جستجوی مقالات مرتبط با کلیدواژه "تحلیل روند" در نشریات گروه "علوم پایه"

In this study, the trend of mortality rate from opioid abuse in different regions of the world from 1990 to 2019 was investigated based on socio-demographic index at three levels (1. low/low middle, 2. middle, 3. high/high middle) worldwide, using data from the Global Burden of Disease. Results in general, at the low, low middle, middle and high middle socio-demographic index levels during these 30 years have seen a downward trend in mortality rates, although countries with low socio-demographic indicators have experienced a slight increase. In countries with high socio-demographic level, there is a significant upward trend in the rate from opioid abuse between the years. During these 30 years, the average annual changes (APC) of countries with high/high middle social-demographic index levels of about 4 per 100,000 people and in countries with low/ low middle and middle levels of this index were estimated to be -0.5 and -2.5 per 100,000, respectively. In this study, Joinpoint Regression Analysis was used.

Precipitation fluctuation is a critical factor in understanding climate, as it has far-reaching impacts on the environment, economy, and society. Excessive or insufficient precipitation can result in severe floods and droughts, causing significant consequences for both nature and humanity. For this reason, it is vital to understand the variability, behavioral changes, and extreme precipitation levels to successfully manage industries like agriculture, water resources, urban planning, and transportation. In this study, to investigate the extreme values of precipitation, the trends of four precipitation indices of 44 synoptic stations in Iran were calculated and compared for two recent climate normal periods of 1981-2010 and 1991-2020. Four precipitation indices, specifically PRCPTOT95, PRCPTOT99, R10MM, and R20MM, were investigated after undergoing quality control and data homogenization. An evaluation of the trend of heavy precipitation in two periods demonstrated a decrease in the eastern and northwestern parts of the country, while an increase was observed in the Zagros and northern regions. The increasing trend in the second period has become more significant in the northern part of the country, while the decreasing trend in the western part has decreased in the second period. The analysis of mean precipitation indices in two periods showed that heavy precipitation had increased in the second period on the coasts of the Caspian Sea, Zagros Mountains, and southern parts and decreased in the east of Iran.

To assess thermal comfort of residences, several different factors as meteorological, physiological, and socio-cultural, should be considered. The integrated effect of these variables on thermal stress can be obtained and evaluated using thermal comfort indices. Thermal comfort as a bio-meteorological index is of special importance. The purpose of this research is to analyze the seasonality and trend of heat stress in Iran in the period from 1981 to 2020. In this research, the Universal Thermal Climate Index (UTCI) index as a common thermal index was evaluated for outdoor thermal comfort, using ERA5 dataset. ERA5 is the fifth generation ECMWF reanalysis data for the global climate and weather for the past 4 to 7 decades. The ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave, and land-surface quantities. An uncertainty estimate is evaluated by an underlying 10-member ensemble at three-hour intervals. Such uncertainty estimates are closely related to the information content of the available observing system which has improved considerably over time. They also indicate flow-dependent sensitive areas (Hersbach et al., 2020). Also, root mean square error (RMSE), Percent bias (PBIAS), Nash–Sutcliffe model efficiency coefficient (NSE), and Root Mean Standard Deviation Ratio (RSR) metrics were used to evaluate the quality of ERA5 dataset.The seasonal variability of the UTCI index shows that this index has significant regional heterogeneity in Iran. The increase in UTCI from the north to the south of Iran leads to an increase in thermal stress. The spatial distribution of areas that do not have thermal stress during the hot period of the year are mainly consistent with the altitudes. During the cold seasons of the year, areas with elevations of more than 3,000 meters in Iran have moderate cold stress. The investigation of the trend of thermal stress during the last four decades, which was analyzed with the modified Mann-Kendall test, shows that the UTCI in Iran has a dominant increasing trend. The UTCI index shows an increasing trend in the spring and autumn seasons by 100%, and in the winter and summer seasons at 99.83 and 99.75% of the country, respectively. The maximum significant increasing trend of the index at the level of 0.05 was achieved in the spring. In the same way, the highest value of Sen's slope estimator test of the area-averaged trend is also seen with the value of 0.52 oC in this season in the study period. The results of this study for climatology and the trend of the UTCI index in Iran show that: 1- There is a close relationship between heat and cold stresses in Iran and topography, but this relationship is not a linear; 2- Along with global warming, the UTCI index in Iran during the years 1981-2020 has shown an increasing trend; 3- In general, areas with UTCI cold stress in the country are decreasing and areas with heat stress are increasing; 4- One of the key findings in this study is the significant increase in trend of the UTCI index in the spring season.

