جستجوی مقالات مرتبط با کلیدواژه « cropping pattern » در نشریات گروه « آب و خاک »

Evapotranspiration variations (ET0) were investigated and analyzed using Minitab16 software for the 2010-2019 period using the Nizab system's data in Yazd province, and then ET0 was predicted until 2027. Based on the results, the increase of ET0 in cities of Yazd province was affected by the enhancement in wind speed and weather temperature, and the decrease in relative humidity from 2010 to 2019. To determine the appropriate model, Ardakan, Abarkooh, and Taft cities were selected as a representative in each climatic group, and ET0 data for the years 2010 to 2015 were considered as the input data of the software and ET0 data for the years from 2016 to 2019 were used to validate the determined model. The prediction of the determined models showed an increasing trend of ET0 for cold seasons in Ardakan and Abarkoh by 2027. Also, the model prediction showed a decreasing trend of ET0 for hot seasons in Taft by 2027. Also, the ET0 will not change significantly in cold seasons. In Abarkoh and Ardakan cities, autumn-spring crops such as wheat and in Taft city, spring-summer crops such as sunflower will be more affected by ET0 variations.

Due to the limitation of surface water resources and excessive exploitation of underground water, the underground water table in many plains of Iran is in an unfavorable condition. One of these critical plains is the Dehgolan Plain, which is still facing a water shortage crisis despite its designation as a prohibited area. Therefore, in this research, the effect of tax and subsidy incentive policies for each added or saved cubic meter of water consumption on the changes in the cultivation pattern has been investigated in three scenarios of 10, 20, and 30 percent increase in the shadow price of water (714 Tomans) in 2023. The required data were collected by referring to Kurdistan Regional Water Company, Agricultural Jihad Organization, and the country's water demand system for seven major crops including Wheat, Barley, Forage corn, Potato, Cucumber, Alfalfa, and Rapeseed in Dehgolan plain. Then, the data were analyzed using the positive mathematical programming (PMP) model. The results showed that the application of tax and subsidy policies pushes the cropping pattern towards low-water-absorbing crops such as barley, wheat, and canola. It was also found that these policies reduce water consumption and gross farm yield. These findings show that the mentioned incentive policies can be an effective tool for managing water consumption in the agricultural sector. Of course, it is necessary to consider alternative solutions such as the use of new irrigation methods in addition to these policies to prevent negative effects on farmers' income.

This study was conducted to evaluate the real cropping pattern of Khuzestan province in a normal water year (2018-2019) in terms of water withdrawal management from surface resources. For this purpose, the actual evapotranspiration of the products was calculated from the ratio of the available yield of different products (according to the agricultural statistics of 2018-2019) to the potential yield (the highest yield according to the agricultural statistics) by applying the country's water demand line system based on 10-year meteorological data. The results showed that the total water withdrawal from surface resources for the cultivated area of the crop year 2018-2019 (except greenhouses, livestock, poultry, and some products with a small area) was 18856 MCM, so the actual consumption (net irrigation requirement) was estimated 4310 MCM. Considering the Khuzestan Water Scarcity Adaptation Program, the total demand for agriculture and the environment with a confidence level of 80% in the Karun and Karkheh basins was 36 and 23.8% lower than the river flow, respectively, while it decreased to -72% in the Jarrahi basin, which indicated the failure to achieve the minimum environmental requirement. Since the Karkheh River flow has a more severe fluctuating behavior than that of Karun, this behavior cannot be predicted in the linear analysis of average values, and in droughts, it is less than the mentioned number. Therefore, dynamic planning in the field of cropping pattern change, providing various types of drought insurance, implementing infrastructure for the temporary purchase of water rights by the government, and other support policies are suggested in basins such as Karkheh, which has a highly fluctuating behavior in water supply.

