Geographic Data
Hamed Asghari; Mohammad Reza Fallah Ghanbari
Abstract
Extwnded Abstract
Abstract
Introduction: How to invest and choose the right place to build a factory is one of the issues that is of vital importance for factories / companies or organizations due to its effects on factors such as performance, profitability, competitiveness, survival and various criteria ...
Read More
Extwnded Abstract
Abstract
Introduction: How to invest and choose the right place to build a factory is one of the issues that is of vital importance for factories / companies or organizations due to its effects on factors such as performance, profitability, competitiveness, survival and various criteria such as social, economic, environmental, quality and Quantities and other goals are always noticeable to investors and managers.
Materials & Methods: Since decision-making in this field is strategic and as a result, the incomplete information of experts in conditions of uncertainty may reduce the success of future exploitation; Therefore, researchers have introduced different methods to choose the right place; D number theory as an extension of Dempster-Shafer theory in locating, while solving the deficiencies in Dempster-Shafer theory, takes into account the lack of expert information in forecasting. In this research, due to the significant amount of demand and sensitivity in the correct direction of capital resources, considering the high amount of capital required and the great importance in choosing the right place in the geography of Iran to achieve success, and that investing in this industry has always been attractive, while choosing criteria with The importance of investigating the selection of a suitable location for the construction of an edible oil refinery in thirty-one provinces of the country with the combined method of Analytical Hierarchy Process and D-Number Theory (D-AHP), due to its ability to analyze data under conditions of uncertainty that can provide a more realistic estimate , has been investigated.
Results & Discussion: the factors affecting the research problem of this research in the form of a combined method (D-AHP) and based on the consensus of the opinions of ten experts and experts have been helped with the help of brainstorming, which include: access to Raw materials, provincial demand, fixed capital costs such as land, etc. and the production capacities (factories) in the region and the frequency of consumption in the neighborhood of the province and the potential threat to the industry in case of a favorable focus are based on the behavior of consumers and political and social factors. Based on the hierarchical structure, the paired relations of D numbers for the criteria, sub-criteria (1 to 17) and options at different levels of investigation and weights have been calculated with this method, and the criteria of access to raw materials (crude oil) and provincial demand are the most important criteria. Finally, the important weights and ranks of places (provinces) in relation to the overall goal have been calculated and prioritized. Important criteria include: access to primary oil raw materials (distance from ports), fixed capital costs such as land, etc., the amount of demand in the provinces, the amount of previously created production capacities, the frequency of consumption in the neighborhood of the provinces, the lifespan of the industry in The future and political and social factors have been investigated and evaluated for 31 provinces of the country with the combined method (D-AHP) and with the consensus opinion of ten experts in the field of Iranian oil industry.
Conclusion: Therefore, the suitable place for investment in the future according to the importance coefficient of the criteria and sub-criteria and in the order of priority are as follows: provinces; Tehran (first priority), Semnan (second priority), Alborz (third priority), Central (fourth priority), Mazandaran (fifth priority), Isfahan (sixth priority), Qom (seventh priority), Fars (eighth priority), Lorestan (priority 9th), South Khorasan (10th priority), Khuzestan (11th priority), Kahkiloyeh and Boyar Ahmad (12th priority), Zanjan (13th priority), Hormozgan (14th priority), Kerman (15th priority), Yazd (16th priority), Chaharmahal and Bakhtiari (17th priority), Bushehr (18th priority), Qazvin (19th priority), East Azerbaijan (20th priority), Razavi Khorasan (21st priority), Hamadan (22nd priority), West Azerbaijan (23rd priority) ), Gilan (24th priority), Kurdistan (25th priority), North Khorasan (26th priority), Ardabil (27th priority), Sistan and Baluchistan (28th priority), Ilam (27th priority) 9th), Kermanshah (30th priority), Golestan (31st priority). Finally, the important weights and ranks of the places (provinces) have been calculated and prioritized in relation to the overall goal, which will facilitate optimal decision-making and appropriate selection for new investment and prevent waste in the consumption of capital resources and strategic planning in the long term and prevent It helps and prevents the crisis of reduction of national gross product and reduction of capacity or closure of factories, which will lead to unemployment of many employees and activists in this field and social consequences. And it shows the rational policy making to reach the desired situation.
Seyyed Keramat Hashemi-Ana; Mahmud Khosravi; Taghi Tavousi; Hamid Nazaripour
Abstract
Extended Abstract Introduction Precipitation is one of the vital climatic parameters that plays a major role in human life. Therefore, the impact of Precipitation in occurrence or non-occurrence of droughts and dry spells have been very effective. Identification and extraction length of dry spells ...
