Journal of Agricultural Economics & Development

Abstract Abstract
Title
Policies and Strategies for Mitigation of Greenhouse Gases Emissions in Agricultural Sector of Iran
Introduction
Greenhouse gases such as carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O), and F-gases (Chlorofluorocarbons (CFCs), Hydrofluorocarbons (HFCs), and Perfluorocarbons (PFCs) such as C₂F₆, CF₄, SF₆, and NF₃) play a key role in increasing global warming and intensifying climate change through their absorption and re-emission of thermal radiation. Among economic sectors, agriculture significantly contributes to these emissions via crop cultivation, enteric fermentation in livestock, application of chemical and organic fertilizers, rice paddies, and energy consumption. The agricultural sector of Iran contributes a considerable amount to the total greenhouse gases emissions, thereby playing an important role in climate change. This study aims to quantify greenhouse gases emissions from Iran’s agricultural sector and identify policies and strategies for emission mitigation.
Materials and Methods
Greenhouse gases emissions from agricultural sector of Iran were estimated using data on livestock, fertilizer amount use, rice cultivation, and energy consumption. All emissions were converted to CO₂-equivalent (CO₂eq) using Intergovernmental Panel on Climate Change (IPCC) Global Warming Potential (GWP) values, allowing aggregation of total emissions and comparison across sources. GWP indicates how much energy one ton of a given gas absorbs over a specific time period (usually 100 years) relative to one ton of CO₂. Carbon dioxide, with a GWP value of 1, serves as the baseline and can remain in the atmosphere for thousands of years. If a gas has a GWP of 10, it means that one kg of that gas traps ten times more heat than one kg of CO₂.
Results and Discussion
Studies indicate that agricultural sector of Iran contributes significantly to greenhouse gases emissions. Major sources include chemical and organic fertilizers (18.3 Mt CO₂eq), enteric fermentation in livestock (20 Mt CO₂eq), on farm electricity application (19 Mt CO₂eq), natural gases usage (11 Mt CO₂eq), fossil fuel consumption for agricultural machinery (8 Mt CO₂eq), and rice cultivation (1 Mt CO₂eq), totaling 78 Mt CO₂eq. Indirect emissions from soil carbon release, livestock grazing, and crop residue burning are estimated about 25 Mt CO₂eq. Overall, total agricultural emissions are approximately 103 Mt CO₂eq, representing about 10% of Iran’s total greenhouse gases emissions. These findings indicate that official estimates by organizations such as IPCC and United Nations Framework Convention on Climate Change (UNFCCC), relying on approximate data and lacking large-scale field measurements, likely underestimate actual emissions, highlighting the need for revision and careful consideration in national policy-making.
Conclusion
The increase in greenhouse gases emissions has significantly impacted the global climate, including a 1.6 °C rise in average temperature, glacial melting, altered precipitation patterns, increased evaporation, and depletion of surface and groundwater resources. While Iran and several other countries examined in this study such as India, Mexico, Turkey, Pakistan, and Egypt were unable to reduce emissions between 2005 and 2023, experiences from the United States demonstrate that supportive legislation and dedicated funding at the policy level can effectively reduce greenhouse gases emissions. Inefficient use of nitrate fertilizers is one of the main sources of greenhouse gases emissions in the agricultural sector, especially in countries like Iran, where nitrogen use efficiency is low. In this context, allocating a portion of Iran’s gross domestic product (GDP) to support low carbon agriculture is recommended. Strategies such as using sustained- or controlled-release fertilizers (SRF/CRF), promoting renewable energy, gradually transitioning from traditional to industrial livestock systems, applying methane-reducing additives and vaccines, and implementing integrated farming systems like agroforestry can be effective. Achieving sustainable, low-carbon agriculture in Iran requires a comprehensive approach based on real data, improved input management and production practices, renewable energy infrastructure, and legal, financial, and research support for low-carbon technologies.
Acknowledgement
This research is financially supported by the National Agriculture and Water Strategic Research Center of the Iran Chamber of Commerce, Industries, Mines and Agriculture (ICCIMA) under grant No. ص/10/2/960. Any findings, inferences and opinions, expressed in this study are those of the authors and do not necessary reflect the official standing of the ICCIMA. The authors declare that they don’t have any conflict of interests relative to this study.
Keywords: Carbon sequestration, Climate change, Global warming, Methane, Nitrous oxide.
Keywords: Carbon sequestration, Climate change, Global warming, Methane, Nitrous oxide.
Keywords: Carbon sequestration, Climate change, Global warming, Methane, Nitrous oxide.

Abstract Abstract
Introduction:The agricultural sector is considered one of the important pillars of sustainable development in various countries due to its fundamental role in ensuring food security, creating employment, preserving natural resources, and supporting economic development. In addition to meeting food demand, this sector has an impact on the growth of production, creation of added value and the development of rural areas through extensive links with other economic sectors. Agriculture is considered a cornerstone of national economies due to its vital role in ensuring food security, creating employment, preserving natural resources, and contributing significantly to non-oil exports. This fundamental status underscores the sector’s substantial value to the national economy through extensive backward and forward linkages. Furthermore, agriculture possesses a significant potential to stimulate production in other economic sectors; consequently, a decline in agricultural output can reduce value-added across the broader economy. In several developed nations, the agricultural sector ranks as the primary source of employment, positioning it as a pivotal component that contributes to socio-economic stability. The deep and multifaceted interconnections of the agricultural sector with other economic domains establish it as a driving force for growth and sustainable development at national and regional levels. However, climate change, manifesting in phenomena such as consecutive droughts, devastating floods, unprecedented temperature increases, and disruption of regular rainfall patterns, poses a serious threat to the sector’s productive capacity, presenting structural challenges to food security and the livelihoods of its stakeholders. Chaharmahal and Bakhtiari Province, as a significant agricultural hub, due to its climatic sensitivities and heavy reliance on surface and groundwater resources, necessitates a transition towards “climate-smart agriculture.” The primary objective of this research is to conduct a multi-dimensional evaluation (economic, socio-environmental, and technical-institutional) of climate change adaptation strategies and to provide a scientific decision-making framework for local stakeholders.
Materials and Methods: A hybrid decision-making framework integrating the Fuzzy Delphi Method (FDM), Fuzzy Analytic Hierarchy Process (FAHP), and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was employed. First, potential climate adaptation strategies were identified through a comprehensive review of national and international literature. Subsequently, the Fuzzy Delphi Method was applied with the participation of nine experts (five university faculty members and four specialists from the Agricultural Jihad Organization) to screen and confirm the ten most appropriate adaptation strategies. In the second stage, the relative weights of the economic, social, environmental, and technical–institutional criteria and their corresponding sub-criteria were determined using FAHP based on the judgments of sixteen experts (five university faculty members, six agricultural specialists, and five managers from the Agricultural Jihad Organization). Finally, the selected adaptation strategies were prioritized by integrating the FAHP-derived weights with the TOPSIS method.
Results: The findings from the FAHP analysis indicate that the “economic” and “environmental” criteria are the most critical components in the innovation adoption process. Specifically, the sub-criterion of “Financial Return and Profitability” with an overall weight of 0.1685 and “Sustainable Water Resource Management” with a weight of 0.1364 were identified as the primary priorities. In the final ranking, the option of cultivating climate-resilient crop varieties secured the first rank with a score of 0.719. This strategy directly addresses farmers’ livelihood concerns and climatic limitations by reducing water requirements and maintaining yield stability. Crop rotation combined with cover cropping ranked second with a score of 0.700, highlighting the importance of ecosystem-based approaches and the enhancement of soil health (weight 0.0848). The options of conservation tillage (with a score of 0.668) and smart irrigation (with a score of 0.654) also achieved subsequent ranks. Conversely, technologies such as the Internet of Things, due to their need for specialized knowledge and technical infrastructure, and crop insurance, owing to its reactive nature (compensation for losses rather than prevention), received the lowest priority.
Conclusion: The findings indicate that economic performance, sustainable water resource management, and institutional capacity are the key determinants in prioritizing climate-smart agricultural strategies. Among the evaluated options, cultivation of climate stress-tolerant crop varieties and crop rotation with cover crops emerged as the most effective adaptation strategies. These findings suggest that policies promoting Climate-Smart Agriculture should prioritize economically viable, resource-efficient, and practically implementable strategies. Accordingly, strengthening agricultural extension services, promoting the development and dissemination of climate-resilient crop varieties, and designing targeted economic incentives for the adoption of prioritized adaptation measures can significantly facilitate the transition toward climate-smart agriculture.
Keywords: Climate Change; Climate-Smart Agriculture; Multi-Criteria Evaluation; FAHP; TOPSIS
JEL Classification: Q10; Q15; Q18; Q54

