ام السلمه بابایی فینی

Access to water resources from the perspective of quality and quantity necessary for human life and human activities. The protection of these resources, especially fresh water as one of the most important factors is necessary to protect the health and development of communities. It is obvious that the first step for the conservation and optimal utilization of these resources should have the knowledge and identification of potential sources And by doing continuous monitoring of comprehensive knowledge about a qualitative change them to obtain and provide the context of sustainable development. The results show that frequent and persistent drought in recent years has exacerbated the drop in groundwater level plain And despite the establishment of various industries with its natural pollution and increased use of chemical fertilizers in the desert, with little change in reducing the chemical quality of groundwater resources was made. Results of interpretation are diagrams and charts, represent about 63 percent of agriculturally choice in the category C2S1 and C3S1 are 37 percent of the rest of the class. For industrial use about 82% of cases of type are read and 16% of depositing the samples are considered, only 2% of the remaining balance are examples of the type. About 55% of the water in hard water category and 23% in the category of very hard, and the rest (22%) as moderately hard water are introduced. More than 70 to 80 percent of the water in the well and the rest of the acceptable category and only about 3 percent in mid-fall.

The street network as a communication artery, is an important component of rural settlements tissue, and basically, texture is irregular and complex, and rural guide plan to regulate the streets network in the village runs. But, usually in implementing these projects, several problems such as Equal attention to rural and urban street network and benefiting from experiences of urban patterns, disregarding the fields formation and the nature of their performance, low attention to topographic conditions and needs of the people, the lack of cooperation of the public and local institutions and etc. prevent the proper implementation of such projects.
Given that in the planning and design of rural road network in the guide plan, attention to issues such as determining the functional hierarchy of roads, according to the characteristics of each level and attention to environmental and economic and social factors in creating and expanding roads, is important. Essential is evaluation the condition of rural roads network in the villages where has been implemented in it guide plan, to be examined role this plan in the guided and regulating of the rural Lifeline.
THEORETICAL FRAMEWORK: One of the most important structural elements of rural development to support the rural poverty and reducing the vulnerability of rural areas is attention to the physical dimensions of economic, social and human environment in rural areas. In this context, organizing accessibility to services, transport and rural communications is one of the main objectives of rural physical development. The first time, attention to the rural road network and the level of its hierarchy in the national road system in India was conducted in Nagpur region between years 1943 to 1961, and today, China as a global leader of the road expansion and modernization of rural streets network is known. Accommodations have a significant impact on the development of physical-spatial street network, depending on the optimum use of them. Indeed, one of the ways to guide land use and prevent violations of it is improving the rural roads network. Thus, the coefficient optimal use of the road network is dependent on several factors:- Using streets network for traffic of the vehicles
- Streets Network positive effect on reducing transport services and increasing the speed, reliability, and safety
- The use of street network for economic activity and trade
- Expedite in services and aid to others.
In the design and engineering of streets Network in the city inside, suburban and other settlements, streets are placed in four categories: 1. Main street; 2. Street collector; 3. Local minor street; and 4. Entry and access.
About the importance of the streets network in the shaping and organizing rural settlements several theories have been proposed. Most notably, the theory of natural movement and the importance of analyzing the spatial structure of street network, spatial arrangement theory, perspective of functional separation paths (linear model), the theory of interconnectedness.
The research method is descriptive-analytic. For data collection, library and field studies have been used. The study consisted of 24 villages of the Zanjan county in which guide plan has been completed and is assessable. Using the cluster sampling method 10 villages have been selected from 10 districts. Rural population of sample is 11554 people that using Morgan table, a sample of 373 people were selected as statistical sample. To analyze the data from one sample t test, chi-square goodness of fit test (χ2) and kolmogorov - smirnov test (K-S) with the help of SPSS software has been used. Indicators of research include "street network width”, "Pattern making of street network”, "Landscape and architecture of the street network", "street network slope" and "surface and coverage of the street network".
Research findings show that, based on single-sample t test among the rural streets network indicators, component "the materials quality of the street network infrastructure" with the statistic t 091/6 is highly adapted to the street network standards. According to the chi-square goodness of fit test, the greatest satisfaction from index "length and width of street network» (χ2= 889. 52) and the lowest satisfaction from index "level and streets network coverage » (χ2= 21. 667) is. Also, in the Kolmogorov-Smirnov goodness of fit test by comparing normal and Poisson distributions, observe card results in the field network indicators status, as well as satisfaction questionnaire statistical population, is non-normal distribution of samples. Also, there is a difference between the normal distribution (N= 2. 324) and Poisson distribution (P= 1. 679). However, the amount of K-S in the Poisson distribution rather than a normal distribution. These factors indicate that the situation of the indicators of research is improving and developing. Also, the average rural streets network in compliance with the standards and satisfy the villagers is equal to 3. 32. This value is average.
According to the findings of quantitative study about the positive impact of guide plan to improve rural streets network and also, according to the results of previous research which showed that the physical plans and development of the rural streets network prevent violations and surface water repelling, and the garbage collector, accelerate the access to services, guide land use and increase the reliability and safety of the traffic in the village. Implementation of Rural guide Plan to improve road network and compliance with standards, as well as increasing rural satisfaction from their performance, increased efficiency of the network in the rural settlements. To improve the situation, increasing local control and organization, confirming the quality of materials by experts, monitoring the Regulatory compliance after implementation, attention to the architecture and aesthetics and safety in the streets network design are essential.

