lead to the intrusion of saline water into surrounding aquifers, systematic management through the establishment of a groundwater protection area is required. The analytic hierarchy process (AHP) model is used to delineate this protection area based on two primary factors and five secondary factors related to saline water intrusion. The study area is divided into 987 gridded cells with a unit size of 100 × 100 m, and the final evaluation score for each cell is calculated using the AHP model. Consequently, several artificial neural network models based on a multilayer perceptron are developed using the AHP’s secondary criteria and the evaluation score. Comparing the evaluation scores of ANN and AHP, more than 180 samples are required in the ANN model to insure high R2 between the original and estimated values. The ANN model is more consistent than the AHP model when determining groundwater protection area, because it can be re-constructed due to the changes in some secondary criteria and also changed due to a standardization process. The final evaluation score by the ANN model based on 300 samples, with the highest R2, is calculated and the regions with a score higher than 2.0 are selected as the groundwater protection area, accounting for 15% of the total cells. This area is similar to the range within approximately 200 m of the GA Waterway and also includes some changing sites in hydrogeochemistry and electric conductivity, which is produced by saline water intrusion. If the land-use type, groundwater levels, and some other criteria change at any cell, the ANN model can be re-executed to verify whether the cell belongs to a groundwater protection area. Considering that salinity of groundwater near the waterway can be affected by various factors including well depth, pumping conditions, and groundwater levels, the ANN model, which is a non-linear model, can be more effective for prediction than the AHP model.     

Automatic detection of earthquake-induced ground failure effects through Faster R-CNN deep learning-based object detection using satellite images

Natural Hazards - The seismically induced ground failure is defined as any earthquake-generated process that leads to deformations within a soil medium, which in turn results in permanent...     

Measured and perceived visual complexity: a comparative study among three online map providers

We present a study on human perception of map complexity, with the objective of better understanding design decisions that may lead to undesirable levels of complexity in web maps. We compare three complexity metrics to human ratings of complexity obtained through a user survey. Specifically, we use two algorithmic approaches published by others, which measure feature congestion (FC) and subband entropy (SE), as well as our own approach of counting object types rather than individual objects. We compare these metrics with each other as well as with human complexity ratings for three maps of the same area from map providers Google Maps, Bing Maps, and OpenStreetMap. Each map design is assessed at three different scales (levels of detail). We find that (1) the FC and SE metrics appear to be adequate predictors of what humans consider complex; (2) object-type counts are slightly less successful at predicting human-rated complexity, implying that clutter is more important in perceived complexity than diversity of symbology; and (3) generalization choices do impact human complexity ratings. These findings contribute to our understanding of what makes a map complex, with implications for designing maps that are easy to use.     

Climate change in Turkey for the last half century

Climate change and its urban-induced bias in selected Turkish cities is studied with a quality controlled temperature and precipitation data of Turkish stations in the period of 1950–2004. These stations are classified into two groups according to their populations; S1, including rural and suburban stations and S2, including large urban stations. Moving average signals, 365-day, and their digital low pass filtered versions are produced to eliminate the short term fluctuations and examine the possible trends or anomalies in climate data. Furthermore, ‘relative difference’ signals are introduced and applied to temperature and precipitation series to observe the actual local changes in the climate data independent from large-scale effects. Mann–Kendall test statistics are calculated for maximum, minimum, mean temperature and precipitation series and plotted on maps to determine any spatial trend patterns. Signal analysis show a cool period extending from early 1960s till 1993, generally with the lowest temperature values on 1992–1993 owing to the eruption of Mount Pinatubo. A last decade significant warming trend is observed in both of the series, S1 and S2, leading to 2000–2002 temperatures to be recorded as maximums in record history. The variability of urban precipitation series is generally larger than the rural ones, suggesting that urban stations can experience more frequent and severe droughts and floods. Though not significant, an increase in the urban precipitation compared to the rural one is also found. Spatial analysis resulted in significant warming in southern and southeastern parts of the country. Particularly, minimum temperature series show significant warming in almost all of the regions indicating the effect of urbanization. Significant decreases of precipitation amounts in the western parts of Turkey, such as Aegean and Trachea regions, are found. On the other hand, some Turkish northern stations show increases in precipitation of which some are significant.     

Sea level pressure patterns associated with dry or wet monthly rainfall conditions in Turkey

Summary  Monthly rainfall totals at 7 stations across Turkey and sea level pressure (SLP) in 16 grid points in the region delimited by the 20° E and 50° E longitudes and by the 30° N and 45° N latitudes were analysed. Data were available for a period longer than sixty years. The standard deviations of SLP at each grid point for each month, were calculated and mapped. For each station, months were defined as dry or wet according to their z scores: ≤ −1.0 or ≥ 1.0 respectively. Maps showing the SLP z scores of the corresponding dry or wet months for each station were prepared. The maps, enable to distinguish between SLP patterns associated with dry or wet conditions. Furthermore, correlations between monthly rainfall in each of the stations and SLP at each grid point were performed. The correlation coefficients were mapped. (a) The variability of the SLP decreases from the Balkans towards the Arabian Peninsula and is much larger in winter as compared with summer. (b) Relationship between rainfall in Turkey and the regional SLP is large in winter and non existing in summer. (c) Pressure patterns associated with dry conditions, show usually positive SLP departures, whereas, pressure patterns associated with wet conditions show usually negative SLP departures. (d) There is a great resemblance between pressure patterns associated with wet conditions and correlation maps of the same months. Received September 4, 2000 Revised January 15, 2001     

Joint parameter estimation from magnetic resonance and vertical electric soundings using a multi‐objective genetic algorithm

Magnetic resonance sounding (MRS) has increasingly become an important method in hydrogeophysics because it allows for estimations of essential hydraulic properties such as porosity and hydraulic conductivity. A resistivity model is required for magnetic resonance sounding modelling and inversion. Therefore, joint interpretation or inversion is favourable to reduce the ambiguities that arise in separate magnetic resonance sounding and vertical electrical sounding (VES) inversions. A new method is suggested for the joint inversion of magnetic resonance sounding and vertical electrical sounding data. A one‐dimensional blocky model with varying layer thicknesses is used for the subsurface discretization. Instead of conventional derivative‐based inversion schemes that are strongly dependent on initial models, a global multi‐objective optimization scheme (a genetic algorithm [GA] in this case) is preferred to examine a set of possible solutions in a predefined search space. Multi‐objective joint optimization avoids the domination of one objective over the other without applying a weighting scheme. The outcome is a group of non‐dominated optimal solutions referred to as the Pareto‐optimal set. Tests conducted using synthetic data show that the multi‐objective joint optimization approximates the joint model parameters within the experimental error level and illustrates the range of trade‐off solutions, which is useful for understanding the consistency and conflicts between two models and objectives. Overall, the Levenberg‐Marquardt inversion of field data measured during a survey on a North Sea island presents similar solutions. However, the multi‐objective genetic algorithm method presents an efficient method for exploring the search space by producing a set of non‐dominated solutions. Borehole data were used to provide a verification of the inversion outcomes and indicate that the suggested genetic algorithm method is complementary for derivative‐based inversions.