Search published articles
Showing 25 results for Hejazizadeh
Joan Amini, Mehri Akbari, Zahra Hejazizadeh, Ali Akbar Shamsipur,
Volume 0, Issue 0 (3-1921)
Volume 0, Issue 0 (3-1921)
Abstract
Green spaces have a key role in moderating urban micro-climatic conditions, beautifying urban landscapes, citizens' leisure time, and also reducing noise and air pollution and absorption of Aerosols. In addition to the significant advantages of green space, water consumption and irrigation needs is one of the main limitations of green space development in Tehran that nowadays faced to critical water shortage. Calculating water footprint in green spaces, as the total amount of fresh water required to maintain green space throughout the year, is one of the indicators by which the compatibility of tree and plant species with climatic conditions can be assessed. The main object of this study is to estimate the water footprint of Laleh Park in Tehran province of Iran. The Green space soil water balance (SWB) model was used to calculate water footprint in this park. The required data that including: average daily temperature, total precipitation and moisture depth of zero to 30 cm of soil, were obtained from the Geophysical meteorological station of Tehran for 2018. Data related to soil water drainage were also estimated based on standard laboratory samples of green space soils. The results indicated that in the warm months (June to September) of the year, the total water footprint of Laleh Park in Tehran was 4 to 5 thousand cubic meters per month (m3/m), while the winter months (December to March) total estimated water footprint were less than 1400 cubic meters per month. The generalization of 30 Centimeters depth soil moisture data of the geophysical meteorological station to Laleh Park, released that, in the warm month of the year, Green Water (groundwater or surface water) had the largest portion (more than 90%) in the water footprint of Laleh Park, While in the winter months (December and to march), the green water (water from snow and rain) is main participant in providing soil moisture, more than 90% of the total water footprint of Laleh Park has related to this source.
Hamzeh Alizadeh, Mehry Akbary, Zahra Hejazizadeh, Mohamad Ahmadi,
Volume 0, Issue 0 (3-1921)
Volume 0, Issue 0 (3-1921)
Abstract
Kermanshah province, especially Ravansar city is one of the important regions of the country in the agricultural and horticultural sector, most of the time the hail phenomenon causes significant damage to these sectors. One way to reduce this damage is to install an anti-hail system. To achieve this goal, 37 station hail data were clustered and three main clusters were obtained representing hail days; Each of the clusters has been plotted and analyzed in terms of geopotential height of 500 hPa, moisture level of 700, and map of 1000 to 500 hPa of temperature and omega. The results of the study of hail patterns show; A low-altitude system is essential in the Middle East; To direct hot and humid air from the southern offerings to the region; At the same time, it is necessary to have high instability and weak static stability in the atmosphere on the surface of the earth, as well as the presence of sufficient moisture that can provide showers. Hierarchical analysis (AHP) method was used for location in GIS environment and parameters such as (slope, slope direction, temperature, humidity ...) were evaluated. These criteria were classified as operating maps, each separately and were scored according to the degree of priority in establishing the device. The final map shows the location of the system: Parts of the northwest of the region (Mansour Aghaei and Ghori Qaleh) and northeast of the central part of Ravansar and parts of the southwest of the area due to the appropriate geographical conditions and appropriate to them, sufficient temperature and humidity and the direction of the southwest slope, and having Favorable conditions for severe instability followed by hail; Anti-hail system is very important for construction in these areas. In general, about 32.6 square kilometers have relatively favorable conditions and about 3 square kilometers have very favorable conditions for the construction of the system.
