Irrigation
Helaleh Fahimi; Abd0llah Faraji; bohlul alijani
Abstract
Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity ...
Read More
Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea. Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea. Arabia Antyciclone (AA), is a component of atmospheric circulation affecting the cold-period precipitation in Iran. This study aimed to investigate the role of AA on the cold-period extreme precipitation in Iran. To this end, 7 patterns with the highest extreme precipitation and the highest spatial homogeneity during a 31-year period (1989-2020) were investigated. Using the ERA5 data, geopotential altitude and specific humidity maps were plotted. The results showed that the location and expansion of the AA changed under the influence of the tropical penetration of Western systems at different levels. By ascending to higher levels, due to the greater influence of Western systems, the AA finds a more southern position, and its effects on Iran are diminished. The AA in interaction with the mid-latitude cut off low and the southern branch of the westerlies leads to the formation of an atmospheric river (AR) with a tropical origin. Moreover, with its anticyclonic current, it leads to the humidity feeding of the atmospheric river along its way to enter Iran. Meanwhile, it is an important factor in the transfer of humidity to East Central Africa, where the atmospheric river is formed. At the ground level, the AA diverts humidity from the Arabian Sea and the Persian Gulf to the western and northwestern regions, preventing widespread entry of the Turkey low into the western and southwestern regions of Iran. It also prevents Sudan low from entering the Middle East by entering the southern Red Sea.
Agricultural Meteorology
A. Gholami; H. Mir Mousavi,; M. Jalali; K. Raispour
Abstract
Introduction
Clouds can be considered as one of the most complex and influential variables of the atmosphere system in forming of the climate structure of the earth. When the condensation process takes place at a higher altitude than the earth's surface, it creates clouds. Cloudiness represents ...
Read More
Introduction
Clouds can be considered as one of the most complex and influential variables of the atmosphere system in forming of the climate structure of the earth. When the condensation process takes place at a higher altitude than the earth's surface, it creates clouds. Cloudiness represents the percentage of the atmosphere that is covered by clouds. Clouds, as one of the most complex variables of the climate system, besides changing the energy balance, are also effective in the spatial and temporal distribution of many climate variables. Clouds have a lot of temporal and spatial variability and can affect the climate through many complex relationships and affect the water cycle. The investigation of clouds holds great significance as they serve as the bridge between synoptic systems and the Earth's surface climatic conditions. Any alteration in cloud-related parameters can trigger a domino effect, influencing various other climatic variables. It's worth noting that Iran exhibits a lower average cloud cover of 26%, notably less than the global average of 50%. This places Iran in the category of countries with relatively minimal cloud cover.Hence, possessing insights into the atmospheric cloud cover conditions in Iran becomes imperative for early detection and management of hydroclimatic crises, particularly in the context of water scarcity and drought-related challenges.
Data and Methods
In the current research, the cloud data of 93 synoptic meteorological stations of Iran have been used in the daily time period during the statistical period of 1991-2021. The amount of cloudiness is an estimate of the nearest octa (eighth) and values 0 and 8 are completely clear and completely cloudy, respectively. In the present study, Kolmogorov-Smirnov, Anderson-Darling and Lilliefors test were used to determine the normality of the data at the 95% confidence level for annual, monthly and seasonal scales.
In the subsequent phase, we employed both parametric and nonparametric methods to discern trends within the cloudiness time series. The parametric approach involved a linear regression test based on the least squared error method, while the nonparametric method employed the Mann-Kendall test. These tests allowed us to identify data trends, accounting for both normal and non-normal distributions of cloudiness. Furthermore, we explored the interplay between cloud cover and spatial factors, namely latitude and longitude, employing Pearson's correlation coefficient. This analysis shed light on the relationships between these variables. Conclusively, we created a spatial distribution map depicting the extent of cloudiness across various stations. This mapping allowed us to dissect the temporal-spatial distribution of cloudiness, comprehend alterations in cloud cover, and investigate the contributing factors behind these changes.
Results and Discussion
The results of Normality Tests according to the Kolmogorov-Smirnov test showed that all the stations did not have a normal distribution however, during the other two tests, except Arak, Kashan, Sarakhs, Takab, Kahnuj, Ramhormoz and Ramsar, other stations had normal distribution. The tests to determine the trend based on the parametric linear regression test based on the least squares error method showed a decreasing trend in 44 stations and an increasing trend in 3 stations of Ardabil, Qom and Sarab. According to the non-parametric Mann-Kendall test, among the stations without normal distribution, Kahnuj, Ramhormoz and Sarakhs stations have a decreasing trend, and no special trend was observed in other stations. The relationship between the two factors of latitude and longitude with the cloudiness variable using the Pearson correlation coefficient indicates a negative relationship (-0.42) between the cloudiness variable and the longitude factor as the amount of cloudiness in Iran's atmosphere decreases with the increase of latitude. Hwoever, the relationship between cloudiness variable and latitude, a positive relationship (0.75) was obtained as the amount of cloudiness increases with the increase of latitude. The survey of the annual cloudiness map of the stations shows the highest amount of cloudiness is in the South, Southwest and East of Caspian Sea. The lowest amount of annual rainfall was in South and Southeast of Iran. The statistical analysis of annual cloudiness data in Iran showed that the amount of cloudiness in Iran is 27.5%. Examining the normal distribution of monthly and seasonal values indicates the non-normality of the data with the Kolmogorov-Smirnov test, but based on the Lilliefors and Anderson-Darling tests, the winter and spring seasons and the months of December, January, February, April and May had a normal distribution and the autumn and summer seasons and the months of June, July, August, September and October did not have normal distribution. Seasonal and monthly trend with linear regression method shows a decreasing trend in winter and spring seasons and cold months of the year. According to the Mann-Kendall method, there was a decreasing trend in the fall season and no significant trend was observed in the summer season.
Conclusion
The purpose of this research was to investigate the temporal and spatial changes of cloudiness in Iran. The results showed a decreasing trend in 47 stations and an increasing trend in only 3 stations and no significant trend was observed in other stations. Also, in monthly and seasonal scales results indicated a decreasing trend in all stations in the cold months of the year and winter, spring and autumn seasons. Examining the relationship between the spatial factors of longitude and latitude with the cloudiness variable using Pearson's correlation coefficient also indicates a negative correlation with longitude and a positive correlation with latitude, and this indicates a large spatial difference in the amount of cloudiness in the country. In general, it can be said that spatial factors (longitude and latitude) were internal factors in the spatial changes of clouds and climatic systems such as Siberian high pressure, sub-tropical high pressure, westerlies system and moisture from the seas of Oman, India and the Persian Gulf and sometimes the Red Sea as external factors were in the temporal changes of clouds. So, cloudiness was a variable that was directly related to other climate variables. Thus, cloud cover was a variable that was directly related to other climatic variables, and its decrease or increase causes the values of elements such as temperature, precipitation, and humidity to change. Therefore, studying this important climate variable and investigating its changes is very important and especially in the discussions of droughts and water crises, it has a special place.
Agricultural Meteorology
N. Torabinezhad; A. Zarrin; A.A. Dadashi-Roudbari
Abstract
Introduction
Drought is a costly natural hazard with wide-ranging consequences for agriculture, ecosystems, and water resources. The purpose of this research is to determine the characteristics of drought and its types in Iran during the last four decades. Drought turns into different types in the water ...