Different parts of the climate system as well as precipitation are subject to the global warming and climate change. The aim of present study is monitoring different aspects of changes and trends in precipitation over Iran, using MERRA2 reanalysis data from 1990 to 2020 based on 7 indices including Maximum 1-day precipitation (Rx1day), Simple precipitation intensity index (SDII), Maximum length of dry spell (CDD), Maximum length of wet spell (CWD), Annual count of days when PRCP ≥ 10mm (Rx10mm), Annual count of days when PRCP ≥ 1 mm (Rx1mm), and Annual total precipitation on wet days (PRCPTOT). MERRA2 is the second generation of Modern-Era Retrospective Analysis for Research and Applications (MERRA) by NASA’s GMAO (National Aeronautics and Space Administration, Global Modeling and Assimilation Office), with spatial resolution of 0.5o (approximately 50 kilometers) and temporal resolution up to hourly data. Correlation analysis between MERRA2 and observation data of 48 weather stations indicates acceptable results all over the country especially for the North, the North West and the Western parts. The highest values of R2 was 0.94 calculated for the wet regions of the North and Northwest, the least values were 0.63 for the arid regions of the South and the Central parts of Iran. Mann-Kendall non-parametric test was used for trend analysis and detection. Mann-Kendall test uses time series data for consistently increasing or decreasing trends in a variable and can works with all statistical distributions. The results show a decreasing trend on 0.95 significance level in 3 indices including PRCPTOT, Rx1day, Rx10mm, in the West and Northwest of Iran. Previous researches confirmed and reported the similar results. In the North East part of the country (parts of the Khorasan-e-Razavi, Semnan and Golestan provinces) positive increasing trends was detected. Considering this distinct regional discrepancy in calculated trends (trends in indices), it is necessary to focus on the effects of possible changes in pressure and synoptic systems on the precipitation changes over Iran. For RX10mm increasing trends was detected for the South and South East of the country. Due to the high absolute humidity in these regions, if condition is suitable for convection and air ascending, Sudan low pressure and Indian monsoon make possible high amount of intense convective rainfall origin from Indian ocean. Overall, MERRA2 shows an underestimate for the region of highest rainfall (North of the country) and an overestimate for arid regions. As a conclusion, based on the results of this study it is necessary to have a distinct precise plane not only for managing the decreasing trends in precipitation and water deficits, but also for mitigating impacts of intense rainfall and flash floods. Further studies needed to determine simultaneous (combined) effects of precipitation and temperature changes in other to manag water resources.

Given the impact that climate change has on the planet, which is currently one of the most important challenges facing the international community, efforts to understand climate change events as much as possible are certain. The purpose of this study is to detect and analyze the trend of climate change, especially climatic elements of precipitation and temperature in the city of Sari in Mazandaran province. 

The method of this study was to analyze the statistical process of climatic factors of precipitation and temperature at 4 stations (Sari, Amol, Gharakhil and Babolsar) in the period of 20 and 30 years (1987-2017) using non-parametric Mann-Kendall test and climate sensing software of the Meteorological Organization of Iran. Also, to determine the location of climate change more precisely, Arc statistics was used in Arc GIS software.

The Kendall test showed that 3 stations (Gharakhil, Babolsar and Sari) had a significant leakage trend in terms of temperature rise over the 30-year period with U + (3.87, 3.80, 1.75). But it does not show significant trends in precipitation. The Climate Change Detector also emphasizes that the temperature rise at these stations is tangible and this has led to climate change in this area. Earth statistic test also revealed that most climate change occurred in the area of Sari and changed from a mild to moderate state.

The area under study has undergone severe climate change, and this climate change directly affects the water balance of the region, increasing water requirements, decreasing soil moisture, vegetation density, rangeland capacity and agricultural products, and considering that groundwater resources are the most important source of supply Water is needed in different parts of the region, it also reduces the level of water table and reduces the quality of groundwater resources. In addition, this means reducing the frequency of precipitation, increasing rainfall, soil erosion and natural resources.