Dr Hassan Kharajpour, Dr Zahra Hejazizadeh, Dr Bohloul Alijani, Dr Mohammad Hossein Nasserzadeh,
Volume 0, Issue 0 (3-1921)
Volume 0, Issue 0 (3-1921)
Abstract
Considering the undeniable impact of agricultural plants on climatic and regional changes, it seems necessary to conduct regional research to understand the reaction of each agricultural plant in different stages of growth in relation to weather elements. If the temperature of the air along with the warm cloud is lower or higher than a certain threshold, its development will stop. Between the two limits, there is an optimal temperature where the plant grows the fastest. Temperature and clouds are both the most important climatic elements in agriculture. Both climatic parameters together cause stress in wheat and lower the productivity of the product. Considering the strategic nature of wheat, in order to increase the level of production, in the present research, while taking advantage of the experiences and methods and models used in foreign and domestic researches, it was practical in Kermanshah province due to the extent of the land under wheat cultivation and The significant amount of production, which has a special place in this field at the level of the country, the determination of the statistical threshold and the synoptic analysis of warem cloud temperatures on the performance of the wheat crop are investigated. According to the investigations and consultations with agricultural engineers, the maximum temperature along with cloudy days causes the phenomenon of greenhouse and excessive heat, which causes the fall of flowers, rot, sterility of pollen grains, fruit reduction, Premature aging and poverty become seeds, and this phenomenon occurs mostly in the months of May and June.
Sharifeh Zarei, Dr. Bohloul Alijani, Dr. Zahra Hejazizadeh, Dr. Bakhtiar Mohammadi,
Volume 0, Issue 0 (3-1921)
Volume 0, Issue 0 (3-1921)
Abstract
In this research, the most important synoptic patterns of widespread snowfall in the eastern half of Iran have been investigated. For this purpose, the current weather code data and snow depth of synoptic stations in the eastern half of the country during the statistical period of 1371-1400, for the months of October to March, were received from the country's meteorological organization. In order to investigate widespread snowfall, the days when more than 70% of the studied area saw snowfall at the same time were extracted as a widespread day. In order to perform synoptic-dynamic analysis of widespread snowfall in the eastern half of Iran, the classification method using cluster analysis was used and the maps of the representative days including atmospheric temperature, moisture flux, geopotential height, vorticity, front formation, jet stream, omega index and orbital and meridian wind data were drawn. Trend analysis was also performed using the Mann-Kendall test. The results showed that 3 patterns justify the snow cover in the studied area. These patterns are: high pressure in Siberia and central Europe-low pressure in eastern Iran, high pressure in western Iran-low pressure in Sudan, high pressure in central Europe-low pressure in eastern Iran and Afghanistan. In all the patterns in the middle of the atmosphere, the intensification of the meridian currents of the western winds along with the formation of high pressure and low-pressure centers has caused blocking in the path of the western currents and has provided the conditions for the ascent of the air. The concentration of the negative omega field and the relative positive advection, along with the location of the northeastern region of Iran in the left half of the outlet of the Subtropical Jet, have caused severe instabilities and widespread snowfall in the region. Also, the results showed that despite the absence of a trend in the number of snow days in the northeast of Iran, the number of snow days has decreased over time.
Ms Atefeh Bosak, Dr Zahra Hejazizadeh, Dr Akbar Heydari Tashekaboud,
Volume 0, Issue 0 (3-1921)
Volume 0, Issue 0 (3-1921)
Abstract
Air pollution has significant impacts on human health, environmental quality, and the sustainable development of cities. This study aimed to evaluate PM10 using meteorological data from the city of Ahvaz through statistical methods and artificial neural networks. Daily meteorological data and air quality control station data for 4485 days (from 2011 to 2023) were obtained from the National Meteorological Organization and the Khuzestan Department of Environment. Initially, the data were processed and refined, and their normality was assessed using the Kolmogorov-Smirnov test. Given the non-normality of the data, Spearman's and Kendall's Tau-b methods were employed to examine their correlations. The time series and statistical information of the data were obtained using Python programming language. Furthermore, to predict future PM10 levels, the Multilayer Perceptron (MLP) neural network method was utilized. The results of these analyses indicated a significant correlation between meteorological variables and PM10. The Spearman and Kendall Tau-b correlations showed that PM10 had a positive and significant correlation with wind speed (0.094 and 0.061) and temperature (0.284 and 0.187) at a 99% confidence level. Conversely, PM10 exhibited a negative and significant correlation with visibility (-0.408 and -0.300), wind direction (-0.048 and -0.034), precipitation (-0.159 and -0.125), and relative humidity (-0.259 and -0.173) at the 99% confidence level. For future PM10 predictions, the MLP neural network was used. The model was of the Sequential type with an input layer consisting of 6 neurons, three hidden layers of Dense type with 16, 32, and 64 neurons, and an output layer with a linear activation function. The mean squared error (MSE) for the training set was 0.0034, and for the validation data, it was 0.0012. For the test set, the obtained validation accuracy was mse_mlp=0.0048 and val_loss=0.0012. The results indicate a significant direct or inverse correlation between meteorological data and PM10. Additionally, the outcomes of the MLP neural network demonstrated that the network provided satisfactory performance and acceptable predictions for PM10 data in Ahvaz.
