فهرست مطالب zahra ghaffari moghadam

Foreign trade is one of the important factors in economic development and provision of foreign exchange revenue. In recent years, the existence of price fluctuations in the oil market has faced many changes in the country's foreign exchange income and has affected the country's economy. And this shows the necessity of diversifying export products and trade and emphasizing the importance of trade in non-oil products. Therefore, it is inevitable to focus on the trade of the agricultural sector with regard to goals such as self-sufficiency and food security and the possibility of high foreign exchange earnings in the said sector. Dates are one of the most important non-oil items in Iran, which have a long history. In terms of date history, Iran has always ranked first in the world.

In this study, the short-term and long-term effect of the real exchange rate, date production and the ratio of the domestic price to the world price on the export volume of this product using the ARDL model and the error correction model (ECM) in Iran during the years 1370-1400 were estimated. Investigating the long-term relationship between model variables, short-term dynamics of the model and the adjustment speed of the short-term to long-term imbalance has been estimated.

The results show that in the short term, the ratio of domestic to foreign prices has a positive and significant relationship on the amount of date exports, and in the long term, the ratio of domestic to foreign prices and the exchange rate have a positive and significant effect on the volume of date exports. Also, the results indicate the existence of a long-term and significant relationship between the variables of the model.

Since the exchange rate has a positive effect on the export of dates, with the increase in the exchange rate, the income from the export of dates increases, and this increases the motivation of exporters to increase the amount of date exports. Reducing currency deviations will increase the export of dates, so it is recommended that the country's foreign exchange policies be adopted to support exports and reduce imports of agricultural products. In this regard, prevention of exchange rate fluctuations as well as clear information about the future trend of exchange rate changes will play an effective role in increasing exporters' income and the amount of exports and maintaining Iran's position in global markets. The ratio of the domestic price to the world price in the long term has had a significant effect on the amount of date exports at level 10%. If the government's policy is to reduce exports based on various policies, especially the preservation of water reserves, an increase in the domestic price compared to the world price (through export duties) is suggested.

Global warming and the loss of freshwater resources have turned attention to promoting crop water productivity by focusing on the role of crops’ embedded virtual water. Indeed, the production pattern based on maximizing water productivity and minimizing virtual water is gradually replacing the traditional patterns that were based on maximizing production and yields.

The present research aimed to present a cropping pattern and water allocation to crops and regions based on the virtual water scenario and water productivity. The research used a bi-level programming model (leader-follower) and applied the objectives of maximizing economic profit and water productivity and minimizing the Gini coefficient and virtual water to optimize irrigation water allocation among irrigated regions and crops and determine the optimal cropping pattern for crops in five regions, including Zabol, Zahak, Nimruz, Hamun, and Hirmand, for 2022-2023.

When virtual water and water productivity were considered, the system’s economic profit was estimated at 3.02 × 1013 IRR and 3.04 × 1013 IRR, respectively. Also, the highest water and cultivation area were assigned to melon and onion.

Considering the Virtual water content (VWC), less water was assigned to crops with higher Virtual water content, i.e., wheat and barley. When the water productivity index was considered, the results revealed that more water was allocated to crops with higher water productivity, such as melon and onion. The proposed model can be used to determine a cropping pattern that considers minimizing virtual water and maximizing water productivity as its objectives.

Water scarcity has become a problem of concern for many cities in the world. Predicting water demand helps policymakers and water suppliers maintain the balance between the supply and demand of urban water resources, thereby preventing water wastage and shortage. Forecasting Urban Water Consumption (UWC) has a significant impress on efficient urban water management in cities in arid regions when considering the implications of climate change.  In this research, five firefly algorithms were used to estimate the consumption of drinking water in the Sistan region for the years 2006-2020 and were compared. The data from 2006 to 2015 were used for training and learning and finding the optimal weight of the model, and the remaining data from 2016 to 2020 were used to test the model. The results of the model showed that 5 different FA models can get possible answers. In the exponential and hybrid models, the relative error in the NDFA algorithm is 0.19, which has the lowest relative error among other algorithms, and in the linear model, the VSSFA algorithm has the lowest relative error with a relative error of 0.196. Therefore, the exponential model and NDFA method have better performance than other models and algorithms. And its prediction accuracy is above 81%. After ensuring the accuracy of the algorithm, the consumption of drinking water was predicted for the years 2023, 2024, and 2025. The results showed that the peak consumption is in July and August and the total consumption in 1402, 1403, and 1404 is equal to 7293, 7558, and 7674 thousand cubic meters, respectively.

