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Earthquake-induced landslides are of the phenomena that have caused huge losses to human in recent years. Although many studies on the identification and characterization of landslides are generally done, the review of landslides caused by earthquakes is very young especially in Iran. This paper describes zoning of landslides triggered by 1990 Rudb...
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... every decade, devastating earthquakes and coseismic landslides had occurred in Iran and resulted in catastrophic losses, few quantitative studies have conducted regarding the impact of controlling factors on a complete inventory of coseismic landslides. Khodashahi et al. (2018) used the CAMEL method to evaluate coseismic landslides by the Rudbar-Manjil earthquake (1990) qualitatively and prepared a zonation map of the study region (650 km 2 ). According to their results, the CAMEL method provides a better predicting and zoning performance in coseismicity of soil landslides compared to coseismic rock landslides; however, a significant portion of the landslides is rockslide, rock avalanche, rock slump, rock-block slump, rockfall, and debris slides in the study region (Komak Panah and Hafezi Moghadas 1993). ...
This study is a revised inventory of landslides triggered by the Rudbar-Manjil earthquake (Mw = 7.3), 1990, obtained through the study of Komak Panah and Hafezi Moghadas (1993), interpretations of the stereoscopic aerial photos, and field data. We mapped the 223 coherent landslides with a total area of 11.3 km2 and a calculated volume of 3.8 × 108 m3 using a digital elevation model (DEM, 12.5 m) within the geographical information system (GIS) software. The correlation between landslide occurrence (size and distribution) and the controlling factors was analyzed using the bivariate model and the linear automated modeling (LINEAR) procedure in the SPSS software. Both LINEAR models of landslide volume (LV, m3) and landslide area (LA, m2) indicate the distance from the fault surface rupture is the most influencing factor on size prediction of coseismic landslides. The LA is more dependent on seismic factors, whereas the LV is on the lithology and topographic factors. The result of principal component analysis (PCA) model, using the GIS, showed that most landslides occurred in the red band (including 95% of the variance of controlling factors). Thus, the selected factors to investigate the landslide occurrence are valid and the PCA can be used to identify regions prone to coseismic landslides. The curves of landslide number density (LND, landslides/km2), landslide area percentage (LAP, landslide area/total area%), LA, and LV have a multimodal distribution (several patterns of response) by the topographic and seismic factors. It is recommended that other models be applied to better investigate the local effects of factors on the coseismic landslides.
... 2. Maintain adequate liquidity ratios for emergency needs. 3. Respecting liquidity ratios set by the monetary authority in addition to setting a minimum liquidity limit in line with the Bank's activities (Al-Tayy and Mahmoud, 2013) (Khodashahi et al, 2018). ...
This current research aims to identify the most important factors affecting Iraqi commercial banks using the CAMELS model. The research was based on a sample of (13) Iraqi commercial banks listed in the Iraqi Stock Exchange. The CAMELS, which consists of (30) equation, was used for the research. The economic inflation and other economic factors affecting the distribution of the financial ratios of the equations on five levels within the CAMELS standard were considered. An algorithm was adopted in the MATLAB program, in addition to adopting statistical categories method, taking the large differences between one ratio and another and adjusting the categories according to the standards of (CAMELS). The research found that Iraqi banks suffer from weaknesses in some sensitivity aspects of market risks and unable to handle the heavy shocks in market risks as well as its low management, other details are mentioned in the summary.
... 2. Maintain adequate liquidity ratios for emergency needs. 3. Respecting liquidity ratios set by the monetary authority in addition to setting a minimum liquidity limit in line with the Bank's activities (Al-Tayy and Mahmoud, 2013) (Khodashahi et al, 2018). ...
This current research aims to identify the most important factors affecting Iraqi commercial banks using the CAMELS model. The research was based on a sample of (13) Iraqi commercial banks listed in the Iraqi Stock Exchange. The CAMELS, which consists of (30) equation, was used for the research. The economic inflation and other economic factors affecting the distribution of the financial ratios of the equations on five levels within the CAMELS standard were considered. An algorithm was adopted in the MATLAB program, in addition to adopting statistical categories method, taking the large differences between one ratio and another and adjusting the categories according to the standards of (CAMELS). The research found that Iraqi banks suffer from weaknesses in some sensitivity aspects of market risks and unable to handle the heavy shocks in market risks as well as its low management, other details are mentioned in the summary.
This study has reviewed and completed the database of landslides triggered by the 1990 Rudbar- Manjil earthquake (Ww=7.3), using previous studies, stereoscopic interpretation of aerial photographs, and checking satellite images (before and after the earthquake). We mapped 223 coherent landslides as polygons and central points using a digital elevation model (DEM, 12.5 m) by GIS software. A quantitative hazard zoning of the size (area and volume) of landslides was implemented based on controlling parameters by automatic linear regression (LINEAR) and geographically weighted regression (GWR) models. The controlling parameters include geotechnical group (cohesion and internal friction angle), topography (elevation, slope, aspect, and curvature), and seismic (distance from the fault rupture surface and the epicenter of the earthquake, the intensity of Arias, and the peak ground acceleration). The results showed that the quantitative zoning of the GWR model is more consistent with the size of existing landslides compared to the LINEAR model. The landslide area (LA) and landslide volume (LV) have a multimodal distribution compared to seismic and topographic parameters. Therefore, the nonlinear GWR model prepares a more accurate prediction of zoning than the linear regression model owing to the local effects of controlling parameters on the size of landslides.
Keywords: Landslides triggered by the earthquake, Linear regression model, Weighted geographically regression, Rudbar-Manjil.
This paper presents a semi-empirical model to predict earthquake-induced displacement of slopes, based on a coupled stick-slip-rotation (CSSR) analysis recently developed by the authors in a preceding study. The earthquake database selected for the analyses was constituted of 3319 records (including two horizontal components) of ground accelerations associated with 461 earthquakes that occurred in Iran. The presented predictive model was developed by the multiple regression analyses and represents sliding displacement as a function of the maximum velocity coefficient-time history (kv-max), yield acceleration coefficient (ky), slip length (L), and period ratio (Ts/Tm). The conditions of efficiency, sufficiency, and predictability of the seismic parameters have indicated that kv-max is the best choice satisfying these conditions to be used in the predictive model compared with the other intensity measures. A semi-empirical equation has been proposed to assure the predictability condition of kv-max. Performance of the presented semi-empirical model is evaluated by comparing its predictions with a few selected regional and global models recently proposed for sliding displacement of slopes.
