جستجوی مقالات مرتبط با کلیدواژه « climatic parameters » در نشریات گروه « آب و خاک »

Climate changes caused by the progress and industrialization of human societies have caused changes in the intensity and frequency of heavy precipitation and floods, which have caused irreparable damages. In order to reduce these damages, it is necessary to identify the changes in the threshold values ​​of precipitation and factors affecting it each region. Quantile regression methods are able to examine the trends not only in the median, but also in different ranges of the data series. Therefore, the purpose of this research is to investigate the seasonal trend of different amounts of precipitation and also to investigate the relationship between the climatic parameters of minimum temperature, maximum temperature, minimum relative humidity, maximum relative humidity and wind speed on different amounts of precipitation in different climates of Iran.

In the first step, the daily time series of climate data including precipitation, minimum and maximum temperature, minimum and maximum relative humidity and wind speed for a period of 45 years in different seasons for 5 synoptic stations of Babolsar, Shiraz, Bandar Abbas, Khorram Abad and Torbat Heydarieh were formed. In the selection of study stations, we tried to select stations with different climates and with appropriate statistical period. Then, to investigate the trend of seasonal changes of different amounts of precipitation in different quantiles (quantiles 0.01, 0.05, 0.1, 0.25, 0.5, 0.75, 0.9, 0.95 and 0.99) was analyzed using the quantile regression method in all study stations. In the next step, the relationship between the climatic parameters on different amounts of precipitation (low to very high amounts of precipitation) in different seasons was investigated for each of the stations using the quantile regression method. Then the results were analyzed.

The results of examining the changes trend of daily precipitation are showed that the high amounts of precipitation in the spring season in Bandar Abbas, Shiraz, and Torbat Heydarieh stations were reduced significantly, but very high amounts of precipitation (0.95 and 0.99 troughs) in the station Babolsar and Khorramabad have increased. Also, very high daily precipitation amounts in summer have decreased in Bandar Abbas station but increased in Torbat Heydarieh and Khorram Abad stations, significantly. While in the winter season, different amounts of precipitation in all seasons have a decreasing trend and there was only a significant positive slope in very high amounts of precipitation (slope of 0.99) in Babolsar station. In the investigation of the parameters affecting the extreme precipitation, the results showed that the amount of impact on the occurrence of heavy rainfall was relatively higher than low to median rainfall. The parameters of minimum temperature, minimum humidity, maximum humidity and wind speed have a positive effect and the maximum temperature parameter has a negative effect on heavy rainfall in different seasons and stations.The highest positive effect coefficients were in spring for wind speed in Babolsar (1.8), in summer for wind speed in Babolsar (3.8), minimum and maximum temperature in Bandar Abbas (-4.03 and 1.53), in Autumn season for maximum humidity and wind speed in Babolsar (2.57 and 2.99) and wind speed in Khorram Abad (1.54) and in winter, for wind speed in Babolsar and Bandar Abbas (1.94 and 6. 2), and minimum temperature in Torbat Heydarieh (0.96). Also, the highest negative effect coefficients of maximum temperature were in autumn and winter seasons (-0.88 and -0.72) in Babolsar and autumn season (-0.63) in Shiraz.

The significant changes in increasing and decreasing precipitation are mostly related to the amounts of heavy precipitation, which are different in different seasons and climates. Also, the precipitation of the stations near the north and south coasts have been influenced by climatic parameters to a greater extent. In general, it can be said that flood precipitations are influenced by climatic parameters such as wind speed, humidity and temperature in order of importance and this effect is different depending on the location and time and the influence of different factors. Therefore, it is necessary to apply accurate planning for the correct use of received rainfall and optimal management in the target area using the results of such studies.

In this study, spatial-temporal variation of dust deposition rate in the western and eastern half of Tehran and its climatic parameters affecting were studied. At 34 points in the city, dust samples were collected by glass traps from the roof, for twelve months, and the climatic data were obtained and analyzed from relevant organizations. The highest deposition rate is in the western half of the city and its total amount has varied from 54.52 to 121.21 g/m2/y. In both halves of the city, summer has the highest dust deposition rate and its central areas have the highest amount. There were significant positive correlations between dust deposition rate with temperature and medium wind speed, and there were significant negative correlations between dust deposition rate with rainfall and relative humidity in all months, which justifies the high dust deposition rate in the dry seasons of the year. The results of stepwise regression showed that rainfall was the most important factor affecting the dust deposition rate in both halves of the city. The city of Tehran has a special geographical location the presence of mountains like a barrier has prevented dust from leaving the city and the air inlet corridor of Tehran has faced problems due to the expansion of building construction and high-rise building. Other factors affecting the rate of dust deposition in this city, in addition to the distance from the main source of dust production, atmospheric parameters can be mentioned the existence of barren lands around the city, vegetation cover, construction operations, and traffic.

