An ultraviolet-selected galaxy redshift survey – III. Multicolour imaging and non-uniform star formation histories     

Mark Sullivan  Marie A. Treyer  Richard S. Ellis  Bahram Mobasher 《Monthly notices of the Royal Astronomical Society》2004,350(1):21-34

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Land Subsidence Susceptibility Zonation of Isfahan Plain Based on Geological Bedrock Layer     

Fatolahzadeh  Sina  Nadi  Bahram  Ajalloeian  Rassoul 《Geotechnical and Geological Engineering》2022,40(4):1989-1996

Geotechnical and Geological Engineering - In the present paper, the effect of the depth of the bedrock layer on the land subsidence of the Isfahan plain was studied. The geological bedrock layer...  相似文献   

Incorporating synoptic-scale climate signals for streamflow modelling over the Mediterranean region using machine learning models     

Ozgur Kisi  Bahram Choubin  Ravinesh C. Deo 《水文科学杂志》2013,58(10):1240-1252

ABSTRACT

Understanding streamflow patterns by incorporating climate signal information can contribute remarkably to the knowledge of future local environmental flows. Three machine learning models, the multivariate adaptive regression splines (MARS), the M5 Model Tree and the least squares support vector machine (LSSVM) are established to predict the streamflow pattern over the Mediterranean region of Turkey (Besiri and Baykan stations). The structure of the predictive models is built using synoptic-scale climate signal information and river flow data from antecedent records. The predictive models are evaluated and assessed using quantitative and graphical statistics. The correlation analysis demonstrates that the North Pacific (NP) and the East Central Tropical Pacific Sea Surface Temperature (Niño3.4) indices have a substantial influence on the streamflow patterns, in addition to the historical information obtained from the river flow data. The model results reveal the utility of the LSSVM model over the other models through incorporating climate signal information for modelling streamflow.  相似文献   

Monte Carlo analysis of the effect of spatial distribution of storms on prioritization of flood source areas   总被引：1，自引：0，他引：1  

Bahram Saghafian  Saeed Golian  Mohammad Elmi  Ruhangiz Akhtari 《Natural Hazards》2013,66(2):1059-1071

Implementation of structural and non-structural flood control measures in flood-prone watersheds is on increasing demand. Different watershed areas are not necessarily hydrologically similar and impose variable effects on the outlet flow hydrograph. Meanwhile, prioritization of watershed areas in terms of flood generation is essential for economic flood control planning. Previous works have focused on the definition of a flood index that quantifies the contribution of each subwatershed unit or grid cell to the outlet flood hydrograph through the application of unit flood response (UFR) approach. In the present research, for the first time, the effect of spatial pattern of storm events on the flood index variation was assessed via a Monte Carlo uncertainty analysis. To do so, the UFR approach was carried out for a large number of randomly generated rainfall spatial pattern. The proposed methodology was adopted to the Tangrah watershed in northern Iran. The watershed is frequently hit by floods that have historically caused loss of life and properties. The results indicated that for the more frequent flood events, the flood index is quite sensitive to the spatial distribution of rainfall such that for the highest ranked subwatershed (SW6), the standardized variation of the flood index values (i.e., the uncertainty range) decreases from 1.0 to 0.5 when the rainfall depth increases from 20 to 150 mm, respectively. The results further revealed that increasing the rainfall depth from 20 to 150 mm would cause the effect of rainfall spatial distribution on subwatersheds’ flood indices to diminish. The implications are that if flood control measures are designed for more frequent floods with lower return periods, an uncertainty analysis is required to identify the range of flood index variations.  相似文献   

Chemistry of the Karst Sarabkalan Spring,Iran, and Controls of PDO and ENSO Climate Indices on It     

Abolfazl Rezaei 《Ground water》2021,59(2):236-244

The Sarabkalan Spring serves as a primary water supply to irrigation and domestic use in the Sirvan Region, Iran. As it has a highly variable discharge, understanding its teleconnections with large-scale climate variability is crucial. In this study, we first characterize the springshed and its corresponding karst aquifer system using genetic algorithm analysis on the spring discharge, water balance calculations, temporal variations of physicochemical parameters, and stable isotopes along with considering its geological settings. Then, the large-scale climate indices teleconnections with precipitation and spring discharge are studied using wavelet analysis. Results reveal that the springshed contains two karst subaquifers resulting from geological and morphological settings. Unlike most developed karst systems in Zagros, which show one peak, the spring has two principal flow peaks over most hydrological years where the second peak occurs over the dry season. It takes ∼99 d (from lag correlation over 2008-2019) and ∼145 d (from δ¹⁸O measurements over 2018-2019) for rain water to reach the Sarabkalan Spring. Moreover, intense precipitations would result in an increase in discharge and a decrease in electrical conductivity, Ca + Mg, HCO₃, SO₄, Cl, ionic strength, and δ¹⁸O of the spring because of the developed karst conduit(s). It is further found that a positive Pacific Decadal Oscillation phase coupled with El Niño causes an increase in both the precipitation and spring discharge, signifying the influence of the atmospheric circulations of the Pacific Ocean on the spring behavior.  相似文献   