Abstract Among different food groups, animal-based products systematically exhibit the highest greenhouse gas emission intensities. Life cycle assessment (LCA) evidence indicates that beef and lamb have the greatest emission intensities, while poultry, eggs, and dairy products are associated with comparatively lower levels, although they still emit substantially more greenhouse gases than plant-based food sources. These differences are primarily driven by processes such as enteric fermentation, methane emissions, feed production, and land-use change associated with livestock feed cultivation. Consequently, the composition of household food baskets plays a critical role in determining total emissions, and even modest shifts in consumption patterns can significantly alter dietary carbon footprints. In high-income countries, dietary transitions are largely influenced by environmental awareness, health policies, and changing consumer preferences. In contrast, in developing countries, consumption patterns are more strongly shaped by economic variables such as income levels, relative food prices, and economic uncertainty. Therefore, reductions in high-emission food consumption do not necessarily reflect deliberate pro-environmental behavior and may instead result from declining welfare and reduced purchasing power. This issue is particularly important in developing economies where macroeconomic shocks can substantially reshape dietary structures. Accordingly, analyzing emission trends without accounting for macroeconomic conditions and structural changes in consumption may lead to misleading interpretations. However, a review of the literature reveals that environmental studies have primarily focused on carbon footprint quantification, while food economics research has concentrated on the impacts of economic shocks, with limited systematic integration between these two strands of research. As a result, the relative contribution of behavioral change versus economic pressure in driving dietary carbon footprint dynamics remains insufficiently understood.Despite the growing body of literature in life cycle assessment, index decomposition analysis, and food economics, several critical gaps persist. LCA-based studies have mainly estimated emission intensities but have not addressed the drivers of temporal variation. Moreover, applications of the Logarithmic Mean Divisia Index (LMDI) in Iran have largely been confined to the energy and industrial sectors, with no prior studies examining animal protein consumption systems. In addition, most sustainable diet studies implicitly assume that dietary change is driven by informed consumer choice, neglecting the role of macroeconomic conditions, while food economics studies have rarely considered the environmental consequences of economic shocks. Consequently, a conceptual gap remains between food consumption patterns, macroeconomic shocks, and carbon footprint dynamics. This study addresses these gaps by focusing on the animal protein consumption basket, applying the LMDI method to decompose activity and structural effects, and integrating environmental analysis with macroeconomic shocks in Iran, including inflation, exchange rate fluctuations, and economic sanctions. This integrated framework enables the separation of environmentally motivated behavioral changes from those induced by economic constraints.
The present study examined the evolution of the carbon footprint associated with animal protein consumption among Iranian households over the period 1992–2024 by applying the Logarithmic Mean Divisia Index (LMDI) decomposition method to quantify the contributions of the activity effect (changes in consumption level) and the structural effect (changes in the composition of the consumption basket) across six distinct economic sub-periods. The results indicate that variations in the carbon footprint were driven primarily by macroeconomic shocks including inflation, international sanctions, exchange rate fluctuations, and changes in household purchasing power rather than by environmental policies or deliberate pro-environmental behavioral change. During periods of economic expansion, rising animal protein consumption constituted the main driver of emission growth, whereas during periods of instability, reduced consumption and economically induced shifts in dietary composition contributed to declining carbon footprints. Throughout the study period, red meat remained the largest contributor to emission variability, while poultry served as the principal substitute. However, the decline in dairy consumption observed in the later years also points to adverse economic consequences for food security and dietary quality. Overall, the findings suggest that the recent reduction in emissions should not necessarily be interpreted as evidence of a transition toward a sustainable food system; rather, it largely reflects economic constraints and reduced access to high-quality protein sources. Achieving the simultaneous objectives of emission reduction, food security, and public health therefore requires integrated policy interventions that combine lowering emission intensity in livestock production, restructuring the protein consumption basket, and maintaining the economic accessibility of nutritious foods. In this regard, policies such as promoting sustainable dietary patterns, improving productivity and reducing emission intensity in the livestock sector, employing price-based and informational instruments (e.g., carbon labeling), and integrating climate policies with food-security and nutritional-equity objectives are recommended. In addition, simultaneous monitoring of environmental and nutritional indicators is essential for a comprehensive assessment of food-system sustainability.

Abstract Introduction
Agriculture encompasses a set of activities related to various raw agricultural, horticultural, livestock, forestry and aquatic products by various groups of farmers (farmers, gardeners, livestock keepers, beekeepers, foresters, aquaculture, fishermen, etc.) that are produced in the context of the climate and through a combination of production factors of labor, capital and natural resources (land, water, etc.). Unlike industrial and service activities, the production of agricultural products is carried out in the context of nature (as an uncontrollable environment) and is completely and directly dependent on climate conditions and its changes.
This study investigates the nonlinear dynamics and multi-scale interactions between climate-economic variables and Iran's agricultural value added during 1981–2023 (1360–1402 in the Iranian calendar) through an innovative hybrid wavelet-machine learning framework. Given Iran's severe vulnerability as an arid nation experiencing accelerated climate change—characterized by 15% declining rainfall and 1.2°C rising temperatures over recent decades—understanding the complex mechanisms driving agricultural productivity has become critical for food security and sustainable development.
Materials and Methods
In order to answer the main question of the present study and achieve its objectives, a combination of parametric (econometric models) and non-parametric (intelligent models) methodologies has been used. The correct specification of an economic model means the correct selection of explanatory and dependent variables (based on economic theories), the type of relationship between these variables, and the precise definition of the relationships between variables and parameters. The explanatory variables affecting agricultural value added have been selected based on the theoretical foundations of economic growth and empirical studies.
The research methodology integrates three sequential analytical phases. First, the Brock-Dechert-Scheinkman (BDS) test confirmed strong nonlinear dynamics in all time series variables except annual rainfall, justifying the necessity of nonlinear modeling approaches. Second, discrete wavelet transform (DWT) was applied for multi-scale denoising using optimal wavelet functions (Daubechies 4–8, Haar 2) selected per variable to extract meaningful signals while eliminating noise. Third, three advanced machine learning algorithms—bootstrap neural network (NB), bootstrap forest (BF), and support vector machine (SVM)—were implemented on wavelet-denoised data to model complex relationships and rank variable importance through sensitivity analysis and total effect metrics.
Results and Discussion
Empirical results demonstrate the superior performance of the hybrid wavelet-bootstrap neural network (Wavelet-NB) model, achieving an exceptional coefficient of determination (R² = 0.99) in both training and validation phases—significantly outperforming Wavelet-BF (R² = 0.93 validation) and Wavelet-SVM (R² = 0.85 validation). Variable importance analysis within the optimal Wavelet-NB model revealed a distinctive ranking of influential factors: (1) agricultural labor productivity (total effect: 0.338), (2) lagged agricultural value added (0.216), and (3) annual mean temperature (0.162) emerged as the three dominant drivers. Notably, annual rainfall exhibited negligible influence (total effect: 0.007), while evapotranspiration showed virtually no impact—likely attributable to limitations in annual-scale climatic data aggregation that mask intra-annual variability critical for agricultural processes.
These findings carry significant theoretical and policy implications. The paramount importance of labor productivity underscores the diminishing returns of labor-intensive agricultural strategies in Iran's evolving economic landscape, signaling an urgent need for mechanization, skill development, and technological adoption. The substantial influence of temperature (third-ranked driver) confirms climate change as a direct threat to agricultural output, consistent with projections of 5–10% yield reductions per 1°C warming for staple crops. The weak impact of annual rainfall metrics does not imply water's unimportance—rather, it reflects methodological limitations in capturing irrigation-dependent production systems where groundwater and surface water dominate over direct rainfall reliance.
Conclusions
Methodologically, this research contributes to climate-agriculture literature through three innovations: (1) rigorous BDS testing to validate nonlinearity before model selection, (2) systematic wavelet denoising optimized per variable to enhance signal extraction across temporal scales, and (3) comparative assessment of three machine learning architectures with graphical sensitivity profiling for transparent variable ranking. The negligible performance of annual evapotranspiration metrics further suggests that monthly or seasonal climatic indicators would yield more accurate agricultural impact assessments.
Policy recommendations emphasize three strategic priorities: (1) shifting agricultural development policies from labor expansion toward productivity enhancement through precision agriculture and heat-resilient crop varieties; (2) integrating climate adaptation into agricultural planning with temperature thresholds as early warning indicators; and (3) improving climatic data infrastructure to capture sub-annual variability essential for modeling irrigation-dependent production systems. This hybrid wavelet-machine learning framework offers a replicable methodology for climate-vulnerable arid regions globally seeking robust analytical tools for sustainable agricultural planning under accelerating climate change.