Optimal use of dam’s water resources is a serious challenge in water resources management and engineering, due to continuous droughts and water shortages. Therefore, in order to comprehensively management in the used amount of dam’s water resources, it is essential to establish a control mechanism in the release of water resources. In this study, an improved evolutionary algorithm entitled "Adaptive Differential Evolution by Choosing of Dynamic incremental intervals (ADECDII)" was proposed to optimize the single-reservoir water system. Efficiency of the ADECDII approach was to use the dynamic incremental interval selection scheme for parameters adjustment of the classical differential evolution (DE). Problem modeling was defined as a problem of minimization with the objective function of error values between real demand and released water, with one-month time periods between 2008-2018 years, on Baft Dam in Kerman province. ADECDII performance evaluation was compared with six advanced algorithms. Based on the statistical results, lowest average of the dam water shortages with mean error of zero ( ) MCM (Million Cubic Meters) was recorded for ADECDII, which proved the efficiency of the proposed approach in the optimal allocation of released water values. This is while, other comparable algorithms could not report a real shortage of less than 0.37 MCM. The average of runtime for ADECDII was 7.15 sec, which was three seconds longer than DE runtime. Also, ADECDII in the tests of reliability index, vulnerability index, resilience index, sustainability index, difference absolute error values between released water values and total demand in an annual average, and convergence rate clearly showed a higher performance in compared to other comparable algorithms.

Water is a critical input for agricultural production and plays an important role in the sustainable development of the agricultural sector and the economic development of other sectors. Water shortage is one of the major challenges that most countries in the world are struggling with. The great importance of determining the optimal cropping pattern of crops and irrigation allocation planning in the water shortage conditions prevailing in Iran's watersheds is not hidden from anyone. This study aimed to optimize water allocation and determine the optimal cropping pattern of crops in five cities of the Sistan region under different management scenarios.

In this study, a model with a two-level planning approach, the Stackelberg game framework, and a genetic algorithm, was developed to optimize the water allocation between irrigated areas and crops, as well as to determine the optimal cropping area in 5 cities of Sistan region (including Hamon, Hirmand, Zahak, Nimroz and Zabol) to confront different water conditions. Selected products include wheat, barley, onion, melon, watermelon and alfalfa. The problem was solved in the form of nine scenarios, including three scenarios of irrigation efficiency, three scenarios of climatic conditions, and three scenarios of low irrigation conditions, and compared with the baseline scenario.

For water allocation among the studied regions in the baseline scenario, the most and least water was allocated to Zahak and Hirmand areas, respectively. Among the studied crops, the most water was allocated to the melon due to its low water requirement and high economic value compared to other crops, and the least amount of water was allocated to the alfalfa due to its high water requirement; also the melon with 13503.5 ha had the highest cropping area and alfalfa with 4.85 ha had the lowest cropping area in a total of five cities. The total cropping area obtained by the model was 18240.32 ha. The value of the Gini coefficient was 0.0053, which is small and close to zero, indicating that the water allocation between the regions was fair. The total interest rate obtained in the baseline scenario was 5.06 ×1013, which by applying irrigation efficiency scenarios of 50 and 70 percent, the amount of profit has increased by 12% and 34%, respectively, and the cultivated area by 27% and 47% compared to the baseline scenario. And in normal and wetyear conditions, the amount of total profit has increased by 28% and 54%, respectively, and the cultivated area by 40% and 65% compared to the baseline scenario. By applying the low irrigation scenario, the interest rate decreases compared to the baseline scenario, associated with the saving of a large volume of irrigation water, which leads to an increase in the cropping area of crops with higher economic efficiency. Therefore, by applying various scenarios, the cropping pattern moves towards crops with less water requirement and higher economic value.