Read More
Introduction
Drought is a costly natural hazard with wide-ranging consequences for agriculture, ecosystems, and water resources. The purpose of this research is to determine the characteristics of drought and its types in Iran during the last four decades. Drought turns into different types in the water cycle and imposes many negative consequences on natural ecosystems and different socio-economic sectors. According to International Disaster Database (EM-DAT), drought accounts for 59% of the economic losses caused by climate change. Many parts of the world have experienced extensive and severe droughts in recent decades. In Iran, droughts have occurred frequently during the last four decades and have become more severe in the last decade.
Materials and Methods
In this research, we used precipitation, temperature, wind speed, and sunshine hours of 49 synoptic meteorological stations during 1981-2020. Drought has been investigated with The Standardized Precipitation-Evapotranspiration Index (SPEI) in four scales of 3, 6, 12, and 24 months, which represent meteorological, agricultural, hydrological, and socio-economic droughts. To calculate the SPEI, the precipitation variable (P) is analyzed with the cumulative difference between P and potential evapotranspiration (PET). In other words, surplus/deficit climate water balance (CWB) is considered. The FAO Penman-Monteith method was used to calculate PET. Then, using the RUN theory, the characteristics of drought, including its magnitude, duration, intensity, and frequency, were determined for all four investigated scales.
Results and Discussion
The results showed that the frequency of drought events fluctuates from a minimum of 12.13% to a maximum of 18.13% in different regions of the country during 1981-2020. The climatological study of drought characteristics shows that the most frequent drought events occurred in the west, southwest, and southern coasts of the Persian Gulf and northwest of Iran compare to other regions of the country. This is while the duration of the drought period is longer in the eastern and interior regions of Iran. Examining the types of droughts shows that more than 60% of the droughts occurring in Iran are moderate droughts. Moderate and severe droughts are mostly seen in the west, southwest, and northwest of Iran. The duration of Iran's drought varies from at least 3 months in meteorological drought to more than 8 months in socio-economic drought. Therefore, droughts are more frequent in the western regions and longer in the eastern regions. The intensity of drought is also higher in the eastern and interior regions than in the western and northwestern regions of Iran. The decadal changes of drought show that the duration and magnitude of drought in Iran have increased and the severity of the drought has decreased during recent decades.
Conclusion
The intensity, magnitude, and duration of the drought period in Iran increased with the increase of the investigated scales from 3 months to 24 months. Examining the average frequency of drought showed that as we move from meteorological drought to socio-economic drought, the frequency of drought increases, which confirms the previous findings. The eastern and southeastern parts of Iran have experienced a longer duration and larger magnitude of drought than the western and northwestern Iran, which can be caused by the climate conditions of this region, i.e., high temperature and evapotranspiration and less precipitation, and seasonality.
The maximum magnitude of drought in Iran is related to socio-economic drought (SPEI-24) followed by hydrological drought (SPEI-12). This characteristic has increased especially in the last two decades (2001-2020) compared to the previous decades (1981-2000). This is while the magnitude of meteorological (SPEI-3) and agricultural (SPEI-12) droughts do not increase much in the last two decades compared to the previous decades.
Anthropogenic activities play a more prominent role in increasing the magnitude of socio-economic (SPEI-24) and hydrological (SPEI-12) droughts than natural forcing. With the construction of many dams and the digging of countless deep wells, as well as changing the direction of rivers, the water cycle has been completely affected by human activities during the last four decades in Iran. Obviously, anthropogenic activities play an important role in increasing the magnitude of hydrological and socio-economic droughts. In contrast, meteorological and agricultural droughts have not shown many changes in Iran.
The results of the decadal average of drought intensity showed that this characteristic of drought in the last decade (2011-2020) has decreased compared to previous decades (1981-2010). On the other hand, as mentioned earlier, the magnitude and duration of drought, especially for hydrological and socio-economic droughts, have increased in the last two decades (2001-2020). Therefore, the reason for the decrease in the severity of the drought has a statistical explanation before it has a climatic reason because the severity of the drought is calculated by dividing the magnitude of the drought by its duration.
Agricultural Meteorology
S.M. Afzali; J. Khoshhal Dastjerdi; A. Torahi
Abstract
Introduction: One of the most critical human issues globally is producing more food for the world's growing population. The climate of each region is an effective factor in the agricultural sector and the amount of its production. Iran is one of the world's date-producing countries, which ranks second ...
Read More
Introduction: One of the most critical human issues globally is producing more food for the world's growing population. The climate of each region is an effective factor in the agricultural sector and the amount of its production. Iran is one of the world's date-producing countries, which ranks second in terms of date production and exports. This plant has 200 genera and 4000 species, each of which can adapt to arid regions and can have the highest production and economic efficiency in its proper place. It is a monocotyledonous plant from the Palmaceae family that needs at least 10 degrees Celsius for continued growth. Growth will stop at temperatures below 10 degrees Celsius, and temperatures below 4 degrees Celsius will encounter cold stress. This plant is sensitive to environmental conditions and cannot live qualitatively and quantitatively in all hot and dry regions. On the other hand, the palm tree is a plant that lives up to several hundred years, and some of its varieties bear fruit up to 200 years old, but their valuable and economic life is on average about 50 years. It is noteworthy that this tree did not produce an economic crop until ten years ago. Dates have an important role in currency exchange, job creation, food security, and strengthening global competitiveness by providing income from non-oil exports. Therefore, the construction of a palm tree is a risky long-term investment in the country. Dates have different varieties, each capable of adapting to a region of arid regions and can produce the most production and economic efficiency in its proper location. Global warming, its impact on different regions of the earth in the future, and the response of the living creatures of these regions in the last century have led planners and scientists of many disciplines, especially climatology researchers, and in particular agricultural climatologists, to understand climate conditions and design long-lived sustainable plants that can survive in future environmental conditions and have good economic returns, design programs, and awareness algorithms.Materials and Methods: One of the best is the maximum entropy model (MaxEnt). By applying this algorithm, it can be predicted how the species will exist in different regions based on the presence of the species. The present study was conducted by field method, descriptive, and library statistics. The data used included WordClim site data (bioclimatic variables), presence data of two cultivars of date palm, Gantar and Halawi, daily meteorological data, elevation, and land slope based on the suitable land slope for palm tree cultivation, high and low temperatures, and phonological data. CCSM4 model with quadratic scenarios of 2.6, 4.5, 6.0, and 8.5 was used to predict and estimate different country regions in terms of talent for cultivation of two selected date varieties. Due to the higher value of AUC in Scenario 4.5, this scenario was considered as the selected scenario. This study is different from previous studies using the CCSM4 climatic model, new diffusion scenarios (RCP), and prediction of date distribution concerning its cultivars, while previous studies on prediction of date distribution have not paid any attention to it.Results and Discussion: The results showed that the distribution and cultivation area of Gantar and Halawi are different, and in the future, the suitable area of cultivation of Gantar cultivar will decrease, and the suitable area of cultivation of Halawi cultivar will increase. Jacknife test showed that the model successfully predicted the potential of cultivation area based on the AUC criterion and temperature-related biological variables (Bio 1, Bio 6, Bio 8, and Bio 10) had the most significant impact on the distribution modeling of cultivars. Therefore, with the rising temperature, parts of the country, especially the foothills of the plains, become more susceptible to cultivation. So that at present, when the maximum height for the optimal growth of cultivars is about 700 meters, it will reach about 1200 meters in the coming decades. At present, Iranshahr city in Sistan and Baluchestan province has the most desirable area of Gantar and Halawi cultivar cultivation. However, in the next decade, the most desirable cultivation area will be the Gontar cultivar in Ahvaz city and Halawi cultivar in Jask city. It was also found that using WorldClim site data for perennial and especially long-lived plants was not sufficient. Because in these data, high and low temperatures that can destroy the plant during its life or shorten its life and reduce the economic fruit of cultivation are not included, and of course gardening and fruit trees are a long-term investment. The risk of investing should not be increased.