Abstract Introduction The rapid growth of the global population, ongoing climate change, and limited production resources have intensified concerns about food security. Sustainable food production systems, particularly grazing-based livestock production, play a vital role in addressing these challenges. However, these systems face numerous obstacles in developing countries and arid/semi-arid regions, including heavy reliance on natural resources, climate change impacts, and drought vulnerability, lower efficiency compared to other production methods, high greenhouse gas emissions, and competition for agricultural land allocated to feed production. Additionally, high operational costs and susceptibility to livestock diseases have significantly reduced both the profitability and sustainability of these systems. In Iran, livestock production systems remain predominantly traditional and are evaluated as unsustainable in terms of environmental, economic, and social indicators. Kermanshah Province, with approximately 2,500 rangeland systems and 63,000 rural and nomadic households, represents one of the most important livestock production hubs in western Iran. However, the presence of 1.4 million livestock units exceeding rangeland carrying capacity, combined with significant climatic changes over the past three decades (including rising temperatures, declining precipitation, and intensifying droughts), has made this region an ideal case study for examining sustainability challenges in livestock production systems. This study aims to identify and analyze the challenges facing livestock production systems in relation to climate change impacts in Kermanshah Province. Materials and Methods This research was conducted in Kermanshah Province, located in the middle part of the Zagros Mountains. Kermanshah Province, as one of the livestock breeding hubs in the Middle Zagros, plays an important role in providing livestock feed from rangelands. The province contains approximately 2,500 rangeland systems supporting about 63,000 rural and nomadic households. These households primarily rely on rangeland grazing to meet their livestock feed requirements. Based on forage production capacity, the rangelands can sustainably support only 1.5 million livestock units, while the current livestock population exceeds this capacity by approximately 1.4 million units. Recent studies indicate significant climatic changes in the province over recent decades, particularly increased drought intensity and duration, which have directly impacted natural forage availability and threatened the sustainability of livestock production systems. Methodologically, this quantitative, applied research employed a survey approach. The study population consisted of 140 experts and specialists in livestock production and natural resources management from Kermanshah Province, with 131 participants studied through census method (with 93 % rate of return) based on their research and practical experience in livestock production systems and associated challenges. Data were collected using a researcher-developed questionnaire, designed through literature review and interviews with livestock production experts. Content validity was assessed by agricultural and natural resources experts from Kermanshah and faculty members from the University of Tehran's Agricultural Management Department. Discriminant validity was confirmed using average variance extracted (AVE). Reliability was evaluated through Cronbach's alpha and composite reliability. Data processing utilized SPSS 27 and Smart PLS 3 software packages. Results and Discussion The findings revealed that the most critical sustainability challenges for grazing-based livestock systems in Kermanshah Province were, in order of significance: environmental (β=0.756), economic (β=0.683), managerial (β=0.669), technical (β=0.593), social (β=0.563), and legal challenges (β=0.454). Environmental challenges emerged as the foremost sustainability barrier, underscoring their pivotal role in determining the overall sustainability of pastoral livestock systems according to expert assessments. Among environmental factors, climate variability and drought (factor loading=0.858) were identified as the most severe environmental challenges. Given that climate change impacts are projected to exacerbate system vulnerability - particularly when combined with rapid population growth and economic development that intensify food demand - these findings highlight the urgent need for adaptive strategies to mitigate climatic effects. Economic challenges represented the second most significant sustainability obstacle. Within this category, high prices for production inputs and animal feed (factor loading = 0.856) emerged as the most prominent economic constraint. This finding reflects the substantial financial burden on pastoralists for procuring inputs and animal feed, which increases production costs and may compromise their capacity for sustainable rangeland utilization. Managerial challenges ranked third, with poor community organization in local associations for coordinated action and inadequate service provision (factor loading=0.837) representing critical management shortcomings. Technical challenges represented another key sustainability barrier, where low productivity of grazing livestock was identified as a fundamental technical constraint. This emphasizes the importance of enhancing livestock productivity to improve overall system efficiency and profitability in the province. Social challenges ranked fifth, with insufficient awareness and knowledge regarding drought management and its impacts on rangelands (factor loading=0.853) being the primary social challenge. This underscores the critical need for educational interventions to improve pastoralists' understanding of drought management and rangeland conservation. Finally, legal challenges (β=0.454) were ranked as the least severe sustainability obstacle. Within this category, insufficient government budgeting and credit allocation for natural resource conservation and rangeland management (factor loading=0.874) emerged as the most significant legal constraint. This hierarchical challenge structure provides valuable insights for prioritizing intervention strategies to enhance the sustainability of grazing-based livestock systems in semi-arid regions. Conclusion Understanding these challenges can contribute to developing practical solutions for enhancing the sustainability of these systems. To improve the sustainability of livestock production systems, several strategies are proposed, including: establishing local cooperatives, enhancing access to technical training, developing innovative technologies, and providing financial support to livestock producers.

Abstract In recent decades, the significance of the issue of climate change has escalated due to its intensified impacts, potentially diminishing or halting economic growth, particularly in developing countries and vulnerable sectors such as agriculture. Climate change may be considered the most important and complex human challenge. Among the economic effects, trade variables have been examined inadequately. Accordingly, the focus of this study is to investigate the impact of climate change on the export and import of agricultural products in Iran over a forty-year horizon, which was carried out using a dynamic input-output model. This study uses scenarios of temperature anomaly to examine the impact of climate change on different sectors of Iran’s economy. The findings indicate that climate change has a significant impact on the growth of both exports and imports of agricultural products. Under normal conditions without climate change, the average annual growth rate of agricultural product imports is 2.7 percent. However, this rate decreases to 1-1.8 percent when different climate change scenarios are taken into account. Regarding the exports, the corresponding value is 2.75 percent, expected to be reduced to 0.55-1.8 percent.  In addition, it was found that agricultural trade will be dominated by cereals import. Also, the total trade of the Iranian economy will change in favor of non-agricultural commodities

Abstract Introduction
 Various studies have shown that changes in rainfall due to climate change can affect the stability of food supply and in fact climate change by increasing the prevalence and severity of drought or flood, crop yields, food access and also effect food prices. According to the FAO, Iran's food security rank is 82 out of 125 countries in the world, and one of the reasons for this rank is the excessive waste of agricultural products in Iran. As a result, citing a wide range of previous studies, it has been documented that the impact of climate change on food security for countries that are more dependent on agriculture is largely negative and has significant effects. Therefore, in present study, citing theoretical foundations and foreign and domestic studies conducted in the field of food security especially in Iran, factors such as food prices, climate change, household income, exchange rate and targeted subsidy policy as factors affecting selected food security and their effect on food security of urban households in Iran were studied.
Materials and Methods
 In this study, it was our goal to find the effects of food price variables, climate change, household income, exchange rate and targeted subsidy policy on food availability by estimating single equations of the food security index.
In this study, based on the subject literature and available information, the self-explanatory model with wide intervals (ARDL) and the error correction model (ECM) introduced by boys and colleagues have been used to examine integration and estimate short-term and long-term relationships between variables. Data required for the present study, regarding the open market exchange rate and food prices (food and beverages) from official statistics based on the annual reports of the Central Bank of the Islamic Republic of Iran and the necessary information to calculate the food security index of households and average household income from detailed results Expenditure and income of urban households of the Statistics Center of Iran, for the period 1398-1399 has been extracted.
Results and Discussion
 The results showed that in the long run, a one percent increase in food prices reduces the food security index of Iranian urban households by 21 percent. As expected, the coefficient of variable climate change has a negative and significant effect on the food security index, and with its increase, the production of food and agricultural products decreases, and as a result, the food security index decreases. The growth rate of free market exchange rate with a negative sign at the level of one percent is significant. Since the agricultural industry in Iran is an industry highly dependent on imports. As a result, the increase in the exchange rate increases the price of agricultural products and affects food security. Annual household income has a positive and significant effect on household food security index. By increasing household income and assuming its appropriate distribution in society, it can be concluded that urban households are faced with increased purchasing power and ability to meet their food needs, and this variable has a positive effect on energy status and food security. The virtual variable of the years of implementation of the law on targeted subsidies is also significant at the level of 10% with a negative sign. The results show that in the long run, the implementation of this law has reduced the activity of farmers due to rising prices of agricultural inputs and energy carriers, this issue leads to a decrease in domestic food production and thus increases their prices and ultimately reduces food security of households. The estimated coefficient of ecm (-1) is equal to the negative value of 0.42 and is statistically significant at 1% probability level. The value of this coefficient indicates that each year 0.42% of the imbalance of one period of food security of urban households in Iran in the next period is adjusted.
Conclusion
 Given the negative effect of food price index and exchange rate on food security of urban households, the application of appropriate exchange rate policies can be very effective in reducing inflation, especially food price inflation, which threatens the country's food security. With increasing investment, domestic food production is approaching self-sufficiency in this sector, in which case food prices will be subject to domestic supply and demand, and to some extent will be protected from exchange rate fluctuations and food imports, and this will create food security and prosperity. The economy in the country will help a lot. Given the negative effect of targeted subsidies, a review of the implementation of targeted subsidies policy to establish food security for households is proposed. To reduce the negative effects of climate change on food security, selective strategies must focus on addressing the adverse effects of climate change and food insecurity. Educating and strengthening public belief in climate change and water crisis, formulating long-term and short-term plans and policies for water resources management under climate change conditions with the participation of all relevant organizations and moving towards modern methods can be effective in reducing the effects of climate change.

Abstract Abstract
This paper evaluates the effect of water scarcity and climatic conditions on farmers' irrigation decisions in the production of major crops including wheat, barley, cotton, sugar beet, and alfalfa in North-Khorasan province. Farmers’ irrigation decisions are defined with a management model composed of equations of the share of irrigated land, technology adoption, and the irrigation frequencies, which investigated the effect of water scarcity indicators and climatic factors, farm water supply method, land characteristics, and farmers’ demographic features. For this purpose, the required data were collected from the 380 questionnaires, completed by farmers in cultivation year of 2017-2018. Then, the equations of the management model were estimated using fractional logit, binomial logit, and OLS methods. The results indicated that economic and physical scarcity of water resources, climatic conditions of temperature and precipitation, severe events of frost and heat, and drought have noticeable impact on farmers’ irrigation decisions. Farmers try to reduce the damage caused by climate change and water scarcity by deciding to irrigate their farms and adopting new irrigation technologies. Also, the type of water sources, i.e. surface and groundwater, irrigation method, soil quality of cultivated land, and land size have significant effects on their decisions. In regions without available surface water resource, the cultivation areas of irrigated land are declined. Also, due to water scarcity, farmers are more willing to invest on new technologies to improve irrigation efficiency. In the farms with higher soil quality, improved cropland direction and slope, and resource availability, farmers are more willing to invest on new irrigation methods and increase irrigation frequencies. Therefore, the implementation of policies on improving land quality and cropland integration can increase the acceptance of new technologies, and reduce the water usage. In addition, farmers’ demographic characteristics such as experience, tenure, and education influence their decisions for irrigation. Creating suitable conditions for the education and training of farmers will increase farmers’ awareness of new agricultural methods and the importance of water resources. Findings of this study provide vision on – how of farmers reaction against crop production systems as well as mitigation policies to confront climate change impacts.