Esmaeail Ahmadi, Zahra Hejazizadeh, Bohlol Alijani, Mohammad Saligheh, Hassan Danaie Fard,
Volume 15, Issue 36 (6-2015)
Volume 15, Issue 36 (6-2015)
Abstract
The more exposure to Climate change / variability, the more vulnerability and a community with low adaptive capacity and high sensitivity is more vulnerable. Vulnerability reduction depends on adaptation policy and strategies. Designing and assessing these strategies require climate vulnerability (CV) measuring. To produce a new CV index, as a main propose of this study, first: The score of exposure factor for two five span years was calculated based on four synoptic stations data (Zabol, Zahedan, Iranshahr and Chabahar). Second: The scores of adaptive capacity and climate sensitivity were determined using all of the country census and yearbook data for 1385 and 1390. Third: Due to the nature and factors of vulnerability, a climate vulnerability index was developed based on the multiplicative-exponential model (CVIMEM). Forth: The index was calculated for the province and sub regions. The result shows, although the Sistan and Baluchistan (SB) adaptation capacity was increased, but because of the increased exposure and sensitivity, this province is 16.3% more vulnerable. Area with very high vulnerability label expanded from 57.5% to 100%, which reflects the spatial expansion of vulnerability over SB. The overall result is that vulnerability reduction needs for accurate and continuous measurement, on the increase adaptation capacity and mitigate climate sensitivity.
Zahra Hejazizadeh, Parisa Sadat Ashofteh, Ebrahim Fatahi, Zahra Gholampour,
Volume 15, Issue 38 (4-2015)
Volume 15, Issue 38 (4-2015)
Abstract
Abstract
In this study, the predicted monthly temperature and rainfall data from HadCM3 model (base period, ۱۹۷۲-۲۰۰۱) and next period (۲۰۱۱-۲۰۴۰) under A2emission scenario were used to investigate the impacts of climate change on runoff variations in the Kor river basin. HadCM3 model output was downscaled based on a temporal downscaling approach (Change Factor) and spatial downscaling approach (Proportional) for the basin. The time series of monthly temperature and precipitation were produced in future period. The results showed that temperature and rainfall will increase and decrease in the future period relative to the base period, respectively. Then, the calibrated IHACRES model was used to model rainfall-runoff relationships in the Kor river basin. Then, the downscaled monthly temperature and rainfall time series in next period were employed to rainfall-runoff model and the monthly runoff time series were simulated for period ۲۰۱۱- ۲۰۴۰. The comparison of future period runoff relative to observed period showed that the annual runoff in the basin for period ۲۰۱۱-۲۰۴۰ will decrease about ۹٫۴۳% with respect to base period.
Dr Zahra Hejazizadeh, Mr Meysam Toulabi Nejad, Mr Alireza Rahimi, Mrs Nasrin Bazmi, Mrs Atefeh Bosak,
Volume 17, Issue 47 (12-2017)
Volume 17, Issue 47 (12-2017)
Abstract
The aim of this study is modeling spatiotemporal variations of albedo. This study was conducted using simultaneous effects of several components, such as wetness of surface layer of soil, cloudiness, topography and vegetation density (NDVI), using MEERA2 model with a resolution of 50 in 50 km during 2000-2010 in Iran. The results of spatial analysis of albedo values in Iran showed that the highest value is in 44 to 45 degrees of east longitude about 2.8 to 3.3 and the lowest value of albedo is also in 52 to 53 degrees of east longitude, that is, the eastern slopes of the Zagros Mountains, have been recorded at 1 to 1.5 units. In terms of provincial rank, the largest albedo is about 0.25 units in Ilam province and the Fars province is ranked next about 0.24 units. The lowest amount of albedo also in the Gilan provinces and in next Mazandaran province are about 0.19 and 0.18 respectively. In addition, the results of temporal analysis in seasonal scale showed that the highest albedo in Iran in winter was 0.26 and its lowest amount was recorded in spring with 0.23 units. In general, according to the factors used, it can be said that the western and central parts of the country have a highest albedo, and the north and northwest regions of the country have a lowest albedo.
