Preliminary Investigations On Flood Susceptibility Mapping in Ankara (Turkey) Using Modified Analytical Hierarchy Process (M-Ahp)

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The 17 March 2005 Kuzulu landslide (Sivas, Turkey) and landslide-susceptibility map of its near vicinity

Landslides are common natural hazards in the seismically active North Anatolian Fault Zone of Turkey. Although seismic activity, heavy rainfall, channel incisions, and anthropogenic effects are commonly the main triggers of landslides, on March 17, 2005, a catastrophic large landslide in Sivas, northeastern of Turkey, the Kuzulu landslide, was triggered by snowmelt without any other precursor. The initial failure of the Kuzulu landslide was rotational. Following the rotational failure, the earth material in the zone of accumulation exhibited an extremely rapid flow caused by steep gradient and high water content. The Agnus Creek valley, where Kuzulu village is located, was filled by the earth-flow material and a landslide dam was formed on the upper part of Agnus Creek. The distance from the toe of the rotational failure down to the toe of the earth flow measured more than 1800 m, with about 12.5 million m3 of displaced earth material. The velocity of the Kuzulu landslide was extremely fast, approximately 6 m/s. The main purposes of this study are to describe the mechanism and the factors conditioning the Kuzulu landslide, to present its environmental impacts, and to produce landslide-susceptibility maps of the Kuzulu landslide area and its near vicinity. For this purpose, a detailed landslide inventory map was prepared and geology, slope, aspect, elevation, topographic-wetness index and stream-power index were considered as conditioning factors. During the susceptibility analyses, the conditional probability approach was used and a landslide-susceptibility map was produced. The landslide-susceptibility map will help decision makers in site selection and the site-planning process. The map may also be accepted as a basis for landslide risk-management studies to be applied in the study area. © 2005 Elsevier B.V. All rights reserved

Susceptibility assessments of shallow earthflows triggered by heavy rainfall at three catchments by logistic regression analyses

Sometimes regional meteorological anomalies trigger different types of mass movements. In May 1998, the western Black Sea region of Turkey experienced such a meteorological anomaly. Numerous residential and agricultural areas and engineering lifelines were buried under the flood waters. Besides the reactivation of many previously delineated landslides, thousands of small-scale landslides (mostly the earthflow type) occurred all over the region. The earthflows were mainly developed in flysch-type units, which have already presented high landslide concentrations. In this study, three different catchments - namely Agustu, Egerci, and Kelemen - were selected because they have the most landslide-prone geological units of the region. The purposes of the present study are to put forward the spatial distributions of the shallow earthflows triggered, to describe the possible factors conditioning the earthflows, and to produce the shallow earthflow susceptibility maps of the three catchments. The unique condition units (UCU) were employed during the production of susceptibility maps and during statistical analyses. The unique condition units numbered 4052 for the Agustu catchment, 13,241 for the Egerci catchment and 12,314 for the Kelemen catchment. The earthflow intensity is the highest in the Agustu catchment (0.038 flow/UCU) and lowest in the Egerci catchment (0.0035 flow/UCU). Logistic regression analyses were also employed. However, during the analyses, some difficulties were encountered. To overcome the difficulties, a series of sensitivity analyses were performed based on some decision rules introduced in the present study. Considering the decision rules, the proper ratios of UCU free from earthflow (0)/UCU including the earthflow (1) for the Agustu, Egerci and Kelemen catchments were obtained as 3, 6, and 5, respectively. Also, a chart for the proper ratio selection was developed. The regression equations from the selected ratios were then applied to the entire catchment and the earthflow susceptibility maps were produced. The landslide susceptibility maps revealed that 15% of the Agustu catchment, 8% of the Egerci catchment, and 7% of the Kelemen catchment have very high earthflow susceptibility; and most of the earthflows triggered by the May 1998 meteorological event were found in the very high susceptibility zones. © 2005 Elsevier B.V. All rights reserved

Application of logistic regression for landslide susceptibility zoning of Cekmece Area, Istanbul, Turkey

As a result of industrialization, throughout the world, cities have been growing rapidly for the last century. One typical example of these growing cities is Istanbul, the population of which is over 10 million. Due to rapid urbanization, new areas suitable for settlement and engineering structures are necessary. The Cekmece area located west of the Istanbul metropolitan area is studied, because the landslide activity is extensive in this area. The purpose of this study is to develop a model that can be used to characterize landslide susceptibility in map form using logistic regression analysis of an extensive landslide database. A database of landslide activity was constructed using both aerial-photography and field studies. About 19.2% of the selected study area is covered by deep-seated landslides. The landslides that occur in the area are primarily located in sandstones with interbedded permeable and impermeable layers such as claystone, siltstone and mudstone. About 31.95% of the total landslide area is located at this unit. To apply logistic regression analyses, a data matrix including 37 variables was constructed. The variables used in the forwards stepwise analyses are different measures of slope, aspect, elevation, stream power index (SPI), plan curvature, profile curvature, geology, geomorphology and relative permeability of lithological units. A total of 25 variables were identified as exerting strong influence on landslide occurrence, and included by the logistic regression equation. Wald statistics values indicate that lithology, SPI and slope are more important than the other parameters in the equation. Beta coefficients of the 25 variables included the logistic regression equation provide a model for landslide susceptibility in the Cekmece area. This model is used to generate a landslide susceptibility map that correctly classified 83.8% of the landslide-prone areas. © 2006 Springer-Verlag

Correction to: On the use of hierarchical fuzzy inference systems (HFIS) in expert-based landslide susceptibility mapping: the central part of the Rif Mountains (Morocco) (Bulletin of Engineering Geology and the Environment, (2020), 79, 1, (551-568), 10.1007/s10064-019-01548-5)

The published version of this article unfortunately contained a mistake