Considering the climate suitability in cropping pattern selection is vital in maintaining food security. In this study, the climate suitability of East Azerbaijan Province, north east of Iran, for the cultivation of strategic crops of wheat and barley during four decades 1980 to 2000s was evaluated. Land units were classified based on the covered area of each synoptic weather station using Thiessen method. Climate suitability for rainfed and irrigated wheat and barley was evaluated according to their climatic requirements using the square root-parametric method. Results revealed that during the recent four decades, the climate suitability class for irrigated studied crops was very suitable across the province, but in case of rainfed cultivation, various suitability classes including moderate to unsuitable were observed in different regions. The results confirmed that despite of some unfavorable effects of climate change on suitability of region for both crops cultivation, these impacts might be compensated, to some extent, by technology or management improvements. According to this study, determination of an optimum cropping pattern, adjusting agronomic practices and changing of rainfed wheat to barley in this province may be recommended.

One of the strategies for agricultural development is the optimal use of irrigation and drainage networks, which will lead to higher productivity and environmental protection. The present study used the system dynamics approach to develop a model for simulating the cultivated area of the Shahid Chamran irrigation and drainage network located in Khuzestan province by considering environmental issues. Limit test and sensitivity analysis were used for model validation. The results showed the proper performance of the model and the logical relationship between its parameters. Also, the cropping pattern of the network was determined in two modes of non-stepwise and stepwise changes to determine the optimal cultivated area of the Shahid Chamran network with environmental objectives and minimize the amount of salt from drains. The results showed that the amount of optimized output salt from the network has decreased in both non-stepwise and stepwise changes compared to the existing situation in the region. The total output salt in the current situation, from 2013 to 2017, was obtained at 2799, 2649, 2749, 2298, and 2004 tons.day-1, respectively, in the stepwise changes, are 2739, 2546, 2644, 2223, and 1952 tons.day-1, and finally, in the non-stepwise changes, are 2363, 2309, 2481, 2151, and 1912 tons.day-1. The results showed that the non-stepwise changes due to considered limitations have been more successful in reducing output salt than the stepwise changes. The analysis of the results showed the model's success in optimizing and achieving the desired goals. The results showed that the present model has good accuracy in simulating and optimizing the irrigation network, cropping pattern, and defining other scenarios.

Water is one of the most important factors of development in human societies, water scarcity, specially fresh water which is one of the main limitation for agricultural, economic and social development in most developing countries. Providing and implementing an optimal cropping pattern, in addition to better management of water and soil resources, can lead to reducing production risk, increasing the ability to deal with crises, improving employment, better management of providing services to farmers, and providing the possibility of expanding agro-based industries. In many regions of the world, including in Iran, many studies have been done to improve the cropping pattern in different regions. Despite the existing problems in designing and implementing the appropriate cropping pattern in the plains, modifying the cropping pattern based on scientific principles and emphasizing the reduction of water consumption while reducing water consumption provides the possibility of sustainable agriculture and in terms of economic and social aspects. Implementing an optimized cropping pattern in the Farahan Plain is an undeniable necessity to preserve national resources. This study was conducted with the objective of optimizing the cropping pattern in the area, taking into account multiple criteria.

In this research, considering the importance of determining the cropping pattern based on the multiple objectives of the decision makers, it was tried to determine the optimal cropping pattern by using mathematical programming and fuzzy logic by establishing a compromise between the objectives of the cropping pattern. The model considered for this study was in the framework of the goal of the maximum ideal distance (Fuzzy Composite Distance). Also, in order to use water resources sustainably, scenarios of cropping patterns are presented based on different conditions of water resources uses. Based on the basin's water resource stability, an optimal cropping pattern was developed to address the conditions of normal water resource exploitation, as well as sustainable and unsustainable scenarios. Each scenario corresponds to a specific period. To achieve this, a multi-objective planning approach was utilized, integrating water, food, energy, and economic profit indicators. The resulting optimal cropping pattern considers stable water resource utilization during normal, drought, and wet periods, ensuring sustainable conditions.
 