Naseh Qaderi, Bohloul Alijani, Zahra Hejazizadeh, Mohammad Saligheh,
Volume 18, Issue 48 (3-2018)
Volume 18, Issue 48 (3-2018)
Abstract
Wheat is the main focus of the economy of Kurdistan province in which the annual fluctuation of wheat yield is 4/11 times as affected by the climatic elements of the site. This study investigated the role of agro-climatic variables and indices on rainfed wheat yield in Kurdistan province. The data of planting area, amount of production, damages and yield of wheat of 31-year in 10 regions of Kurdistan along with the hourly, daily, decade, monthly, seasonal and yearly levels data of 22 synoptic stations were collected. The correlation between wheat yield and 128 independent variables was calculated. The effect of variables on yield evaluated by multivariate regression. The spatial analysis of variables was performed and the spatial model of wheat yield was introduced for province and regions. The results showed that climatic elements in various regions are different, in a 99% confidence. Most of the independent variables alone have a significant effect on wheat yield, but in the stepwise model, 7 variables such as: the number of rainy days of the year, the sum of the degree hours (of temperature less than -11 ° C) in germination and tilling stage, annual precipitation and the precipitation of November are determinants of the yield. Yield and effective independent variables have significant spatial differences even in a cluster climate type. The highest and lowest coefficient of variation of wheat yield is related to Bijar and Kamyaran areas, respectively. Kamyaran and Sanandaj regions have the highest and lowest yield, respectively. Bijar is the highest risk region of the province for wheat production.
The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas.
The results of this study showed that with a 99 percent confidence, climatic elements (variables) vary in different regions. Most of the independent variables have a significant effect on wheat yield in simple linear regression, but in Stepwise method, due to the internal correlation between variables, just variables entered that have insignificant correlation with each other and have more effects than other variables. The variables affecting the performance are differentin various regions, and from the point of view of effectiveness, the arrangement of the variables in different areas vary too. In other words, even in two regions with a climatic type (based on the Modified De Martonne method), both agro-climatic indices and wheat yield are significantly different. The impact of effective variables on yield at any time and place depends on the time of year and the phonological stage of wheat. At one time the environmental conditions of different regions in terms of temperature, humidity and precipitation differ, based on phonological stages of the regions. The time of the vulnerability of wheat varies from place to place. Wheat vulnerability at flowering stage is more than other stages. The effect of independent variables on yield at different times of year is proportional to the phonological stage in years Different and different in different regions. In Kurdistan province, the number of rainy days of the year, total degree hours the temperature reaches below -11 °C (sum of hours with below -11 °C temperature) from germination to tillering stage, the annual precipitation, the rainfall in the fifth decade of the water year (the precipitation of 11-20 of November), annual relative humidity and total degree hours the temperature reaches above 30°Ctemperature (sum of hours with above 30 °C temperature) in milky and dough stage is the determinants of the production of rainfed wheat. In Baneh and Marivan areas, the coefficient of variation (CV) is lower and in Bijar and Divandareh regions CV is more than other regions. Kamyaran region has the highest yield, Baneh and Marivan were ranked secondjointly. Sanandaj and then Bijarhave the lowest yield. Each region has a model for wheat yield and determinant factors vary from region to region. Although the annual production of Bijar is higher than other areas, wheat production in the Bijar region has a higher risk than other areas.