S.M.J. Nazemosadat; L. Abbasi; S. Mehravar
Abstract
Introduction:Based on the research and assessment carried out during the Climate Change Enabling Activity Project under United Nations Framework Convention on Climate Change (UNFCCC) and using the scenarios proposed by IPCC, it is estimated that if the CO2 concentration doubles by the year 2100, ...
Read More
Introduction:Based on the research and assessment carried out during the Climate Change Enabling Activity Project under United Nations Framework Convention on Climate Change (UNFCCC) and using the scenarios proposed by IPCC, it is estimated that if the CO2 concentration doubles by the year 2100, the average temperature in Iran will increase by 1.5-4.5°C which will cause significant changes in water resources, energy demand, agricultural products and coastal zones. The present study is aimed to investigate the characteristics of climate change in Iran and some parts of the neighboring countries. Identifying the spatio-temporal changes in three atmospheric variables comprising perceptible water (PW), specific humidity (SH) and vector wind (VW, U and V components) over 1960-2017 was the main themes of the study. Materials and Methods: Monthly values of these variables during wintertime (January to March) were extracted from the CDC/ Reanalysis 2/ NOAA in 2.5 * 2.5 grids for the period of 1960-2017. The study area locates between 20o to 45o N and 30o to 70o E. After averaging monthly data into seasonal series, as first step, significant changes in the considered series were investigated between two equal periods having 29 years of data (1960-1988 and 1989-2017). In the second step, the 58 years of the study period were divided into five successive decades (1960-2009) and a period with eight years (2010-2017). The Kolmogorov-Smirnov (K-S) field significant test was used for assessing the spatio-temporal difference between the obtained maps associated with various decades. Results and Discussion: According to Figures 1 and 2, for both of the 29-year time-scales (1960-1988 and 1989-2017), PW was maximum (12 to 17 kg/m2) alongside the northern coasts of the Persian Gulf and the Oman Sea. After this, PW had the highest values over the southern coasts of the Caspian Sea (10 to 12 kg/m2). Oppose to these coastal areas, minimum values of this variable with about 6 to 10 kg/m2 were associated with the Zagros mountains. In general, PW exhibited an inverse relationship with elevation. In contrast to PW, SH maximized (4.2 to 5 g/kg) over the Zagros ranges and its relationship with elevation was generally positive. The lowest value of the SH data was about 3.5 g/kg suggesting relatively low variation in the SH data within the country. Compared to the 1960-1988 period, a significant decline was observed in the values of PW and SH in 1989-2017. Although this decline was obvious over all parts of the country, it was slightly significant for the southwestern (northwestern) districts. Compared to the first half of the study period (1960-1989), PW (or SH) decreased by about 2.5 kg/m2 (or 0.6 g/kg) in southwestern and 0.3 kg/m2 (or 0.15 g/kg) in northwestern parts of Iran for the recent half (1989-2017). Differences between wind data during these two time-periods were mostly either northerly or easterly suggesting a significant decrease in the rain-bearing southerly or westerly circulation over 1989-2017. Anomalies of the near-surface wintertime winds were mostly found to be southerly or westerly during 1960-1988 implicating the possibility of moisture transport from the Persian Gulf, the Oman Sea, the Mediterranean Sea, and the Red Sea into the most parts of Iran. Conversely, the anomalies were either northerly or easterly in1989-2017 suggesting less moisture transport into Iran for this recent period. In the decadal time-scale, maximum values of PW, SH, as well as southerly or westerly circulations, were observed during 1960-1969. The given results suggest that the enhanced (or suppressed) values of PW and SH are generally harmonized with the strengthened southerly and westerly (or northerly and easterly) wind anomalies. For this period, prevailing of southeasterly winds over the Caspian Sea enhanced or suppressed the measure of PW, SH over the western or eastern coasts of the Sea, respectively. Even though the mentioned atmospheric circulation patterns were generally similar for the 1960-1969 and 1970-1979 decades, positive anomalies of PW and SH, as well as the westerly and southerly airflows, were slightly suppressed for the second decade. The anomalies of westerly and southerly winds decreased by about one-fifth for 1980-1989 as compared with that in 1960-1969 resulting in a significant decrease in the PW and SH data for this decade. Although these anomalies were slightly positive over most parts of Iran, their weakness did not allow significant improvement in the PW and SH values. The period of 2000-2009 was evaluated as the driest decade of the study period for which the negative anomalies of PW and SH, as well as westerly and southerly circulations, were maximized (in absolute values). In spite of the fact that these undesirable conditions have recovered during the period of 2010-2017, PW and SH were still very low for this recent period. With the exception of the 1990-1999 decade, PW and SH have continuously decreased for the decades after 1970. The rain-bearing southerly and westerly winds have been gradually replaced with dry northerly or easterly wind during the recent periods. Conclusion: The findings showed that the PW and SH distribution patterns are close together in the 29-year periods, the measures were, however, significantly smaller in the second period than in the first. The wind anomalies, which were mostly southerly and westerly in 1960-1988, have been changed to northerly and easterly in 1989-2017. Since the southerly and westerly winds play an influential role in moisture transfer to Iran, their reduction in the second period is consistent with the observed decrease in PW and SH. Among the ten-year periods, the highest positive PW and SH abnormalities are associated with the 1960 and 1969 decade. This positive anomaly decreased over the time. Since a positive trend is observed for 2010-2017, it can be concluded that 2000-2010 is the driest decade of the study period. The positive anomalies of westerlies (easterlies) and southerlies (northerlies) increased (decreased) the magnitudes of PW and SH.
S. Sanjari; M.H. Farpoor; M. Mahmoodabadi; S. Barkhori
Abstract
Introduction Increasing demand for an international classification system as a unique communication tool in soil science has caused development of different systems. Like many other countries, Soil Taxonomy and WRB are the most popular soil classification systems in Iran. Genetic and morphologic ...