According to the results, more water has been allocated to crops with higher economic value and less water requirement. Therefore, if crops with less interest rate compared to their water use and crops with high water requirement are removed from the cropping pattern and crops with higher economic efficiency and less water requirement are replaced in the cropping pattern, it can be a good solution to confront water shortage conditions. The increase in irrigation efficiency increased the total interest, thus it is recommended to save water used by plants through the improvement of irrigation technology and increase irrigation efficiency. The proposed model in this study can be employed for correct and efficient planning for agriculture and water resource management in various conditions.

The critical situation of water resources in arid and semi-arid regions of Iran, especially the Sistan region, has faced a serious problem in the process of sustainable development in this region. Insufficient attention to the optimal management of agricultural water resources and the continuation of some current incorrect methods is one of the main factors in the failure to achieve sustainable agricultural and rural development. In this research, with the optimal management of the Hirmand River in the agricultural sector, an attempt has been made to develop the agricultural and rural sectors of the Sistan region. For this purpose, game theory has been used to allocate water between agricultural lands in rural areas of Sistan in 2020-2021. The meta-heuristic algorithm was used to run the game, combining a dynamic genetic algorithm and fuzzy programming method. The results showed that the use of the proposed model could lead to an efficient and fair distribution of water between irrigated areas and different crops so that maximum profit is obtained from this allocation and by increasing irrigation efficiency from 35 to 50 and 70% of the total profit will increase from 314810 to 544390 and 896050 million Rials. According to the results of this study, it is suggested that high-yield crops such as onions and melons be replaced with low-yield crops such as wheat and barley. Also, due to the water crisis in the Sistan region, the results of Stackelberg game modeling in this study can be used for optimal water allocation in the Sistan region.

According to statistics, Sistan region is one of the arid and low water areas. And the issue of water shortage and drought is one of the crises that threaten the Sisan region in the near future. Water and poverty are closely linked, so a strong assessment of water stress is essential to identify areas in need and develop appropriate interventions to reduce poverty. The Water Poverty Index (WPI) is a tool for assessing water stress by linking physical estimates of available water levels with socioeconomic incentives for poverty. It is also a comprehensive tool for managing and evaluating water resources. This study presents the application of water poverty index (WPI) to estimate and compare water stress levels in 5 cities of Sistan region in 2021-2022. The results of the study show that the average poverty index in the cities of Sistan region in the same weight condition is 0.48 and, in the weight, according to AHP method is 0.43. The water poverty index varies from 0.60 to 0.23 among the cities of Sistan. hirmand city has more water stress compared to other cities. In order to deal with water poverty in Sistan region, management and optimal use of water resources, especially in drought conditions, is very important.

One of the largest water transfer projects in the country is the Sistan Plain Pipe Water Transfer Project, which can be used to manage few water in the best way. The purpose of this study is the optimal allocation of water resources in the agricultural sector using game theory and emphasis on the water market in the Sistan region in 2019-2020. For this purpose, the Stackelberg-Nash-Cournot equilibrium model has been used in two general allocation and market conditions.To solve the model, metaheuristic process has been used, which is a combination of Dynamic genetic algorithm and fuzzy programming method. The results showed that with the creation of a water market in the region, the total profit of the system has increased from 58548 to 85932 million Rials, which is a change of 383.75 million Rials. The value of index E decreased with the creation of the market, the rate of these changes is 7.7%, and also the results show that the creation of a water market provides the possibility of fair distribution of water between regions. by reduction the irrigation coefficient and using the traditional irrigation system at the farm level, profits will decrease. Therefore, the formation of a regional water market in the Sistan region, in addition to changing the amount of water allocated to crops in the study areas, has changed the profits of the cultivation pattern and in general leads to improving farmers' incomes and creating justice in allocation. Water flows between the regions of Sistan region.