Dust storm is an important atmospheric phenomenon. It has important environment, health, economic and social activities due to penetration of suspended particles of dust to the atmosphere. Measurements resulting from earth and satellite stations show the fact that particles of dust in storms, remain in the nature for a long time. They can get far away by wind, hundreds of kilometers from their origin and have destructive effects. This phenomenon is one of the most disastrous calamities in deserts and half dried regions of the world. It causes many environmental problems in these regions.
Iran is on the dried and half dried belt in the world. Therefore, it is exposed to local and synoptic dusts repeatedly.
Wind with high speed in short time is called storm, storm with unstable air. If unstable air is humid, it is called storm and lightning. It is also called dust storm.
On the basis of the world Meteorological Organization agreement, in case in a station, the wind is beyond 15 meters per second and horizontal vision is less than one kilometer, dust storms occur. There are different methods and data for studying dust storm. One of them is synoptic-dynamic studying on this phenomenon.
According to the terms of the dust storms formation, bare lands of world desert regions (Africa, the deserts of the Middle East, China, Australia and the United States of America) are prone to such storms. Dust storm creative power can arise from the Ocean systems, such as Hurricane of North Atlantic Or due to high pressure gradient difference between two agent regions of this phenomenon, rare sand storms originating from the desert to reach the Arctic region.
In recent years, during which we have been faced with a lot of dust storms, the study of this phenomenon, especially for half western storms of the country and those derived from West surrounding borders confirms the importance of this phenomenon in all aspects of the inhabitant's life of this land. The current study seeks to investigate the pattern of atmospheric circulation and surface conditions that shape them in terms of spatial and temporal view, which has shaped after big dust storms identification in the period of 1985 to 2005.
Study area: Taking into consideration the accelerating trend of the emergence of dusts in the west of Iran, the mentioned region was selected to conduct the research. The mentioned region in the south covers the northern shores of the Persian Gulf from the 30 degree of the north latitude to the borders of north –north West of Iran.
Material and For doing such a research, the data of frequency of dust and standardized pressure of the sea level for the earth surface were collected from the state meteorology organization (dust data with code 6) and the ocean-atmospheric organization, respectively.
Also geo-potential-meter and wind orbit and longitude data were obtained from the National Organization of ocean-atmosphere. These data with local separation capability of 2/5 degree in longitude and latitude are in the form of daily average. The above data are NCEP-DOE Reanalysis 2, that is advanced version of data in model NCEP Reanalysis with no error in quantity.
To study the significant difference in the abundance average of dust stream in the west region of the state during 1989-2005, T test with the two independent samples was used. The prerequisite of doing this test is the study of normality of frequency data of dusts, because in the event of lack of normality of the frequency of dusts, it is necessary to use the equality of non-parameter of this test, i.e. Mann Whitney U Test. In order to study the normality of data, the Kolmogorov–Smirnov test was employed.
After testing comparative hypothesis, different time cycles, regarding to frequency of dust were specified. Then huge dust stream s occurred from 2000-2010. These data were obtained from the site of U.S.A National Organization of space aviation.
In order to study the presence of difference in the frequency of the data in the hot season (April to September) and cold season (October to March), the t test with two independent samples were used.
The test is used to calculate confidence interval or difference hypotheses test of two independent samples. In other words, in this test obtained averages from random samples are judged. This means we choose random samples from two different communities (here warm season and cool season) (recorded stations of dust frequency) and also compare average of two communities with each other.
This method is based on the t normal distribution and it is best used for small samples that the data are near normal or normally distributed. So at the beginning of the notion normality of the data must be calculated. In the current study the Kolmogorov - Smirnov test was used.
Results showed that the dust frequency mean has normal distribution in studied stations during 1989 to 2008. Thus, t test with two independent samples can be used for investigation of dust frequency differences in the two warm and cool seasons.
To interpret the t test results with two independent samples first equality or inequality of dust frequency variance should be investigated in the two warm and cold seasons. The test which is used to this purpose is Levene's test. In this test, first conversion is performed on dust frequency in both warm and cold seasons and thus new data is calculated for each of these two groups. Then, t-test is done on the new data.
Comparative analysis of 40 dust stream occurrence during the last 11 years and considering different periods (calculated in testing difference hypothesis) led to presenting the patterns of occurrence of dust stream During hot periods (April to September) and cold periods (October to March).
The monthly average of dust in the west of Iran indicates the maximum of frequency for the occurrence of dust in April to September and contrary to that, in other months, the frequency of this phenomenon reduces.
The synoptic analysis of dusts in hot seasons: Studying the maps of pressure of ground surface and geo-potential height, the speed and direction of wind at the level of 850 hPa during the hot season, it was specified and that in most cases, a low pressure has taken shape at ground surface located in the west of Iran , i.e. in agreement with the centers of dust (so called Oman-Persian gulf low pressure which are observed in form of a flare of seasonal low pressure of India) and at the level of 850 hPa, a low height in the north, west and north west of Iran is observed which transfer dust into the western regions of Iran.
The synoptic analysis of dusts in the cold season: Studying the maps of the land level and geo-potential height, the speed and direction of wind at 850 hPa during the cold season, it was specified that an asymmetric model leading to the dust (opposite to the hot season which was fixed for all samples) results from different conditions. In line with this, with the study and cultivation of samples collected, it was specified that the emergence of dust in the cold season is mostly a function of the 850 hPa rather than surface.
Research results show that the frequency of dust in hot seasons is more than that of the cold season and this difference is meaningful with confidence level of 95%.
This meaningful difference derives from their creator systems and specifications of the earth during hot and cold systems. Although instability in the cold season is more than the hot season, the humidity on the earth surface, prevents the formation of dust. The comparative patterns show that those factors that create dust in cold seasons are more variable due to the variety of pressure systems that affect Iran.