Meysam Toulabi Nejad, Dr Zahra Hejazizadeh, Mrs Atefeh Bosak, Mrs Nasrin Bazmi,
Volume 18, Issue 49 (3-2018)
Volume 18, Issue 49 (3-2018)
Abstract
The purpose of this study was to investigate the effects of the North Atlantic Oscillation on the middle levels of Atmosphere and precipitation changes in the West of country. To do this, first monthly rainfall data of 17 synoptic stations of the West Country in period of 30 years from 1984 to 2014 of country were collected from Meteorological Organization. As well as North Atlantic Oscillation data and anomalies geopotential height data, sea level pressure and precipitation were received from NOAA. To clarify the relationship between the NAO index phase with precipitation of west of Iran used Pearson correlation coefficient was at least 95%, (P_value = 0.05). Finally, using synoptic maps, spatial relationships among data, were analyzed. The results indicate that between North Atlantic Oscillation changes with middle level height anomalies of the Atmosphere and the amount of precipitation in West of Iran in January, March, April and November there is communication and concurrency. The results showed that , at a time of sovereignty positive phase of the North Atlantic oscillation , an average of height atmospheric middle level in mid - western Iran 17 meters long - term and less than the average rainfall per month 23.5 mm increased and wetly sovereign. But when phase of governance is negative, high atmospheric middle level anomaly to an average of 20 meters more than normal. As a result, the drought will prevail in the west and precipitation in the region each month will face a reduction of 30 mm. In general, we can say that droughts more severe than wet coincide with the negative phase of the North Atlantic Oscillation is positive phase.
Adel Nabi Zadeh Balkhanloo, Zahra Hejazizadeh, Parviz Zeaiean Firoozabadi,
Volume 18, Issue 50 (3-2018)
Volume 18, Issue 50 (3-2018)
Abstract
Continuous decline in Lake Urmia water levels In recent years, the decline of rainfall and river flows and constant droughts has become the main concern of the people and the people. To study climate change and increase of temperature in the catchment area of Lake Urmia, two factors for measuring the temperature and properties of satellite images were used which indicate the importance of land surface temperature changes (LST) and normalized vegetation differences (NDVI). This study was carried out using the satellite data of the periodic watershed (2008-2008) to investigate the spatial relationship between NDVI-Ts and NDVI-ΔT to investigate the actual agricultural drought occurrence. The goal is to extract the VTCI (vegetation temperature index) index, which is capable of identifying drought stress at regional scale. The results showed that the slope is negative for the warm edge, where it is positive for the cold edge. The gradient gradient shows that the maximum temperature is reduced when the NDVI value increases for any interval. The slope on the cold edge indicates that the minimum temperature rises when the NDVI value rises. Overall, at the warm and cold edges, it has been observed that the drought trend over 2009-2008 is higher than in 2010. In the days of Julius Day 257, the slope of the cold edge from 2008 to 2010 is decreasing. But at the hot edge, intercept pixels for 2008 is more than 323 degrees Kelvin, where in 2009-2010 it is less than 323 degrees Kelvin. In general, the correlation coefficient (R2) is different in the TS-NDVI spacing between (0.90-0.99). The present study showed that with the integration of satellite satellite data with meteorological data, the VTCI threshold for drought stress varies from year to year depending on the data conditions.
Saeed Javizadeh, Zahra Hejazizadeh,
Volume 19, Issue 53 (6-2019)
Volume 19, Issue 53 (6-2019)
Abstract
Drought is one of the environmental events and an inseparable part of climatic fluctuations. This phenomenon is one of the main characteristics of the various climates. Awareness of spatiotemporal behavior is effective in land planning. The spatial statistical methods provide the means by which they analyze the spatial patterns of random variables such as precipitation. In this study, using the rainfall data of 84 selected synoptic stations during the period of 30 years (1985 to 2014) in Iran, the spatial analysis of drought has been investigated. Initially, using SPI values (timescales 3, 6, 12, 24 and 48 months), drought and traumatic periods of the area were identified and using the Geostatistic Analyst extension, the drought was zoned by interpolation methods. Moran statistics were used to explain the pattern of drought in Iran. The results of Moran index for drought showed that the values for different years during the statistical period have a positive and close to one, indicating that the SPI drought index data has spatial self-correlation and cluster pattern. Also, the results of Z score and P-value values, clustering of a spatial distribution of drought, were confirmed.