Read More
Introduction Increasing demand for an international classification system as a unique communication tool in soil science has caused development of different systems. Like many other countries, Soil Taxonomy and WRB are the most popular soil classification systems in Iran. Genetic and morphologic soil properties are used for soil classification in both systems. However, correlation of the two systems and efforts to harmonize them have been a major concern among soil scientists. Comparing Soil Taxonomy and WRB in gypsiferous and calcareous soils of central Iran, Sarmast et al. (13) reported that WRB using various qualifiers is more effective than Soil Taxonomy. Since no study on soils of Iranshahr and Dalghan Regions located in Sistan and Baloochestan Province has performed and/or no reported data is available, the present research was performed to: 1) study morphological, physical, and chemical soil properties in the area, 2) classify soils based on Soil Taxonomy (2014) and WRB (2015) systems, 3) compare the two systems for soil description in Iranshahr and Dalghan regions as a part of Sistan and Baloochestan Province, central Iran. Material and Methods: The study area starts from Iranshahr (590 m asl) in the center of the province and extends to Dalghan (390 m asl) in west. Alluvial fan, pediment, playa, and hill were among different landforms identified using field studies, topography maps (1:50000), and Google Earth image observations. To cover the maximum soil variations in the area, 10 representative pedons were selected, described, and sampled. Results and Discussions: Calcic, gypsic, anhydritic, argillic, natric, and salic horizons identified after field work and laboratory analysis. Results of the study showed that addition of Yermic Torrifluvent, Yermic Torriorthent, Calcic Gypsiargid, Gypsic Natrsalid, Natric Gypsisalid, Anhydritic Gypsisalid, Anhydritic Calcisalid subgroups to Soil Taxonomy system from one hand, and addition of anhydrite and aquic (for Solonchak reference soil group) qualifiers to WRB system from the other hand, causes a higher correlation and more harmonization between the two classification systems. Meanwhile, the minimum percentage of calcium carbonate equivalent necessary for calcic horizon identification in coarse textured soils including gravel in Soil Taxonomy is also suggested to be added to WRB system. Besides, requirements of salic horizon in WRB system is recommended to be added to Soil Taxonomy. At the same time, soil names in WRB system provide more information and data about soil properties and characteristics in young soils (such as yermic qualifier showing desert pavement) compared to Soil Taxonomy. Soil Taxonomy is not able to properly classify saline soils of arid regions down to subgroup level which is a weak point for this system. That is why newly added Gypsic Natrsalids is suggested for soils with natric, gypsic, and salic horizons in the upper 100 cm of the soil. On the other hand, the requirements of salic horizon in WRB system (the minimum EC content of 15 dS/m and the EC multiplied by the horizon thickness of more and/or equal to 450) are also suggested for Soil Taxonomy. Conclusion: Results of the study for both saline and sodic soils show more capability of WRB system compared to Soil Taxonomy to classify soils. From soil management point of view, natric horizon causes more negative effects compared to salic horizon because Na disperses the soil particles and destroys soil structure and sodic soils need more practices to be improved compared to saline soils. Results for gypsiferous soils also show more capability of WRB system compared to Soil Taxonomy because gypsum content which is important for gypsiferous soils management is properly concerned in WRB system. However, lack of anhydritic horizon in WRB seems to be a weak point for this classification system. That is why it is suggested to be added to WRB (13). Since Soil Taxonomy does not use independent abbreviations for anhydritic horizon compared to gypsic horizon, the Ba and Baa abbreviations are also suggested for Soil Taxonomy to be added.
H. Asakereh; S.A. Masoodian; M. Darand; S. Zandkarimi
Abstract
Introduction: Studies of the atmosphere over the last hundred years have shown that human activities have caused changes in the atmosphere. The tropopause is one of the layers of the atmosphere whose changes have recently been introduced as a sign of a human impact on climate change. The height ...
Read More
Introduction: Studies of the atmosphere over the last hundred years have shown that human activities have caused changes in the atmosphere. The tropopause is one of the layers of the atmosphere whose changes have recently been introduced as a sign of a human impact on climate change. The height of the tropopause is affected by its upper and lower layers (the stratosphere and troposphere). The results of the studies conducted by various researchers have shown that different factors affect the height of tropopause and its changes, which can be divided into two groups. The first group of natural factors (such as changes in solar radiation and weather due to volcanoes, etc.) and the second one is human factors (including changes in greenhouse gases, human-induced changes affecting the ozone of the stratosphere and the production of air vents from human resources, etc.). Thus, altitude tropopause is naturally influenced by spatial characteristics (e.g. latitude and altitude), time (such as the time of year and hours of the day) as well as the frequency of atmospheric actions that determine climatic conditions. Materials and Methods: Compared to the studies performed globally, a limited number of studies concerning the tropopause have been conducted in Iran. Moreover, the applied methods and the length of the dataset were often inadequate. Therefore, in the present study, the daily data of temperature, and geopotential height from the European Centre for Medium-Range Weather Forecasts (ECMWF) for 700 to 50 hpa with a spatial resolution of 0.25 × 0.25 longitude/latitude were applied from 1979 to 2018 for the detection of tropopause. Accordingly, 2491 cells covered across Iran. The LRT was used to detect tropopause. The tropopause is defined as ‘‘the lowest level at which the lapse-rate decreases to 2 ºC/km or less, provided that the average lapse-rate between this level and all higher levels within 2 km does not exceed 2 ºC /km”. In the present study, in addition to changing the position, changing the scale (variance) as well as the shape of the frequency distribution (skewness and elongation) of the tropopause pressure level in each of the pixels on Iran was investigated. To calculate skewness, and kurtosis, daily tropopause height data were used. For each of the months studied, diffraction, skewness, and elongation were extracted using daily data and finally using data during the 40 years. The extracted trends of variance, skewness, and kurtosis were examined for each month. To track the synchronicity and conformity of changes in altitude and trend of tropopause pressure level with the trend of changes in mean monthly temperature in the lower and upper levels of the tropopause and the trend of the temperature difference between the two layers around tropopause was also evaluated over 40 years. In order to evaluate the long-term trend of each of the studied indices (mean, variance, skewness, and kurtosis) in relation to the height and pressure level of the tropopause, linear regression method with least-squares error method was used. Results and Discussion: The results of the study of altitude trend and tropopause pressure level showed that in most of the months studied and in most parts of the country, the trend of changes in tropopause pressure level was not significant at the level of 95% confidence. According to the results obtained for the winter months, it was found that the trend of a tropopause pressure level in December had no statistical significance over Iran at a 95% confidence level. In January and February, the obtained trend was not statistically significant except for southeastern areas. In the summer months, unlike the winter months, the trend of tropopause pressure levels was significant in most regions. During the summer months, in areas where the trend was significant, the trend of tropopause pressure levels was positive. Examination of the trend of tropopause height in terms of meters showed different results with pressure level. During the winter months, the trend was positive in all regions, and in January and February, this trend was significant in many areas, while the summer months did not exhibit a significant tropopause. The results of examining the trend of the low temperature of the tropopause in summer and winter months showed that the observed trend was not statistically significant in December, but in other months, a positive and significant trend was detected. Examination of the temperature trend in the high level of tropopause also showed that the temperature trend in this part of the atmosphere, like the low level of the tropopause in large parts of the country in the studied seasons, lacked statistical significance. Examination of the trend of the temperature difference between high and low levels also showed that the trend of the temperature difference between these two levels was statistically insignificant at the majority of cases. The temperature difference trend of the two levels studied in the summer months was negative and significant at most regions. In other words, the decrease in the temperature difference between low and high tropopause in these two seasons and in some areas indicates a strong decrease in tropopause. Examination of the trend of variance, kurtosis and skewness also showed that the observed trend lacked statistical significance in the two studied chapters at most areas. There was also no relationship between the surface temperature trend and changes in tropopause height. Conclusion: The results of this study showed that tropopause had no statistically significant trend in most areas and months. Moreover, the significant trend was not related to the two temperatures around tropopause and surface temperatures.