Snow and snow melt runoff have a major role to play in supplying water. In this study the impact of climate change on runoff caused by snowmelt was studied in Sarab Seyed Ali watershed in north of Lorestan province. In this study, using snow cover level extracted from Landsat 5 and 7 satellite images and climatic data predicted by general circulation model using Lars-WG software snowmelt runoff under three scenarios A1B, A2 and B2 in the year 2010 to 2013 was simulated using the SRM model. The simulation results were evaluated using two statistic including coefficient of determination and volume difference. The value of 0.87 for the coefficient of explanation and -3.62 for the volume difference indicates the accuracy of the model. Then, using these three scenarios, the climate parameters for 2020 to 2060 were predicted through general circulation model, then using the predicted climate parameters, the rate of snow cover was estimated through multivariate regression equations and was into to SRM model. the simulation was done for 2020 to 2060. The results showed that the average runoff in November to May for the three scenarios was 4.3, 4.4 and 4.2 m3/s respectively, while the long-time mean runoff from 1980 to 2013 was 6.07 m3. However, this decrease in future runoff volume can be justified by the reduction of snow cover.

Moisture content of surface soil is an important variable in nature's water cycle, which plays an important role in the global equilibrium of water and energy due to its impact on hydrological, ecological, and meteorological processes. Soil moisture is a determining factor in many complex environmental processes and plays a determinative role in the occurrence of agricultural drought. In this study, based on estimated soil moisture data by SWAP model and data of the IPCC Fifth Assessment Report, agricultural drought was determined by the use of soil moisture deficit index for the future period. The climatic data was estimated using six GCM models and two RCP4.5 and RCP8.5 emissions scenarios, and downscaled by LARS-WG model, and was entered into the SWAP model. Finally, by using soil moisture data of 30 cm depth, agricultural drought was evaluated using SMDI index. The results of climate parameter changes showed that the minimum and maximum temperatures and rainfall in the future period would increase compared to the base period and RCP8.5 scenario estimated higher temperatures and less rainfall than RCP4.5 scenario. Results of estimated SMDI values for the future period showed that RCP4.5 scenario has a higher average of SMDI amount than RCP8.5 scenario. Also, both scenarios show the normal moisture amount for future period and the predicted SMDI amount for the future period is higher than the base period.

As a highly productive product, walnut plays an important role in the social and economic condition of farmers in various regions across Iran, and there has been a dramatic increase in the area under cultivation of this product in recent years due to its economic return. Walnut trees are highly sensitive to the climate conditions. Therefore, before Cultivation of this product, which requires a relatively high initial investment, it is necessary to take certain measures to identify and assess suitable lands for planting walnut trees. Therefore, this study aims to identify and assess suitable lands for planting walnut in the entire of Tehran province that would result in a desirable production efficiency. For this purpose, this study uses climatic parameters (including temperature, relative humidity, precipitation, and wind speed) from 12 synoptic stations within Tehran Province and 8 stations from adjacent provinces for an 11-year statistical period (from 2004 to 2014), topography, and land use for site selection and zoning of suitable regions for cultivation of Persian walnut. First, raster data layers were generated using all the parameters under study. Then, through a review of literature and expert views on physiological properties and growth requirements of walnut, the desirable and undesirable thresholds for its cultivation were determined. Next, analytic hierarchy process (AHP) and a researcher-made questionnaire were used to calculate the effectiveness and priority of each parameter. Furthermore, a fuzzy membership function was used to normalize the data layers. Finally, the final zoning map was prepared and extracted using fuzzy overlay tools in ArcGIS. According to this map, an area of 243882.9562 hectares, equal to 17.82% of the entire area of Tehran Province proved very suitable for cultivation of Persian walnut. Moreover, the findings indicate that the three parameters of temperature, relative humidity, and aspect have a special significance and effect on the growth of walnut trees.

Wind erosion climatic factor is a measure of climatic factors explaining the wind erosion erosivity. Humidity and wind speed are climatic characteristics that must be considered as the erosion parameters. In this study, linear moment analysis (L-moments) and wind erosion climatic factor were used to evaluate the regional climate’s tendency effect on wind erosion in Yazd province. Wind erosion climatic factor is calculated from wind speed quantiles, and other available meteorological data. Climatic factor analysis is done by Monthly average and daily maximum of wind speed and other available meteorological data from 14 meteorological stations in Yazd province. Three homogeneous groups of wind speed were considered based on results of regional analysis. Then regional wind speed quantiles were calculated and their results is used for calculating wind erosion climatic factor values for two 6-month wet and dry periods that belongs to every homogeneous region. In addition, erosion climatic factor values was estimated for each station by using Weibull distribution and the results were compared with the values of the regional erosion climatic factor. Results showed that estimated values using the regional-based approach have smaller mean square error than the Weibull method. Therefore, this method can be assessed the regional risk of wind erosion in arid and semi-arid environments.