Climate change is exacerbated by natural factors such as aridity and drought or human activities. Identifying and revealing the changes in each factor and what cause them is considered the first step in the study of the process of climatic elements. The trend analysis might be due to natural changes, such as drought or human activities e.g. increasing greenhouse gas emissions. However the trend in the climatic factors of each area might be normal, its continuity in the coming years may have more significant effects on the economic and social components. Climate change in a region can be detected by investigating the changes in the average rainfall and temperature. This research was carried out in order to identify the time variation of climate parameters (temperature and precipitation) in decuple agroecology regions of Iran.

For this study, data on temperature and precipitation variables were extracted annually from all provinces of the country during the period 1985-2015 from the Meteorological Organization of Iran. Since the distribution of a number of climatic parameters such as temperature and precipitation climatic series is not normal, the non-parametric Mann-Kendall method was used for analyzing their distribution.  To determine the level of significance in variables and to determine the trend of annual changes, Mann-Kendall test was used with XLSTAT extension software.

The results showed that temperature variable in Central, Northwest, Caspian Coastal Plain, Khuzestan, Central Zagros, Arid Southern, Khorasan, Southern Coastal Plain Arid Central zones had an upward trend and no trend in Southern Zagros zone. Precipitation variable was decreasing in Khuzestan and Khorasan. Precipitation variables in Central, Northwest, Caspian Coastal Plain, Central Zagros, Arid South, Arid Southern, Arid Central and Central Zagros zones were not trendy. The increase in temperature will lead to a significant increase in the annual evapotranspiration rate (which is already higher than annual precipitation in most parts of Iran). The Intergovernmental Panel on Climate Change regards this issue as a serious challenge to arid and low rainfall regions, including Iran, and as a consequence, predicts that the production of strategic products in Iran will decrease compared to the current level of production. The vastness of Iran, along with its geographic location, and the location of heights, prevent the region from fully absorbing the atmospheric humidity. The existence of such conditions causes an inhomogeneity in the amount and pattern of precipitation that has crystallized in the temporal and spatial behavior of the climatic factors. This could be a warning to a country like Iran that is heavily in need of water, and will face water scarcity in the future.

The results of the research showed that the mean annual temperature significantly increased in all stations. However, there is no particular trend for the rainfall situation Due to the arid and semi-arid climate of Iran; Iran is one of the countries facing water shortage. Obviously, this shortage will greatly affect agricultural production.