Nooshin Ahmadibaseri; A.A. Sabziparvar; M. Khodamoradpour; L. Alados Arboledas
Abstract
Introduction: Surface Solar Radiation (SSR) as the largest source of land-surface energy is an important parameter in meteorological and climatological studies. Limitations in ground-based measurements have encouraged the users to approach low cost and reliable methods to estimate radiation components, ...
Read More
Introduction: Surface Solar Radiation (SSR) as the largest source of land-surface energy is an important parameter in meteorological and climatological studies. Limitations in ground-based measurements have encouraged the users to approach low cost and reliable methods to estimate radiation components, for the regions where the ground-based radiation data are sparse. Different methods have been developed for estimating SSR including empirical models, radiative transfer models, semi-empirical models, and models based on satellite and reanalysis products. In most studies in Iran, empirical methods have been investigated. Despite the simplicity of these models, they do not accurately represent SSR variations because of not considering all the parameters affecting radiation variations, at large spatial scales with different climates. The Global Land Data Assimilation System (GLDAS) is a combination of measured and satellite data that uses advanced land surface modeling and data assimilation methods. One of the strengths of this model that makes GLDAS unique is that it has global coverage, high spatial-temporal resolution and is available for free. GLDAS is a terrestrial modeling system uncoupled to the atmosphere. This work was aimed to evaluate SSR derived from GLDAS using ground measurements over Iran from 2012 to 2015 on a daily basis.
Materials and Methods: In this study, measured SSR in 24 radiometer stations of Iran from 2012 to 2015 was extracted. Since the measured data are associated with some errors, the quality of the data must be checked and screened before use. In this study, Moradi's proposed method was used to control data quality. The studied areas were classified into three zones of coastal, arid and semi-arid climates based on Digital Elevation Model (DEM) and UNESCO climate classification approach. The GLDAS SSR outputs were extracted with a spatial and temporal resolution of 0.25° grid cell and 3-hourly from 2012 to 2015. The GLDAS is one of the LDAS projects and has been extended jointly by the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) and the National Oceanic and Atmospheric Administration (NOAA) National Centers for Environmental Prediction (NCEP). The purpose of GLDAS is to produce high quality temporal and spatial land surface data. GLDAS drives three land surface models: Mosaic, Noah, and CLM. GLDAS assessments SSR at the land surface using a method and cloud and snow products from the Air Force Weather Agency's (AFWA) Agricultural Meteorology modeling system (AGRMET). Since the GLDAS data are created using the gridded Binary format, the nearest neighborhood interpolation method was used to match these data with ground-based data and GLDAS datasets were generated for station points using CDO software. In this study, GLDAS datasets were compared against measured SSR datasets by four validation metrics. The metrics used are determination coefficient (R2), the mean bias error (MBD), the mean absolute error (MABD), relative mean absolute error (RMABD) and root mean squared error (RMSE).
Results and Discussion: Statistical analysis showed that the performance of GLDAS in SSR evaluation is reasonable in Iran with a high-efficiency coefficient of 0.88. Also, it was shown that the GLDAS has a higher ability to estimate SSR under clear sky (warm seasons) conditions than cloudy conditions (cold seasons). Similar to the obtained results, Träger-Chatterjee et al. (2010); Jia et al. (2013); Boilley and Wild (2015) and Heidary Beni and Yazdanpanah (2017) also showed that the ERA- Interim, NCEP-DOE, RegCM4 and angstrom model are also more capable of estimating SSR in warm seasons. Seasonal bias variations at three studied areas showed that the most changes occurred in summer and least changes in winter. The highest overestimation was also observed in the coastal areas in summer and the lowest overestimation in the semi-arid regions in spring. The evaluation of the GLDAS performance against the site measured SSR data suggests that the GLDAS tends to underestimate in 71% of the studied stations. Moreover, the stations located in the arid region provided a better estimation of SSR as compared with semi-arid and coastal locations. These results were compared with those of Boilley and Wald (2015) that showed ERA-Interim and MERRA reanalysis models have high uncertainty in areas with tropical humid climates, and in regions with arid climates, models perform better in SSR estimation. Our findings were also in good agreement with their results.
Conclusion: GLDAS SSR outputs can be used for agricultural studies. This is due to the facts that arid and semi-arid climates are dominant in Iran and the growing season is mostly in the warm season.
tayebeh shojaee; Gholamabbas Fallah Ghalhari
Abstract
Introduction: In order to choose the best forms for each region and invest, the climatic conditions should be considered. Among the climatic elements, thermal indexes are effective factors in the production cycle, and the quality and quantity of grapes. Given the lack of water resources and the threat ...
Read More
Introduction: In order to choose the best forms for each region and invest, the climatic conditions should be considered. Among the climatic elements, thermal indexes are effective factors in the production cycle, and the quality and quantity of grapes. Given the lack of water resources and the threat of climate change, there is a need for potentiometry and clustering of different regions.
Materials and Methods: According to the content and purpose of statistics and information, the hourly and daily climatic data of 200 climate stations were used. In order to compute the required chilling, the CH model was prepared and implemented. According to daily and monthly statistics, climate parameters were refined and investigated. We used a weighting method based on hierarchical approach for accurate decision making and identifying the relative importance of climatic criteria for grape cultivation. For the following climatic criteria, the information layer was arranged through a database of 200 meteorological stations of the Iranian Meteorological Organization. For the following geographic criteria, layers were used in the country. In order to determine the suitable areas for planting grapevine, using the Analytical Hierarchy Process (AHP) method in the Epert choice11 software environment, the criteria and sub criteria were weighted. Then, using the Geographical Information System, the layers were overlapped based on their weight and the final land suitability map for planting grapevine in Iran was obtained based on climatic conditions.