Read More
Extended Abstract Introduction Precipitation is one of the vital climatic parameters that plays a major role in human life. Therefore, the impact of Precipitation in occurrence or non-occurrence of droughts and dry spells have been very effective. Identification and extraction length of dry spells in arid and semi-arid regions are very important. According to the most recent climate classification that has been done, about 90 percent of the areas of Iran are located in arid and semi-arid climate, and more than 40 percent are facing a severe water crisis. Therefore, understanding the behavioral mechanisms of dry spells have a great significance in arid and semi-arid areas like Iran, especially with the pose of the phenomenon of climate change that caused the worsening dryness and desertification in some of the regions. Many researches simulated dry spells with climate change approach and use of the output of AOGCM models. Researches in this category are in less numbers, but the most recent research has been done by the authors (hashmy titles et al., 2015), investigating and modeling the length of dry spells in the Southwestern area of Iran. The aim of this research is to examine the Validation of AOGCMs Capabilities for Simulation Length of Dry Spells under the Climate Change and Uncertainty in Iran Materials & Methods According to the aim of this research, we used two databases in this study. The first database involves collecting and analyzing all data base information (minimum temperature, maximum temperature, rainfall and sunshine) on a daily scale in 234 synoptic stations (with different statistical period). But the format for the data station and point during the period of statistical modeling was needed for more than 30 years, which has a large statistical defects were excluded, and finally 45 synoptic stations that have favorable conditions (the maximum area coverage and continuous and reliabledata) were selected for the final processing of the first data base. The period of 1981-2010 was used as the base period.The second database contains data provided by version 5 models (LARS-WG) and on emission scenarios (B1, A1B, A2) from AOGCM models for the 2050s to be downscaled. In fact, this data is the first data base (minimum temperature, maximum, precipitation and sunshine) prepared based on the format models for analysis and predicting climate change, after downscaling it. Because this research was based on study and extraction length of dry spells in the range of long-term with the approach to climate change, so the methodology is based on several stages. At first, verification (validation) of LARS-WG, to ensure efficiency in the process model simulation will be discussed. Then the performance and capabilities of 15 AOGCM models in the new version of Lars-wg will be assessed. At the end, the precipitation threshold is defined and extraction of the longest length of dry spells and comparing it with the maximum length of the dry spells will be simulated. Results & Discussion After calibrating the model of statistical properties (comparison tests T, F and P values (decision criteria), all stations were used to confirm the validity of the model. The results of this calibration indicate that in more than 96% of the stations, for the minimum and maximum temperature and sunshine model, show high accuracy (results of error in Dezful and Gorgan stations were greater). In all of these stations like Abadan station, variables significant (P-value) were at./05. It is acceptable that the data generated is random.Considering the bias error, at more than 95 percent of stations there were very good agreements between the observed and modeling data (for every 4 variables). Based on the principles of (1 to 3), and using statistical methods and indicators, the AOGCM models to simulate and extract during dry spells were examined and it was found that two models (Hadcm3 and GFDL-CM2.1) had maximum performance (correlation) and the lowest error in estimating for simulation data precipitation. The model (INM-CM3 and NCPCM) have least amount of correlation and efficiency. To estimate the maximum length of dry spells Hadcm3 results were used under scenario (A2 and B1) for the decade 2050 and the use of the results of other models was skipped in this research. Maximum dry spells in Iran comply with dryness condition in central and eastern areas. So that the country could be on the threshold of ./1 mm divided into 6 orbital regions of the northern circuit during the period of 37 days (in Rasht station) minimum and 351-day observation period in Southeastern Chabahar stations. The values show that the threshold of ./1 mm at more than 65 percent of the area’s dry spells over 7 months there was no rain on them yet. With a threshold of 5 mm needs maximum length of dry spells that lasted about a year with 364 days in Yazd station. That is roughly the size of 5 mm precipitation a year not registered at this station. Conclusion Modeling dry spells by computing scenarios of climate change and taking into consideration uncertain resources at the AOGCM models output, showed that based on the worst-case scenario (A2), and the most critical situation (2080), the average temperature of the country has increased 2.7 degrees (ºC) and Despite increased precipitation in some Stations, the average rainfall is facing a 33% reduction in the whole country. According to the most optimistic scenario (B1), the average temperature of the country is increasing by 1.4 (ºC) and the precipitation is decreasing by 14% in relation to the observation period. The results of the uncertainty examination for dry spells in Iran showed that in both 2050s and 2080s and based on all three scenarios (B1, A1B, A2), length of dry spells increases in all areas of Iran. Most of the changes in length of dry spells belong to the northwestern areas of Iran (Urmia, Khoy, Kermanshah, Hamedan and Lorestan).
Mohsen Abbasnia; Taqi Tavousi; Mahmood Khosravi; Toros Hossein
Abstract
Recognizing and evaluating the climate changes in the coming decades is absolutely necessary for the purpose of appropriate environmental planning in order to adapt and mitigate its effects. In this research, the SDSM model was successfully calibrated and validated (1981-2010) tocomparatively analyze ...
Read More
Recognizing and evaluating the climate changes in the coming decades is absolutely necessary for the purpose of appropriate environmental planning in order to adapt and mitigate its effects. In this research, the SDSM model was successfully calibrated and validated (1981-2010) tocomparatively analyze and explore the future maximum daily temperature variations over Iran forthe two future periods of (2041-70 and 2071-99) and based on the output of two general circulation models of atmosphere, namely, Hadcm3 and CGCM3 under the existing emission scenarios (A1B, A2, B1, B2), relative to the baseline period of 1981-2010. In other words, with regard to the uncertainty for the maximum daily temperature of the future data, downscaling was performed in 7 synoptic stations as the climatic representatives of Iran. Analysis of the output uncertainty showed that CGCM3 model under the B1 scenario among all different models-scenarios has had the best performance in simulating the future temperature. Also, the findings of the research on the studied stations indicate that the temperature in Iran in the middle and final decades of the 21st century increases in averagebetween 1 to 2 degrees Celsius, which based on different scenarios of the Hadcm3 model, this temperature increase has been higher compared to the CGCM3 model. In terms of spatial dispersion of the changes in the GIS environment based on the output of all scenario-models, the lowest temperature increase was observed at Bandar Abbas station located on the south lowland coast of Iran, and on the contrary, the temperature rise reaches the maximumat the Tabriz station located onthe northern latitudes and highland and mountainous regions of Iran. In total, the important and effective factors in the future changes of Iran's temperature can be classified into three groups: factors of altitude, latitude and atmospheric humidity, because, based on all the outputs of model-scenarios, the stations located on the northern latitude elevations of Iran will experience the highest temperature rise compared to the stations located on low-altitude and adjacent to the southern coast of Iran.