Investigation of the future trend of changes in the density and health of the vegetation due to climate and land use/land cover changes can be useful in ecological and environmental studies using time series data especially in dry and semiarid brittle ecosystems. Time series analysis is a powerful tool for investigating the trends of natural phenomena in the past and present. The Satellite Time Series provides the most appropriate data for analysing the trend of changes in natural and human phenomena and predicting for the future. A time series is the collection of statistical data collected at regular intervals. Determining the trend (increasing, decreasing and unchanged) of the vegetation can be one of the ways to help manage vegetation monitoring. In this regard, the use of statistical tests to determine the trend of time series data is essential. There are different methods for determining the process, which are divided into two sets of parametric and nonparametric methods. Since satellite imagery is one of the best time series illustrations, the use of these data in trend studies is fruitful. Vegetation indices are used to monitor and evaluate vegetation dynamics using satellite imagery. NDVI is the most famous useful in plant monitoring. The NDVI, is used as a useful indicator of photosynthesis capacity identification, usually used to examine environmental and ecological changes. Therefore, remote sensing through the NDVI satellite index can measure surface vegetation changes due to the strong correlation between the vegetation and this index. The NDVI is also reliable for identifying vegetation stress because, as a result of degradation of vegetation in the land, vegetation characteristics such as health, density are majorly changed Materials and methods Monthly MODIS NDVI times series images from the MOD13A3 series, were collected from the site of NASA from 2003 to 2014 (144 images). Then the images from Gavkhuni basin have been extracted to determine the trend of vegetation changes. Mann-Kendall test was presented based on the significance of the Tau Kendall correlation coefficient (τ) and then developed. Correlation coefficient measures the relationship between two series of variables to determine if the first variable increases with increasing the second variable, or decreases or the patterns of change are not relate together. This method is widely used to handle time series. In general, Mann-Kendall statistical test can be used to determine the uniform trends of ubnormal distribution data based on the ranking. Given that the Mann-Kendall test, in addition to the trend, also specifies the type of trend occurring, this model does not require the input of normal data. In the test, for time series data trends, positive values indicating incremental trends and negative Z values represent decreasing trends. Results Vegetation fluctuations of mean monthly MODIS NDVI time series images of Gavkhoni basin from 2003 to 2014 were presented. The maximum vegetation cover is observed in spring months. This increase reached its maximum during the course of the study in 2007, and then reached its maximum four months later and then sharply declined in 2008. In 2009, vegetation cover in Gavkhuni basin is relatively modest. In fallowing, the fluctuations are almost the same, but declined sharply in 2014. In addition, the highest vegetation density is observed in the western and central regions of Gavkhuni basin. Also, this figure shows that vegetation density is high in 2003-2006 and has declined significantly by 2014. Accordingly, the vegetation cover increased in January 2003 through January, a dramatic drop in February, a slight decrease in March to May, a modest increase in June to July, a slight increase in the months of July to September, in October And November has been a slight decrease, and December has seen an increase in vegetation. The trend of long-term vegetation changes in Gavkhuni basin based on 144 images of the monthly MODIS-NDVIwere implemented in the Idrisi Tersset software. At first 144 time series images were converted into TSF file format. The resulting trend map indicates that the vegetation trend is incremental with a value of τ equal to 0.68 to a decreasing trend with the value of τ equal to -0.65. Accordingly, the trend of increasing vegetation is more dispersed in the north-eastern and central to west parts of the basin, and slightly to the south of Gavkhuni basin. In addition, the largest decline in vegetation occurs in the central regions of the east and south of Gavkhuni basin. This trend is evident in the northern and western basins as well as in the south of the basin. In addition, decreasing trend of vegetation is more concentrated in areas of basin which referring to the use/land cover map are aquaculture. This trend indicates a sharp decrease in the rain-fed agriculture. Referring to the land use/land cover map, the vegetation cover of the Gavkhuni wetland during the study period has also been subject to decreasing or unchanged trend. The vegetation of the rocky areas of the north-east of the basin has also increased marginally. Accordingly, the most extensive areas indicates unchanged trend of vegetation in Gavkhuni basin. The results showed that the largest decline in vegetation was observed in 2007, when the catchment area was faced with drought at this time. Also, the annual average vegetation map in 2014 with the least amount of vegetation density has been encountered. Due to the fluctuation of vegetation, the need for serious attention of planners is required because it can be said that vegetation as the representative of environmental health also reflects the characteristics effective biophysics in growth, such as adequate water, undiluted and nutritious soil, etc., provide both the protection of wildlife and soil conservation against erosion. Also, since vegetation cover has declined from 2003 to 2014 in the months of April and May (when is the beginning of the growth season in the Gavkhuni basin), it indicates a crisis in agriculture in the Gavkhuni basin. The regional variations of vegetation in Gavkhuni basin from 2003 to 2014 through the time series images of MODIS NDVI was determined using non-parametric Mann-Kendall Tau and contextual tests, and areas with increasing, decreasing and unchanged vegetation cover were determined. The results showed that the extent of the vegetation variation trend as well as the extent of the decreasing trend in the Contextual Mann-Kendall method was more than Tau Mann-Kendall, and the trend in most of the area remained unchanged, which only indicates whether vegetation is present in this area or not. This case is achievable by comparing the trend map with land use / land cover map in 2014 or following years. In addition, it was revealed that the decreasing trend with the sever vegetation decline has occurred in the central regions of the Gavkhuni basin and along the Zayandehrud River and also in the urban areas, which can indicate the high urban growth and land use /land cover change from the vegetation to the construction site in this basin. Accordingly, a sharp decreasing trend was observed in the northern and western regions as well as in the south of the basin, which with referring to the land use /land cover maps and type /vegetation maps, these areas are highest proportion of rangeland vegetation and fertile farming along the Zayanderroud River. These lands affected by land cover/land use and have been severely subjected to land degradation due to the dryness of Zayandehrud Rive in recent years. This urged urgent measures to prevent land degradation. In addition, since the highest reduction in temporal monitoring in the Gavkhuni basin has been observed in the months of April to June, and these months are growth season and cultivation in the Gavkhuni basin, this necessitates a serious actions to mitigate the risks. Also, the study of vegetation trends showed that during the study years, saline lands in the Gavkhuni basin increased and the agricultural land was significantly reduced.

