A geohazard reconnaissance study based on geoscientific information for development needs of the western region of Istanbul (Turkey)

The role of geoenvironmental information is becoming increasingly important as legislative changes have forced developers and planning authorities to consider more implications and impact on the environment of large-scale development initiatives. Therefore, integration of surface and subsurface geoscientific information for development needs has prime importance and provides a means of identifying potential problems and opportunities at an early stage in any planned development. However, from the experience of recent natural disasters, it is evident that this was not case the taken into consideration in many countries. In addition to thousands of casualties, many urbanized areas, industrial districts and large-scale engineering structures suffered severe damages from the natural hazards due to many reasons including the lack of preliminary engineering geological maps and zoning maps of the settlement areas. Turkey is one of the countries which is exposed to natural hazards such as earthquakes, landslides and floods. In particular, the devastating 1999 Kocaeli earthquake, which affected the Marmara Region of Turkey, focused the attention on densely urbanized and industrialized metropolitan areas such as Istanbul. The rapid growth of Istanbul, particularly towards west with minimal geoscientific information resulted in an overwhelming pressure on the natural environment. In addition, a large earthquake, which is expected to occur in the Marmara Sea within the next 30 years, also pose a threat to the city and its surroundings. In this study, on the basis of the geological, geomorphological and geophysical reconnaissance study, an integrated geoscientific data were collected from the western region of Istanbul and evaluated for geohazards. The paper focuses on the geological and geomorphological aspects that control the occurrence of some geohazards such as earthquake-induced liquefaction, landslides and flooding. In this context, the geological map of the region was revised and Quaternary deposits were classified into 11 units, in detail. Liquefaction-prone areas were evaluated by using geomorphological criteria based on field investigation, by the examination of the available records from 88 boreholes drilled on recent deposits and by the data from resistivity profiles. The landslides within the region were classified according to their type, relative depth and activity. In addition, fluvial and marine flood-prone areas were also delimited within the region. Finally, a series of maps such as landslide inventory maps, and maps showing liquefaction- and flood-prone areas were produced with the aid of Geographic Information Systems (GIS) to assist in designing further detailed site investigations and to reduce costs by ensuring a more focused approach to strategic planning and site selection.     

Causes, mechanism and environmental impacts of instabilities at Himmetoğlu coal mine and possible remedial measures

 Since the commencement of mining at the Himmetoğlu coal mine, northwest Turkey, serious stability problems have led to interruptions in mining and some environmental effects. A geotechnical investigation was initiated in 1997 and the significant factors that influence the stability have been defined. This paper outlines the results of the field and laboratory studies associated with the causes and mechanism of the slope instabilities and their environmental impacts. The possible remedial measures to improve the stability and to minimize the environmental problems are also described. Back-analyses and data from long-term monitoring indicate that the failures occur along two or three planar surfaces by combination of faults and localized strata steepening adjacent to the faults. The stability is sensitive to changes in length of the lower part of the basal sliding surface and shear strength of the bedding surfaces in the overburden. Suitable remedial measures include slope flattening (i.e. staged bench stripping), proper drainage and spreading of a rock blanket on the pit floor to increase spoil pile stability. Received: 18 April 2000 · Accepted: 15 August 2000     

Liquefaction potential and susceptibility mapping in the city of Yalova, Turkey

This study presents results of both field and laboratory tests that have been used to asses liquefaction susceptibilities of the soils in Yalova city, located in the well-known seismically active North Anatolian Fault Zone. Liquefaction potentials of the sub-surface materials in Yalova city were estimated by using the standard penetration test (SPT) method of field testing. The data obtained have been mapped according to susceptibility, and the susceptibility maps based on the geotechnical data indicated a moderate to high susceptibility to liquefaction for the magnitude of earthquake of M=7.4. Both the high groundwater level and the grain size of the soils, in conjunction with the active seismic features of the region, result in conditions favourable to the occurrence of liquefaction. When the surface and near surface geological conditions were taken under consideration, it was seen that the study areas geology is prone to liquefaction having a moderate liquefaction susceptibility. If geologic and geomorphological criteria are considered, it should be understood that the study area as discussed under the regions geology is susceptible to liquefaction. The geotechnical data largely support the geologic-based liquefaction susceptibility of the study area.     

Precipitation forecasting using classification and regression trees (CART) model: a comparative study of different approaches

Interest in semiarid climate forecasting has prominently grown due to risks associated with above average levels of precipitation amount. Longer-lead forecasts in semiarid watersheds are difficult to make due to short-term extremes and data scarcity. The current research is a new application of classification and regression trees (CART) model, which is rule-based algorithm, for prediction of the precipitation over a highly complex semiarid climate system using climate signals. We also aimed to compare the accuracy of the CART model with two most commonly applied models including time series modeling (ARIMA), and adaptive neuro-fuzzy inference system (ANFIS) for prediction of the precipitation. Various combinations of large-scale climate signals were considered as inputs. The results indicated that the CART model had a better results (with Nash–Sutcliffe efficiency, NSE?>?0.75) compared to the ANFIS and ARIMA in forecasting precipitation. Also, the results demonstrated that the ANFIS method can predict the precipitation values more accurately than the time series model based on various performance criteria. Further, fall forecasts ranked “very good” for the CART method, while the ANFIS and the time series model approximately indicated “satisfactory” and “unsatisfactory” performances for all stations, respectively. The forecasts from the CART approach can be helpful and critical for decision makers when precipitation forecast heralds a prolonged drought or flash flood.