The inherent problem lying with the lack of development in Iranian tourism industry prompted the author of the current research paper to put forward the hypothesis that it would probably be possible to find a solution through comparing the laws and regulations of the Islamic Republic of Iran with those of some developed countries. It is hoped that research projects like the present one can help get this overwhelmingly important industry get moving. For this purpose, the laws of the Islamic Republic of Iran and some developed countries on such areas as visa issuance, customs roles, transportation, cargo and passenger transfer laws, transit insurance and issues related to the judiciary and the courts were compared and contrasted. The current research project ends with an answer to the question: "Can a comparative study of the laws and regulations of the Islamic Republic of Iran and some developed western countries open a way into helping the Iranian tourism industry in order for it to thrive?" To answer the above question, one can safely say that "the laws and regulations of the Islamic Republic of Iran on tourism are thorough in terms of being parts of the Iranian international laws." A proper implementation of such laws, however, can contribute to not only evaluation of laws regarding tourism industry in the Islamic Republic of Iran but it can help introduce new techniques and initiatives in the process of sustainable tourism development.

The purpose of this research is to study the method of distribution of thermal models of land surface and the normalized indicator of vegetation and the relationship between these two variables in the cold and hot seasons in Isfahan city as one of the most important population centers in Iran. In line with this objective, employing the four images of the Landsat TM sensor, the land surface temperature and the normalized Index of vegetation in a 19-year time span was made in the dates of January 7, 1991, June 16, 1991, December 29, 2010 and July 4, 2010. The results of the research showed that: On 7 January, 1991, the minimum temperature of-1/1 centigrade, the maximum temperature of 16 centigrade with an average of 5/1 and standard deviation of 1/4 were calculated. On 16 June, 1991, the minimum temperature of 16, the maximum temperature of 33 centigrade with an average of 28 centigrade and standard deviation of 3, On 4 June, 2010, the minimum temperature of 18, the maximum temperature of 37 , with an average of 29 centigrade and standard deviation of 3/2, On 29 December, 2010, the minimum temperature of -3/6, the maximum temperature of 19, with an average of 7/7 centigrade and standard deviation of 3/2 were calculated. Also, the index minimum On 7 January, 1991 of -0/96 and its maximum of 0/78 with an standard deviation of 0/1 and On 16 June, 1991, the minimum index of -0/36, the maximum of 0/66 and the standard deviation of 0/14, On 4 June, 2010, the minimum index of -0/23, the maximum of 0/68 and the standard deviation 0/11 and on 29 December, 2010, the minimum index of -0/4, the maximum of 0/56 and the standard deviation of 0/066 were calculated. The dispersion of the hot temperature range in the regions of 5, 6 and 13 and in the cold period of the year and the hot temperature range in the regions of 6 and 5 and cold in the peripheral regions of Zayandeh Rood (River) in the hot period of the year is observable.

One of the basic needs in the field of rural development is providing social health for villagers to to create appropriate basis to use social, economic and environmental possibilities of the village. So, rural development does not just include economic and agricultural aspects, but includes other aspects of life such as environmental, social, wellbeing and health aspects. Henceforth, dealing with the concept of health and specifically in social dimension, is one of the necessities in rural planning and development in our country, so that -through pathology of rural settlements in this sector, the solutions for social well-being promotion and subsequent development of rural economic, scientific, social, cultural and environmental aspects are provided in these settlements. Thus, the present study aimed to analyse and evaluate the state of social well-being in rural settlements in the county of Zanjan and identify strategies for its development and strengthening in these settlements.THEORETICAL FRAMEWORK : Health, including Full Welfare of physical, mental and social. One of the most important aspects health, social well-being. To analyze the social well-being in society, health -Pivot and patient-Pivot approaches are studied. In most studies and social researches, the health-Pivot approach is used. There are also different models in this field, that social well-being model of Keyes, model and Miringof model and quality of life model of the most important models in this regard. Social well-being studies done in rural areas in the form of healthy village approach. Based on this approach, healthy rural is village in which they continually be prepared the optimum conditions, the possibility expanding of cooperation Intersectoral of environmental engender. Hence, in the rural with high social well-being, participation and environmental preservation is a priority than other factors.