In recent decades, air quality change and its risks are correlated with the expansion of urban and industrial areas and other land-use changes. One of the important effects of land use/cover changes (LUCC) is wind erosion and as a result, an increase in particulate matter (PM) concentration in residential areas. For this reason, the effects of LUCC on PM concentration in Tehran’s airshed was studied. Material and methods: Data on LUCC and landscape metrics were studied in the years 1985, 2000 and 2014. Then, the relationship between LUCC and PM concentration in Tehran was investigated by trend analysis methods. To find the most important wind directions with strong effects on Tehran’s air quality, conditional probability function (CPF) and directional relative strength (DRS) were used. LUCC results showed that the area of agricultural land-use has been expanded from 1985 to 2000, yet decreased from 2000 to 2014. The trend was vice versa for barren lands during the mentioned time periods. In addition, the urban area has increased in the whole period. The landscape metric results showed that landscape patches became smaller and the landscape has been fragmented. The results of the PM10 concentration trend analysis revealed that it has been increased dramatically since 2007. Comparison of the average concentration of PM10 before and after 2007 showed a significant difference. The results of CPF and DRS illustrated that no specific wind direction was detected before 2007, but afterwards both increased in specific directions (south to west), which is compatible with most LUCC and fragmented areas in these directions. Our results showed that specific wind directions may lead to an increase in the PM10 concentration which is compatible with LUCC directions. Therefore, LUCC could be a significant reason for the increase in PM10 concentration in Tehran.

The aim of this article is the examination of trend of wind speed changes in Zabol synoptic station by using of nonparametric ways. Mann-kendall and Sens Estimators slope two tests which are the commonest nonparametric ways used for trend analysis in month scale. These two upper tests on date month speed wind and maximum wind and maximum win frequency in mention station during 1963-2014 the period applied. The results showed that two ways in all months. In%95 confidence level were nearly in the same. Besides Mann-Kendall test has not shown special trend while in the ways of Sens Estimators slope has shown special trend. the results of study has shown non-trend in maximum wind speed in Sens Estimators slope in%95 confidence level and%99. While in Mann-Kendall test during August confidence level was different. The results of speed changes in Zabol synoptic station during 1963-2014 which the 120 days winds increased were increasingly and positive which this increase in the wind maximum speed were sensible than average wind speed. The results of this study shows that there is significance increasingly trend in both average quantity speed wind and maximum wind.

Groundwater has long been the most trusted water source of human beings that is used in the agricultural and drinking sectors. In order to be aware of water condition and its optimized management, it is necessary to carefully examine groundwater level fluctuations and groundwater quality that are influenced by different factors. While carefully monitoring the fluctuations and quality of groundwater, we can have reliable planning in water supply and source management. Therefore, this study aims to determine the trend of changes in quality parameters of groundwater of Shabestar plain in order to understand the quality of groundwater and to specify its application.
Material and In this study, in order to understand the quality of Shabestar plain’s groundwater and to specify its application, the chemical results of 15 qualitative variables of groundwater samples belonging to 13 stations located in the study area during the years 1382-1999 were compared while using non-parametric Mann-Kendall test, and then effect of the first-order autocorrelation was eliminated from the data series. Slope of the trend line was calculated by the age method. The qualitative parameters in this study are total anions, total cations, EC, SAR, CL--, , Ca2, TH, Ph, TDS, , Na%, Na, Mg2 and K that are measured two times every year.
The results show that time series related to qualitative variables has ascending trend in most of stations (except Ali-shah station, Sefid-kamar station and low water months of Shabestar plain). They show positively significant trend at 5% level with 36 series (18%) in months of high level of water and with 17 series (9%) in months of low level of water. Furthermore, “Ali-shah” and “Sefid-kamar” stations have the highest rank in the highest negative trend in two months with high- and low- levels of water. The comparison of stations suggests that quality of Shabestar plain’s groundwater has critical condition in southern part of plain. Generally we can conclude that the quality of groundwater in the study area has decreased over time. The results achieved from investigating the values of time series correlation coefficients of qualitative variables with normal annual precipitation in the periods (1382-1388) show that none of the qualitative variables have a special significance at the 5% level with the amount of annual precipitation. The overall result of this section suggests the lack of relationship between annual precipitation and qualitative variables, while ground water level has almost steadily dropped with quality variables during common statistical years (1383-1391). Also, climatic variables such as rainfall, temperature and evaporation were not identified as factors in changing the qualitative characteristics of Shabestar plain’s groundwater and we come to this conclusion that their adverse changes were influenced by human factors.
According to achieved results, we can say that if the current condition continues, it is not possible to steadily use groundwater source in Shabestar plain. Water quality will be negatively affected by the lack of treatment of urban and industrial wastewater, the release of agricultural wastes at the plains, adjacency to Urmia Lake, and the development of salt marsh.