Mehdi Shafaghati, Zahra Hejazizadeh, Hasan Afrakhteh,
Volume 20, Issue 56 (3-2020)
Volume 20, Issue 56 (3-2020)
Abstract
Each geographical location, topography, landscape, flora and fauna, air and climate natural resources for tourism and recreation form. Given that every business needs a bed a place in the geography of this place, defined geographical space.This geographical space supplier of tourist activities. Many factors affect the tourism industry, one of the most important climates. Along with geographic location, topography, landscape, flora and fauna, water and air as one of the most important local resource base plays a role in the development of tourism industry. Gilan province is one of the countries northern even with Mesa 14711 square kilometers .The province has two different morphology of the southern part of the province of North Alborz heights shown and the foothills and plains in coastal areas. The province because of the special circumstances of the geographical, exquisite natural scenery and abundant water resources in the row is one of the most tourist areas of the country. In this study, with the presentation of applied research, analytical and application software, Excel, Google Earth, ArcGIS10 to check the status of existing and potential climate in Gilan province was one of the country's Northern provinces. Which has convenient facilities in the field of tourism is also significant to analyze the specific situation of the province and also to discuss tourism and its development will conform to discuss climate. The result of climatic classification methods Domarten temperature and precipitation maps also will be show that there are good conditions for tourism development in the province and Finally, using the climate index TCI zoning province, and the results were presented in the field of tourism.
Mohammad Hossein Nasserzadeh, Zahra Hejazizadeh, Zahra Gholampour, Bohloul Alijani,
Volume 20, Issue 57 (6-2020)
Volume 20, Issue 57 (6-2020)
Abstract
The plant community in an area is the most sensitive indicator of climate. A visual comparison of climate and vegetation on a global scale immediately reveals a strong correlation between climatic and vegetation zones and this relationship, of course, are not co-incidental. The main object of this study is to reveal the spatiotemporal association between climatic factors andvegetation Cover (NDVI) incorporate MODIS and TRMM product in Kohkiloyeh O Boirahmad province of Iran. So that the in this paer we use MOD13Q1 of MODIS product as NDVI layer for study area. MOD11A2 as landsurface temperature and 3B43 TRMM as meanmonthly accumulative rainfall for study area during 2002 to 2012 in 0.25° spatial resolution also were used as climatic factors. We use the correlation and cross-correlation analysis in 0.95 confident level(P_value =0.05) to detection the spatial and temporal association between the NDVI and 2 climatic Factor(LST and rainfall). The results indicated that during winter (December to March) the spatial distribution of NDVI is highly correlated with LST spatial distribution. In these months the pixels which have the high value of NDVI are spatiallyassociated with the pixels which have highest value of LST (6 to 14C°).As can be seen in table 1. Season the spatial correlation among NDVI and LST is so high which is statistical significant in 0.99 confident level in winter. In transient months such as May, October and November,(temperate months in study region ) the spatial correlation among NDVI and LST is falling to 0.30 to 0.35 which is not statistical significant in 0.95 confident level. Finally in summer season or warm months including Jun to September, we found the minimum spatial association among the NDVI and LST.. In temporal aspect we found that the maximum correlation between NDVI and LST simultaneously appears and not whit lag time. The spatial correlation of NDVI and TRMM monthly accumulative rainfall was statistical significant in spring season (April to Jun) by 1 month lag time in remain months we don’t find any significant correlation between NDVI and rainfall.
Mojtaba Shahnazari, Zahra Hejazizadeh, Mohammad Saligheh,
Volume 20, Issue 59 (12-2020)
Volume 20, Issue 59 (12-2020)
Abstract
Abstract
In this research, while studying climate conditions in the current period and analyzing changes in temperature, precipitation level, and the sunlight received, current conditions were also analyzed based on daily data from synoptic stations in the region, which had meteorological data recorded for at least 30 years. Given the environmental conditions necessary for the growth of rice, the availability of its phenological data, its high-low temperature thresholds, the Degree Day systems needed for the completion of its life cycle, and the phenological processes related to its economic production, a suitable agricultural calendar was specified. During the March-July period, this calendar showed variations in different provinces. Based on the current temperature conditions and the probable continued warming trend of the planet in the decades to come, nwoDscale was applied to the output from the atmospheric general circulation model MCdaH3 under scenario using LARS-WG5 model. In this study, years between 1969 and 1990 were used as the base period, while years between 2046 and 2065 were studied as the future period. Temperature and precipitation conditions for the future period were simulated. Obtained output was then studied and compared with temperature conditions that were suitable for the plant to grow in the region. With some differences, results showed that the agricultural calendar for rice in Gilan and Mazandaran provinces will shift to winter. Given the different temperature conditions of Golestan province, its agricultural calendar will shift to spring.
