فهرست مطالب الهام کلبعلی

Determining the future climate situation by using climate models seems necessary to consider in the field of adaptation or reducing the adverse effects of climate change. In this research, the temporal trend of rainfall, minimum and maximum temperature in the four stations in the Qarasu basin and in addition to, investigated using Thiessen's interpolation method. Among the five models of the CMIP6, three models were selected as the best models and used for MME. Biass Correction was done with CMHyd software for scenarios SSP2-4.5 and SSP5-8.5 in periods 2026-2050, 2051-2075 and 2076-2100. The trend of variables in the base period (1990-2014) and future were investigated with Mann-Kendall test and sens slope. The results of analysis significant trends annual average maximum and minimum temperature of all stations and in catchment area according to SSP2.4-5 scenario in two near and middle future periods and for SSP5-8.5 scenario in all three future periods have a significant trend at the 99% level. In analysis significant trend seasonal rainfall according to SSP2.4-5 scenario in the summer season distant future all stations and in near future of the station area of Gorgan regional water company at the 95% level and for the SSP5-8.5 scenario only in the winter season in the distant future Ghafarhaji station has a significant trend at the 99% level. The future monthly rainfall in the catchment area according to scenario of SSP2.4-5 in August at the 99% probability level and SSP5-8.5 in March at the 95% probability level have a significant trend.

This study was carried out to evaluate the economic and technical effects of climate change on the agricultural sector of Ghareso basin in Golestan province. In the first part, using the IHACRES rainfall-runoff model and rainfall, temperature, and monthly runoff data during the base period (1994-2010), the Ghareso river flow was simulated during the period of 2011-2040. Then, the probabilistic status of water resources allocation and provision of agricultural sector was evaluated by WEAP model. In the second part, in order to reduce the negative effects of climate change on the agricultural sector, using the goal programming economic model, optimal cultivation with the goals of minimum water consumption and maximum future profits was determined. The results of the first part showed that runoff decreases in the upcoming periods by 31.34% compared to the base period. In addition, the results of the WEAP model indicate an increase in the unmet need of the agricultural sector in the region under study. This result suggests that with the continuation of climate change in the future to reduce the negative effects in agriculture, the region's cultivation pattern should be changed to remove cotton and increase barley and rice. These changes were identified in the results of the second part of the model through the Goal Programming Model. In the optimal cultivation pattern, the gross profit of farmers in the studied area in the period of 2011-2040 increased from 1386 billion Rials to 1991 billion Rials compared to the base year.

In the present study, dealing with water deficit challenges for Gorgan River Basin has been considered. Golestan province's economy is dependent on agriculture but the occurrence of drought periods reduced the agricultural production and consequently the region's economy is in crisis. Therefore, performing studies for programming and management of the water resources of the province and the water allocation in the margin of Voshmgir dam in Gorganrood basin has a great deal of importance. The issue of the allocation of water resources is proposed in order to maximize the expected profit of the water system. According to the regional water organization policy, one of the main goals of Voshmgir dam water management is the allocation of water between the competing consumers. If the amount of promised water is released in the future, the expected net profit of the system will be realized and if it is not released, the system will experience losses.
In this studyWater supply is considered stochasticand objective function of the model is to maximize the system (Agriculture, Aquaculture and Environment) profit and optimal allocation of water during the programming period using a two-stage stochastic model as follows: Constraint of the available land: Constraint of the available water in each of the main canals: Constraint of the available water: Constraint of the amount of inflow water
Reservoir capacity constraint
Constraint on the maximum and minimum water demand for environmental sector
Constraint on the maximum and minimum water demand for crops
Constraint on the maximum and minimum water demand for warm-water fish
Constraint on non-negativity of the decision variables in the model
The length of the right main canal of this network is about 17.76 km and the length of the left main canal is about 21.338 km. In this study, is considered for the right main canal and is considered for left main canal. Lands under irrigation network are considered in three regions. Right bank regions and sample farm are covered by the network in the right part of the network and the left bank regions are covered by the network on the left. Thus, there is one region in the left side of the network and there are two regions on the right. The major crops cultivated in the agricultural lands of the network include wheat, barley, canola, cotton, alfalfa, sunflower, rice, cotton-melon, and maize. Due to the random nature of the river flow to the dam, fixed and determined data cannot be used to calculate the volume of water entering the irrigation system, for this reason, using simulation techniques, we can predict the future behavior of the system for each reservoir. The results of the study showed that only agriculturalsector suffers from water deficit and target water demand of the other sectors is supplied and there is no deficit of water for these sectors and target water demand, lack of water and the final allocation of water in the agricultural sector are declined under different efficiencies of irrigation. If other sectors are remained unchanged and irrigation efficiency did not affect them, it is because irrigation efficiency has a direct impact on the water use in agriculture and decreases by increasing the efficiency of the allocated water to this sector and the amount of water stored in the reservoir for the coming year is added. By increasing the efficiency of irrigation which has a direct impact on water use in agriculture sector, the amount of water deficit reduced as a result of the increased system profit.
The results showed that there is no water deficit for aquaculture and environmental sectors in the scenarios of dry, wet and normal years and the target water demand of these sectors is supplied. However, the amount of water deficit in agricultural sector in dry year with the probability of 18% and under the efficiencies of 37, 45 and 51 percent would be 40.98, 23.67 and 14.07, respectively. With the increase in efficiency, water demand in agriculture, water deficit and ultimate allocation of water to this sector are decreased and system profit under different efficiencies is increased. Based on the obtained results, highlighting the irrigation efficiency and allocating the minimum water demand of the sectors is recommended.