The results showed that the amount of water consumed by the optimal cropping pattern compared to the existing cropping pattern under normal, drought and wet conditions is reduced by 23.2, 29.2 and 18.1%, respectively. On the other hand, compared to the existing cropping pattern, the amount of calories produced by the optimal cropping pattern under normal, drought and wet conditions increases by 51.7, 61.9 and 45.2%, the average energy efficiency increases by 40.9, 42.8 and 35.8% and the net profit productivity increases by 43.3, 30.9 and 44.2 %, respectively. Based on the obtained results, it can be seen that in the optimal cropping pattern in drought conditions, the cultivated area of crops such as potatoes, onions, tomatoes, grain corn, sugar beets, beans, alfalfa and watermelons should reach to the zero or be at the lowest possible level. In normal and drought conditions, the cultivated area of these crops should be minimal. On the other hand, the area under cultivation of crops such as fodder sorghum, fodder corn, saffron, cumin, camellia and medicinal plants should be increased and the cultivation of these crops should be promoted at the region. Also, regarding horticultural products, the cultivated area of walnut, apple, peach, apricot and almond orchards should be minimized and replaced with plants such as grapes, oleaster, jujube, barberry, rose, and figs.

Based on the obtained results, it was found that the use of the optimal cropping pattern derived from the indicators of water, food, energy and economic profit is completely superior and preferred over the existing cropping pattern and single purpose optimal cropping pattern. In order to achieve sustainable water resource management, it is recommended to modify the cropping pattern during drought, normal, and wet periods based on the suggested optimal cropping pattern. The existing cropping pattern currently falls short in terms of achieving the four objectives of water, food, energy, and economic profit. Therefore, it is crucial to develop main plans and strategies in the Farahan Plain that align with the implementation of the proposed optimal cropping pattern. By doing so, it will be possible to optimize the allocation of water resources and achieve improved outcomes in terms of water availability, food production, energy efficiency, and economic profitability.

Due to the increasing population growthand limited resources available, achieving a suitable cropping pattern from which maximum utilization of production factors and inputs, especially water as a limiting factor, can be obtained, is an undeniable necessity. The aim of this study was to rank arable crops in the Farahan plain using multiple criteria and analytic hierarchy process. Forthis purpose using AHP method cultivable crops were ranked based on four indices of water, food, energy and economic profit and also the combination of these four indices. The results of AHP analysis showed that the economic profit criteria with a weight of 0.35 and then water consumption with a weight of 0.31 are the most important factors in prioritizing arable crops in the Farahan plain. The value of consistency ratio in all criteria and sub-criteria was less than 0.1, which indicates the acceptable level of agreement in the analysis. The results showed that the first priority of cultivation in the region based on water consumption criteria, were saffron, cumin and camelina, basedon calorie production, were forage sorghum, potato and corn, based on energy consumption were, forage sorghum, forage corn and grapes and based on the economic benefits were, lavender, thyme and borage, respectively. The results showed that the current cropping pattern in the study area is not an acceptable cropping pattern and optimizing the cropping pattern based on the multiple criteria and prioritizing crop cultivation based on these criteria should be on the agenda of managers and decision makers. Prioritization of crops cultivation based on the fourcriteria mentioned in this study provides the foundation for the gradual implementation of the optimal cropping pattern in the plains. Therefore, according to the results obtained in this study, it is suggested to use multi criteria decision-making methods to prioritize arable cropsand select the optimumcropping pattern.

In the present study, a model was developed using a system dynamics approach to simulate and optimize the profitability of crops of the Jofeyr (Isargaran) Irrigation and Drainage Network located in Khuzestan Province. To validate the results, the statistical indicators of root mean square error (RMSE), standard error (SE), mean biased error (MBE), and determination coefficient (R2) were used. To validate the simulation results of the benefit-cost ratio, the values of these indicators were obtained 0.25, 0.19, 0.005, and 0.96, respectively. Then, to determine the optimal cultivated area of the network and increase the profitability, the cropping pattern was determined both non-stepwise and stepwise in 2013 to 2017 cropping years. In the non-stepwise, the cultivated area of each crop changed from zero to 2 times of current situation. In stepwise, due to social and cultural conditions of inhabitants, this change was slow and 10% of the current situation every year. The analysis of the results showed the success of the model in optimizing and achieving the desired goals and the total benefit-cost ratio increased in all years both non-stepwise and stepwise. For example, in 2017 compared to 2016, production costs decreased by 7.1 percent and sales prices increased by 5.8 percent, and increased the benefit-cost in 2017 compared to the previous year. The results showed that the present model has good accuracy in simulating and optimizing the irrigation network, its cropping pattern, and defining other scenarios.