This research using descriptive-analytical method, social well-being in rural settlements of Zanjan County is reviewed. In the context, for collecting data from field studies methods and the library is used. The Statistical Society is 258 rural point. And using method of simple cluster sampling, and with the help of province political boundaries from each district were selected randomly 1 village. Thus, 12 rural point were selected as the samples. In the next phase given that the households number of simple rural 12 of about 4213 households is. Using Morgan table, 352 households were selected as samples for the questionnaire distributed. To analyze the data, with Kolmogorov-Smirnov test, the amount of normal Frequency distribution of experimental and theoretical Frequency was evaluated. Then by using exploratory factor analysis, the main factors to determine the appropriate Pattern of variables were identified. The statistical calculations were performed using SPSS software and Lisrel. Indicators of research based on models and theories indicator Keyes social well-being, social well-being indicators of Miringof and the indicators of quality of life of Malcolm Shukner is set. And for each of the three models separate questionnaire was designed.

The study shows that the social well-being status of rural, based on Keyes model, the amount of social well-being in this rurals is at an average level with an average of 3.32. Also, Based on calculations Kolmogorov-Smirnov, the significant level (P-Value) participation in indicators, prosperity and social cohesion less than P0.05. And the null hypothesis is confirmed. Quality of life model is not in Desirable condition, with a mean of 2.6. Weakness in the index, has a direct refers to the weakness of social and economic infrastructure. In this context, Kolmogorov-Smirnov goodness of fit test indicates that Economic and health indicators with a significant level of 0.000 (P

One of the basic priorities in rural development is the reduction of inequalities between city and villages and the villagers due to lack of services and facilities will supply their needs through repeated references to urban centers. One of the solutions for rural planners is to develop the services and some urban usages in rural areas including development of Information and Communication Technology (ICT) agencies in rural centers, so that about 9721 ICT agencies are working in the villages of the country. Therefore, the aim of the study is to evaluate the role of ICT agencies in rural area of GharehPoshtlu district of Zanjan city. The research method is descriptive-analytical method and library and filed studies have been used for gathering data. Statistical society includes 9 rural points with 6417 people in GharehPoshtlu district which rural ICT agencies are placed there. The sample size was estimated 95 people by Cochran sampling method. For data analysis and testing the research hypothesis, T single sample test, path analysis model and SPSST, Exel and ARC GIS have been used. In this study, the economical, social, informative and service indicators were considered as in dependant variables and rural development index was considered as dependant variable and the role of rural agencies have been studied in three sections. The study results show that the effect coefficient of ICT agencies and rural communications on service index, informative index and economical index are 17.617, 9.898 and 8.810 respectively and such agencies affect on the development trend of rural areas through promoting the above mentioned indicators. To extend the functions of such agencies in the area, development of scientific, communication, cultural infrastructures and communication between local institutions with ICT agencies is necessary

The main objective of this study is to evaluate the effects of climatic signals on the discharge rate of the two nominated stations and fluctuation of Uremia lake water، during the time period of 22-years (1986-2007). To do this، data of the two nominated stations، monthly data of Southern Fluctuation Index (SOI)، North Atlantic fluctuation (NAO) and ENSO index in NINO1+2، NINO3، NINO4 and NINO3. 4 were used. Large-scale climatic data signals were obtained from NCEP data center. Data about average monthly discharge rate of Dashband and Sarighmish stations was prepared from the data center of the Ministry of Energy. Firstly، for primary study of the data and the correlation between them in order to provide the best model to predict discharge rate، time steps of 0، 3 and 6 months were considered. In examining the discharge rate in various time intervals of the under study stations، it was obtained that the correlation in the delayed time intervals of six-months is more than the simultaneous and three months delay. After explaining the relation and its type، the forecasting model was designed using artificial neural network and the results of the model were evaluated and analyzed. Given the significant correlation in time intervals، it was realized that large-scale climatic indices، from the view point of common atmospheric circulation and large atmospheric systems in the study area have a significant impact on temperature، rainfall، discharge rate and fluctuation of Uremia lake water. Study the output models of artificial neural network indicates that the most effective signals of the discharge rate is NINO3. 4، NINO3، NINO1+ 2and least effective signals are NAO، SOI. According to the findings، it can be concluded that a significant relationship exists between discharge rate and climatic signals.