Hamideh Afsharmanesh, Zahra Hejazizadeh, Bohloul Alijani,
Volume 21, Issue 61 (6-2021)
Volume 21, Issue 61 (6-2021)
Abstract
Climate predictions have been made in global, regional and local simulation, and climatic parameters have changed in terms of trends and models in climatology, futures studies are less visible in literature and climatology literature therefore environmental planning and futures analysis are an attempt to look at the long-term future in the field of climatology. Today, one of the most important challenges of the present and future is the increase in temperature and is the lack of climatic comfort. The growth of Tehran's metropolitan area, improving living standards, expanding urbanization and industry, climate change, and the energy shortage crisis are important. The survey forms were prepared by the climatologists and managers of Tehran and data analysis, futuristic techniques such as scenario for data analysis tool in this study was MICMAC software. have been used. In the research process, the most important key factors and drivers in relation to futures studies were identified in relation to the increase of temperature in the city of Tehran.
Mini scenarios and a comprehensive scenario were defined in three cases:
- Improvement of the Micro-Climatic Conditions of Tehran City + Climatic Comfort of Citizens
- Lack of good micro-climate in Tehran + low climatic comfort of citizens
- The lack of improvement in the micro-climatic situation in Tehran + the lack of climate comfort for citizens and increased energy consumption
Mrs Zahra Hejazizadeh, Mr Farshad Pazhoh, Mr Fardin Ghadami, Mrs Haniyeh Shakiba,
Volume 22, Issue 65 (6-2022)
Volume 22, Issue 65 (6-2022)
Abstract
The aim of this study is to synoptic analyze of the number of frost days in a year of Khuzestan province. For this purpose, using the minimum daily temperature data of 12 stations during the statistical period of 1992 to 2017, the Meteorological Organization of the country, 54 days of frost was identified. Sea level pressure, Geopotential Height, Zonal and meridian wind and temperature of 500 hPa data with size of 2/5 * 2/5 degree arc from the National Oceanic and Atmospheric United States of America were extracted. On the matrix of the variance of sea level pressure data in 54 days, the analysis of the basic components was performed and 10 components which identified 83% variance of the sea level pressure. Then, by applying the hierarchical cluster analysis method, the integration method was applied to the scores of the 10 components and 5 patterns of sea level pressure were identified. The results showed that frost phenomenon in Khuzestan province occurs from November to march and its trend is decreasing during the statistical period. Also northern and western parts of the province have allocated the most frequency of frost. Also the synoptic condition analysis of troposphere showed that 5 sea level pressure pattern with different make ups lead to pervasive frosts of Khuzestan province. Weak and moderate frosts formed by the influence of Siberian and European cold high pressure systems. But severe frosts occur with spread of Iceland low pressure to Iran, along with strong cold pressures. Meanwhile, the powerful Siberian high pressure is present in most of the patterns, which its interaction with sub polar and Icelandic low pressure, plays the most role in the most severe frost in the province of Khuzestan. Also in the middle level of troposphere penetration of deep troughs from northern latitudes and east European huge blockings has the most role, which has advection of cold air from the side west of troughs on the country and during the intensity of the frost added to its continuity.
Mr Mahmood Hosseinzadeh Kermani, Dr Bohlul Alijani, Dr Zahra Bigom Hejazizadeh, Dr Mohammad Saligheh,
Volume 22, Issue 67 (12-2022)
Volume 22, Issue 67 (12-2022)
Abstract
The main aim of this paper is to determine the capable areas for cultivating pistachio through considering of Geo statistical Analysis the major effective factors. The necessary climatic daily data of weather stations For the 300 synoptic stations, the station was set up by 2016. The topographic data include relief, slope, aspect, and TIN layers extracts from 1:250000 topographic maps of the region. The maps of land use and vegetation land cover were prepared from the 1:250000 maps of national soil and water Research Institute. The spatial analysis facilities of GIS were utilized for numerical calculation and the spatial geodatabase of the region was established. Then spatial and description data was entered into the data bank. Finally by overlaying analysis in ArcGIS, cultivated area was classified according to its capabilities. The results showed that 707273/88 KM2 Of the area (43%), Not suitable for spreading pistachio cultivation (Including altitudes and urban use and steep slopes, seaside and riverside streams, shoals, saline and swampy lands) and 585130/39 KM2 (35/57%) From the country of Iran Area Including plain areas and agricultural use) was recognized as suitable for the expansion of pistachio cultivation. These areas are located in the east and south east, center and northeastern Iran.