Abstract Introduction: Climate change and increasing global warming are intensifying droughts, changes in rainfall distribution and depletion of water resources over time. Persisting hot and dry weather has intensified the phenomenon of climate change and posed serious threats to the country's water resources, resulting in the inability to meet the needs like drinking, environmental, industrial and agricultural ones. The fifth report of the Climate Change Board also shows that the phenomenon of climate change in many parts of the world has had a negative impact on agricultural production; but the application of appropriate and timely adaptive scenarios against climate change can reduce the negative effects of this phenomenon on the agricultural crops yield. Bushehr province is mostly exposed to climate change and drought because of its geographical location. According to the National Meteorological Center, the area affected by drought in this province during the ten-year period ending in March 2019, was 83%. Up to 80% of the plains of the province have a negative groundwater level. This problem is more severe in some plains of the province, including Bushkan plain, the water level of this plain has decreased by 1.31 meters annually. This plain is considered as the agricultural hub of province and Dashtestan city. Thus the study of the effects of climate change on the hydrological and agricultural situation of the Bushkan plain and the analysis of the effectiveness of adaptive scenarios to reduce the negative effects of this phenomenon is very important.
Materials and Methods: In this study, in order to create optimistic and pessimistic scenarios of climate change, the LARS-WG microscale model was used. Then, in order to investigate the effects of climate change on the hydrological status of Bushkan plain, water needs of agricultural crops and crops yield, simulated climate change scenarios and adaptive scenarios include improve irrigation efficiency and deficit irrigation were entered into WEAP model and its agro-agricultural model, MABIA. For the purpose of investigating the adaptation of agricultural production systems to changes in available water and yield as well as to measure the effectiveness of adaptive scenarios, a positive economic planning model was used. For economic model, statistics and information related to the cultivation area, production costs, prices and yields of crops in different areas of Bushkan plain were obtained through the Jihad Agricultural Organization and also completed 100 questionnaires from farmers in the area. Random sampling method was used to calculate the sample size.
Results and Discussion: By applying two scenarios, optimistic A1B and pessimistic A2, in general, it can be concluded that the most changes in precipitation were in autumn and winter and the most temperature changes were at least in autumn and spring. Also, applying a pessimistic scenario will cause more drastic changes than an optimistic scenario. The results of MABIA model show that by applying both climatic scenarios, the average water requirement of all agricultural products increases during the simulation period compared to the base period.
Increasing water demand and decreasing available water have caused water stress and as a result reduced the yield of various agricultural products in Bushkan plain. The results show that the average crop yields decreases, but the highest reduction of yield in both scenarios is related to wheat crop. The results of PMP model indicates that the application of optimistic and pessimistic scenarios will reduce the area under cultivation of this plain by 42% and 55%, respectively. On the other hand, among different crops, the area under cultivation of crops such as wheat, barley and watermelon has declined more sharply. However, the application of adaptive scenarios to improve irrigation efficiency and under-irrigation somewhat offsets the effects of climate change. In optimistic climate change, adaptive scenarios to improve irrigation efficiency and use of deficit irrigation method will improve the area under cultivation of agricultural products by 6 and 4 percent, and in pessimistic climate change by 3.8 and 2.3%.Comparison of the results of applying adaptive scenario shows that despite the less effect of deficit irrigation on improving the area under crops, the increase in profit in this scenario is more than the improvement of irrigation efficiency and the reason is the costs of improving irrigation efficiency compared to the deficit irrigation scenario.
Conclusion and Recommendations: Principles of resource management and low productivity have led to declining groundwater levels and as a result the ban on the exploitation of more groundwater in the plains of Bushehr province, including the Bushkan plain. Accordingly, in this study, the consequences of climate change on the hydrological and agricultural situation in the Bushkan plain of Bushehr province as well as the effectiveness of adaptive scenarios were investigated .Finally, based on the results of the present study, it is suggested that farmers use scenarios such as deficit irrigation methods and improve irrigation efficiency to prevent water loss and reduce the yield of these crops. However, since the results showed that using deficit irrigation method will improve agricultural profits more than improving irrigation efficiency, therefore, using deficit irrigation method has priority over improving irrigation efficiency. Also due to the low impact of climate change on water demand and canola yield, canola is suggested to local farmers as an alternative crop for wheat and barley crops.

Abstract Introduction: During the last decades, climate change has been highly disjointed. Recent studies on climate change has approached the assessment of impacts of this phenomenon and adaptation strategies under biophysical or social perspectives. In the field of agriculture and water resources, most assessments have been based on biophysical modelling focusing on the agronomic dimension or the hydrological dimension. Therefore, integrate biophysical and social aspects looking at environmental and human contexts are vital for investigation of climate change and adaptation strategies effects. In line with this, varied types of integrated modelling frameworks have been developed to address the different scales (from the crop to the river basin) and the different dimensions of climate change, water and agriculture (hydrological, agronomic, socio economic). Water resources in the Halil-Rud river basin are likely to be seriously affected by climate change in the form of increased water scarcity and more frequent droughts which leads to conflicts among different water users and uses, especially between agricultural sector and Jazmourian wetland services. However, because of the multidimensional and multi-scalar nature of water management and climate change, it is needed to integrate tools for the analysis of impacts and adaptation. In line with this, current study presents an economic – hydrological model to evaluate potential effects of climate change and adaptation strategies on irrigated agriculture and to solve or mitigate water resources conflicts among different water users and uses in studied basin.
Materials and Methods: This study, combines a farm-based economic multi-objectives optimization model with the hydrologic model water evaluation and planning (WEAP) which can represent the socio-economic, agronomic and hydrologic systems in a spatially-explicit manner covering all dimensions and scales relevant to climate change. To this end, current study was organized in two sections. In the first section, the effects of a climate change under A2 scenario and balanced groundwater withdrawal (sustainable groundwater use) on hydrological and economic performance of basin level were investigated using an economic, agronomic and hydrologic model. Finally, adopting suitable adaptive strategies on hydrological and economic conditions were evaluated using that model. A2 scenario is primarily simulated through the hydrologic model, as it represents physical characteristics of the crop and water systems, through changes in climate variables. On the other hand, adaptation strategies that affect human behavior are firstly simulated by the economic multi-objectives model. The hydro-economic simulation model is started with the multi-objectives model run which include economic and hydrological objectives. Then, Using the MABIA method and WEAP irrigation water requirements would be calculated, allocating water to crops depending on water availability and established priorities, and estimating crop yields would be done. After the first economic-hydrologic model simulation, there is a second economic-hydrologic iteration. The economic model uses WEAP results on water delivered to irrigation communities (water availability constraints at farm level), crop yields (used to calculate the gross margin per crop) and irrigation water requirements under the simulated climate scenario and adaptation strategies to simulate farmers' adjustment of cropping patterns to a new optimal land allocation.
Result and Discussion: results indicates the multi-dimensional effects of climate change and adaptation strategies and show the large potential of integrated hydro-economic models for representing the multi-scale processes related to climate change and water management. The analysis of decisions taken at farm level has been proven to be necessary, as crop model results capture the potential of farm level adaptation to mitigate the damaging effects of climate change and these are relevant to climate change adaptation as highlighted by Reidsma et al. (2010). Results for the climate change under A2 scenario and balanced groundwater withdrawal scenario (combined scenario) on status of hydrological and economic in the level basin showed that crops yield, areas with available water and water demand reliability would decrease, while crops net water demand and areas water unmet demand would increase and farmers’ income would decrease between 10 to 37 percent for upstream, between 24 to 47 percent for middle and between 30 to 50 percent for downstream units in long –term horizon in comparison to base scenario. But, adopting suitable adaptive strategies and measures could mitigate the effects of climate change on hydrological conditions specially for downstream areas and economic conditions including upstream areas. Finally, combined suitable water transmission system, modern irrigation technologies, saffron crop cultivation and deficit irrigation of some crops adaptive strategies simultaneously indicated that unmet water demand significantly decreases and the total gross margin of agricultural sector increases by 68% in comparison to base scenario under climate change.

Abstract Introduction: The potential impacts of climate change on water resources and food security are receiving growing attention especially in regions that face growing challenges like water demands for agricultural, domestic and environmental uses. The anticipated climate change are likely to impact water resources (surface water and groundwater) by altering precipitation patterns and change in nature of rainfall regimes. Apart from the effects on water availability, climate change is expected to adversely affect crop productivity, food security and food producers' income. Climate changes could affect the four dimensions of food security; food availability, access, utilization, and stability. Therefore, this study aims at investigating the economic effects of climate change on the agricultural sector (including the yield of crops, water resources, food security and profitability) in Hamadan-Bahar plain. The hypothesis tested in this research is that climate change has negative impacts on the agricultural sector in the study area and it is necessary to present solutions to reduce these effects. Accordingly, the question answered in this study is whether climate changes in the region reduces crop yields, the profitability of the agricultural sector, and aggravate the scarcity of water resources. For this purpose in this study, the effects of climate change in different scenarios on regional cultivation pattern, basic food cultivation pattern, gross profit of farmers, physical and economic productivity of water and food security in Hamedan-Bahar plain have been investigated and then various suggestions to these problems have been presented.
Materials and Methods: For this purpose, the physiological, hydrological and meteorological aspects of the problem were integrated into an economic model and the changes in cultivation pattern of the plain were projected in counterfactual climatic scenarios. Accordingly, the outputs of the HadCM3 model under the scenarios of B1 (optimistic) and A2 (pessimistic) were utilized for the fourth report; additionally, the outputs of the ensemble model under RCP 2.6 (optimistic) and RCP 8.5 (pessimistic) scenarios were used for the fifth report of IPCC. Then, the variables of rainfall and temperature for the horizon of 2070 were predicted under scenarios B1, A2, RCP2.6 and RCP8.5 using the Lars-WG model. In this regard, the yield response functions of the products with respect to climatic parameters by the Generalized Maximum Entropy method (GME) were estimated and the elasticity of the yield of the products with regard to temperature and rainfall were calculated. Then products yield changes on the 2070 horizon under different climate change scenarios were predicted and by including it in a positive mathematical programming (PMP), the impact of different climate change scenarios on regional cultivation pattern, basic food cultivation pattern, gross profit of farmers, physical and economic productivity of water and food security were examined. To estimate the yield response regression model and predict climate changes by LARS_WG model, the data on the period 1982-1982 were used. Also the data and information of farmers were obtained using a two-stage cluster sampling method in 2018 (baseline).
Results and Discussion: The results indicate an increase in temperature, a decrease in precipitation, a decrease in the supply of water resources, and consequently a decrease in the yield of most basic food products and an increase in the yield of some vegetable and summer crops were anticipated in all scenarios. The results also showed that the occurrence of the mentioned consequences has negative effects on the total production of crops, the amount of production of basic food products and the gross profit of farmers in the region. And in this regard, in the most pessimistic scenario on the horizon of 2070, it will impose a loss of 490 billion rials on farmers. The increase in the physical and economic efficiency of water in different scenarios shows that water is becoming more valuable due to the decrease in the quantity of water due to climate change. Therefore the economic value of water would increase in the future decades in Hamadan-Bahar plain, which itself represents the severity of water scarcity in the agricultural sector.
Conclusion: The occurrence of climate change by affecting water resources, crop yields, cultivated area, food production and ultimately farmers' incomes, in addition to imposing economic and environmental losses, would affect various aspects of food security such as food availability, access, stability and utilization. Accordingly, in order to maintain and improve the yield of crops and reduce the possible losses imposed on income and food security of the region, it is vital to adopt appropriate strategies compatible with climate change, including the use of new irrigation technologies, deficit irrigation methods and to reform the cultivation pattern by selecting products with higher economic value in order that increase water productivity. Finally improving management of water resources and farmers' income at the plant, farm and region levels, is crucial.

