For precipitation regionalization of Kurdistan province and access to a suitable pattern in this context, annual precipitation of 83 stations are collected for a period of 30 years (1978-2007) from Applied Meteorological Research Centre of Kurdistan Province. Using rotated PCA approach by Varimax method showed that approximates 86.75 percent of annual precipitation variations of Kurdistan province can be explained by 7 components. The result of PCA used as an entrance of cluster analysis with Ward’s technique and it was distinguished that Kurdistan province has 3 different precipitation regions called west region with high precipitation, central region medium precipitation and east region with low precipitation region. Region East with it, slow precipitation is the biggest precipitation one in the Kurdistan province that Annual mean precipitations is about 368.7 mm. The central region with medium precipitation region is the second large region of precipitation. Annual mean precipitation of this region is about 537.7 mm. Western high precipitation region is the smallest region of precipitation and at the same time it is the wettest region of precipitation in Kurdistan province. The annual mean precipitation of this region is about 706 mm.

One of most effective factors on life of an area is its climate type so that dispersion of types of plants and animals has a tight relationship with climatic condition of every area،thus understanding of climate type of an area and effective elements that are determinant of climate of that area is preferable so climatic division or understanding of climatic flattening is sensory for planning in order to optimal exploitation and area utilization. Hence the purpose of this study is to identify environmental powers and the most important climatic elements influencing on climate of yazd and to separate locally climatic sub areas of yazd by using modern statistical methods. In this article, climatic Regionalization of yazd is performed by multivariate methods and features of every climate is separately stated. For accessing to this purpose, statictcal data of 28 atmospheric variables related to 25 barometric stations were elicited from aerology organization, that they provided annual average of 27 climatic elements of 25 barometric stations of yazd. This matrix was averegged 25´27 as small as cell (pixcel) 15´15 kilometric by kriching method and changed to matrix 27´579. Then modern methods based on base components analysis and cluster analysis techniques were used، by applying base components analysis on matrix, correlation of data matrix showed that we can describe 99.3 % dispersion of data by six components. First component is humidity- windy elements determine the highest dispersion of data (43.8) that quantity profile of yazd is shown as following by this method according to importance of element: Temperature-humidity component, precipitation-humidity component, dusty component, windy component. By applying hierarchical cluster analysis and integration method on score of components, climate areas of yazd were divided to six areas including: 1- moderate and relativly arid climate of Abarkooh - Harat 2- moderate and arid and dusty climate of Shirkuh 3-Semi warm and hyper arid climate of Yazd_Bafgh 4-warm, hyper arid and dusty climate of Tabas 5-Semi warm and arid climate of Dastgerdan 6- Semi warm and arid climate of Dey hook.

In this research work, Intra-species karyotypic diversity for 17 populations of Silybum marianum from different geographical regions of Iran along with one population from Hungary were investigated. To prepare the appropriate chromosomal specimen, one and a half centimeters of root tip were isolated, after using fixation of pre-treatment, the picture were taken from the karyotypes which prepared and the chromosome base number of all of them was x = 17, therefore the number of chromosomes obtained 2n = 34. In terms of karyotypic symmetry indices DRL, S%, TF%, A1 and A2, there were significant differences between ecotypes at probability level of 1%, which indicates that there were genetic diversity between the studied ecotypes. Regarding these results, the Ramhormoz ecotype and then the Shushtar ecotype were considered as the most asymmetric and most advanced ecotypes and the ecotype of Najaf-Abad and ecotype of Karaj-2 were considered as the most symmetrical and incomplete ecotypes. Based on the cluster analysis, the karyotypic characters of the populations were divided into three groups. The greatest difference was observed between the two Ramhormoz and Najafabad ecotypes. To determine the contribution of each karyotypic trait in the creation of diversity among ecotypes, factor analysis was carried out and the first, second and third factors accounted for more than 87% of the variation among the populations. The results of karyotypic analysis showed that there is a high karyotypic variation among Silybum marianum ecotypes in Iran, so that they can be used in breeding programs and widening genetic diversity in gene pools.

The weaknesses of the traditional climatic classification methods in presenting the climatic realities of Caspian region and showing the new methods'' merits based on multivariate statistical methods, and geographical information system in presenting the climatic regions of Caspian, are among the most important ideas of conducting this study. To do so, we used the data of synoptic stations of north and north east of the country in a period of 20 years. To analyze 19 climatic elements in “Factor analysis” method; at first the map of each studied climate of the region was traced by “Surfer software” on the bases of Pixel in a 15*15 km measure. And also by “minimum curvature” method, data of each map become interpolated. After that, data of each map were changed to digital data, which a matrix in a 266*19 measure was formed of those digital data. By analyzing the matrix in “Factor analysis” method, it was certificated that 98% data variance of it is of the precipitation and temperature that Data consist: 50% of the primary factor and 48% of the secondary factor. Quantities of precipitation and temperature were analyzed by “agglomerative hierarchical cluster analyzes” in “ward” method that the Caspian region was divided to four regions in the aftermath; moderate and humid, moderate and semi humid, cold and low precipitation, and semi cold and low precipitation. These minor climatic regions are greatly influenced by some climatic factors, as the remoteness and farness from the sea and the elevation increase. Climatic varieties in the eastern parts, especially in the limits of Golestan province, are more evident.

