On the Correction of Spatial and Statistical Uncertainties in Systematic Measurements of 222Rn for Earthquake Prediction

In earthquake prediction studies, the regional behaviour of accurate ²²²Rn measurements at a set of sites plays a significant role. Here, measurements are obtained using active and passive radon detector systems in an earthquake-active region of Turkey. Two new methods are proposed to explain the spatial behaviours and the statistical uncertainties in the ²²²Rn emission measurements along fault lines in relation to earthquake occurrence. The absolute point cumulative semivariogram (APCSV) and perturbation method (PM) help to depict the spatial distribution patterns of ²²²Rn in addition to the joint effects of the K _dr, the radon distribution coefficient, and the perturbation radon distribution coefficient (PRDC). The K _dr coefficient assists in identifying the spatial distributional behaviour in ²²²Rn concentrations and their migration along the Earth’s surface layers. The PRDC considers not only the arithmetic averages but also the variances (or standard deviations) and the correlation coefficients, in addition to the size of the error among the ²²²Rn measurements. The applications of these methodologies are performed for 13,000 ²²²Rn measurements that are deemed to be sufficient for the characterization of tectonics in the Keban Reservoir along the East Anatolian Fault System (EAFS) in Turkey. The results are evaluated for the ?çme earthquake (M _L 5.4, 5.7 km, 23 June 2011), which occurred in the vicinity of the EAFS.     

Using high resolution images and elevation data in classifying erosion risks of bare soil areas in the Hatila Valley Natural Protected Area, Turkey

Soil erosion is one of the most important environmental problems. In the case of small scale areas where soil properties and climate have relatively uniform characteristics, vegetation cover and topography (i.e. ground slope) are the main factors that affect the amount of soil erosion. Lack of vegetation cover on bare soil areas, including forest road side slopes, especially in mountainous regions with steep slopes, may significantly increase the erosion rate. Determining and classifying erosion risks in such areas can help preventing environmental impacts. In this study, remotely sensed data and elevation data were used to extract and classify bare soil erosion risk areas for a study area selected from Hatila Valley Natural Protected Area in northeastern Turkey. High resolution IKONOS imagery was used to apply land use classification in ERDAS Imagine 9.0. To generate erosion risk map of the bare soil areas, classified image was superimposed on top of slope map, generated based on a Digital Elevation Model (DEM) in ArcGIS 9.2. The results indicated that 1.43, 5.85, 34.62, 53.16, and 4.94% of the bare soil areas in the study area were under very low, low, medium, high, and very high erosion risks, respectively. The overall classification accuracy of 82.5% indicated the potential of the proposed methodology.     

Prediction of Density Flow Plunging Depth in Dam Reservoirs: An Artificial Neural Network Approach

Experimental findings and observations indicate that plunging flow is related to the formation of bed load deposition in dam reservoirs. The sediment delta begins to form in the plunging region where the inflow river water meets the ambient reservoir water. Correct estimation of dam reservoir flow, plunging point, and plunging depth is crucial for dam reservoir sedimentation and water quality issues. In this study, artificial neural network (ANN), multi‐linear regression (MLR), and two‐dimensional hydrodynamic model approaches are used for modeling the plunging point and depth. A multi layer perceptron (MLP) is used as the ANN structure. A two‐dimensional model is adapted to simulate density plunging flow through a reservoir with a sloping bottom. In the model, nonlinear and unsteady continuity, momentum, energy, and k–ε turbulence equations are formulated in the Cartesian coordinates. Density flow parameters such as velocity, plunging points, and plunging depths are determined from the simulation and model results, and these are compared with previous experimental and model works. The results show that the ANN model forecasts are much closer to the experimental data than the MLR and mathematical model forecasts.     

Characteristics of the 1912 co-seismic rupture along the North Anatolian Fault Zone (Turkey): implications for the expected Marmara earthquake

Evidence of right‐lateral offsets associated with the 1912 earthquake (M_w 7.4) along the North Anatolian Fault (Gaziköy–Saros segment) allow us to survey (using DGPS) the co‐seismic and cumulative slip distribution. The damage distribution and surface breaks related with the earthquake show an elongated zone of maximum intensity (X MSK) parallel to the fault rupture on land but this may extend offshore to the north‐east and south‐west. Detailed mapping of the fault using topographic maps and aerial photographs indicates the existence of pull‐apart basins and pressure ridges. At several localities, the average 1912 offset along strike is 3.5–4 m and cumulative slip is 2–6 times that of individual movement. The fault rupture geometry and slip distribution suggest the existence of three subsegments with a combined total length of 110–120 km, a fault length and maximum slip similar to those of the 1999 Izmit earthquake. The amount of slip at the north‐easternmost section and in the coastal region of the Sea of Marmara reaches an average 4 m, thereby implying the offshore extension of the 1912 rupture. The results suggest that the 1912 event generated up to 150 km of surface faulting, which would imply a M_w 7.2–7.4 earthquake and which, added with rupture lengths of the 1999 earthquakes, help to constrain the remaining seismic gap in the Sea of Marmara.     

Quantitative assessment of remotely sensed global surface models using various land classes produced from Landsat data in Istanbul

Digital elevation model(DEM) is the most popular product for three-dimensional(3D) digital representation of bare Earth surface and can be produced by many techniques with different characteristics and ground sampling distances(GSD). Space-borne optical and synthetic aperture radar(SAR) imaging are two of the most preferred and modern techniques for DEM generation. Using them, global DEMs that cover almost entire Earth are produced with low cost and time saving processing. In this study, we aimed to assess the Satellite pour l'observation de la Terre-5(SPOT-5), High Resolution Stereoscopic(HRS), the Advanced Space-borne Thermal Emission and Reflection Radiometer(ASTER), and the Shuttle Radar Topography Mission(SRTM) C-band global DEMs, produced with space-borne optical and SAR imaging. For the assessment, a reference DEM derived from 1∶1000 scaled digital photogrammetric maps was used. The study is performed in 100 km2 study area in Istanbul including various land classes such as open land, forest, built-up land, scrub and rough terrain obtained from Landsat data. The analyses were realized considering three vertical accuracy types as fundamental, supplemental, and consolidated, defined by national digital elevation program(NDEP) of USA. The results showed that, vertical accuracy of SRTM C-band DEM is better than optical models in all three accuracy types despite having the largest grid spacing. The result of SPOT-5 HRS DEM is very close by SRTM and superior in comparison with ASTER models.