Effects of environmental factors on classification of loessderived soils and clay minerals variations,northern Iran

Land-use type under different topographic conditions and human activities affects soil development. We investigated the effects of land-use, topography and human activity on soil classification changes in the Toshan watershed in northern Iran. Seven representative pedons derived from loess parent materials were studied on different land-uses and topographic positions. The studied pedons in forest (FO) on backslopes and footslope were classified as Calcic Haploxeralfs and Typic Haploxeralfs, respectively. The soils in abandoned lands (AB) and orchards (OR), where formerly under natural forests, located on the shoulder and backslopes positions were classified as Calcic Haploxeralfs and Vertic Haploxeralfs, respectively. Well-developed argillic horizons as indicators for higher degrees of soil evolution were observed in more-stable areas under the natural forest or less disturbed areas. Clay lessivage through these soil profiles have led to formation of Typic or Calcic Haploxeralfs, while under croplands (CP) were classified as Typic Calcixerepts. Conversion of sloping deforested areas to CP along with inappropriate management have accelerated soil erosion, resulting in unstable conditions in which decalcification and formation of developed soils cannot occur. Paddy cultivation in flat areas has caused to reduced conditions and formation of Typic Haplaquepts. Because of unfavorable conditions for chemical weathering (e.g. lower water retention compared to more-stable areas) no vermiculite was detected in the CP. The results showed that evolution and classification of the studied soils were strongly affected by land-use type, topography and management.     

Finite Element Modeling of Extensional Structures in the Annapurna Region of Central Himalayas

Two-dimensional, elastic, plane-strain, finite element model are generated to investigate the extensional structures mainly normal fault in the Annapurna region, central Himalaya. The numerical study was performed on the Miocene geologic profile considering both of the convergent displacement and rock layer properties in the regime. Results show that the normal fault primarily influenced by model geometry, rheology (layer properties) and boundary condition (applied convergence displacement). Simulated normal fault density exhibits very high intensity in Lesser Himalaya then in the Tethys Himalaya and low intensity in the Higher Himalaya, suggesting the vulnerability of fault development to low-grade metamorphic rock than the high-grade rocks. The location of normal fault predicted by the numerical model analysis is consistent to the position of normal fault segments by Kaneko (J Geol Soc Jpn 103(3):203–226, 1997). In this studies, it also believed that the presence of these normal faults and underthrusting of the sub-Himalayan sequence with associated tectonic forces, the Himalayan Metamorphic belt has been exhumed and differentially domal uplifted and then segmented into several blocks.     

A Multiple SVM System for Classification of Hyperspectral Remote Sensing Data

With recent technological advances in remote sensing sensors and systems, very high-dimensional hyperspectral data are available for a better discrimination among different complex land-cover classes. However, the large number of spectral bands, but limited availability of training samples creates the problem of Hughes phenomenon or ‘curse of dimensionality’ in hyperspectral data sets. Moreover, these high numbers of bands are usually highly correlated. Because of these complexities of hyperspectral data, traditional classification strategies have often limited performance in classification of hyperspectral imagery. Referring to the limitation of single classifier in these situations, Multiple Classifier Systems (MCS) may have better performance than single classifier. This paper presents a new method for classification of hyperspectral data based on a band clustering strategy through a multiple Support Vector Machine system. The proposed method uses the band grouping process based on a modified mutual information strategy to split data into few band groups. After the band grouping step, the proposed algorithm aims at benefiting from the capabilities of SVM as classification method. So, the proposed approach applies SVM on each band group that is produced in a previous step. Finally, Naive Bayes (NB) as a classifier fusion method combines decisions of SVM classifiers. Experimental results on two common hyperspectral data sets show that the proposed method improves the classification accuracy in comparison with the standard SVM on entire bands of data and feature selection methods.     