Results and Discussion: Pairwise comparison of criteria and sub-criteria based on hierarchical analysis showed that the criterion of climatic conditions with a weight of 0.63 was considered as the most important criterion in determining suitable areas for grapevine cultivation. Pairwise comparison of the climatic conditions criterion indicated that the sub-criteria of 451 were the highest among the sub-criteria in the grape trees. Temperature sub-criteria exhibited the greatest weight during the slump and growth period. Paired comparison and spatial distribution of the climate-chilling showed that a large part of the country does not supply winter creeps or cold storage for grapevine trees. The southern half of Iran is entirely unsuitable due to the existence of mild winters for commercial cultivation of creeping trees such as grapes. Paired comparison and spatial distribution under the climatic criterion of the slump period demonstrated that largest spatial distribution is allocated to the middle class in the margin of highlands and high latitudes regions. Paired comparison and spatial distributions under the scale of the growth period illustrated that the spatial pattern in this sub-criteria is highly dependent on the altitude and latitude. From the north to the south and from the west to the east, the suitability for growing grapevine decreases. Paired comparison and spatial distributions under the climatic criteria of absolute minimum temperature revealed that in terms of absolute minimum temperature, there is a limitation on grapevine for some regions of Iran. These areas are mainly mountainous belts of the Zagros mountain, the northwest cold region and northeastern Iran. Paired comparison and spatial distribution under the climate criteria of maximum air temperature showed that temperatures above the threshold of 40 degrees Celsius adversely influence the quality and yield of grapevine. In fact, in terms of absolute maximum temperatures, more than half of the country's surface area is unsuitable. Paired comparison and spatial distributions under the geographic scale elevation above sea level showed that suitable altitude areas are limited to the high and mountainous regions of the northwestern, northern, and northeastern Iran. Paired comparison and spatial distributions under the relative climate of relative humidity indicated that due to the relative humidity of the grape vine compared to many fruit trees, the relative humidity in Iran is high for the grapevine tree. Paired comparison and spatial distributions under the climatic criteria of sunshine hours illustrated that the distribution of sunshine hours affects the latitude factor causing an increase in sunshine hours from north to south. A wide range of growing fruit trees in terms of sunshine days can be found in Iran. Therefore, most regions in the country provide unlimited solar radiation for grapevine growth. Paired comparison and spatial distributions under the geographic scale elevation above sea level showed that altitude plays an important role for locating vineyards. Suitable high-altitude areas are limited to the high and mountainous regions of the northwestern, northern, and northeastern Iran. Paired comparison and spatial distribution below the gradient geographic scale showed that planting fruit trees, especially grapes, is more cost-effective in steep slopes. Considering the high adaptability and physiological conditions of the grapevine, almost all regions of Iran, except very high and mountainous regions, are suitable for planting grapes. Suitable vineyard cultivars are adapted to the slopes of mountainous and relatively high mountainous regions in the mid-west, northwest, northeast, and scattered areas of the center, east and south east of the country. The range of cultivating grapevine trees is 42% of the country's surface area.
Conclusion: The results revealed that the climate criterion has a pivotal role for determining land suitability for grapevine trees. The suitable vineyard cultivars are located in the mountainous and relatively hilly mountains in the northwest, northwest, northeast, and dispersed areas of the center, east and south east of Iran. These findings are important for land use planning and spatial planning with emphasis on climatic and geographic capabilities for efficient use of natural resources.
Ali Chavoshian; P.S. Katiraie-Boroujerdy
Abstract
Introduction: Precipitation has an important role not only in the variety of scientific applications including climate change, climate simulations, weather modeling, and forecasting but also in decision making such as water management, hydrology, agriculture, drought, and crisis management. Different ...
Read More
Introduction: Precipitation has an important role not only in the variety of scientific applications including climate change, climate simulations, weather modeling, and forecasting but also in decision making such as water management, hydrology, agriculture, drought, and crisis management. Different temporal resolutions and coverages of data are required for this and other applications. For example, long term meteorological data are needed for monitoring the climate variability and trends and for climate simulation assessments in local and global scales. Also, present data are used to assimilate into forecast models to improve the predictions. Historical and present precipitation data are the main requirements to monitor and predict droughts which help to early warning system and water management decisions in a country. The recent rainfall data are also the primary input of hydrological models to flood forecast in a basin. The accurate estimation of precipitation amount is vital for these applications.
Materials and Methods: However, rainfall is discontinuous and varies greatly both in time and space which makes it parallel with difficulties in the actual measurements. The two main sources of observational precipitation datasets are ground-based rain gauge measurements and space-based remote sensing satellite estimations each one with its own limitations and strengths. Historically, rain-gauge measurements have been considered as the “ground truth”, but they have mostly limited to land surface, the measurements are sparse or nonexistent in some regions like deserts or high topographic areas. Although rain gauges measure rainfall directly, their data are only representative for a limited spatial extent and may be subjected to some errors caused by local effects such as topography or wind-induced undercatch. An alternative approach which can provide relatively homogenous estimates with complete coverage over most of the globe is based on using satellite observations. Therefore, satellite data are capable to estimate precipitation over the oceans and over remote areas where few or no ground measurements are available. The satellite-based precipitation estimates are derived mainly from visible, infrared (IR) and passive microwave (PMW) radiances which are measured by satellites. Although the visible channels cannot be used at night, the IR data are available in fine spatial resolution (about 3-4 km) with high temporal sampling (15 min) which are provided by geosynchronous satellites. Another source of data is PMW that can be used to estimate rainfall more directly. Low-altitude polar-orbiting satellites serve to measure the PMW data. Although, the microwave sensors can penetrate into the clouds and provide more information about the cloud characteristics such as water vapor, cloud particles, and structure of hydrometeors, but at the expense of temporal sampling. In recent years, different algorithms have been developed using the combination of the IR, Visible (VIS) and PWM observations to provide more accurate rainfall estimations in high spatial and temporal resolutions. To demonstrate the similarities and differences between the spatial distribution of different satellite-based and gauge-based precipitation datasets over Iran we compared seven different datasets. For comparisons all datasets are regridded to 0.25-degree latitude longitude spatial resolutions. Then the spatial distribution of the mean and relative standard deviations of annual precipitation of these datasets have been calculated. We also used more than 2000 rain gauges to evaluate the selected datasets. To reduce error only 228 pixels, include at least 3 rain gauges are used for comparisons of spatial average of monthly, seasonal and annual precipitation of gauge and seven datasets.
Results and Discussion: The results showed a large amount of differences in annual precipitation between seven selected datasets. The most differences pronounce in wet areas in the north of Alborz Mountain, in the semi-arid and arid regions of the central desert and in the high mountainous areas of the southern Zagros. The reason for these differences is that not only satellite-based but gauge-based datasets have large uncertainties estimating areal precipitation in such high topographic areas. The satellite products are prone to some errors arising from not fully understood physical process, sampling error and parameter estimation. Therefore, verification of precipitation datasets is one of the most important parts of the data development and refinements. In this paper, the spatial distribution of seven different global-observational precipitation datasets over Iran are compared for the period 2003-2007. At first all datasets were regridded to 0.25° spatial resolutions using linear interpolation method. Then, the mean and relative standard deviation of annual precipitation of the datasets were calculated to analyze the spatial discrepancies between datasets. The areal average of annual precipitation and the contribution of seasonal precipitation were calculated for comparison purposes. The results showed that areal average of annual and seasonal precipitation for 228 selected pixels for PERSIANN-CDR, TRMM, and GPCP which are satellite-based and gauge adjusted datasets are more similar to the rain gauge data than other datasets. The results for the above datasets are even better than CRU and APHRODITE which are gauge-based datasets.
Conclusion: The results showed that the satellite estimates are not capable to show the precipitation (detection and amount) over the coast of Caspian Sea and the high areas of the Zagros Mountain as well as other parts of the country. There are some useful recommendations for data users at the end of this paper. In fact, in this paper our spatial focus is on Iran and we introduced a web address which data users can access freely from one of the most popular and widely used satellite-based products in easy-to-use format only for Iran. The results show considerable differences between the datasets. The difference is about 0.8 times of mean annual precipitation (about 300 mm in a year) for the coast of Caspian Sea. The satellite-based estimations were less accurate over the coast of Caspian Sea and high mountainous area of the southwest of Zagros comparing to other parts of the country. While spring precipitation shows maximum contributions in annul precipitation for in-situ datasets, winter precipitation shows maximum contribution in annual precipitation for other datasets. The results showed that areal average of monthly, seasonal and annual precipitation over 228 selected pixels for PERIANN-CDR, TRMM and GPCP were consistent with rain gauge data. CMORPH and PERSIANN underestimate areal average of monthly and seasonal precipitation over the pixels.
