The role of meteorological forcing and snow model complexity in winter glacier mass balance estimation,Columbia River basin,Canada

Glaciers are commonly located in mountainous terrain subject to highly variable meteorological conditions. High resolution meteorological (HRM) data simulated by atmospheric models can complement meteorological station observations in order to assess changes in glacier energy fluxes and mass balance. We examine the performance of two snow models, SnowModel and Alpine3D, forced by different meteorological data for winter mass balance simulations at four glaciers in the Canadian portion of the Columbia Basin. The Weather Research and Forecasting model (WRF) with resolution of 1 km and the North American Land Data Assimilation System with ~12 km resolution, provide HRM data for the two snow models. Evaluation is based on the ability of the snow models to simulate snow depth at both point locations (automated snow weather stations) and over the entire glacier surface (airborne LiDAR [Light Detection and Ranging] surveys) during the 2015/2016 winter accumulation. When forced with HRM data, both models can reproduce snow depth to within ±15% of observed values. Both models underestimate winter mass balance when forced by HRM data. When driven with WRF data, SnowModel underestimates winter mass balance integrated over the glacier area by 1 and 10%, whilst Alpine3D underestimates winter mass balance by 12 and 22% compared with LiDAR and stake measurements, respectively. The overall results show that SnowModel forced by WRF simulated winter mass balance the best.     

Prediction of unconfined compressive strength of carbonate rocks using artificial neural networks

The unconfined compressive strength (UCS) of intact rocks is an important geotechnical parameter for engineering applications. Determining UCS using standard laboratory tests is a difficult, expensive and time consuming task. This is particularly true for thinly bedded, highly fractured, foliated, highly porous and weak rocks. Consequently, prediction models become an attractive alternative for engineering geologists. The objective of study is to select the explanatory variables (predictors) from a subset of mineralogical and index properties of the samples, based on all possible regression technique, and to prepare a prediction model of UCS using artificial neural networks (ANN). As a result of all possible regression, the total porosity and P-wave velocity in the solid part of the sample were determined as the inputs for the Levenberg–Marquardt algorithm based ANN (LM-ANN). The performance of the LM-ANN model was compared with the multiple linear regression (REG) model. When training and testing results of the outputs of the LM-ANN and REG models were examined in terms of the favorite statistical criteria, which are the determination coefficient, adjusted determination coefficient, root mean square error and variance account factor, the results of LM-ANN model were more accurate. In addition to these statistical criteria, the non-parametric Mann–Whitney U test, as an alternative to the Student’s t test, was used for comparing the homogeneities of predicted values. When all the statistics had been investigated, it was seen that the LM-ANN that has been developed, was a successful tool which was capable of UCS prediction.     

Environmental impacts of blast-induced acceleration on slope instability at a limestone quarry

The main objective of this study is to evaluate the influence of blast-induced acceleration on the stability of slopes at Arakli-Tasonu limestone quarry where a planar shear failure has recently been observed. The planar failure occurred within rock layers consisting of limestone and clayey limestone. The triggering mechanism of the planar shear failure was investigated using blast-induced acceleration values obtained from 73 shots, field measurements, laboratory assessment of rock material properties and utilizing limit equilibrium analysis. From the analysis of slope stability, the safety factor at a magnitude of 0.106g was found to be lower than a minimum value of 1.2 in the case of a water-filled tension crack of a slope, 15 m depth. These findings indicate that the planar shear failure was strongly influenced by the acceleration of uncontrolled blasting operations as well as heavy rainfall.     

Snow avalanche incidents in north-western Anatolia,Turkey during December 1992

Snow avalanches take place in the mountainous regions of Turkey mostly in the eastern Anatolia Region with an average annual death toll of 23 people and much damage to property. However, in the mountainous areas of the Kastamonu and Sinop provinces in the western part of the Black Sea Region of Turkey between 25 and 30 December 1992, blizzards with heavy snowfall caused roof collapses and major avalanche events whereby 16 people were killed and 2 injured. When past records were investigated, there was no evidence that avalanche accidents had been encountered in the region where the dominant precipitation type is rain in the coastal zones and snow over the mountains. Moreover, avalanche prevention measures are so limited that the resettlement of villages or hamlets located in risk zones is common practice. In this article, avalanche formation associated with the meteorological conditions and geomorphologic features is discussed.This study was partially supported by Tübitak (Scientific and Technical Research Council of Turkey) with Project No. YBAG-0067.     

Probabilistic Seismic Hazard Assessment for Izmir, Turkey

Izmir, the third largest city and one of the major economic centers in Turkey, has more than three million residents and one-half million buildings. The city, located in a seismically active region in western Anatolia, was a subject of the 1997 RADIUS (Risk Assessment Tools for Diagnosis of Urban Areas against Seismic Disaster) project. In this paper, the seismic hazard of Izmir is investigated through probabilistic seismic hazard assessment. First, the seismic setting of Izmir is presented. Considering the statistics of earthquakes that took place in the region during the period 1900–2005, a simple seismic hazard model is used to facilitate the assessment. To account for modeling uncertainties associated with the values of seismicity parameters, a logic tree procedure is employed in carrying out the seismic hazard computations. The resulting weighted average seismic hazard, presented in terms of peak ground acceleration and associated probability of exceedence, could be considered the “best estimate” of seismic hazard for Izmir. Accordingly, for a return period of 475 years, for rock sites, a PGA value of 0.34 g is calculated. This PGA hazard estimate is close to the current code-recommended design acceleration level for Izmir.