Water quality refers to the chemical, physical and biological characteristics of water. It is a measure of the condition of water relative to the requirements of one or more biotic species and or to any human need or purpose. It is most frequently used by reference to a set of standards against which compliance can be assessed. The most common standards used to assess water quality are related to health of ecosystems, safety of human contact and drinking water. Some studies have focused only on chlorides alone without considering the nitrates. Reports of harmful effects for human health have been reported only for nitrates. Therefore, reducing nitrates level below the specifications of WHO may yield ‘‘healthy’’ water. On the other hand, high levels of chlorides may render the water undrinkable due to its salinity. In other words, focusing only on chlorides would not solve the problem since people would rather drink non-salty water than water with high level of nitrates which is proved to be dangerous in terms of health. This research considers both nitrates and chlorides using goal programming, which provides a way of striving toward more than one objective function simultaneously. It seeks to establish a specific numeric goal for each of the objectives, and then seeks for a solution that minimizes the weighted sum of deviations of objective functions from their corresponding goals. The purpose of this study is to achieve an optimal combination for drinking water according to the World Health Organization standards and the maximum desirable standard of groundwater in the study area of Aghala using weighted goal programming model. Goal programming formulation: Assuming that we have () wells, the amount of chlorides in the th well is () mg/l and the amount of nitrates is () mg/l. Moreover, the ith well can discharge the amount of S () at a given operational level. Since the levels of nitrates and chlorides are high in some wells and low in others, it is known that mixing of certain proportions from given wells will help achieve the required objective. It is also assumed that there are () reservoirs (destinations) each of which can accommodate a certain amount of water that satisfies the demand of the specific region. Let () represent the demand required for reservoir () and ()the amount of water () discharged from well () to reservoir (). The maximum allowable amount of chlorides per liter (WHO standard) is (), while the maximum allowable amount of nitrates according to WHO standards is (). Therefore, the writers formulated a goal programming model of optimal water allocation in Aghala region as follows (All the symbols are difided in the first table of the text): a)Objective function b)Well capacity constraints c)Reservoirs capacity and demand constraints d)Balance constraint amoang the nodes e)Groundwater reservoirs capacity f)Air reservoirs capacity g)Chlorides balance constraints h)Nitrates balance constraints i)All variables are ≥0. The set of constraints in Eq. (b) guarantees that the total amount of the discharged water from certain wells does not exceed their capacity. While the constraints in Eq. (c) require that the amount of water supplied to a given reservoir from given wells does not exceed the capacity of that reservoir. Eq. (d) represents balance constraint among the nodes. Eqs. (e) and (f), respectively, represent groundwater and air reservoir capacity in the case study area. Eqs. (g) and (h), respectively, also represent the chlorides and nitrates balance before and after mixing. The assumption in the (chlorides/nitrates) balance constraints is that there are no reactions due to water mixing which may decrease the amounts of both elements under study. Therefore, this assumption, though approximate, guarantees that the levels of nitrates and chlorides can always be equal to or less than the amount determined by World Health Organization (WHO). Moreover, it is assumed that the system experiences no loss of nitrates as shown by preliminary experiments. In other words, the results will always be on the conservative side. Solution of the above model results in obtaining combination of wells and the amounts of water from each well. This research describes a mathematic programming model dealing with achieving an optimum mixture of water from different underground wells, each having different amounts of nitrates and chlorides. The amounts of chlorides and nitrates in each of the wells may be higher or lower than the World Health Organization (WHO) standards. Therefore, the optimum mixture would be the one that meets WHO standard which is 250 mg/l for chlorides and 50 mg/l for nitrates. A goal programming model was developed to identify the combination of wells along with the amounts of water from each well that upon mixing would result in minimizing the deviation of the amounts of chlorides and nitrates from the standards of WHO. Application of the proposed model to the real case example (Aghala region) demonstrates the reliability and flexibility of the model. The most important results of this study showed that according to the WHO standards and the difference elements of each the wells, water withdrawal of the combination of the wells is an appropriate way to allocation of reservoir water. The purpose of this study is to achieve an optimal combination for drinking water according to the WHO standards and the maximum desirable standards of groundwater in the Aghala region using weighted goal programming model. In this region, there are 4 groundwater wells, 6 air reservoir and 2 ground reservoir (to save and transport water to the air reservoir) to supply drinking water for 17 villages. The results of this study also showed that the amount of water withdrawal in the wells in the WHO standard and maximum desirable standard is different. The most water withdrawal in the condition of WHO standards and maximum acceptable standard is belonging to well number 3 and the least withdrawal amount is belonging to well number 1 due to high concentration of nitrate in this well. According to the results in the maximum acceptable standard, there was not water withdrawal of well number 3 because of the high concentration of nitrate in this well. Therefore, according to the WHO standards and the difference elements of each the wells, water withdrawal of the combination of the wells is recommended. Finally, wells with levels of nitrates and chlorides that are highly intolerable can be used for drinking purposes upon mixing.

Agricultural sector to meet the requests such as a higher yield، less pollution and fulfill consumer demands due to increasing scarcity of resources is under pressure. According to the importance of efficiency in productivity growth، this index can play an important rule، especially in developing countries، for the development of agricultural systems in order to meet these requests. The aim of this study was to evaluate the technical، economic and allocative efficiency of producers of saffron for Qaen region using data envelopment analysis. Information and data is collected through completion 50 questionnaires in year 2011-2012. Results show that average technical efficiency، allocative and economic in condition of constant return to scale are 0. 86، 0. 92، and 0. 88 and in condition of variable return scale are 0. 89، 0. 92، and 0. 80، respectively. Also، according to the results obtained، educating and advising farmers to the proper use of available resources، and promotion، and the use of appropriate technologies such as improved efficiency is recommended.