Water, as a major limiting factor in production, plays an important role in determining the type of agricultural activities in Iran. The occurrence of droughts in recent decades have also threatened these activities. Today, one of the most effective responses and strategies for agricultural drought risk management is to identify vulnerable areas and determine the optimal pattern of low-water cultivation. Therefore, the aim of this study is spatial analysis of agricultural drought vulnerability and introduce a pattern of low-water cultivation and compatible with arid areas in Pishkuh watershed in Yazd province. In this research, first the dominant garden species in the study area were identified and after calculating their water requirements, a map of the agricultural drought vulnerability in the study area was prepared. The results showed that the southern to southwestern of study area, including the villages of Sanich, Darreh Shir, Darreh Sir, etc., have the highest vulnerability to drought compared to other areas. Therefore, it is recommended to be cultivated garden species with the least water requirement such as almond and Grapes with water needs of 753 and 798 mm during the growing period, respectively. Also Results showed that the central, eastern, and northwestern of study area, including Islamieh, Navab, Nasrabad villages and etc., have a moderate and relatively low vulnerability. In addition, it is recommended to plant the species with moderate-water needs such as pomegranate and apricot. Therefore, changing and modifying the cultivation pattern, such as reducing the planting areas with high water requirements, developing species with low water needs, and increasing water efficiency, is one of the most necessary activities for managing agricultural drought risk.

The application of simulation-optimization models is a valuable tool for selecting the appropriate cropping pattern. The main objective of this research is to develop a two-objective simulation-optimization model to determine the pattern of cultivation and water allocation. The model performs the optimization with the multi-objective metamorphic algorithm (MOALO) after simulating different states of the cultivation pattern. The decision variables including land and water allocated to ten-day periods of plant growth were designed in a way that the minimum utilization of water resources and economic maximization were identified as target functions. The developed model was used to simulate and optimize the cultivation pattern with an area of ​​5500 hectares and water allocation of Semnan plain with renewable water at the rate of 60.8 million cubic meters. Harvesting scenarios of 80 (GW80) and 100 (GW100) percent of renewable groundwater and scenarios of change in existing cropping pattern of 30 (AC30) and 60 (AC60) percent were considered and each scenario was simulated with the MOALO algorithm. Optimization using the proposed model in four scenarios improved the water and economic objective functions compared to the initial simulation performance. The results showed that the four proposed scenarios were obtained by minimizing the water objective function and maximizing the economic objective function relative to the current situation (simulation). In general, the proposed model had a good performance despite its simplicity, which is a specialized tool to optimize the crop pattern with water allocation.

Iran is one of the most important countries in citrus (oranges) production. Citrus fruits are grown in different soils with a wide range of physical, chemical and fertility properties in the country, although some restrictions in the cultivated lands cause yield loss. In this regard, the present study was conducted to investigate the effect of physical, chemical and soil fertility characteristics on citrus yield in important areas under cultivation, the regression relationships of characteristics with yield, and the rating of soil and land parameters.

The 138 oranges orchards (118 orchards for rating and 20 orchards for validation) were selected in Fars, Mazanderan, Kerman and Guilan provinces. In each garden, a questionnaire was completed, a soil pedon was studied and soil samples were taken to carry out the appropriate physicochemical analyses. The selected soil and land characteristics were soil salinity (EC), exchangeable sodium percentage (ESP), pH, gypsum content, soil calcium carbonate (TNV), organic carbon (OC), clay, sand, silt, gravel, and soil available phosphorus and potassium contents. From the whole obtained data, 20 data were considered for validation purpose and the remaining data were used for modeling based on stepwise multivariate and simple regression methods. In these equations, the relationship between yield, as dependent variable, with soil and land characteristics, as independent variables, was investigated. Finally, land characteristics rating was obtained by the FAO method and the proposed crop requirements table was evaluated using the validation dataset.