In this study, data is used to identify trend of annual and seasonal dusty days in Tabriz Synoptic Station. First, to provide a preliminary view of the climatology of dust in the Tabriz City, yearly and monthly changes of average number of days with dust is analyzed by using charts. Then, to review the trend of occurrence of these phenomenon two non-parametric statistical methods of Mann-Kendall and Sen’s Estimator was selected. The results showed that because of input data nature, the Mann-Kendall and Sen’s Estimator methods have very good performance for analyzing of dust phenomena trend. Although the climatic condition of Tabriz region is not Favorable for dust production, but observation frequency of dusts in this region has significant increased trend. And the seasonal changes in dust frequency were shown that dust observations in all seasons except winter increases at 95% or 99% confidence level. Also the use of rank test of Mann-Kendall clear that frequency of dusty days has increased in Tabriz since 1956.

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.

In different regions, precipitation takes place with different persistencies and every persistency supplies a share of rainfall days and precipitation. Therefore, the importance of rainfall persistence could be evaluated in all places. Iran is located in Mid-Latitude of an arid region, in which the mean rainfall is 250 mm and it has dramatic tempo-spatial changes. Rainfalls with short persistence are of characteristics of arid regions and it is also tangible in Iran. However, Iran’s rainfalls persistence ranges from 1 to 45 days and have dramatic tempo-spatial changes, but the maximum amount and days of rainfalls are supplied by rainfalls with short persistency. So, the phenomenon of rainfalls with long persistency is considered as an extreme event which has extreme variability. As the persistence of precipitations increases, their role in generating Iran’s rainfall days decreases severely in such a way that the maximum rainfall days of Iran is supplied by one-day rainfalls. However, the share of one-day rainfalls in the supply of precipitation days of Iran’s Western half is more accentuated. In contrast, the increase in the persistence of rainfalls does not have an identical role in decreasing the supply of Iran’s precipitation. As the persistence of precipitations increases, the share of precipitation in the Central and Southwestern Iran decrease severely, but in Western and Northern Iran, vice versa is the case. In some heavy precipitation regions of Iran’s Western half, the decrease of precipitation persistence is associated with the decrease of the share of precipitation supply and in other regions; the decrease of the share of precipitation supply is gradual. Therefore, in every space, some of the persistent rainfalls supply the great share of precipitation days and precipitation amount and are considered important. However, it is possible that this precipitation persistency do not have such importance in those areas. Every kind of variability and change in the role of precipitation persistence in every space will be considerable. Spatial changes of one-day precipitation’s share in the supply of Iran’s precipitation days and precipitation amount could be evaluated from this angle. To evaluate the changes in one-day precipitation’ share in the supply of precipitation days and precipitation amount, the daily observations of precipitations in 1437 stations of throughout Iran was used. Drawing upon Kriging method, the observations of the stations were generalized in a regular network by 15*15 km dimensions and Iran’s isotheral digital maps were developed from 1961/03/21 till 2004/12/30. These digital maps include daily time series (15991 days) of precipitation amount for 7187 cells. Precipitation persistence in the time series of every cell was evaluated and in addition to that, their share in the supply of precipitation days and precipitation amount of each cell were also calculated. Then, the most important persistence of Iran’s precipitations (one-day persistence) was identified and their importance was investigated. Yearly and monthly time series of one-day precipitation’ share in the supply of precipitation days and precipitation amount were entered in a trend analysis for evaluating and understanding its changes and its results were considered. In spatial analyses including identification of climatologically variables trend, more confident way is that firstly, spatial interpolation is done; then, an appropriate trend test is performed on the data on the nodes. The results obtained from such analyses not only enjoy higher