Global changes in extremes of the climatic variables that have been observed in recent decades can only be accounted anthropogenic¡ as well as natural changes. Factors are considered¡ and under enhanced greenhouse gas forcing the frequency of some of these extreme events is likely to change (IPCC¡ 2007 Alexander et al.¡ 2007). Folland et al. (2001) showed that in some regions both temperature and precipitation extremes have already shown amplified responses to changes in mean values. Extreme climatic events¡ such as heat waves¡ floods and droughts¡ can have strong impact on society and ecosystems and are thus important to study (Moberg and Jones¡ 2005). Climate change is characterized by variations of climatic variables both in mean and extremes values¡ as well as in the shape of their statistical distribution (Toreti and Desiato¡ 2008) and knowledge of climate extremes is important for everyday life and plays a critical role in the development and in the management of emergency situations. Studying climate change using climate extremes is rather complex¡ and can be tackled using a set of suitable indices describing the extremes of the climatic variables. The Expert Team on climate change detection¡ monitoring and indices¡ sponsored by WMO (World Meteorological Organization) Commission for Climatology (CCL) and the Climate Variability and Predictability project (CLIVAR)¡ an international research program started in 1995 in the framework of the World Climate Research Programme¡ has developed a set of indices (Peterson et al.¡ 2001) that represents a common guideline for regional analysis of climate. It is widely conceived that with the increase of temperature¡ the water cycling process will be accelerated¡ which will possibly result in the increase of precipitation amount and intensity. Wang et al. (2008)¡ show that many outputs from Global Climate Models (GCMs) indicate the possibility of substantial increases in the frequency and magnitude of extreme daily precipitation. eneral circulation models (GCMs) are three-dimensional mathematical models based on principles of fluid dynamics¡ thermodynamics and radiative heat transfer. These are easily capable of simulating or forecasting present-future values of various climatic parameters. Output of GCMs can be used to analyze Extreme climate. For this study high quality time series data of key climate variables (daily rainfall totals and Maximum and minimum temperature) of 27 Synoptic stations were used across Iran from a network of meteorological stations in the country. In order to get a downscaled time series using a weather generator (LARS-WG)¡ the daily precipitation output of HadCM3 GCM¡ SRES A2 and A1B scenario for 2011-2040 are estimated. The Nine selected precipitation indices of ETCCDMI[1] core climate indices are used to assess changes in precipitation extremes and monitor their trends in Iran in the standard-normal period 1961–1990 and future (2011-2030). Due to the purpose of this study¡ at first changes in extreme precipitation indices in the standard-normal period is evaluated and its results show annual maximum 1-day precipitation increased in many regions in the East of Iran. Simple measure of daily rainfall intensity (SDII)¡ annual maximum consecutive 5-day precipitation¡ annual count of days with daily precipitation greater than 10mm (R10mm)¡ annual count of days when rainfall is equal to or greater than 20 mm (R20mm) have increased in the central areas¡ regions in the north ¡ north east and southern parts of Iran. Similar results are obtained for the R25mm index. The consecutive dry days (CDD) index has generally increased across the west areas¡ southwest¡ north¡ northwest and southeast of Iran and indices of consecutive wet days (CWD) decreased in these areas. Trends of extreme precipitation indices simulated by HadCM3 SRES A2 showing increases RX1Day in North West expect west Azerbaijan Province¡ central¡ southwest¡ north east and coasts of Caspian Sea. Similar results are obtained for the R5mm index expects northeast. There are mixed changes in R10mm across Iran¡ increasing in west¡ southwest¡ coasts of Caspian Sea¡ Hormozgan and Ardebil provinces¡ East Azerbaijan¡ Zanjan and Qazvin provinces. Similar results are obtained for the R20¡ 25 mm index in northeast¡ south of Caspian Sea¡ and some parts in western and central areas. Same as HadCM3 SRES A2 pattern there are mixed changes in R10mm across the region. Positive trends are seen in part of the Isfahan¡ Markazi¡ Kuhkilue ¡ Lorestan¡ Ilam¡ Chaharmahaland Khozestan provinces and some part of Hormozgan and Kerman and some areas in north west. Similar results are obtained for the R20mm and R25mm index and in west of Yazd to north of Khozestan provinces have increased. Consecutive wet days (CWD) have increased over most of the west of Iran¡ Khorasn Razavi and Southern Khorasn provinces¡ In contrast consecutive dry days (CDD) index has generally increased in many parts of the region.
[1]. Expert Team on Climate Change Detection and Monitoring Indices

Earth has ever been exposed to environmental hazards. The hazards are continually occurring in the world in the recent years. Among them, atmospheric elements have created many human and financial losses in different regions. One of the hazards is dust events and in its severe case is dust storm. It happens more frequently in arid and semiarid regions in deserts and their surrounding areas. Dust events is a natural phenomenon occurring in regions that have large parts of arid and desert regions, devoid of vegetation cover and other surface coatings areas. Lengthy periods of drought and principle of non-interference in nature may be the cause of this phenomenon. In addition to reducing the horizontal sight and ist effects, e.g., traffic issues, it has also many environmental impacts especially on human health. Dust storms can cause transport accidents. Perhaps more importantly, dust emissions from dried lake basins introduce fine particles, salts, and chemicals into the atmosphere, with a suite of health impacts, including not only respiratory complaints, but also other serious illnesses. They can also lead to particulate levels that exceed internationally recommended levels and transport allergens including bacteria and fungi. In the recent years, dust storms in western part of Iran have caused various problems for people. The main objectives of this study are to monitor and assess the spatial and temporal distribution of the storms over the western of Iran during the last two decades. Data and case study area: The data for the analysis are including statistical data of dust (taken from Meteorological Organization) in daily basis during the 8-hour observation in period of twenty years (1989-2008). Up to 26 stations in the western portion of Iran with appropriate distribution have been selected (Arak, Ardebil, Oroomieh, Western Islamabad, Omidiyeh, Ahvaz, Ilam, Abadan, ParsAbad, Tabriz, KhorramAbad, Khorramdareh, Khoy, Dezful, Dehloran, Zanjan, Saghez, Sanandaj, Shahrekord, Qazvin, Kermanshah, Makoo, Mianeh, Hamadan, Hamadan Nozheh, Yasooj). Reviewing the existence trend in the data has been studied in two forms of spatial and temporal. To investigate the spatial trend in data Trend Analysis in ArcMap10 application has been used. To achieve this, annual and monthly frequency and dust mean in all studied stations have been examined in relation to latitude and longitude. Several methods have been proposed for the study of time trend in the panel data. It can be classified into parametric (t, trend analysis) and nonparametric (Mann-Kendall, Kendall's Tau Spearman coefficient and Sen's trend Tests) methods. Accordingly, the first step to choose an appropriate parametric and nonparametric method is awareness of the normal distribution of data. In this regard, the normality of the data is investigated based on Kolmogorov - Smirnov test (K-S test). Kendall's Tau correlation coefficients for all pairs, i=1,2,…n,(xi,yi), can be calculated using the following algorithm. In comparison pairs (xi,yi) with (xi,yi) hold for every i and j, if xi> xj and yi> yj. So, yiyj, is added one unit to ni. Then, Kendall statistic is calculated from the following equation: For n larger than 40, the central limit theorem can be used. Expected value and variance Tmk are calculated using the following equations: Where the n, is the group number which have the same rank and is the same level of data in each group. The statistic obtain statistic as the following equation, with a normal distribution. If the relation| is satisfied, ascending and descending trend is rejected at the significant level α, in which Significant level. Also if0 or 0, the trend is ascending or descending, respectively.

