Davor Pollak

The determination and estimation of elastic behaviour are essential in engineering practise, especially in quarrying, mining, construction, and all engineering professions that perform operations dealing with rock materials. Young’s modulus, or modulus of elasticity, is the most important property describing the deformability of rock material. In this paper, grain-supported carbonates from Croatia are described and their elastic modulus and significant physical and mechanical properties are determined. The analysis of the collected data was performed in the R statistical environment. Estimation models based on multiple linear regression and the regression tree model were created. The methodology of model development and evaluation in R environment is described in detail. According to the more stringent coefficients (RMSECV and adjusted R²) used to evaluate the success of the estimation, simple regression tree models were found to perform well for the preliminary estimation, while more complex models based on Bagging performed very well.

In this paper, for the first time, a regional-scale 1:100,000 landslide-susceptibility map (LSM) is presented for Sisak-Moslavina County in Croatia. The spatial relationship between landslide occurrence and landslide predictive factors (engineering geological units, relief, roughness, and distance to streams) is assessed using the integration of a statistically based frequency ratio (FR) into the analytical hierarchy process (AHP). Due to the lack of landslide inventory for the county, LiDAR-based inventories are completed for an area of 132 km². From 1238 landslides, 549 are chosen to calculate the LSM and 689 for its verification. Additionally, landslides digitized from available geological maps and reported via the web portal “Report a landslide” are used for verification. The county is classified into four susceptibility classes, covering 36% with very-high and high and 64% with moderate and low susceptibility zones. The presented approach, using limited LiDAR data and the extrapolation of the correlation results to the entire county, is encouraging for primary regional-level studies, justifying the cost-benefit ratio. Still, the positioning of LiDAR polygons prerequires a basic statistical analysis of predictive factors.

The complete geological characteristics of the wider area of the Pelješac peninsula are presented: lithostratigraphical, structural/tectonic and seismotectonic. The main accent is put on engineering geological characteristics of clastic sediments in Mali Ston Bay encountered during investigations for implementation project of the “Mainland-Pelješac” bridge. The bridge large proportions with 2404 m in length and with 14 pylons under the sea, requested thorough and expensive in-situ and laboratory investigations which enabled development of detailed and reliable engineering model of quaternary clastic sediments at the explored site. The results clearly indicate three different engineering units which are predominantly classified according to the obvious difference in consistency: Unit A – very soft and soft soil; Unit B – soft to firm soil and Unit C – firm soil. Because of great soil total thickness, locally over 100 m, its generally poor engineering properties and great seismicity of the area the foundation surroundings are unfavorable. The mentioned units which are classified according to its engineering properties also tightly correspond to the deposition environments which represent much wider area than just exploration site. Therefore authors presume presence of units A, B and C in wider area with similar geological situations like proximities of the Zrmanja, Krka, and Cetina deltas.