Abstract Introduction: Understanding the temporal and spatial fluctuations of climatic parameters (such as temperature, precipitation, relative humidity, etc.) and its impact on agricultural sector is essential for managing agricultural resources and adopting appropriate strategies. Precipitation directly affects the production of dry crops by supplying the required moisture for the plant, and indirectly affects the production of aquatic crops through supplying surface and underground water resources. Climate change has an effect on temperature and precipitation distribution and consequently affects the plants water requirement and agricultural water consumption. Overall, climate change is influenced by both temperature and precipitation. Due to the changing rainfall pattern and average temperature of the atmosphere, this phenomenon can damage the production of agricultural products that maintain the major food sources of the country. Given the important role of agriculture in the country's economy and the existence of the ongoing water crisis and drought in the country, climate change can have major impacts on their aggravation. The purpose of the present study is to investigate the effects of climate change and water scarcity on agricultural production, price and income in Iran.
Materials and Methods: The multi-market model, sometimes referred to as the "finite general equilibrium" or "multi-market partial equilibrium model", has reduced the complexities of computable general equilibrium (CGE) models. The AMM template was used for this purpose. To simulate the effects of climate change, crop yields were calculated using yield response coefficients. Then, the demand function of different products was calculated using estimated elasticities and finally climate change has been simulated for 2025.
Results and Discussion: The results showed that climate change would increase, yield of rainfed wheat, blue barley, dry barley and maize grain in semi-arid climate and subtropical climate, in addition dry barley and barley products in warm semi-arid climate and subtropical climate, and finally rainfed barley and corn products Grain in temperate semi-arid climates and subtropicals climate by 2025 relative to current levels. Climate change also would decrease yields of dry wheat and barley in temperate semi-arid climates and subtropicals, and also wheat in warm and semi-arid climates and subtropicals for 2025 compared to the present value. The results also showed that climate change would expand the water available for the blue wheat crop in the semi-arid climate and sub-climates, besides the blue barley crop in the semi-arid, semi-arid, and temperate semi-arid climates for 2025 compared to the present value. Climate change also might reduce the amount of water available for the blue wheat crop in the climate and sub-arid and semi-arid sub-climates, therefor the corn yield in the cold and semi-arid sub-climates and sub-climates for 2025 compared to the present value. The results also revealed that climate change would diminish cultivation of maize crop in semi-arid climate and temperate climates in addition irrigated and rainfed wheat crop in warm and semi-arid sub-climate and also rainfed wheat crop in semi-arid climate by 2025 relative to the present situation. Also the area under cultivation of blue barley and dry barley crops in warm and semi-arid climates, cold and semi-arid climates, and blue wheat crop in semi-arid climates and rainfed wheat crop in temperate and semi-arid climates would decrease by 2025.
Conclusion: The results also demonstrated that with the climate change, the amount of maize crop production in cold and semi-arid climates and sub-climates, and the production of blue and dry wheat crops in warm and semi-arid climates, cold semi-arid, temperate and dry semi-arid climates for 20 years would decrease relative to current value. Also, the production of irrigated and rainfed barley in warm and semi-arid climates, sub-climates and temperate semi-arid climates for 2025 would increase compared to the present situation. Thus the first hypothesis of the study: "Climate change and water scarcity reduces agricultural production" is not approved in Iran. The results also explained that with the climate change the prices of wheat, barley and maize crops in the semi-arid and temperate climates for the year 2025 would also rise, so the second hypothesis of the study "Climate change and scarcity of water resources will increase the prices of agricultural products in Iran” is confirmed. The results also show that with climate change, farmers 'incomes in cold and semi-arid climates, temperate and warm semi-arid climates would increase by 2025 relative to their present value, so the third research hypothesis that "climate change and water scarcity reduces farmers' income" In Iran, " is not confirmed. The results also indicated that wheat, barley and maize exports remained negative by the creation of net climate change for 2025 and that the country's climate change created an importer of these products.

Abstract Introduction: The increase in greenhouse gases has affected global weather, resulting in changes in climate zones. Climate change is mostly characterized by changes in temperature. There is strong evidence showing that climate change will adversely affect the world especially developing countries in the following decades. Agricultural activities are more vulnerable to climate change as they are more dependent on water resources and temperature. Moreover, damages to agricultural activities may contract output in other sectors as well. Given the importance of the issue, Iran is a prominent example since it is located in an arid and semi-arid region, and its average annual precipitation is less than one-third of the global precipitation. In addition, there is a large body of literature indicating an increase in average temperature of Iran over the last decades. Therefore, this study aims to investigate the effect of climate change on the economic growth in Iran.
Materials and Methods: The Solow-Swan growth model was applied to investigate economic growth under climate changing environment. The growth models were estimated using time series data of 1350-1395 (1971-2016). In the growth model, a damage function, change in which damage is a function of temperature, was applied to examine the effect of climate changes. The growth model determinants are physical as well as other types of capital including human, social and environmental capitals. Internet access and phone access were used as proxies for social capital. Also, literacy rate, primary school enrolment rate, and university students were applied as proxies for human capital. Agriculture, mining, and oil and gas production were considered as proxies for natural and environmental resources. Another proxy for environmental capital was the value of natural resources marginal product. This variable is defined as the ratio of CO₂ damages to GDP. Trade impact on economic growth was also investigated through using Foreign Direct Investment (FDI) and trade openness variables. Also, to examine the trend of temperature, an ARMA model was used. GDP is technically considered as an endogenous variable so Generalized Method of Moments (GMM) method is applied.
Results and Discussion: The specification of ARMA model revealed two significant moving average trends including five-year and nine-year. These trends indicate an increasing average for temperature, leaving less doubt about the phenomenon of climate change. Our results showed that the increase in temperature will negatively affect economic growth. It was also found that one-degree increase in average temperature is expected to reduce Iranian GDP by 5-6.6 percent. Physical capital showed the highest contribution to Iranian GDP. Its contribution to the economic growth, in terms of elasticity, was found to be 0.08-0.16. The corresponding values for human and social capital were 0.02-0.06 and 0.03-0.08, respectively. However, environmental capital failed to affect the economic growth significantly. Among the variables applied for human capital, university students were found to play a more significant role. The insignificant effect of environmental capital on economic growth may be attributed to its nature that is used as a public good, resulting in intensive as well as irrational use. Among the variables applied for environmental capital, the value of natural resources marginal product showed a slightly strong effect, needing to be considered as a proxy for environmental capital. Also, FDI showed an insignificant effect; however, trade openness was found to affect economic growth positively.
Conclusion: The general trend of the economic growth in Iran is far from what is expected. In addition, this trend is threatening by, among the others, climate change which is characterized by increasing average temperature as well as decreasing precipitation. Also, as far as the capital is considered, economic growth in Iran is highly dependent on physical capital while the contribution of other types of capital including human, social and environmental capital is not significant. However, it is worth noting that environmental capital seems to be used intensively while for human capital reasons like inappropriateness of labor quality and education system is more acceptable. Even for physical capital, higher contribution is expected since the Iranian economy enjoys lower capital accumulation. It was also found that removing trade barriers and being more connected with the global economy may provide more opportunities to enjoy higher growth.     