K- and Si-Metasomatism, Mineral Transformation and Formation of Granitoids from Basic Rocks in Qooshchi Area, NW Iran. A Mineralogical Context     

PouranBehnia LorenceGCollins BahrainASamani 《中国地质大学学报(英文版)》2003,14(1):34-41

The Qooshchi area lies to northwest of Orumieh Lake in western Azerbaijan, NW Iran. A basement metamorphic complex, consisting of Precambrian schists and gneisses, has been intruded by gabbres and diorites. Granitolds are grouped into five suites according to their mineralogy, texture and exposed features. The main body, pink Qooshchi granite, and apophyse-like, myrmekite-bearing granit-oids are discussed in this paper. On the basis of field observations and microscopic studies, an intensive metasonmtism has overprinted the country rocks, especially gabbros, transforming them into a more felsic composition. A prior event of intensive deformation and cataclasis preceded the metasonmtism, al-lowing the introduction of hydrothermal fluids. K-metasonmtism converted plagiuclase into K-feldspar (microdme), myrmekite, and sodic plagioclase as Si-metasomatism replaced the ferromagnesian silicates by quartz. Apophyse-like bodies within gabbros, called leucometasomatites, are formed during this process.  相似文献   

Wetland classification in Newfoundland and Labrador using multi-source SAR and optical data integration     

Meisam Amani  Bahram Salehi  Sahel Mahdavi  Jean Granger  Brian Brisco 《地理信息系统科学与遥感》2017,54(6):779-796

A vast portion of Newfoundland and Labrador (NL) is covered by wetland areas. Notably, it is the only province in Atlantic Canada that does not have a wetland inventory system. Wetlands are important areas of research because they play a pivotal role in ecological conservation and impact human activities in the province. Therefore, classifying wetland types and monitoring their changes are crucial tasks recommended for the province. In this study, wetlands in five pilot sites, distributed across NL, were classified using the integration of aerial imagery, Synthetic Aperture Radar, and optical satellite data. First, each study area was segmented using the object-based method, and then various spectral and polarimetric features were evaluated to select the best features for identifying wetland classes using the Random Forest algorithm. The accuracies of the classifications were assessed by the parameters obtained from confusion matrices, and the overall accuracies varied between 81% and 91%. Moreover, the average producer and user accuracies for wetland classes, considering all pilot sites, were 71% and 72%, respectively. Since the proposed methodology demonstrated high accuracies for wetland classification in different study areas with various ecological characteristics, the application of future classifications in other areas of interest is promising.  相似文献   

Investigating the efficiency of information entropy and fuzzy theories to classification of groundwater samples for drinking purposes: Lenjanat Plain,Central Iran     

Salahaddin Kamrani  Mohsen Rezaei  Vahab Amiri  Amir Saberinasr 《Environmental Earth Sciences》2016,75(20):1370

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Direct displacement-based design of special concentrically-braced frames in near-fault regions     

Mahmood Yahyai  Bahram Rezayibana 《Bulletin of Earthquake Engineering》2015,13(10):2945-2971

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Feed forward neural network and interpolation function models to predict the soil and subsurface sediments distribution in Bam,Iran   总被引：1，自引：1，他引：0  

Khalil Rezaei  Bernard Guest  Anke Friedrich  Farajollah Fayazi  Muhammad Nakhaei  Ali Beitollahi  Seyed Mahmoud Fatemi Aghda 《Acta Geophysica》2009,57(2):271-293

An application of the artificial neural network (ANN) approach for predicting mean grain size using electric resistivity data from Bam city is presented. A feed forward back propagation network was developed employing 45 sets of input data. The input variables in the ANN model are the electrical resistivity, water table as a Boolean value and depth; the output is the mean grain size. To demonstrate the authenticity of this approach, the network predictions are compared with those from interpolation methods and the same data. This comparison shows that the ANN approach performs better results. The predicted and observed mean grain size values were compared and show high correlation coefficients. The ANN approach maps show a high degree of correlation with well data based grain size maps and can therefore be used conservatively to better understand the influence of input parameters on sedimentological predictions.  相似文献