Hossein Mohammadzadeh; Toba Soleymani valikandi
Abstract
Introduction: Tritium is the only radioactive isotope of hydrogen, with a half-life of about 12.3 years, in water molecule which can be used to determine the age of water in a hydrological cycle. Although hydrogen bomb tests entered a lot of tritium into the atmosphere and then into the hydrological ...
Read More
Introduction: Tritium is the only radioactive isotope of hydrogen, with a half-life of about 12.3 years, in water molecule which can be used to determine the age of water in a hydrological cycle. Although hydrogen bomb tests entered a lot of tritium into the atmosphere and then into the hydrological cycle, but at the moment the average amount of tritium concentration in global precipitations is reaching to about 5 TU. The purpose of this paper is to investigate the tritium concentrations in precipitations of the Middle East countries and to determine the tritium concentration in Iran precipitation (especially in precipitations of the west of Kermanshah province) and to determine the relative age of groundwater resources in Paveh, Javanrood, Ravansar and Sarpule Zahab areas using tritium radioisotope.
Materials and Methods: The required tritium data for the Iran and neighbors and for the global precipitations were retrieved from the Global Networks of Isotopes in Precipitation (GNIP) site of the International Atomic Energy Agency (IAEA). To measure the amount of tritium in Kermanshah precipitations, samples were collected from three rain stations, three wells and from nine springs in Paveh, Javanrood, Ravansar and Sarpule zahab areas during fall 2015 and 600 ml in 600 ml water polyethylene containers, all water samples were analysed at Waterloo University Isotope Laboratory.
Results and Discussion: The amount of tritium concentration in precipitations depends on latitude, longitude, temperature, altitude and the vapor mass. The higher amount of vapor and the lower temperature or the higher altitude, decreases the concentration of tritium. In areas such as Karachi, Bahrain and Adena, due to its proximity to the sea and the higher amount of vapor in the atmosphere, the tritium concentration in precipitation is low. In this paper, the tritium concentration in precipitation and groundwater resources of the west of Kermanshah province was measured at the University of Waterloo-Environmental Isotope Laboratory (UW-EIL). Then the average relative age of groundwater was determined. Results indicate that the tritium concentration in precipitation of the west of Kermanshah is about 6.0 TU and it is much lower in groundwater resources. Based on water age division using tritium concentration, the water of precipitations in the west of Kermanshah is modern and the water of groundwater resources are mixture of modern (recently recharge water) and sub modern water (the waters fed before 1950). By determining the amount of electrical conductivity (EC) and the concentration of tritium in the waters of the region, it is concluded that in the direction of flow, with increasing EC and decreasing the amount of tritium, the water age increases. By examining the EC and the relative age of the waters, it can be concluded that in the Sarpule Zahab area, in Ghaleh Shahin plain, groundwater recharge to the alluvial aquifer in Qaleh Shaheen spring area and then it flow in the direction toward Sarabgarm spring. However, in Boshive plain, the groundwater flow from Marab spring towards the Gandab spring. Tritium has a correlation with the air temperature. The higher the temperature, the more the concentration of tritium in the abundant water resources, and the older age for the water sample. In the study area, the average annual air temperature in the Paveh, Javanrood and Ravansar areas are about 15.1, 15.0 and 14.9 degrees Celsius, respectively, and it is about 19.9 degrees Celsius for Sarpule Zahab area. The average concentration of tritium in Pave and Javrroud is about 3.4 TU, however, in Ravansar and Sarpule Zahab areas are about 1.4 TU and 1.1 TU, respectively Therefore, it is evident that the relative age of groundwater is younger in the Paveh region and it is the oldest in Sarpule Zahab region.
Conclusions: The concentration of tritium is associated with the age of water. The lower the amount of tritium is the oldness of the water. The geology and rocks are affected by the movement of water, which is why the age of groundwater resources in the Paveh region due to the development of karst and the rapid transfer of groundwater is less than the Sarpule Zahab and Ravansar areas. On a global scale, the concentration of tritium in the northern hemisphere’s precipitations is much higher than that of in the southern hemisphere, and in the polar regions’ precipitations it is approximately 4 times of the tropical region’s precipitations. By investigating the concentration of tritium in the rain of neighboring countries of Iran it is concluded that the proximity to the sea and the increase of water vapor in the atmosphere have reduced the amount of tritium concentration.
Keyvan Khalili; Mohammad Nazeri Tahrudi; Rasoul Mirabbasi Najaf Abadi; Farshad Ahmadi
Abstract
Introduction: Climate change in the current era is a very important environmental challenge. Our understanding of the impacts of human activities on the environment, especially those related to global warming caused by increased greenhouse gases indicates that, most probably, a number of hydro-climatic ...
Read More
Introduction: Climate change in the current era is a very important environmental challenge. Our understanding of the impacts of human activities on the environment, especially those related to global warming caused by increased greenhouse gases indicates that, most probably, a number of hydro-climatic parameters are changing. Based on the scientific reports, the average temperature of the earth has increased about 0.6 degrees centigrade over the 20th century and it is expected that the amount of evaporation continues to rise. In this case, the atmosphere would be able to transport larger amounts of water vapor, influencing the amount of atmospheric precipitations (21). Low precipitation and its severe fluctuations in the daily, seasonal and annual time scales are the intrinsic characteristics of Iran’s climates. Based on the research background, it seems that no comprehensive study has been conducted on concentration of winter precipitation in Iran. The aim of this study is to calculate the concentration and Trend of precipitation of Iranian border stations over the last half-century.
Materials and Methods: Iran with an area of over16480000 square kilometers is situated in the northern hemisphere and southwest of Asia. Almost all parts of Iran have four seasons. In general, a year can be divided into two warm and cold seasons. In this study, 18 stations were selected among more than 200 synoptic stations existing in the country, for investigating the concentration and precipitation trend.
PCI Index The PCI index has been proposed as an index of precipitation concentration. The seasonal scales of this index are calculated as equation 1(18):
(1)
Where Pi is the amount of monthly precipitation in the ith month. Based on the proposed formula, the minimum value of theoretical PCI is 8.3, indicating absolute uniformity in the precipitation concentration (i.e. the same amount of precipitation occurs every month).
Trend analysis The aim of process test is to specify whether an ascending or a descending trend exists in data series. Since parametric tests have some assumptions including normality, stability, and independence of variables, where most of these assumptions do not apply to hydrologic variables, the nonparametric methods are more preferred in meteorological and hydrological studies.