Results

The spatial trend in data analysis was examined using the frequency and mean of dust in all examined stations annually and monthly because of the similarity of graphs. Fixing the spatial trend in the data (annual, seasonal and monthly) can indicate that the sources of dust which enter to west part of the country are constant. Dust events have increasing trend from north to south and from West to East, increases primarily and then decreases again. Normality of data was evaluated based on Kolmogorov - Smirnov test (KS test). Because the significant rate in the raw data is less than 005/0, so we can assume H0 (the data have normal distribution) with the maximum reliability 995/0 is rejected versus H1 (data have no normal distribution). This can be concluded that there is not available sufficient evidence to accept the normality of the data and it can be accepted that the data were not normally distributed. The trends of significance in dust data were investigated by Mann Kendall test for existing stations in annual, seasonal, and monthly periods and determined that some of the stations have descending trend and others ascending. Comparison of the P-Value obtained from the tests with a critical level of 05/0 and 01/0 revealed significant at a confidence level of 95% and 99%. In this study, time displacements of the dust events in the studied stations were to be analyzed. To achieve this goal, for each station dust events were gathered monthly and then the month with the most occurrence of the events was determined for every year. For example, the Arak station, illustrated the most dust occurrence in 1989 in the fifth and seventh months (May-July) or the most incidence has been recorded in sixth month (June) in 2008 for Yasouj station. For revealing the months with the peak occurrence of dust in each station, time series for each station were created during the period 1989 to 2008. Plotting the corresponding number for each month against the time of occurrence for each station created scatter plot. In this plot, line fitting with equation of the first degree revealed how is the change trend of dust occurrence. Significant results of this research, for determining the temporal changes for each station showed thatthe month with the maximum dust occurrence has been shifted towards warm or cold months over time. The review divided the studied stations into three groups. The first group indicates the maximum displacement of maximum dust to the warm months,The second group represents the displacement less than a month for the maximum dust.Finally, the third group represents displacement to the colder months.

Conclusion

Analyzing the spatial data trend indicates that the dust data in the studied stations have a north - south trend with linear increase while along the west to east it follows second degree polynomial function (curve with an arc). This indicates that frequency of dust is increasing from west to east and then it has been observedto reduce in the east of the region. It seems that the altitude exposure along the north to south particularly, Zagros Mountains on the path of dust progress has been caused this situation. Constant behavior of the spatial trend for dust frequency in monthly, seasonal and annual scales indicate no change in the dust source entry to the studied region. In other words, the origin and time arrival of dust to studied region have particular order. Time trend of the dust frequency was reviewed in three monthly, quarterly, and annual scales. Significant ascending trend (with 95% confidence level) were observed at Arak, Oroomieh, Western Islamabad, Omidiyeh, Tabriz, Khorramabad, and Sanandaj stations in both monthly and seasonal time scales. However, only two stations (Arak and Khorramabad) have significant ascending trend in an annual scale. In the two stations, Khorramdareh and Qazvinwere also observed in descending trend in dust occurrence frequency with a confidence level of 95% in all time scales. It was found that the maximum frequency of dust occurrence in some stations (Yasooj, Qazvin, Sanandaj, Khorram Abad and Arak) have been shifted to the warm months and in others (Ardebil, Oroomieh, Abadan, Ahvaz, ParsAbad, Tabriz, Khorramdareh, Khoy, Dezful, Dehloran, Zanjan, Saghez, Shahrekord, Kermanshah, and Hamadan) to cold months. In some stations (Ilam, Omidiyeh, Makoo, Western Islamabad, and Mianeh) there was no significant movement.

Drought is one of the atmospheric events that causes great losses and is inevitable in most areas if the world Since soil moisture, stream fiow, and reservoir storge reflect precipitation anamolies, This study aims at a spatial analysis of drought in three Iranian provinces namely North khorasan, Razavi khorasan and South khorasan to quantify precipitation anamolies by means of SPI in 3, 6, 12, and 24 month scale. Monthly precipitation data of 12 long period stations during 1966-2005 were used which was taken from Iranian Meteorological Organization. Geostatistical methods were also applied to prepare spatial distribution maps. The results of the study showed that in 3 and 6 – month- scale period most – severe droughts are are frequent in the Razavi khorasan and North khorasan is affected by severe droughts in the same period. However, in 12 and 24 – month– scale period most serious droughts are frequent in South Khorasan and Western Razavi Khorasan experiences severe droughts. SPI values showed that most droughts happened in the first decade (1966- 1975) and the fourth decade (1996- 2005) as well and 1973 and 2001 have experienced the most serious drought.