The results of descriptive statistics analysis showed that the variance values for available potassium, sand, clay, gravel and TNV were high and for pH and OC and gypsum were negligible. Therefore, most soil properties have a wide range of variation which could be related to the fact that oranges are grown in a wide range of soil types. The value of TNV varied between 10 and 33.3%. The presence of carbonate in soil reduces the availability of macro- and micronutrient elements in direct and indirect manners. The average of EC in the studied orchards was 5.4 dS.m-1. Minimum, maximum and average of ESP were 1.7, 28 and 10.7, respectively. The lowest and highest salinity and sodicity were observed in Mazandaran and Kerman soils, respectively. Maximum, minimum and average percentage of gypsum were 12, 0.36 and 3.54%, respectively. The highest amount of gypsum was observed in Bam and Shahdad regions of Kerman province and the lowest gypsum content was observed in Mazandaran and Guilan provinces. The soil pH varied from 6.63 to 8.8 with the average of 7.8. The soil OC values were between 0.05 and 3.53% and its average was 0.89%, showing the fact that the most studied soils were poor in organic matters. The average of soil available phosphorus and potassium in the studied orchards for citrus was less than the critical level. The average, minimum and maximum of available potassium were 224, 100 and 360 mg.kg-1, respectively. The mean, minimum and maximum amounts of available phosphorus were 21.6, 8 and 45.9 mg.kg-1, respectively. According to the multivariate regression model, among soil properties, EC, ESP, TNV, gypsum, gravel, available phosphorus and potassium were selected by the model. The determination coefficient of the model was 0.95, indicating that these properties have the greatest effect on citrus yield. Simple regression equations demonstrated that TNV, gypsum, EC, ESP, sand, clay, gravel, available potassium and phosphorous had the highest correlation (R2 > 0.6); and soil OC and pH had the lowest correlation (R2<0.2) with yield. The equations also revealed that soil EC, ESP, gypsum, TNV and gravel percentage had the greatest effect in yield loss, and soil organic carbon, absorbed phosphorus and potassium had the greatest effect on increasing citrus yield. As stated in equations, reported permissible and critical thresholds for effective soil properties on citrus yield, were 2.4 dS.m-1 for EC, 5 for ESP, 1.5% for gypsum, 20% for TNV, 22 mg.kg-1 for available phosphorus, 280 mg.kg-1 for available potassium, 110 cm for soil depth, and >2 m for groundwater level. Finally, evaluating the proposed crop requirements table with validation dataset fitted between citrus yield and soil index, resulted in the determination coefficient value of 0.79, denoting the acceptable accuracy of proposed table.

Overall results showed that the main land limiting characteristics for orange production were soil salinity and sodicity, high amount of soil calcium carbonate and gypsum. Among unsuitable physical and fertility properties of soil, salinity and sodicity are the most effective factors affecting yield reduction. Consequently, proper management practices such as introducing cultivars compatible with these soil conditions, soil remediation and leaching operations to reduce soil salinity and sodicity are necessary. Furthermore, in most areas under orange cultivation such as Fars and Kerman provinces, the soil calcium carbonate content is more than the critical level for plant growth. In addition, the averages of soil available phosphorus and potassium were less than the critical levels, which should be considered for nutrient management of orchards. The proposed table of crop requirements seems to be accurate enough to conduct land suitability studies for orange varieties, especially cultivars grown in the north and south of the country.