In statistical analysis of water quality variables, determining the relationships between these variables is one of the most important issues. In this research, Canonical Correlation Analysis was used to find the relation between physical and chemical variables and Principal Component Analysis was used to determine the main variables of Dez water quality. Also for classification of stations Cluster Analysis was used. Results show that there was significant relation between physical and chemical variables of Dez River because of human activities like Haft-Tapeh sugarcane Agro-Industry Company and industrial companies. Also results of principal component analysis showed that Ec, Temprature, SAR, SO4, pH and DO were the main variables of Dez River water quality which were because of human activities and industrial pollutions. Results of cluster analysis for classification of stations showed that Bamdezh and Harmaleh stations (downstream of Dezful city) were in the same class and Tele-Zang station (upstream of Dezful city) was different from other stations then urban zone and human activities have the major impact on station classification.

For better understand of hydrogeochemical processes in the Salmas plain aquifer, this study adopted graphical methods and multivariate statistical techniques to analyze groundwater samples. The results of the Piper diagram and expanded Durov diagram reveals that the major groundwater type is Ca-(Mg)-HCO3 and mixing groundwater type exists in southeast of the Salmas plain. Hierarchical Cluster Analysis (HCA) identified five classes of groundwater type (HC1 to HC5). The hierarchical cluster analysis is able to show the influence of nitrate concentration in classification while the graphical methods cannot. The Stiff diagrams of five classes (HC1 to HC5) show three different sources of groundwater samples. The HC1 to HC3 classes indicate groundwater with limestone and dolomite origin. In HC4 class, Na+ and Clˉ are the dominate ions in groundwater samples and shows saline waters. The HC5 shows mixing groundwater. Using Factor Analysis (FA), we identified three factors that accounted for 85. 03% of the total variance of the dataset. Factors 1 and 2 are reflected the natural hydrogeochemical processes and factor 3 is anthropogenic in the Salmas plain.

In order to detect genetic diversity and effective traits on forage yield of 49 accessions of alfalfa (Medicago sativa), an experiment was used in a simple lattice design with two replications at the Research Center for Agricultural Resources of East Azarbaijan, Tabriz, Iran during 2006. Traits evaluated in this study were: fresh forage yield, dry forage yield, days to %50 flowering, plant height, number of stem, number of nods, internode length, growth rate and leaf to stem ratio. Analysis of variance revealed that there were significant differences among ecnotypes for the most of the traits under investigation. Mean comparisons indicated that the ecotypes Nos. 37 (France), 13 (Tabriz local), 25 (Gorgan), 12 (Sabzevar) and 46 (Heris) were higher producers both for forage yield and quality under irrigation. They can be recommended as early maturing high forage producing and high growth rate ecotypes. Using WARD cluster analysis method, the 49 ecotypes of alfalfa were classified into 5 groups. Based on forage yield and quality, groups 5 and 2 were promising, respectively. Principal components analysis indicated that first PC and second PC significantly affected high yield and quality, respectively.

To determine regionalization of climate in Yazd province, 42 climate parameters were selected from climatology and synoptic stations of the study area and a 15×15 kilometers geographical network was considered to investigate the selected elements in the study area. The elements were studied in each cells knot using krigging method. Reduction of data matrix using factor analysis, varimax rotation, and climate zoning by cluster analysis and ward method were the next steps of the research. The results indicated that 5 factors accounted for 92.83 percent of the variation. These factors included precipitation, thermal temperature, dusty, wind and humidity, which explained 34.70, 32.74, 11.92, 7.08, and 6.39 percent of variation respectively. The results of hierarchical method of cluster showed that Yazd province with 131575 km2 has 6 different zonations including arid and cold, arid and dusty, semi arid and cold, very arid and warm, very arid and windy climes.

Aim: The purpose of this research is to formulate a program and design a suitable model for environmental monitoring of water quality in order to reduce the costs of water quality monitoring and evaluation in No.1 Zabol Chahnimeh. Material & Methods: In this study eight sampling stations were selected in the bed of the reservoir No.1 in order to monitoring and measuring physical, chemical and microbial parameters. Sampling was conducted systematically on a month basis for one year. Then the data were analyzed with the help of multivariate statistical methods such as cluster analysis, Principal Component Analysis (PCA) and factor analysis. Findings: Using multivariate statistical methods, No. 4, 5, 6 stations were selected as the main stations for sampling and factors of temperature, turbidity, DO, COD, magnesium, sodium, calcium, phosphate, chlorine, nitrite, sodium Absorption Ratio and pH was determined as the main water quality indicators. It was revealed that temperature, DO, nitrate and turbidity parameters should be sampled monthly, but the other parameters could be sampled periodically or even quarterly to model an optimal monitoring of water quality in reservoir No.1 during a year. Conclusion: In general, the evaluation of the quality status of this valuable water resource by reducing the number of sampling stations, eliminating some unnecessary parameters and reducing the frequency of sampling completely and without defects and at a much lower cost is done for this reason, having the lowest costs and proper timing, management of the main reservoir will be possible considering all effective parameters.

In order to providing selection indices using heritability and correlation effective traits on yield and multiple regression an experiment was conducted by 265 F3 families as well as parents and F1 related to Gharib × Khazar population in 2009 at Gonbad High Education Center fields. Days to repining (0.97) and panicle number and flag leaf length (0.66) had maximum and minimum heritability, respectively. Positive and significant correlations were detected between plant yield and flag leaf width (0.265**), plant height (0.193**), panicle number (0.734**) and biomass (0.828**). Biomass, days to heading and plant height were explained about 98% of total variation of yield and inserted to model respectively. Phenotypic and genotypic correlations, genetic and phenotypic direct effect in path analysis, heritability were used for construct selection vectors. According to this study, increasing of traits is not result of relative efficiency and compares parameter. Selection indices were showed that yield, significant genetic correlation with yield and high heritability are three important part of selection index. Fifth, Sixth and fourteenth are the most important between discussed indices.