The disparity in agricultural production unit performance is a critical and fundamental issue that necessitates the implementation of required programs and policies to ensure an equilibrium in the distribution of resources and seeds in order to increase efficiency. Enhancing efficiency can result in economic growth and development in the agricultural sector, as well as rural development. In recent years, the potato has been regarded as the dominant crop in Kabodarahang; policy formulation based on production efficiency has become a necessity, given the importance of production and the rational use of seeds in potato production. Thus, the efficiency, effectiveness, and productivity of production units were determined under uncertain conditions using various level-cut and fuzzy data envelopment analysis methods for potato farms in Kabodarahang; the most efficient units were selected. The result indicates that 14% of producers are efficient or near-efficient. Additionally, 75% of producers operate at a level of efficiency between 70% and 100%. In total, unit 6 is the most productive and stable of the other units. As a result, this unit is chosen as the best producer. Efficiency analysis at various levels reveals that producers operate at a high level of efficiency. Therefore, to increase production, manufacturing technology should be enhanced. Thus, politicians and policymakers should take into account new technologies for planting, growing, and harvesting.

Firefly algorithm (FA) is an effective optimization technique based on swarm intelligence, which has been successfully applied to various practical engineering problems. In this paper a new dynamic firefly algorithm is applied for demand estimation of water of river Hirmand in Sistan area and comparative with different firefly algorithm for 2006-2017 years. The data from 2006 to 2014 are used for learning and teaching and finding the optimal weights of the model, and the rest of data (2015-2017) are applied to test the models. The results show that all five FA variants can achieve promising solutions. But NDFA obtains better performance than four other FA variants and its prediction accuracy is up to 97.98%. After ensuring the accuracy of the algorithm, water demand of river Hirmand from 2018-2020 is predicted. And risk assessment of the water shortage under three scenarios of high, average, and low inflow levels for this years.

By attention to water scarcity, need consideration and improvement irrigation systems, necessary to be done studies about this situation. By regard to climate condition and low irrigation efficiency in our country, encouraging the farmers to use this technology and extending modern irrigation system is inevitable. Using modern irrigation methods with high productivity causes an increase in the total area under cultivation and the crop yield per unit area, but also causes of increasing farmers income. In this study attempt that modern irrigation methods has been effective on productivity agricultural between farmers in province Kerman. And also difference productivity agricultural between modern irrigation and traditional irrigation methods have affected by which factors.

the data were collected by completing 140 questionnaires in south of province Kerman in three town (Jiroft, Anbarabad and Kahnoj) by use random sampling. And then consideration productivity agricultural in two modern irrigation and traditional irrigation systems by use Oaxaca-Blinder decomposition method and Recentered influence function model. Then data was analyzed by software Stata.

the result of production function showed that family size, marriage, total area under cultivation, Machinery and labor family were signification variables on productivity agricultural in traditional irrigation and education and type machine were signification variables on productivity agricultural in modern irrigation. The result of decomposition method showed that ratio of Factors explaining was -17 percent and factors unexplained was -19 percent that signification. In other words if Factors explaining in traditional irrigation was small as this factors in modern irrigation than productivity agricultural increased as 17 percent in traditional irrigation. If rate of return specific factors in unexplained sector in modern irrigation was small as this factors in traditional irrigation than productivity agricultural decreased as 19 percent. Recentered influence function method showed that in unexplained sector, type seed, amount of seed and use of machine in high decile and labor family in low decile were case gap in productivity. In explaining sector age, labor family, education and total area under cultivation in high decile and number household and education in low decile were important factors in gap productivity.

Also the result showed that share of unexplained factors more than explaining factors. And traditional systems less accesses to resource high yield and use of modern irrigation system, could increase productivity agricultural. Therefore can be increased level of production by improve irrigation system and optimum use of resource water.

In this study, yield-water and profit function was used to obtain water demand function in agriculture sector. The results showed that the ratio of actual to potential Evapotranspiration had positive, significant effecton the ratio of actual to potential yield for wheat and barley. Also, square ratio of actual to potential Evapotranspiration had negative, significant relationship. After estimation of product function, water demand function for agriculture sector was obtained by profit function. Price elasticity of water demand for agriculture was -1.10 being less than -1 and showing that price policies can be an important factor in the control of non-optimum use of their valuable inputs.