Forecasting Daily Seepage Discharge of an Earth Dam Using Wavelet–Mutual Information–Gaussian Process Regression Approaches

Because of their sensitive structure, earth dams might face failure due to seepage phenomenon. In order to prevent such failure, some equipment like piezometers are installed in the body or foundation of earth dams. This study investigated the importance of piezometer installation level in dam body or foundation using mutual information–wavelet–Gaussian process regression. 27 Piezometers in three section along with reservoir level were employed to predict one-step-ahead seepage discharge of Zonouz earth dam. The daily data of 1 year of piezometer level and reservoir level were collected for this purpose. In order to find the best possible input combination, three groups of modeling scenarios were defined using piezometers and reservoir level time series. As some input combinations had more than two variables, decomposed time series were imposed into mutual information (MI) tool in order to decrement input variables and find the most correlated input–output features. Afterward, mentioned features were imposed into optimized Gaussian process regression (GPR) to be predicted. Different kernels were selected as core tool of GPR, but results demonstrated the capability of radial basis function (RBF) kernel. GPR–RBF structure were optimized using cross-validation technique. Results indicated that input combination including piezometer level and reservoir level of section II, especially piezometer 203 time series led to the best result among all scenarios.     

A procedure for damage-based seismic design of moment frame structures

Bulletin of Earthquake Engineering - A new method for seismic design of structures with the aim of controlling earthquake damage to a prescribed level is presented in this paper. The method is...     

Steel rings as seismic fuses for enhancing ductility of cross braced frames

A new remedy is proposed in this study to increase the ductility of cross-braced frames to a level comparable with ductile moment frames. The suggested system consists of one or two concentric steel rings installed in the cross-braced bay vertically. The steel rings are designed such that they fail in bending sooner than failure of the braces in compression. Then the rings act as seismic fuses with multiple bending plastic hinges. Using nonlinear static analysis, it is shown that the proposed system can be designed to behave like cross-braced frames with regard to stiffness and strength, and like special moment frames with regard to ductility. Seismic design factors for the proposed system are recommended based on nonlinear pushover and cyclic analysis studies.

     

Conversion factors for design spectral accelerations including soil–structure interaction

In this paper maximum response of a single degree of freedom system resting on a flexible base is determined under consistent earthquakes and the results are presented as acceleration spectra including soil–structure interaction (SSI). Flexibility of base is modeled using frequency-dependent springs and dampers. The spring–damper coefficients are calculated for the desired natural mode of vibration of a multi-degree-of-freedom system. Consistency of earthquakes is maintained considering their magnitude, distance, local soil type, and return period. The latter parameter is accounted for by the use of earthquake categories identified by their similar spectral values. Ratio of spectral acceleration modification factors with SSI from this study to those calculated using the ASCE 7-10 procedure are determined for each case. Examination of the resulting curves shows that the mentioned code is conservative/non-conservative in estimation of spectral responses with SSI in certain cases for the lower/higher modes of vibration. The code’s procedure is modified using the developed curves for a conversion factor.     

Disaster risk management in agriculture: tragedies of the smallholders

Agriculture sector is exposed to a variety of risks and uncertainties which can lead to sizeable losses in crop yields and alter farm incomes. Risk management is, therefore, an essential element of the overall farm management process. Farmers have number of options in managing farm risks; however, smallholders, due to their small operations and limited financial capabilities, find it difficult to adopt sophisticated risk management strategies to overcome yield and income instabilities at farm level. This study is, therefore, designed to investigate the enabling environment for small farmers to manage climatic risks at farm level. A total of 330 sampled respondents from Khyber Pakhtunkhwa Province of Pakistan are randomly selected for the study using multistage sampling technique. Analysis of variance technique is employed to compare the risk management adoption decision of small, medium and large farmers. A post hoc analysis is also performed to highlight the difference in means and the magnitude of differences. The results indicate that smallholders have significantly lower access to credit (both formal and informal), formal information sources along with significantly higher perceptions of pest and diseases. Smallholders are also at the tail end in the adoption of precautionary savings and agricultural credit to manage climatic risk at farm level. The study urges for risk management policies particularly in favor of the small farmers and intervention in the existing information and credit provision programs to facilitate smallholders in managing farm risks.