Results and Discussion: The PCI index was calculated using the monthly precipitation of the selected stations at seasonal and winter time scales over a 50-year period. This period was then divided into two 25-year sub-periods for the investigation of changes in average values of PCI (7). In the first 25-year span, the irregular precipitation distribution has been observed in the Bandarabbas station and its surroundings in winter season. In none of the studied stations, highly irregular precipitation occurred. The highest share of PCI was relatedto the precipitation average distribution class, and the northern, northwestern, and northeastern parts of the country have a uniform precipitation distribution. In winter, within the first 25-year period, the country had ideal conditions in terms of precipitation and its concentration in the mentioned regions. Within the second 25-year period, the intensity of irregular precipitation concentration decreased, as the regions that had confronted strong precipitation irregularities wereadded to regions with uniform concentration. At the seasonal scale and in winter, the country’s share of uniform distribution diminished in the second 25 years, and overall most parts of Iran have been covered by average precipitation distribution. The uniform precipitation distribution in recent years (second 25 years) has decreased in winter in such a way that no uniform distribution has been observed in the northeast of the country and uniform distribution belongedto the Caspian sea border strip, southern regions of west and east Azerbaijan stations (Urmia, Khoy and Tabriz stations) along with Kermanshah, Sanandaj, and Zanjan stations.
Trend analysis of the PCI In winter the Abadan, Ahwaz, Bandarabbas, Birjand, Kermanshah, Sanandaj, Urmia and Zahedan stations experienced an insignificant decreasing trend in PCI. At other stations, an insignificant increasing trend was observed in the PCI series. Overall, 9 out of 18 considered stations, witnessed increasing PCI trend implying increased irregularities in winter precipitation.
The results of Mann-Kendall trend test for precipitation Based on the results it can be observed that in winter Ahwaz, Gorgan, Khoramabad, Kermanshah, Ramsar, Rasht and Sanandaj experienced an insignificant decreasing trend in precipitation. In Khoy, Sanandaj, Tabriz, Urmia, Zahedan, and Zanjan stations, the decreasing precipitation trend in winter was significant. Overall, 12 out of 18 studied stations have been afflicted with a decreasing precipitation trend in winter.
Conclusion: Precipitation Concentration Index (PCI) is an index for determining the precipitation variations in a certain region and PCI analysis can reveal the accessibility to water in an environment. In this study, the PCI was used to analyze the precipitation concentration at two annual and seasonal time scales throughout the Iran (from 1961 to 2010). The PCI zoning results at the seasonal scale demonstrated that precipitation concentration had the same trend within the two 25-year sub-periods. These results also revealed a high PCI in provinces with low precipitation such as Zahedan. These stations, according to Oliver (18) classification, have irregular and sporadic precipitation duringwinter. Overall, the PCI analysis at the seasonal scale indicated that the regions covered by polar-continental, Europe-originated polar-continental and North Atlantic ocean-originated polar-continental have the best precipitation concentration throughout the country. The results of this index provided valuable information for water resources managers in regions with low-precipitation, consistent with research by Gozzini et al (7). The results of modified Mann-Kendall (MMK) test for PCI in Iran revealed a decreasing trend over the last 50 years. Based on the obtained results in winter, the Khoy, Sanandaj, Tabriz, Urmia, Zahedan, and Zanjan stations experienced a significant decreasing trend. The existence of an increasing trend in PCI albeit insignificant reveals changes in Iran's winter precipitations confirmed by Mann-Kendall test for precipitations in 18 studied stations. Overall, it can be concluded that the decreasing trend in Iran's winter precipitation has resulted in increasing PCI and thereby increased irregularities in winter precipitations, especially in winter season.
mohammad jafar nazemosadat; K. Shahgholian
Abstract
The aim of this study is to assess some synoptic characteristics of heavy precipitations in southwestern parts of Iran and evaluate the relationship between them with the Madden-Julian Oscillation (MJO). Research is conducted with regard to distribution of precipitation per month and identifying their ...
Read More
The aim of this study is to assess some synoptic characteristics of heavy precipitations in southwestern parts of Iran and evaluate the relationship between them with the Madden-Julian Oscillation (MJO). Research is conducted with regard to distribution of precipitation per month and identifying their steam sources. Daily records of the November-April precipitation data in Abadan, Ahwaz, Bandar-Abbas, Bushehr, Shahr-e-kord and Shiraz stations for the 1975- 2011 period are collected as well as same panel data for Yasuj station from 1990 to 2011. Rainfall data are sorted in descending order and precipitation values that were fallen within the 5% and 10% of highest records are categorized as the heavy precipitation. The most frequent precipitations occurred in January, February and December. The most frequent heavy precipitations in Ahwaz, Bandar-Abbas, Bushehr, Shahr-e-kord and Shiraz stations occurred in phase 8, while in Abadan station occurred in phases 7 and 8. Apparently, due to the short duration precipitations data at Yasuj station, the most frequent heavy precipitation observed in phase 2.Synoptic maps show that harmonized with eastward movement of convective precipitation in Indian or pacific oceans.Heavy precipitation forms in the west region of Iran and moves toward southwest and south Central of Iran and then appears to Afghanistan.Formation of a cyclonic circulation that encompasses the Mediterranean Sea, Red Sea and Persian Gulf plays an important role for moisture supplement of these storm activities. The synoptic maps have indicated that main sources of these heavy rainfalls are moisture produced at the Arab sea and western parts of the Indian Ocean.
B. Alijani; P. Mahmoudi; D.M. Kalim
Abstract
By paying attention to the increasingly development that we observe in accuracy and correctness of short term predictions and also by consideration to the development of tool and instruments and methods of safeguarding plants against frost we can revise about determining length of growing season period. ...
Read More
By paying attention to the increasingly development that we observe in accuracy and correctness of short term predictions and also by consideration to the development of tool and instruments and methods of safeguarding plants against frost we can revise about determining length of growing season period. So in this study it has taken an action to extract 3 indexes: the length of potential growing season period and the length of risk management. The length of growing season period consists of chronological space between the occurrence of the last frost in spring and the first frost in autumn that is zero centigrade degree according to the threshold. The length of potential growing season was identified as chronological space between the last prolonged 3 days period having zero or under zero centigrade degree in autumn and it's last prolonged 3 days period in winter or the beginning of spring. The risk management was identified according to the space between the first or last frost days with the first or last prolonged 3 days frost. In continuation, for determining these 3 indexes in Iran, the data of minimum daily temperature of 62 synoptic stations for a 15 years period (1991-2007) during the month October to May was received from meteorology station. The result has shown that the length of growing season period in Iran varies from 161 to 365 day. So that Saghez, Ardabil and Shahr kord stations each with 161,167 and 169 day has the shortest length of growing season in Iran and the stations of southern coast like Chabahar, Khask, Bandar Abbas port, Lengeh port and Booshehr is 365 day. But using the index of length of potential growing season period instead of index of length of development period shows that the length of development period will increase from 4 days in Dogonbadan station to 58 days in Gorgan station. The station of Saghez, Ardabil and Shahr kord that had shortest length of growing season period in Iran ,have again the shortest length of growing season in Iran by this new index .But with the difference that the length of growing season period is 198, 202 and 211 days in order ,it means that in proportion to the length of growing season period ,35,34,41 days was added to their development period. The length of risk management period after southern stations that don't have frost ,the stations such as Dogonbadan ,Dehloran and Bam with 4,8,9 days are 3 stations that have the shortest period of risk management .Tehran, Dushan, Rasht ,Gorgan with more than 40 days have devoted the longest period of risk management in Iran.