Atmospheric circulation patterns are responsible for drought and flood occurrences around the globe; specifically in moderate mid latitude climates. While some circulation patterns are responsible for wet spells and floods as well، the drought events can be attributed to some other circulation patterns. Therefore، identification and distinction of dry/wet producing patterns and the geographical extent of Iran that they may affect is very crucial for many environmental planning. In the present study that aims to identify dry and wet producing atmospheric circulation patterns for Iran، the daily mean sea level pressure and 500 H. pa geopotential height corresponding to 1950-2006 period was retrieved from NCEP/NCAR and used as input variables for Principle Component Analysis coupled with Cluster Analysis. By this procedure all studied days were grouped into 18 clusters and their associated composite maps for both levels were drown and considered as the circulation patterns. To assess the relationship between the identified atmospheric circulation patterns and daily precipitation over Iran the Performance Index (PI) which is a conditional probability index was computed for 54 stations and used in the analysis. This index shows the probability of precipitation occurrence conditioned on the occurrence of a given circulation pattern. The result shows that circulation patterns of CP2، CP3، CP5، CP6، CP7، CP9 and CP10 are dry circulation patterns while CP1، CP4 and CP12 are considered as wet patterns in Iran.

Atmospheric circulation patterns play the main role in the natural phenomenon occurring on the earth, especially in temperate regions. Some atmospheric circulation patterns cause wet periods and others cause low water and dried periods. Thus, because the annual occurrence of drought and wet events result from the general circulation of the atmosphere, recognizing atmospheric circulation patterns are explained, to some extent, for the possibility of evaluating these phenomena before occurance. Studies show that the floods and droughts phenomenan are influenced by atmospheric circulation patterns. Given the close relationship between the patterns and climatic elements, we can also attribute the extreme climatic events, such as floods and droughts, and dried and wet periods, to changes in atmospheric circulation patterns. In this study, from average daily data balance of 500 and the sea level pressure over the period 1960 to 2008 at two degrees intersection of the reconstructed data setshave been used. The selected range covers all systems affecting the area under study during the year. This range consists of 408 cells from 20 to 60 degrees in north latitude and 10 to 70 degrees in east longitude. Total daily rainfall data from selected synoptic stations over the statistical period 1960-2008 were used to assess the role of the patterns in rainfall. Many climate scientists dealing with variables with different scale or large volumes of data employ reduction variable and data strategy by principal component analysis (PCA), (Gadyial, S. and R. N. Lyengar 1980, Kalkstein. S. et al. 1998). Factor analysis is a statistical technique that establishs a especial relationship among a large number of variables that are seemingly unrelated. It is under a hypothetical model and gathers all the variables in the similar groups. This method retains significant and main components in the same groups and reduce the variables. One of the results of factor analysis is to reduce data dimension. Computational steps of the main component analysis is as follows: a) The data and variables Selection. b) The second stage of a data matrix p × n formation where n is the number of days and p is the number of variables. In the third stage since the selected meteorological variables of the unit are different (For example, C, hPa, meters per second, and so on), a correlation matrix was used as input for the main component analysis. Data correlation matrix are calculated according to the following formula. The fourth step is used to determine the number of factors by Catel test. Loadings matrix was calculated in the fifth stage. Loadings show the relationship between the factors and the primary variables. The relationship between atmospheric circulation patterns and rainfall To evaluate the relationship between atmospheric circulation patterns and rainfall, the following index is applied. This index defines the conditional probability of rainfall occurnece and rainfall intensity in a circulation pattern. The index defines a measure of the relative share of the pattern rainfall in total. Where ni is the number of days with i patterns and Ri is the total rainfall during that days and n is the number of days in the period of the study. If PI<1. Or even much smaller than the unit, the weather or type pattern i does not greatly affect the area rainfall. Thus, an increase in the frequency of occurrence of such a pattern, reduces rainfall and subsequently, causes drought in a region. If the PI in the statistical method is greater than the unit, then chance of rain (probability of precipitation) also increase and wet periods will be prevailed. For example, precipitation takes place when weather is wet and there is an acsending factor, these conditions are provided by atmospheric circulation patterns. In this study, using PCA and clustering, eighteen circulation patterns according to the sea levelpressure and 500 hPa level atmospheric condition have been identified over the study area. The results of this study show that there are significant differences in the arrangement of patterns, the weather type frequency and the way they move towards the study region. The PI index is a appropriate criterion to evaluate the Conditional probability of rainfall and rainfall intensity. If the PI index calculated for a wheather type much smaller than unit, wheather type does not play a role in precipitation of that station or region. Therefore, an increase in the frequency of occurrence of such a pattern in a period reduces rainfall and makes the drought events in that region. Due to the PI index and the annual frequency distribution of atmospheric circulation patterns, the results can be summarized as follows. Atmospheric circulation patterns of CP1, CP4, CP5,CP12, and CP15 are part of the patterns leading to heavy and pervasive precipitation. Atmospheric circulation patterns of CP7, CP13, CP16, CP17, and CP18 are part of the patterns leading to moderate precipitation. Atmospheric circulation patterns of CP2, CP8, CP9, C 10, and CP11 are part of the patterns leading to drought, Atmospheric circulation patterns of CP3, CP6, and CP14 are part of the patterns leading to drought. In terms of the annual frequency distribution, atmospheric circulation patterns of CP3, CP5, CP13, and CP15 are active in all seasons of the year, atmospheric circulation patterns of CP2, CP6, and CP10 are active in summer, atmospheric circulation patterns of CP1, CP8, CP9, CP11, CP12, CP14, CP16, C 17, and CP18 in winter, spring and fall and atmospheric circulation patterns of CP7 is active in the spring and fall.