Considering the current and prospect situation of Urmia Lake, the future study of variables of irrigation scheduling and management is one of the priorities of agricultural research to improve the cropping pattern in the east of lake. In this study, the time series of wheat evapotranspiration in sixteen regions of East Azarbaijan located at the east of Urmia Lake was determined using the Penman-Monteith FAO method with the regional crop coefficient. The analysis period was 80 years from 1330-31 to 1396-97, which 50 years (from1330-31 to 1379-80) was applied for the time series modeling, 17 years ( from 1380-81 to 1396-97) for testing and 13 years (from 1397-98 to 1409-1410) for future studying up to 1410. Among the eighteen possible models, the appropriate time series model for wheat evapotranspiration in cold climate regions such as Azarshahr, Osko, Bonab, Tabriz, Jolfa, Maragheh, Malekan, Marand and Miyaneh was acquired as ARIMA (0, 1, 1) and for very cold climates such as Ahar, Bostanabad, Sarab, Shabestar, Kaleibar, Harris and Hashtrood was obtained as an exponential trend model. The wheat evapotranspiration in East Azerbaijan in the past 67 years averaged 478 mm and for the next 13 years averaged 500 mm. The findings of this study are valuable and practical for irrigation scheduling in full and deficit irrigated conditions and reduction of drought damage in east Urmia Lake.

On-time information and real time decision-making are effective factors in the process of water management in the farm. Therefore, in the present study, a real-time decision support system has been developed for the irrigation scheme of Mian-Ab irrigation network in Shoushtar plain with 24 sub-sets of cropping pattern and results are compared with existing pattern. To increase the accuracy of modeling, including soil water balance, crop production and root growth, a one-day time step is considered by replacing real-time data. For this purpose, the Particle Swarm Optimization Algorithm (PSOA) is used to maximize the net benefit of a growing season. The results showed that the optimal economic efficiency of water was obtained for tomato by 92500 IRR/m3. Its yield production also has increased more than 3000 kg/ha in an optimal strategy with a 35 percent reduction in water consumption. Furthermore, critical periods of crop water requirement was between the maximum canopy cover and the start of senescence. Crops like wheat, barley, and rapeseed which their conopy coverage decrease after senescence stage, are more compatible with deficit irrigation.

Allocated water for agricultural crops in a cropping pattern in different regions and seasons is faced with much variation. Therefore, the cultivation of each crop is subject to climatic conditions, drought tension, precipitation, and crop sensitivity with different levels of uncertainty and risk. In this study, the role of allocated water and its time fluctuations for the main crops in Mian-Ab irrigation network in Shooshtar plain have been investigated. The simulation model of cropping pattern with the objective of maximizing net income with irrigation, investment, cultivation, and land constraints was optimized using a simulated annealing algorithm. The obtained responses in the uncertainty conditions will determine the effect of tension fluctuations in fuzzy analysis process. Fuzzy set theory has been defined with triangular membership function and has been divided into five alpha levels of 0, 0.25, 0.5, 0.75, and 1 to find the fuzzy response of the problem. In each positive or negative α level, a genetic algorithm sub-model has been used with a proximity criterion to find the boundary responses. The results showed that the application of optimal strategy reduced water consumption up to 7 MCM/year and increased the net benefit in cropping pattern more than 5×1010 IRR annually. The developed fuzzy model showed that the water efficiency will be increased at least 30% with a 25% reduction in optimal irrigation..

The importance of water as the rarest input to agriculture has led to more attention to increasing the irrigation productivity in recent years. In this study, the compasrison of water productivity in traditional and modern irrigation systems for grain and forage corn in Hamadan province is conducted using three indices of physical and economic productivity of water including CPD, BPD, and NBPD. Firstly, appropriate operators were selected by random sampling and then the necessary data were collected through interviews and completion of the questionnaire. The average physical productivity of water under traditional and modern irrigation systems for grain corn was 0.82 and 1.08 kg/m3 of water, respectively, and for forage corn was 5.11 and 6.67 kg/m3 of water, respectively. The average economical water productivity under traditional and modern irrigation systems for grain corn was 2,849 and 3,665 rial/m3 of water, respectively, and for forage corn was 7,678 and 10,068 rial/m3 of water, respectively. Under modern irrigation systems, the highest amounts of physical and economic productivity of water for grain corn belonged to Asadabad and Nahavand, respectively. For forage corn, the highest amount of physical water productivity was for Nahavand and Tuyserkan and the highest economic water productivity was for Bahar and Nahavand. Based on the results, it can be claimed that traditional irrigation systems should be replaced by modern irrigation systems for grain and forage corn. Also, the cultivation of forage corn should be removed from the cultivation pattern in the Bahar region. These results, in addition to reducing the agricultural water consumption, entail economic benefits for farmers.

