Dynamics of a complex mass movement triggered by heavy rainfall: a case study from NW Turkey

Following a period of heavy precipitation, a large and complex mass movement, namely the Dagkoy landslide, occurred in the West Black Sea Region of Turkey on May 21, 1998. This paper describes the conditioning factors of the landslide and interprets the mass transport processes in terms of a movement scenario. Geology, geomorphology and vegetation cover were considered as the conditioning factors of the failure. Observations showed that the gently sloping (about 10°) area is mostly covered by dense forest trees at the crown where the motion initiated. Significant intersection of the collapsed slope with dip of the local marls seems to have contributed to the formation and geometry of the landslide. The distance from the crown down to the toe of the landslide measured more than 600 m, with about 0.6 km³ total earth material displaced. The landslide has both a block sliding characteristics in the upper portions and a debris flow/soil flow component around the margins of the sliding blocks in the middle parts and at the toe. The proposed scenario for the landslide reveals that the movement was initiated near crown as a result of the excess water content in the marls at the end of 3 days of heavy rainfall. The early perturbations (transverse cracks, ridges, etc.) lasted for 6–7 h, after which the central part of the zone started to move as a soil flow in which very large intact blocks were transported. Even though the movement was very rapid (1.2 m/min), there was no loss of life. However, the movement destroyed 38 houses, one mosque and a considerable amount of farmland.     

The collision experiment between rolling stones of different shapes and protective cushion in open-pit mines

Though gravel cushions are used worldwide in open-pit mines and railway slopes to control the impact of rolling stones, no universal technical standards have been put in place to guide engineers in their correct design, and few laboratory test results are available with which to characterize collisions between rolling stones and a gravel cushion. We carried out a large number of experiments in which rolling stones made of the same material but differently shaped were dropped from various heights onto cushions with various particle sizes and thicknesses. We investigated the characteristics of the resulting collisions, and the relationships between coefficients of restitution(CORs) of blocks with different shape and release height H, cushion thickness h and particle diameter d are obtained through linear fitting method. Orthogonal testing reveals the relative influence of block shape, release height, and the particle size and thickness of the cushion on the collision characteristics, which can assist engineers in designing a gravel cushion suitable to the distribution and weathering characteristics of rolling stones in a specific area.     

Effects of T-shape groin parameters on beach accretion

The effects of various groin parameters (length, head length and opening) and wave parameters (wave height, wave period and wave angle) on the accretion of the area protected by T-shape groins are studied in a physical model. The model studies are performed using regular waves in a basin. A numerical model which depends primarily on a CERC model is employed to examine the effects of some of the above parameters. Good agreement is found in the results of physical and numerical models. The results of a numerical model are compared with field data obtained by deep sounding measurements at Of coasts, Trabzon Province, Turkey. The finding from this study may be employed in designing T-shape groins.     

Determination of bar parameters caused by cross-shore sediment movement

Waves, topographic features and material properties are known as the most important factors affecting the sediment movement and coastal profiles. In this study, considering wave height (H=6.5, 17, 16, 20, 23, 26 and 30 cm) and period (T=1.46 and 2.03 s), bed slope (m=1/10, 1/15 and 1/25) and sediment diameter (d₅₀=0.18, 0.26, 0.33 and 0.40 mm), cross-shore sediment movement was investigated using a physical model and various offshore bar geometric parameters were determined by the resultant erosion profile. The offshore bar geometric characteristics are the distance between the bar crest and the shoreline, the depth from bar crest to the still-water level, the distance between the equilibrium point and the shoreline, the distance between the closure point and the shoreline, and the bar volume. Dimensional and non-dimensional equations were obtained by using non-linear regression methods through the experimental data and compared with those of previously developed equations. The results have indicated that the proposed equations fit to experimental data better than previously developed equations.     

Soil temperature modeling at different depths using neuro-fuzzy,neural network,and genetic programming techniques

The applicability of artificial neural networks (ANN), adaptive neuro-fuzzy inference system (ANFIS), and genetic programming (GP) techniques in estimating soil temperatures (ST) at different depths is investigated in this study. Weather data from two stations, Mersin and Adana, Turkey, were used as inputs to the applied models in order to model monthly STs. The first part of the study focused on comparison of ANN, ANFIS, and GP models in modeling ST of two stations at the depths of 10, 50, and 100 cm. GP was found to perform better than the ANN and ANFIS-SC in estimating monthly ST. The effect of periodicity (month of the year) on models’ accuracy was also investigated. Including periodicity component in models’ inputs considerably increased their accuracies. The root mean square error (RMSE) of ANN models was respectively decreased by 34 and 27 % for the depths of 10 and 100 cm adding the periodicity input. In the second part of the study, the accuracies of the ANN, ANFIS, and GP models were compared in estimating ST of Mersin Station using the climatic data of Adana Station. The ANN models generally performed better than the ANFIS-SC and GP in modeling ST of Mersin Station without local climatic inputs.     

Estimation of Hardgrove grindability index of Turkish coals by neural networks

In this research, different techniques for the estimation of coal HGI values are studied. Data from 163 sub-bituminous coals from Turkey are used by featuring 11 coal parameters, which include proximate analysis, group maceral analysis and rank. Non-linear regression and neural network techniques are used for predicting the HGI values for the specified coal parameters. Results indicate that a hybrid network which is a combination of 4 separate neural networks gave the most accurate HGI prediction and all of the neural network models outperformed non-linear regression in the estimation process.     

Hydrochemical and microbiological quality of groundwater in West Thrace Region of Turkey

The aim of this study was to do a preliminary assessment of the hydrochemical and microbial groundwater quality of the West Thrace region. Forty samples of groundwater collected from Edirne (Site 1) to Gelibolu (Site 2) were assessed for their suitability for human consumption. As³⁻ was non-detectable in all the groundwater and Zn²⁺, Pb²⁺, F⁻, Cu²⁺, NH₄⁺, Cn⁻ PO₄³⁻ and Cl⁻ were all below their respective European Union drinking water directive (EU-DWD) and Turkish food codex-drinking water directive (TFC-DWD). Maximum Acceptable Concentrations (MAC) Ni²⁺, Pb²⁺, Cd²⁺, Mg²⁺, Mn²⁺, and Ca²⁺ levels were detected in upper maximum acceptable concentrations 77.5, 42.5, 35.0, 50.0, 50.0, and 32.5% of the groundwater samples, respectively. However, in terms of Cr³⁺, Ni²⁺ and Pb²⁺, the differences between groundwaters of Sites 1 and 2 were significant (p < 0.05). Eight water samples (20%) had HPC exceeding the EU and Turkish water directive limit 20 CFU (Colony Forming Unit)/ml in drinking water and the maximum bacteria count recorded was 44 CFU/ml. Total coliforms, thermotolerant coliforms, E. coli, Enterococcus spp., Salmonella sp., Staphylococcus spp. and P. aeruginosa were detected in 25, 17.5, 15, 47.5, 15, 27.5, and 15% of the groundwater samples, respectively. Furthermore, heavy metals and trace elements were found after chemical analyzes in most samples. The pollution of groundwater come from a variety of sources, Meric and Ergene rivers, including land application of agricultural chemicals and organics wastes, infiltration of irrigation water, septic tanks, and infiltration of effluent from sewage treatment plants, pits, lagoons and ponds used storage.