Drought is one of the devastating hazards of human history. It can occur in all times and any places. Drought is a regional event that its occurrence in many world zones cannot be avoided. It is more important than other natural misfortunes due to loss of life and property and social factors. This event is more display in arid zones such as Iran for the sake of regional characteristics like small precipitation, intensity in oscillations of rainfall in different years, inappropriate distribution of the rainfall in a period of years and the great fluctuations inplace and time of the rainfall. For this reason this research has studied the severity and spatial organization of these droughts over the country. Important parameters that influences drought are temperature and precipitation. In this research, in order to make a spatial analysis of the long duration droughts in Iran, the precipitation data were used. For this reason the monthly precipitation of 70 long period stations during 1976- 2005 were obtained from the Meteorological Organization of Iran. Researchers all over the world offer different methods for study of the droughts. One of these is Standardized Precipitation Index (SPI). This method was developed by McKee, Doesken, and Kleist (1993) to analyze the impact of precipitation deficit on groundwater, reservoir storage, soil moisture, snowpack, and stream flow in different time scales for defining and monitoring the phenomenon. These time scales reflect the impact of drought on the availability of different water resources. Soil moisture conditions respond to precipitation anomalies in a relatively short time scale. Groundwater, stream flow, and reservoir storage reflect the longer-period precipitation anomalies. For these reasons, McKee et al. (1993) originally calculated the SPI for 3, 6, 12, 24, and 48 months time scales. The SPI computes the temporal frequency and anomalies of droughts. It can also be used to determine periods of anomalously wet events. The SPI is recognized as a better quality model compared to other models. The advantage of this index is that allows the analyzer to determine the number of occurrences of droughts in different stages of time. In the other words, it is, because of the non distance of this index that we could use of it to compare information of different zones and make carefully anextent of drought maps. The other advantage of this index is that it is measuring the drought function of probable density so that you can perform more analysis about that. The study has used the SPI method for a period of12 and 24 months during the 1976-2005. The spatial distribution of the drought was interpolatedvia ordinary kringingin the ArcGIS environment. In this study SPI time series were calculated in time scales of 12 and 24 months. Then, the frequency and spatial distribution of droughts were prepared and analyzed using the Geostatistics methods (Ordinary Kringing). These results have showed that the intensive 12- months period droughts were frequent in the east, southwest, central, and western parts of the country (for example Birjand Station 8%, Ramhormoze Station 6% Ilam Station 5% and Sirjan Station 5%), while the southeast and northern parts experienced moderate and weak droughts. But the 24- months droughts were intensive in the eastern parts of the country(for example, Tabass Station 6%,Ramhormoze Station 6%,Iranshahr Station 6%, and Sirjan Station 5%). This means that the longer droughts are common in the east, where they affect the underground water resources. Drought is one of the devastating hazards inhuman histories. The occurrence of the phenomenon is possible in any time and places. Iran as an arid country with fragile climate is prone to frequent droughts. For this reason this research has studied the severity and spatial organization of these droughts over the country. The study has used SPI method with the 12 and 24 months scales during the 1976-2005 periods. The spatial distribution of the drought was performed via Ordinary Kringingin the Arc GIS software. The results have indicated that the 12-month period droughts were intensive in the east, southwest, central, and western parts of the country while the southeast and northern parts experienced moderate and weak droughts. But, the 24- months scale droughts were intensive on the eastern parts of the country. This indicates that the longer droughts are common in the east, where they affect the underground water resources.

Agricultural cooperatives in the county Khodabandeh decade have seen dramatic expansion in 1370 and 1380. So that until the year 1388, about 340 agricultural cooperatives have been established in this county. However, passive agricultural cooperatives in the Khodabandeh County have risen %10. This shows that, this economic sector in the field of agricultural activities with structural- functional problems is a face. In this paper; using a descriptive-analytical Method, the causes of the increase agricultural cooperatives has been studied. In this context, the required data is collected through field studies and library. Statistical research, including 34 agricultural cooperative disabled with 263 members is. Of these, 93 of whom are random sampling, were selected for the first and second questionnaires. And from 93, 52 of whom are undergraduate sample, the questionnaires were selected as the third and fourth. Also, to explain the data, the Delphi analysis method used is. In this way, to build consensus among members about the subject, in the course of successive questionnaires were distributed along with the feedback control of their severity. The results show that internal problems such as cooperatives, management weaknesses, skills, tastes differ, misplaced expectations of cooperation and some deficiencies in infrastructure of services and planning and policy making by government agencies, the main cause of decline in activity of Cooperatives and they are the result of deactivation. In this context, granting facilities to cooperatives on employment, improving agricultural infrastructure in the villages, providing credit and retail credit for cooperatives, and development of professional and public education for them, the revival of cooperatives will be disabled.