Abstract Introduction: Water resources are under increasing pressure from climate change, population growth, and socio-economic development. Recent assessments have revealed that climate change accounts for about 20% of the increased water scarcity. Due to the impacts of climate change on water resources, agriculture is one of the most important sectors of the economy affected by this event. Accordingly, food security threatened by climate change is one of the most important challenges of the 21st century to provide sufficient food for population growth. Because of the abundant effects of climate change and water scarcity on farmers' welfare, different strategies have been adopted to adapt to these changes. Adaptation can be defined as: “adjustment in ecological, social or economic systems in response to actual or expected climatic drivers and their effects or impacts. Climate change phenomenon has occurred in Iran during recent decades and it will continue in the future with greater intensity based on the seventh report of the Intergovernmental Panel on Climate Change. In other words, Iran’s aridity has been exacerbated by the climatic change to pose serious threats to its water resources and the ability to meet its residential, environmental, industrial, and agricultural water demands. In this regard, improved irrigation efficiency is vital for alleviating water scarcity and can be an adaptation strategy to climate change for this country due to water losses account for at least 45% of the water used in Iran's irrigated agriculture, which arises from inefficient irrigation systems.
Materials and Methods: The Karkheh River Basin (KRB) is one of the largest watersheds in Iran after Karoon and Dez. It is located on the western border of the country in a strategic position. This watershed consists of five sub-basins, namely Kashkan, Qarasou, Gamsiab, Seymareh, and South Karkheh. The Karkheh River Basin deal with water shortage through the frequent droughts in the region over the past decades, leading to major water deficit in downstream of the basin. Also, Climate change is expected to exacerbate the current water problems in KRB. Such ways that, 10-30% decrease in the runoff by mid-century is estimated in this basin thanks to less precipitation and higher evapotranspiration. The aim of current research is to evaluate the potential effects of climate change on irrigated agriculture and irrigation efficiency improvement strategy for adaptation in South Karkheh sub-basin using a hydro-economic model. This model integrates the strengths of the Positive Mathematical Programming (PMP), and Water Evaluation and Planning (WEAP) as a hydrological model. The MABIA module within WEAP was also used to simulate the impacts of climate change scenarios and water availability scenarios on crop yield. The hydro-economic model simulation starts with run WEAP-MABIA model for hydrological simulation of South Karkheh sub-basin. For this purpose, Model calibration was carried out using the PEST method. The Zahraei’s climate change scenarios (2015) were then used as input to the WEAP-MABIA model. Finally, results of the WEAP- MABIA were used as input to the Positive Mathematical Programming model to investigate the effects of climate change scenarios and adaptation strategy (improvement of irrigation efficiency) on the crop patterns and farmers’ profit. Required data for this study were collected from various sources. The data related to the Hydrological aspect was obtained from Khuzestan Water and Power Authority (KWPA) and Khuzestan Meteorological Office for the base period 1960-2018. Also, the required economic data were obtained through interviews with 180 farmers which randomly selected in Karkheh basin and Agriculture Organization of Khuzestan province.
Results and Discussion: The results of the WEAP model show that climate change will decrease the availability of water in agricultural areas of south Karkheh sub-basin. But the impact of climate change varies across regions. So that the water available in Payepol and Karkheh-Noor is reduced by 8.29% and 32.76% respectively. The MABIA method results also indicated that the B2 climate change scenario in the 2018–2050 periods may have a severe impact on crop yields and irrigation water requirements.The MABIA method results  also showed that the climate change scenario will likely lead to crop yield decreases, ranging between 1.5% and 34.05%. These changes in crop yields would be accompanied by increases in irrigation water requirements ranging between 1.11% and 22.43%, for all crops. A strategy to improve irrigation efficiency will mitigate the effects of climate change on the performance of different crops (especially rice crops). The results show that applying this strategy does not have a significant impact on the pure water requirement (actual evapotranspiration of products). In fact, applying this scenario (improving irrigation efficiency by 20%) will reduce gross water requirement by preventing water loss. Finally, results of the Positive Mathematical Programming showed that the total irrigated crop area is reduced under climate change by 17.93%. Therefore, Total agricultural profits decrease by 44% under climate change, compared to the reference scenario. The Karkheh Noor irrigation area faces the largest reductions in crop area. Also, this area shows the largest reduction in agricultural profits (59.9%). In contrast, the smallest decrease in crop area and agricultural profits have occurred in Payepol. But the reduction of water use due to the improving irrigation efficiency will increase the profit of agricultural activity in the Karkheh sub-basin by 340 billion Rials.
Conclusion: This research has tried to contribute to the analysis of climate change impacts and adaptation by addressing the processes that occur at the sub-basin level. The Karkheh sub-basin case study, an illustrative example of critical water and climate interactions, permitted to illustrate climate change vulnerability and adaptation. The results of this study showed that Climate change can affect South Karkheh sub-basin's agriculture through changes in water resource flows and allocations. These changes impose remarkable economic costs on farmers. But the application of on-farm adaptation option via investment in improved irrigation efficiency technology does reduce the impact of climate variability. Therefore, this research demonstrates that the implementation of such a policy, can support adaptation and reduce the risk faced by farmers in light of climate change.

Abstract Introduction: Due to fossil fuels overuse, land use change, global population growth and the development of industrial activity to meet the welfare and demands of the global community, global climate has undergone gradual, but drastic, changes in the post-industrial revolution era mainly manifested in the rise of mean temperature, more frequent extreme climatic events like floods, hails, tropical storms, heat and cold waves, rising sea level, polar ice melting, droughts and etc. Climate change is a mix of dominant and lasting atmospheric characteristics of a geographic area over time and is often based on such variables as temperature, precipitation, humidity, wind, solar radiation, and number of sunny days, sea level temperature, and the thickness of ice layers at sea. Climate of a region is dedictated by a set of these factors in the long run, as well as other local characteristics such as the length of growing season and the intensity of floods whose change influences how people live and harm different sectors including agriculture and environment. Present study aimed to explore the impact of climate change on total agronomical production in 10 agro-ecological zones of Iran.
Materials and Methods: Present study employed panel data econometrics to explore the impact of climate change (mean precipitation, temperature, evapotranspiration rate, relative humidity, wind speed) on total agronomical production over the 1985-2015 periods. The panel data set included the observations related to multiple sectors and have been collected at different times. Panel data has been used when it is impossible to use just time series data or cross-sectional data. They contain more information in addition they are more diverse and have less multicollinearity between variables, so they are more efficient. In analysis of the combined data firstly should consider a certain section (e.g. country, region or province) and then focus on the attributes of the variables related to all N sections over a certain period, T. The number of data is not required to be equal over the sections (unbalanced panel model) and it is also possible to have variables that are constant in a certain section over the studied time period. In a panel data model, the variables are measured sequentially both among the sections of the statistical population and over time. In panel data, before proceeding to model estimation, we should firstly recognize whether panel or pool model is appropriate for the estimation and statistical inference. To do this, we first integrate whole data as pool to estimate the model and calculate the sum of residual squares. Then, the model is estimated as a panel model with different y-intercepts for a certain section and the residual squares are again summed. Finally, F-statistic is applied as the following equation to test the constructed model. The data were collected from Iran Meteorological Organization and Ministry of Jihad-e Agriculture. After checking the stationarity of the data, panel model with random effects has been estimated.
Results and Discussion: The results showed that total agronomical production has been influenced by temperature, evapotranspiration, and wind speed at 0.05 level and precipitation at 0.10 level. The impacts of global warming can be currently observed across the world. Agricultural sector is especially vulnerable to climate change so the rise in average seasonal temperature would shorten the growth period of most crops, causing the loss of their yields. Climate changes, such as the change in temperature, precipitation, pest and disease outbreaks adversely influence food production systems, decrease harvest and jeopardize food security. As predicted for Iran, it is expected that occurrence of climate change – which is characterized by rainfall decline, rise in temperature, and increase in the occurrence of extreme weather conditions – have harmful consequences for the agronomical production.
Conclusion: Climate change imposes remarkable economic costs on agronomical producers. The producers may have to either stop growing these crops or adapt to climate change as far as possible. In most cases, it is not economically feasible for producers to apply adaptive methods and the majority of their life aspects are potentially influenced. According to the results, it is recommended to use water pricing policies in agricultural sector that motivate farmers to use modern irrigation technologies and low irrigation-resistant cultivars, alter planting pattern towards crops with higher water use efficiency, therefore plan for and grant financial facilities, such as crop insurance, in order to prepare agronomical farmers for climate change. 

Abstract Introduction: Climate change is one of the most important issues that affect different sectors of the economy. Climate change affects precipitation and temperature and by disrupting optimal growth conditions will reduce crop yields and thus exert influence on food security and the spread of poverty in agricultural societies as a consequence.  Production sectors, labor income and institutional income are affected by changing climate, and sectors that are more interactive with the agricultural. Specific features of the agricultural sector such as the dependence on climate variables have made this sector the focal point of climate change. Based on this, the present study examines the effect of climate change on economic growth of agriculture in Iran in the form of a dynamic computable general equilibrium model (DCGE). Materials and Methods: In this research, DCGE has been used to investigate the effects of climate change (e.g. reduction of rainfall) on macroeconomic variables in Iran's agricultural sector. In order to implement the DCGE model, the social accounting matrix of 2011 has been used. The social accounting matrix represents the circular flow of funds between sectors, factors and institutions in a market economy. The social accounting matrix, which is a square matrix, is set up to equal the sum of rows and columns. The columns represent the receipts (revenue) and the rows represent the payments. Therefore, according to this definition, the total revenue of all accounts must be equal to the total expenditures of all accounts. In other words, the income of each economy is equal to the total cost of that economy. Since the social accounting matrix is ​​a descriptive tool for illustrating the details of the structure of a country's economy, it will also be considered as a tool for general equilibrium analysis as it provides information on the relationship between production sectors and the external world as well as the relationship between income and consumption.  It should be noted that in the current study, the model was solved in the form of GAMS software. In order to estimate the results, it is necessary to go through two steps. At first, the model parameters are estimated to the value of the model decision variables then the solution would be equal to real values which are called calibration. Subsequently, by changing the variables related to climate change the model decision changes over the years are examined. In other words, by using the DCGE model, we studied the effects of climate change on important variables in the agricultural sector. Results and Discussion: The results of this study about the effect of precipitation on the productivity of the agricultural sector indicate that one percent change in rainfall will reduce the productivity of agriculture by 0.79 percent. Based on the results of previous studies, by 2030 rainfall in Iran will be reduced by 9%, which means rainfall will decrease by an average of 0.3% per year. Thus, the productivity of agricultural sector will decreases by an average of 0.237% per year. Accordingly, the effect of changes in agricultural productivity (technological coefficient of Cobb-Douglas function), as a result of climate change, was measured on the macroeconomic variables of the agricultural sector including production, consumption, investment, exports and import. Results show that climate change decreases the production, consumption, investment and exports, and increases the imports by 2030. Conclusion: The results of this study indicate that considering the amount of rainfall reduction in the 20-year horizon by 2030, the amount of production, consumption, investment and export of agricultural sector will decrease by 4.469, 5.025, 4.462 and 13.770 percent respectively, but imports in this sector will increase by 5.504 percent. Given the impacts of climate change on the macroeconomic variables in the agricultural sector, it is imperative that the government take appropriate measures to support this sector while confronting unfavorable climate. Considering role of capital in agriculture, results of this study indicate that due to the consequences of climate change in the assumed period the investment process of agricultural sector has a smaller share than other sectors. Therefore, in these circumstances, policies such as fixing the price of agricultural commodities, increasing the granting of loans by banks and other policies should be undertaken to encourage the private sector to invest in this sector.