Zahra Hejazizadeh, Sharifeh Zarei, ,
Volume 23, Issue 69 (6-2023)
Volume 23, Issue 69 (6-2023)
Abstract
Abstract
In recent years, attention has been paid to climate change, which could be the result of economic, social, and financial losses associated with extreme weather events. The purpose of this study is to investigate the variation of extreme temperature and precipitation in Kurdistan province. For this purpose, daily rainfall data, minimum temperature and maximum temperature of 6 stations were used during the statistical period (1990-1990). And their changes during the period (2041-2060) using the universal HadGEM2 model under two scenarios RCP2.6 and RCP8.5 and the LARS-WG6 statistical downscaling were investigated. In order to study the trend of climatic extreme indexes, rainfall and temperature indices were analyzed using RClimdex software. The results showed that during the period (2016-1990), hot extreme indicators have a positive and incremental trend. This trend is significant for the "number of summer days" and "maximum monthly of maximum daily temperature" indicators. This is while the cold extreme indexes had a decreasing and negative trend. This trend was significant only for the "cold days" index. Extreme precipitation in Kurdistan province has a negative trend in most stations. ،this trend is significant at most stations, that indicates a reduction in the severity, duration and frequency of precipitation during the study period. The results of the climate change outlook also indicate that the temperature will increase over the next period and rainfall will decrease.
Nasrinalsadat Bazmi, Zahra Hejazizadeh, Parviz Zeaiea Firoabadi, Qholamreza Janbazghobadi,
Volume 23, Issue 70 (9-2023)
Volume 23, Issue 70 (9-2023)
Abstract
This article was written with the aim of revealing land use changes in Urmia city using remote sensing of Landsat satellite images for 4 periods of 8 years between 1990 and 2019. For this purpose, two categories of data will be used in this research. The first category includes data obtained from satellite images and the second category includes ground data taken from Urmia ground station, which includes temperature and other parameters used in this research. The results showed that urban land use in Urmia city has faced significant changes during the statistical period of 30 years. This user has had an increasing trend during all the studied periods, so that during the study period, it has faced a 5-fold increase. Swampy areas and sludge fields east of Lake Urmia have undergone a significant decline during 1990-2019 and has reached less than 6,000 hectares. The citychr('39')s barren lands, which cover a small percentage of the citychr('39')s area, have been declining over the 30-year period under review. The use of gardens has increased during all periods, so that in 2019, its area has reached more than 20,000 hectares. The use of irrigated agriculture has increased during all the studied periods and its area has reached more than 80,000 hectares by 2019. The area of rainfed agricultural lands, after the rangelands, is the widest land use in Urmia, but with a relatively gentle slope has a decreasing trend. Water areas have also been declining, so that in 2019, it has decreased by about 26% compared to 2012. Rangelands, which is the largest land cover in Urmia city, has gone through three different processes during the study period. From 1990 to 1998, these lands did not change significantly, but from 1998 to 2005, the increasing trend and in 2019, with a 10% decrease compared to 2012, reached its lowest area during the statistical period under study, ie less than 20,000 hectares.
Related Websites
- Scientific Publications Commission - Health Ministry
- Scientific Publications Commission - Science Ministry
- Yektaweb Company
Vote
Site Keywords
نشریه, Academic Journal, Scientific Article, کلمه شماره یک, کلمه شماره یک, کلمه شماره یک, کلمه شماره یک, کلمه شماره دو, کلمه شماره یک, کلمه دو
Journal of Applied researches in Geographical Sciences are fully compliant with open access mandates, by publishing its articles under Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2024 CC BY-NC 4.0 | Applied researches in Geographical Sciences
Designed & Developed by : Yektaweb