degree of spatial attribution, but based on closeness principle, spatial order of points themselves provide intuitional reason for accepting or rejecting trend analysis. One-day precipitations supply more share of Iran’s precipitation days compared to remaining precipitation persistencies in such a manner that it may be noted that in all regions of Iran, the frequency of one-day precipitations is maximum compared to remaining precipitation persistence. In contrast, Iran’s precipitation is provided by different persistencies and the share of one-day precipitations in precipitation supply is maximum only in Western half (Central and Southeastern parts). However, although one-day precipitations do not have much importance throughout Iran, the degree of their importance in Eastern half is maximum compared to Western half. The share of on-day precipitations in the supply of Iran’s precipitation days and precipitation amount has changed with time. The results of yearly changes of share of on-day precipitations in the supply of Iran’s precipitation days and precipitation amount indicate that their share in the supply of precipitation days decreases in one quarter of Iran’s area and only in 3% of Iran’s area, their share increases. Given that Western and Central Iran’s maximum precipitation days are provided by one-day precipitations, precipitation days of Eastern Iran have decreased. In addition, their share in the supply of precipitation days decreases in 1/5 of Iran’s area and only in 6% of Iran’s area, their share has increased. On the other hand, Given that Central Iran’s maximum precipitation days are provided by one-day precipitations, their share in the supply of precipitation days has decreased; just in discrete regions and along with Zagros and Alborz unevennesses, their share increases. The results of yearly changes of share of one-day precipitations in the supply of Iran’s precipitation indicate that their negative trend in all rainfall months is greater than their positive trend. Looking more generally into the share of monthly changes of one-day precipitations in the supply of Iran’s precipitation, the aspects of Iran’s precipitation concentration becomes evident, especially in Eastern and Central Iran.

Study of groundwater quality trend in any region is very important from the view of scheduling and sustainable water resources management. In the present study trend analysis conducted on groundwater quality based on information of 32 piezometeric stations located in the Ardabil plain from 1993 to 2008 using the non-parametric Spearman test. Hydrogeochemical variables studied here are Total anions, Total Cations, calcium, magnesium, sodium (Na+), potassium (K), chloride (Cl-), bicarbonate (HCO3-), total hardness (TH), electrical conductivity (EC), sulfate (SO4-2), total dissolved solids (TDS), Na% and pH, which are measured two times a year.One measurement belonged to the month in which groundwater level reach to its highest level that named wet month and other in lowest level that named these as dry months in the present study. Trend line slope estimated using the Sen’s estimator approach. Results showed that concentration of all groundwater quality variables exhibited upward trends at all stations. TDS is the parameter that witnessed the most significant trend in two mentioned months (wettest and driest). For the detected rising trends, the most significant parameters are Cations, EC, Ca and TDS in the most of stations. Median of slopes was positive in the case of all variables. Results for slope of trend lines were shown by Box and Whisker plots for four parameters. In general, quality of Ardebil plain groundwater decreased in the study time period. Strong positive trends observed for water quality in the north, central and east part of the Ardabil plain.

Prediction of the sports records has received a great deal of attention from researchers in different disciplines. This article reviews some of the methods developed by statisticians and offers few improvements. Specific methods discussed include trend analysis, tail modeling, and methods based on certain results of the theory of records for independent and identically distributed attempts. To make the latter theory applicable, and to account for factors affecting the records, adjustments are made to the data in the form of increase in participation or attempts. Models utilized for this purpose include geometric increase, logistic increase, and increase as a non-homogenous Poisson process. A method for prediction of ultimate record is also included together with demonstrating examples using data for men’s long jump and 400 meter run.