Abstract Introduction: Climate is one of the basic factors in nature that its change is one of the most important challenges in current century. Increasing emissions of greenhouse gases, as the most important affecting factor on climate change, lead to change of temperature, precipitation and other climatic parameters. Unlike the other sectors, agricultural sector is more vulnerable to damages caused by climate change, so that the atmosphere precipitation and temperature average patterns changing damages the horticultural and agricultural production which are the main food sources in society. Both amount and quality of production reduction arises from climate change, consequently put farmers' income at risk. In the group of cereals, wheat was the most important crop in the country during the 2013-2014 crop year with the highest cropping area of 51.22%. East Azerbaijan province with the cultivated area of 40.6% of the country's total wheat has ranked sixth among producers of this crop. Ahar, one of the largest producers of wheat, has 95.5% of the province's cultivated area. Rainfall and temperature variations show climate risks for wheat, which are the most important indicators of climate change. Usually, the highest correlation is found between wheat yield and rainfall, so that the correlation coefficient between wheat yield of Ahar and rainfall in wheat growing season (October to July) was 45%, which indicates that most of the variation of yield is explained by rainfall. Therefore, risk management in agricultural sector, particularly weather risk, is highly important; however, risk management strategy cannot be implemented properly without identifying and measuring it. Hence, with attention to the importance of weather risk measurement, in this present study we tried to measure the rainfed wheat yield risk caused by climate change in Ahar County in two base (1986-2015) and future periods (2016-2045). Materials and Methods: We applied weather Value at Risk (VaR) and weather conditional value at risk (CVaR), aquacrop, HadCM3 general circulation models under A2 emission scenarios and downscaling Lars-wg application. For this purpose, we collected weather information between 1986 and 2015 from East Azerbaijan Province Meteorological Organization, yield and soil feature data of 1991-2015 crop years from Management of Agriculture of the city of Ahar. The concept of ‘Weather Value at Risk’ represents a method to measure non-catastrophic economic weather risks. It captures both a socio-economic indicator’s sensitivity and exposure towards weather variability. Weather-VaR (α) denotes the Value at Risk resulting from adverse weather conditions, and represents–for a given level of confidence [α] over a given period of time–the maximum expected losses. Conditional Value at Risk (CVaR) attempts to address the shortcomings of VaR model, which is a statistical technique used to measure the level of risk within a firm. Conditional Value at Risk (CVaR) also known as the expected shortfall is a risk assessment measure that quantifies the amount of tail risk an investment portfolio has. CVaR is derived by taking a weighted average of the “extreme” losses in the tail of the distribution of possible returns, beyond the value at risk (VaR) cutoff point.. AquaCrop was chosen because it is a crop water productivity model that simulates yield response to water of herbaceous crops, and can be used specifically in situations where water is a key limiting factor in crop production. AquaCrop has the additional advantage that it is relatively simple and robust and uses “a relatively small number of explicit and mostly-intuitive parameters and input variables requiring simple methods for their determination”. AquaCrop was specifically designed for “assessing water-limited, attainable crop yields at a given geographical location” and “carrying out future climate scenario analyses. Results and Discussion: The results show that in the future period, precipitation, maximum and minimum temperature, solar radiation, maximum and minimum relative humidity, wind speed and evapotranspiration variables will shift 9.15 millimeters, 0.63 and 0.56 Celsius degrees, 0.06 MJ/m2/d, -0.61 and -0.29 percent, 0.03 m/s and 18.48 millimeters per year, respectively. Based on the weather variables change, the yield average will increase from 0.954 in the base period to 0.999 t/ha in the future period, and beta and wakeby distribution were selected for yield as the best distributions to measure risk. Compared to base period, yield risk is reduced. In three probability levels, that is 1, 5 and 10 percent, and based on VaR method the amounts of risk reduction were obtained 0.139, 0.83 and 0.61 for beta distribution, and 0.297, 0.81 and 0.31 tons per hectare, respectively for wakeby distribution, while in CVaR method for beta distribution were 0.158, 0.115 and 0.93, and for wakeby distribution were 0.403, 0.148 and 0.77 tons per hectare, respectively. Conclusions: According to the results, evapotranspiration is one of the variables that increase the yield risk; therefore, it is recommended that farmers use the natural and artificial mulch to reduce evaporation from the soil surface.

Abstract Introduction: The reducing of supplies of underground water poses a serious threat to the water security of the country, a problems which seems not to have been taken seriously. Climate changes and the result that changing in water cycle have made the challenges of water supply even more complicated. Immediately soaring and unbalance growth of population (about 80 million people in 2015) has to lead a drop in per capita water. The rapid growth of urbanization, interminable migration to the metropolis for better welfare, and the need for more food have testified the need for the promotion of health and hygiene, the industrial development of water demand and consequently the pressure over water resources. Due to population growth in Iran, the annually per capita resources of renewable water which was 7000 m3 in 1956 and in 1996 dropped to 2,000 m3 and it is predicted to decrease to 800 m3 in 2020. Moreover, population settlement pattern have lost its compatibility with the temporal and spatial distribution of water resources in the country (Center Statistics and Water Resources Management, 2015). The purpose of modeling in this study is create and develop a simulation model in order raise our understanding of the resources, the uses of such resources as well as their dynamics so that some of solutions are provided for the system to retain its proper functioning. Material and Method: This study have projected the effects of the agricultural sector on water resources depletion. For this purpose, the model is extended and simulated from 2013 to 2063 to four sections of hydrology, water demand and socio-economic. In this study, we used the econometric time series models to develop a systems dynamic modeling and used annual data from 1983 to 2012 to evaluating the effects of economic, social and environmental effects on water resources. For studying, the stationary of variables which are used in experimental models used Augmented Dickey-Fuller (ADF) and Zivot-Andrews (ZA, the unit root test with one structural break) unit root tests. The data were collected from Central Bank of the Islamic Republic of Iran, Center Statistics of Iran, Iranian Ministry of Agriculture, FAO, World Bank and Iranian Water Resources Management Organization the statistical collected and these data were analyzed by statistical softwares in term of, Stata 12, Excel, Vensim and iThink 9. Systems dynamics has developed in a wide range of issues, Forrester (1973) were used in integrated design strategy and planning. System dynamics is an approach to understanding certain types of the complex system problems. Casual-loop diagrams and the modeling process is a simple way to display the loop structures before formulating equations. Flow diagrams include the rate variables, level, auxiliary and fixed elements and a series of tests, operations, and procedures which organize for integrate network issues in management, economic, financial and industry. In this study based on iThink software, a model was developed for projected the effects of agriculture and non-agricultural sectors on the utilize water sources in Iran from 2013 to 2063. The model extended in hydrology, water demand, agricultural economics, and population sectors. To achieve this, water resources were considered as surface water resources, reservoir, groundwater and virtual water. Results and Discussion: The result of Augmented Dickey-Fuller (ADF) and Zivot-Andrews unit root tests showed that production, import and export of agricultural products, capital of the agricultural sector, exchange rate, consumer price index, oil income, population, income per capita, acreage and water use variables, which except for the oil income and population, income per capita, other variables are rejected the null hypothesis of unit root. The results of Iran's water resources dynamic model simulate from 2013 to 2063, as well the verification results of the surface water, groundwater aquifers and reservoir level variables from 193 to 2012. The results illustrate that Iran's water resources are decreasing and it is projected that extremely depleting in next 50 years. It is projected that surface water discharged very severe and from 450 (billion m3) in 2013 decrease to 386 (billion m3) in 2063. As well the reservoir water shown downward trend behavior and decrease from 30 (billion m3) in 2013 to 22 (billion m3) in 2063 and the accessible groundwater aquifers decreasing from 120 (billion m3) in 2013 to 83 (billion m3) in 2063. Conclusions: Based on simulation model, it is projected that water shortage in agricultural and non-agricultural sectors, the price index of agricultural products and waters price are soaring over time. Thus, some policies can revitalize the water resources such as reducing the number of legal and illegal withdraw ground water, importing water-intensive agricultural products, modifying the cropping pattern, adopting with climate change, importing water and increasing water use efficiency in the agricultural sector.