using mathematical programming models for determining appropriate cropping patterns has recently attracted a lot of attention. The agricultural sector is one of the most important and powerful economic sectors of the country. In the last ten years, its contribution to gross domestic product has been around 18% on average. The method of linear programming has been widely used in the fields of land allocation and determination of optimal cultivars since the 1960s. The purpose of linear programming is to maximize or minimize the objective function by considering a number of constraints and decision variables simultaneously. Fuzzy scheduling allows decision-makers to interfere with non-explicit data and data parameters in models. Compared to other models of math planning, it is more applicable and more flexible to be used in optimization problems and in determining the optimum crop cultivation patterns. Moreover, the results are more reliable (Rastegaripour and Sabouhi, 2009). Mir Karimi et al. (2016) investigated the optimal cultivar pattern in the city of Amol using the ideal planning and taking into account the goals of reducing fertilizer use by seven percent. Their results showed a one-percent reduction in pesticides to protect the environment and a reduction of 93% of water use for the conservation of scarce water resources and sustainable agricultural development. In this study, a fuzzy utopian planning model with three equal weight patterns, different weights, a decreasing weight and an incremental weight for ideals and water resource constraints are designed, taking into account environmental and economic objectives. The main objective of this research is to optimize water and land resources in Hamadan province. First, we introduced a weighted fuzzy goal programming model (WFGP). Using this model, optimum cultivating model for farmers in Hamadan was determined, considering their income goals, environmental goals and sustainability of water resources of the region. Subsequently, the allocation between irrigation water inputs and land surface was calculated considering equal weights, different weights and different decreasing weights for the desired goals.

  Intercropping defined as growing two or more crops simultaneously in the same field, considering for its more sustainability and higher yields compared to sole-cropping. More developed and distributed root systems besides efficient architecture may enhance uptake and efficiency of nutrients. Application of organic fertilizers, on the other hand reduces environmental pollution and lead to longer nutrients recycling in agricultural systems. Considering these issues, this study aimed to evaluate nutrient efficiency of dragonhead - soybean intercropping nourished with organic manure and chemical fertilizer. A RCBD factorial experiment with three replications was conducted at Shahrekord University research farm in 2016. Five sowing patterns include: Sole-cropping of soybean (S), sole cropping of dragonhead (D) and three intercropping ratios of them (S:D 2:1, 1:1, and 1:2) as first factor were evaluated at two fertilization sources (chemical fertilizer and broiler litter) as second factor. Dragonhead and soybean were harvested at flowering and maturity stages, respectively. Concentration of nitrogen, phosphorus, potassium, copper, iron, zinc and manganese were determined for each plot. Finally, uptake of nutrients was calculated by multiplying the concentration by yield. The relative crop yield and relative nutrients yield in intercropping were calculated. The analysis of variance for the obtained data was done by statistical analysis system (SAS V.9) software. The mean comparison was done using the least significant difference (LSD) test at the 5% probability level. The result showed that the maximum uptake of nitrogen (10.59 g.m-2) and phosphorus (1.79 g.m-2) were obtained in sole cropped soybean and dragonhead treated with organic manure, did not show significant difference with intercropped ratio of soybean: dragonhead (1:1). The highest uptake of potassium (14 g.m-2), iron (0.253 g.m-2), zinc (0.065 g.m-2) and manganese (0.080 g.m-2) were achieved in sole cropped dragonhead treated with organic manure too. While for copper the highest ones (0.0135 g.m-2) were obtained in sole cropped dragonhead under organic manure, showing no significant difference with soybean: dragonhead (1:2) ratio under organic manure. The highest relative yield of nitrogen (1.04), phosphorus (1.09) and iron (1.03) was obtained in soybean: dragonhead (1:1) under organic manure. The greatest relative yield of potassium (1.07), copper (1.32) and manganese (1.03) was observed in soybean: dragonhead (1:2) under organic manure.
In this study, organic manure showed significant gains in terms of nutrient uptake compared to chemical fertilizer. In addition to, uptake efficiency of nutrient was higher compared with sole cropping. Intercropped patterns especially for organic manure application enhances nutrient efficiency. So, enhancement of uptake efficiency reduces the need for fertilizers in farm, in addition to lower environmental hazards contributes to increasing economic efficiency