Spatial and temporal distribution of dust deposition rate (DDR) in Isfahan city and the influencing climatic parameters were studied. Dust samples were collected using glass trays placed on the roof of one-story buildings from 20 sites in Isfahan city for 12 months. Climatic data were obtained from Meteorological Organization and analyzed. The highest and the lowest amount of DDR in agreement with the direction of prevailing wind were observed for dry months with eastern and northeastern wind directions and wet periods with western and southwestern wind directions, respectively. This can indicate dust emission from the desert located in eastern part of Isfahan city. Statistically significant inverse correlation between DDR and precipitation and relative humidity, and significant and positive correlation of DDR with Min and Max temperatures in all the studied months and also with Max and average wind speed for dry sampling months may well justify the temporal distribution of DDR in the city. In dry months, finer particles from eastern desert can be transported a longer distance and deposited in the western part of the city, far from the source area. In wet seasons, however, soil aggregates become coarser as a result of particle adhesion. This, in turn, results in the deposition of dust near the source area as the transporting power of dust reduces.

Over the past hundred years, human activity has significantly altered the atmosphere and increase of concentration of greenhouse gases lead to warm the earth's surface. This global warming leads to change of climatic extreme index and increases the intensity and frequency of occurrence of extreme climate events. Investigation of extreme values for planning and policy for the agricultural sector and water resource management is important.In this study, a comprehensive review of extreme indices of temperature and precipitation are discussed. This paper aims to investigate extreme temperature and precipitation indices defined in accordance with CCL, and the study of other climatic parameters in the North East of Iran. In this research, statistics and data of some stations in the North East of Iran during the period 1992-2012 were used. To evaluate the extreme climate indices trend, 27 indices of rainfall and temperature, were defined by the ETCCDMI. They were calculated by RClimdex software. In this software, prior to the index calculation, data by quality control software became quantitative and incorrect data were controlled and outlier data were examined. The indices were calculated by daily data. 11 rainfall and 16 temperature indices were calculated by this software.The target of the ETCCDMI process is to delineate a standardized set of indices allowing for comparison across regions. These extreme indices were classified in five categories which included the percentile-based extreme indices, the absolute extreme indices, the threshold extreme indices, the periodic extreme indices, and the other indices. They were estimated at the 0.05 significant levels. The Mann-Kendall test was used to investigate the climatic parameters, maximum relative humidity, sunshine duration and maximum wind speed. Thermal analysis results are consistent with warming patterns, and they have showed that hot extremes indices have increased. Hot days index (SU25), shows a significant positive trend in all studied stations. Number of tropical nights has a positive trend in all stations. Hot day frequency (TX90P) and hot night frequency (TN90P) in all stations show a positive trend, indicating an increase in the number of warm days and nights. Cold extreme indices show a decreasing trend. (TX10P) and (TN10P) show significant negative trends in all stations and indicate a decrease in cold days and nights. Number of frost day index shows a decreasing trend. Overall, the results revealed a decrease in the severity and frequency of cold events, while warm events during the study period were significantly increased. These results are consistent with the results of the Intergovernmental Panel on Climate Change and global and regional studies. Rising temperatures could lead to increase in the maximum wind speed in the area. In the study of the maximum wind speed process, this trend was observed in most stations, and incremental changes can be associated with a reduction in the maximum relative humidity (which was observed in the results). The sunshine hour parameter depicted a decreasing trend in the most station trend. In the study of all rainfall indices in all studied stations there were a decreasing and negative trend for rainfall, although few significant trends over time were observed. Comparison of years with the highest rainfall and those with the lowest, showed that the amplitude of fluctuations in precipitation in different years is very high and the distribution of rainfall at distinct stations is different. In general, due to the high dispersion and low rainfall in most stations, providing a clear and uniform regional rainfall pattern is not possible. Due to the effects of temperature and precipitation extreme indices in a wide range of human activities, such as agriculture, water management and building design, it is necessary to consider the effects of these extreme climatic events in the future planning and policies in different sectors. Conclusion The results showed that hot extreme indices, such as summer day index, the number of tropical nights, warm days and nights have increased, while, in the period of study, cold extreme indices have decreasing trend, which shows a decrease in the severity and frequency of cold events.The trend of the maximum wind speed was increased in most stations. Rainfall indices show decreasing and negative trends, although over the studied period few significant trends were observed.

The growing season climatic parameters, especially rainfall, play the main role to predict the yield production. Therefore, the main objective of this research was to find out some possible relations among meteorology parameters and drought indexes with the yield using classical statistical methods. To achieve the objective, ten meteorological parameters and twelve drought indexes were evaluated in terms of normality and their mutual influences. Then the correlation analysis between the barley yield and the climatic parameters and drought indexes was performed. The results of this study showed that among the drought indexes, Nguyen Index, Transeau Index, Rainfall Anomaly Index and Standardized Precipitation Index (SPI24) are more effective for prediction of barely yield. It was also found that the multivariate regression is better than the univariate regression models. Finally, all the obtained regression models were ranked based on statistical indexes(R,RMSE and MBE). This study showed that the multivariate regression model including wind speed, sunshine, temperature summation more than 10, precipitation and Nguyen index is the best model for prediction yield production in Miane. Average wind speed and Nguyen index were recognized to be the most effective parameters for yield production in the model.