Abstract Introduction: The increasing global consensus built on empirical evidence, expresses that the world, is facing a threat from climate change. As a result, this can affect the agricultural sector through its productivity changes and so influence food security in the world. This can be more intuitive for countries that are dependent on agriculture. Agriculture is an important sector in Iran that provides 12 percent of gross domestic production (GDP) and 21.2 percent of employment. In this country, annual crops as an important agricultural production have 12.2 million hectare cultivation areas. They are grouped into vegetables, cereals, beans, industrials crops, forage crops and cucurbits. The shares of planted aria for these groups vary in different country's regions due to cultivation conditions differences including climatic variables. This indicates the importance of studying the climatic variable effects on these shares. Therefore, this study is aimed to assess the effect of climatic variables such as temperature, participation, humidity and wind speed on land allocation between annual crop groups in Iran's counties. This can provide useful information about the effects of climatic variable on crop shares. To achieve the purpose, using statistical methods and specifically the fractional multinomial logit model is considered. This study is benefited from advantages such as using of fractional multinomial logit model, comprehensiveness and choosing the whole country as a case study and the specific crops grouping way that distinguishes it's from the other related studies in the country. Materials and Methods: Because the shares (fractions) of annual crop cultivation area for each county(observation) are limited values that vary between 0 and 1 and the sum of them is one, using of fractional models, is considered. In these models the dependant variables vary between 0 and 1, and each observation has several fractions that their summation is one. Papke and Wooldridge (1996) introduced the fractional logit and probit models that have a tow fraction for each observation. After them, Sivakumar & Bhat (2002) introduced the multinomial fractional logit model that can include more than two fractions for each observation. These models use quasi-likelihood methods for estimation of parameters and their standard errors. For estimation of the fractional multinomial logit model, this study uses Iran's 336 counties agricultural and weather information. Annual agricultural crops information is taken from the agricultural ministry and weather information is taken from the national meteorology organization. In this regard, the crops planted area shares and weather information in 1391 are used to explain the shares of annual crops planted area shares in 1392. Results and Discussion: Since the weather information was on monthly scale, estimation of different models with annual crop shares variables and annualy and seasonally, Weather variables (their average, standard errors and coefficient of variation) was considered for choosing the best model based on Akaike information criterion and Bayesian information criterion. Comparing the models showed that the model with annual weather variables averages is the best. So in the next step, using the model, the marginal effects were estimated. According to the result, increasing temperature has created concerns in all fields, including the agricultural sector, affects cereals and beans productions as two important sources of food in the world. It increases the planted area share of cereals and decreases the cultivation area share of beans. The participation affects all groups' cultivation area shares except cucurbits. That is the effect of cereals planted area and its share is stronger, one centigrade degree increasing of temperature increase the share of cereals cultivation area 0.02 percent. Humidity percent influences vegetables and industrial crops planted area shares and increase them. Wind speed respectively decreases and increases industrial crops and cereals cultivation area shares. According to the results also, conventional farming patterns and other agricultural system’s rules such as crop rotation in each area has important effects on the farmers' decisions on land allocations. Conclusion: Based on the above results we can conclude that along with the climate changing, the annuals crops cultivation area shares and thus the amount of their production will be affected in the future. This shows the importance of using accurate methods to predict the possible values of climate variables in country's regions under different scenarios for next years. Because in this way, we can predict potential changes in the future annual crops productions and compare potential production and population food needs. This can determine the gaps between potential production and potential consumption in the future. In this regard, decreasing of agricultural sector problems in the face of climate change in the next decades would be possible by providing appropriate policies and procedures. One appropriate procedure is producing of resistant varieties of climate change results such as rising temperatures. This can define as one of the objectives of agricultural research centers. Considering that this research has studied the land allocation between annual crops, it is suggested to researchers that consider studying of other agriculture's sectors productions such as livestock and Fruit in the next research.

Abstract Introduction: Greenhouse gases absorb the radiation reflected from the earth surface which would otherwise be sent back into space. The composition and mixture of these gases make life on earth possible. In recent years, human activity has affected both the composition and mixture of the atmosphere, modifying the climate. When climate changes, crop production is affected. There are many studies that consider the type and amount of production changes for particular crops, places and scenarios. Others attempt to expand knowledge about production changes and their impacts on economy and regional welfare. Climate change affects agriculture through direct and indirect affects i.e. temperature, and precipitation changes in the biological and physical environment. Restriction in water availability is one of the most dramatic consequences of climate change for the agricultural sector. Water availability is expected to be even more limited in the future. Scarcity of water is due to potential evapotranspiration increase. It is related to increase in air and earth surface temperatures. This phenomenon is important in low-precipitation seasons, and is even more severe in dry areas. The number of regions with loss of soil moisture is expected to increase, resulting in direct economic consequences on the production capacity. Considering the above decisions, the main objective of this paper is to integrate climate change into agricultural decision-making by using an Economic Modeling System to identify the impacts of climate change induced by greenhouse gas emissions on agricultural sector productions and available water resources in the down lands of the Taleghan Dam. Materials and Methods: In this study, the effects of greenhouse gases on climate variables of temperature and precipitation under emission scenarios A1B, A2 and B1 were evaluated using time series data from 1981- 2008 and General Circulation Models (GCM). Then Ordinary Least Squares (OLS) was used to survey the impacts of climate variables on the selected products yield. Changes in agricultural production, farmer’s gross profit and economic value of irrigation water were analyzed and compared with the base year by the regression analysis results in the Positive Mathematical Programming (PMP) model. This methodology that was developed by Howitt (1995) to calibrate agricultural supply models has been used to link biophysical and economic information in an integrated biophysical and economic modeling framework and to assess the impacts of agricultural policies and scenarios. These models are also accepted for analyzing the impact of climate change and water resources management policies and scenarios. The PMP model used in this paper is a three-step procedure in which a non-linear cost function is calibrated to observe values of inputs usage in agricultural production. In the basic formulation, the first step is a linear program providing marginal values that are used in the second step to estimate the parameters for a non-linear cost function and a production function. In the third step, the calibrated production and cost functions are used in a non-linear optimization program. The solution to this non-linear program calibrates to observed values of production inputs and output. The required data in this paper were collected from meteorological stations and the relevant agencies in the Qazvin province. Regression functions estimated in Eviews software package and the PMP model were solved in GAMS (General Algebraic Modeling System) software. Results and Discussion: The results obtained in this paper showed that with emissions of greenhouse gases under the studied scenarios (A1B, A2 and B1), the average annual climate variables of temperature and precipitation changes from 1.64 to 2.28 °C and from20.92 to 1.1 mm, respectively. With these change, the yield of the most selected products decreases in the down lands of Taleghan Dam. Moreover, the obtained results showed that with emissions of greenhouse gases under the scenarios A1B, A2 and B1, the total acreage of the selected products changes from 2.18 to 4.09 percent. Total used water also decreases from 1.67 to 5.18 percent. Moreover, with emissions of greenhouse gas under the above scenarios total farmer’s gross profit decreases from 1.93 to 3.72 percent. However, the economic value of water increases from 4.27 to 13.6 percent in comparison with the base year. Conclusion: In this study finally, in order to reduce greenhouse gas emissions in the vicinity of the down lands of the Taleghan Dam, it is recommended that the government should use punitive tools (green complications) for polluting units and serve the private sectors in forestry projects in the vicinity of the industrial towns. Keywords: Agricultural productions, Climate change, Greenhouse Gases, Positive Mathematical Programming, Taleghan Dam

Abstract Agricultural sector will be most affected by climate change due to its extensive interaction with the environment. and as a result of changing production conditions, community welfare is changed. This study attempted at understanding the welfare effects of changes in climate parameters on the wheat product. Therefore, the yield functions were initially estimated. Supply, demand and import functions were secondly estimated by Simultaneous equations system. Finally, to study the welfare effects resulting from changes in temperature and precipitation, a price-endogenous mathematical programming model in three different scenarios of climate was used. The results showed that in the case of reducing precipitation with increasing temperature, consumer surplus, producer surplus and therefore society surplus will be reduced . Loss of welfare for consumers are higher than what is for producers.

Abstract Over the coming decades, global change will have an impact on food and water security and there are strong indications that developing countries will bear the brunt of adverse consequences from climate change. Agricultural sector is the most vulnerable to climate change, because of its dependence on water and temperature conditions. Consequently, it is important to understand the impacts of climate change on agriculture and natural resources in developing countries. The goal of this study was to estimate the potential impacts of climate change on Fars province’s agricultural sector. To this end, this study was organized in three sections. In the first section, time series data covering 21 years (1988-2008) on crop yields, climate or non-climate related variables were used to estimate yield response functions. In the second section, the yield equations were used to investigate the physical impacts of alternative scenarios. In the final section, a price-endogenous mathematical programming model was used to simulate the welfare impacts of yield changes under various climate change scenarios. Sixteen combinations of alternative climate change scenarios which include 0°, 0.27°, 0.54°, 2.35°centigrade for temperature and -13, -6.5, 0, +20 percents for precipitation were made based on the findings of Ravan (2010). The results showed that both temperature and precipitation had a significant but non-monotonic impact on crop yields. The comparison results indicated that climate change impacts on welfare were mostly positive and the impacts on producers were much more significant than they were on consumers. Social welfare decreases by 1.5 percent if the reduction of precipitation is associated with no change in temperature but it increases by 13 percent at the most humid and warmest scenario. Finally, it was found that temperature is more significant factor than rainfall in the change of social welfare.

Abstract Climate change phenomenon is an important environmental challenge of the world that has increased its speed with the increasing extension of greenhouse gases and remote relationship phenomena. Changes in precipitation level, drought occurrence and in the level of surface and groundwater resources are the recognized consequences of climate change. In order to study climate change phenomenon consequences on agricultural production in Shiraz County, three wells rings in Shiraz plain were selected. Mean statistics of water level in wells were regressed on the year during 1978-2008. Using annual statistic of precipitation during 1958-2008 and standard precipitation index (SPI), the probability of dry year incidence determined. Effects of 5 pumping scenario in 3 states of nature was assessed using two-stage stochastic programming. Results showed that water levels at the desired level of agricultural wells has significant decrease 0.4 percent (p=0.034). The long-run loss of income and farm income under the mild climate change and dry years was 4.5 and 6.4 percent. The short-term loss of income and agricultural income in the same scenarios were estimated from 54 and 30 percent to 74 and 85 percent, respectively. Agricultural water use in the short and long term was estimated less than the status quo. Reduction in water use will lead to reduction in yield and farm income in the performance area, however, will prevent the long-term damages to crop production levels and underground water resources. Finally, taking support policies to increase farmer's incentives in appropriate use of water resources is recommended.