Obtaining appropriate levels of deficit irrigation is necessary to improve water productivity and performance of irrigation networks in deficit irrigation conditions. This study was carried out to develop a nonlinear programming model for determination of an optimal cropping pattern in deficit irrigation conditions. A non-linear model with the objective function of economical water productivity index (Net profit to water consumption ratio) was combined with a crop growth model and it was evaluated using the data of Shahid Chamran irrigation network. Results showed that the highest cultivation area in all scenarios is related to wheat crop. The wheat cultivation area for the 10, 20 and 30 percent deficit irrigation were estimated to be 674, 949 and 1362 ha, respectively. The increased cultivation area in 30 percent deficit irrigation scenario was estimated 92 percent as compared to the full irrigation scenario. The lowest cultivation area in the network was for sunflower with an area of 189 hectares (in 30 percent scenario). The results of this study for the 10 percent scenario indicated that the overall economical water productivity of the network can be increased up to 19% by managing cropping pattern as compared to the full irrigation scenario. While in the 20 and 30 percent deficit irrigation scenarios, the economical water productivity index values increased 21 and 23 percent respectively by implementing optimal cropping pattern. Also studies show that the different combinations of deficit irrigation scenarios for the crops could present different results. Accordingly, the overall water productivity of the network can be increased to a maximum of 15250 Rls/m3, if 10 percent for broad bean and bean, 20 percent for sunflower and potatoes and 30 percent deficit irrigation for wheat are considered.

Excessive withdrawal of groundwater resources in the agricultural sector has led to an increase in cultivated land area and agricultural production, however, it has led to dropping of groundwater levels and drainage of aquifers. Consequently, most of Iran's plains are now considered as forbidden plains for underground water extraction. Therefore, proper policies for management of groundwater resources are essential. For this purpose, the present study aimed to evaluate the effects of economic policies of the agricultural sector on management of ground water resources in Kabodarahang Plain, by using a Positive Mathematical Programming (PMP) and Maximum Entropy (ME). The data and information was collected by referring to the relevant organizations and completing 141 questionnaires with multi-stage cluster sampling by farmers in 2016. The results showed that application of various senarios such as price increases, groundwater allocation , and combination of quotation scenarios simultaneously with increasing prices (combined) at levels of 10%, 20%, and 30% cause reduction in cropped area, decreased net profit of farmers, and reduced water consumption. Also, the results showed that the groundwater price increases scenario was not much effective and only increased the farmer's expenses, but the allocation/quotation polices and the combined policy are recommended as effective policies. Another result revealed that the quotation scenario, compared to the other scenarios, has higher economic returns per cubic meter of water consumption, thus it has been introduced as the best scenario in this research. Finally, it is suggested that the cropping pattern be directed towards products such as wheat and potato that have more gross profit for the water consumed and thus have more economic returns.

North Mahyar plain in Isfahan, is one of the plains which has confront water crisis. In these circumstances, attention to the capacity of the resources and proper management is an important issue to pass this condition. Chitsazan et al. (2013) noted that artificial neural network is able to figure out the relation of hydrologic parameter. Also, this tool can be used in water resources management (Coppola et al., 2005). Therefore, by applying artificial neural network, water-table data and cropping pattern in plain, three land-use scenarios were designed. Water table was simulated for water year of 2008 with one-layer network, Levenberg–Marquardt algorithm, and three functions in MATLAB­­_R2012a. Water table map was prepared by using simulated water table in ArcGIS 10.2, and zoning was performed according to the costs of water pumping. Results showed that 61-86 percent of the plain in all three scenarios had medium limitation. Also, using different management in field like fallowing and planting low-water use crops caused 3 and 5 percent increase in acreage of "without limitation" lands, respectively.