جستجوی مقالات مرتبط با کلیدواژه « الگوی کشت » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

The role of water in agricultural development and economic growth is undeniable. The imbalance between water supply and demand in Iran has created a challenge for the management of water resources, especially in agriculture. Paying serious attention to water productivity and improving it through appropriate methods and policies is one of the most effective solutions to address the water crisis and enhance the quantity and quality of agricultural production. The concept of water productivity is to produce the best and most products with the least amount of water. Agricultural water productivity has received serious attention in recent years from scientific societies related to irrigation and agriculture. The variation in water productivity for different crops at the local level and in comparison with other countries with similar climatic conditions indicates the potential for increasing agricultural water productivity. In the present research, the productivity of agricultural and horticultural products was investigated through field surveys, field measurements, and remote sensing analyses.

First, the status of water resources in the aquifer, including changes in groundwater levels and programmable water, was investigated. Then, the water consumption of agricultural plants was calculated using the difference between effective rainfall and plant water requirement (evaporation-transpiration). In the next step, the cultivated area of Basht Aquifer was examined using Sentinel-2 satellite images in Google Earth Engine software. Yield, dates of planting and harvesting, and irrigation times for agricultural products were verified through questionnaires completed by farmers and experts. After that, the water requirement of the current cultivation pattern was calculated using the FAO Penman-Monteith method. Finally, the productivity of different products was determined by evaluating the products in terms of productivity.

The area of the alluvial aquifer was 45.5 km², with an average length of about 25 km and a width of 5 km. The total volume of discharge and extraction from groundwater resources was 39.723 MCM. The infiltration amount of the Basht alluvial aquifer was calculated to be 7.905 MCM. By joining the outflow streams, including transfer streams through different elevations, the aquifer was recharged with a total of 20.377 MCM. Calculations using the FAO Penman-Monteith method showed that the water requirements of the dominant crops in the aquifer, including citrus fruits, wheat, barley, corn, canola, watermelon, rice, legumes, and alfalfa, were 9170, 5630, 4821, 7863, 5411, 9291, 20234, 5225, and 14083 m³, respectively. In total, the amount of water consumed by the agricultural products of Basht Aquifer was nearly 45 MCM, which was approximately equivalent to 1 m³m⁻² of the cultivated area. This is 2.64 times higher than the amount of water that can be programmed for agriculture (17 MCM).

The cultivation pattern will be influenced by parameters such as the climatic compatibility of products, the potentials of water and soil resources, regional needs, customs and interests of local people, and economic evaluation and income from production. Any change in the cultivation pattern should consider all social, economic, and environmental factors. However, given the existing conditions of the water sources, any cultivation pattern (even those considering high income) that increases discharge compared to the aquifer's recharge sources will be dangerous for future sustainability and will cause groundwater salinization and aquifer subsidence. Cultivation of high water-consumption plants such as seed corn should be stopped due to the severe water conditions of the region, and more investment should be made in developing crops such as canola, which are better adapted to the region's climate.

Many human civilizations have collapsed due to the climate. Historical and geographical evidence demonstrates that the majority of significant and stable civilizations were established in specific geographical-climatic areas with suitable biological conditions. Human civilizations have faced serious damages and collapses due to unfavorable climatic conditions. The existence of most human civilizations can be attributed to climatic conditions, with historical and geographic evidence, especially the special environmental condition of the world in the current situation. Countries that deal with biological, economic, social, and even political issues may not give special importance to this issue. The climate conditions around the world are constantly changing, and there will be severe problems in different dimensions in the not-too-distant future. Their existence could even be threatened by economic problems they will face. The world's population increase and energy demand in today's industrial world also result in damage to the planet's climate and atmosphere, as well as the effects of natural disasters. The human burden has not been spared and has been affected by many fundamental changes, of which the phenomenon of climate change is one of the clear examples. The most important indicators of climate change are temperature and precipitation. The change of each of these factors causes climate variability, which also has consequences on people's lives. The increase in greenhouse gases and suspended particles in the atmosphere, along with variations in the earth's surface, are among the most apparent consequences, and the damage caused by the world's industrial activities and human societies in the past two centuries. Different economic sectors, such as agriculture, industry, tourism, water, and health, are affected by this phenomenon. Based on what has been stated, it can be concluded that climate change will definitely occur in Iran. The agricultural sector will face significant challenges due to the occurrence of such things, given the climatic situation, hydrological characteristics, and limitations of the country's agricultural sector. It has created a unique climatic situation in Iran due to its location. The high-pressure rule in the subtropical zone causes the total amount of precipitation in Iran to be low.

The LARS-WG model is a model that is utilized for exponential micro-scale GCM models. This model is a great choice for generating random weather data, which can be used to generate rainfall, radiation, and maximum and minimum daily temperatures at a station for both current and future climate. In order to model meteorological variables, the LARS-WG model uses a complex statistical distribution. Modeling is based on the length of dry and wet periods, daily precipitation and radiation series, and semi-empirical distribution. Climatic parameters such as minimum temperature, maximum temperature, precipitation, and solar radiation are inputs for the LARS-WG model, which are all in the daily time frame. In this model, temperature is not taken into account when modeling radiation, and the sundial can be utilized instead. From the semi-empirical distribution of the rainfall for the month in question, and without taking into account the wet series or the amount of precipitation from the previous day, the amount of precipitation for one day is calculated. In this model, the temperature is estimated using Fourier series. The daily minimum and maximum temperatures are modeled as random processes using the average and standard deviation of the daily standards, which depend on whether the day is wet or dry. The mean and standard deviation of the seasonal temperature are simulated using the third-order Fourier series. Residue values are determined by subtracting the average values from the observed values, and the minimum and maximum data are utilized in time autocorrelation analysis. Minimum temperature, maximum temperature, precipitation, and radiation are the outputs of this model. LARS-WG model data generation involves three stages: calibrating, evaluating, and creating meteorological data. In the next step, using LARS-WG models under RCP 2.6, 4.5, and 8.5 scenarios and the micro-scale exponential LARS-WG generating model of Jiroft City climate changes during the planting period of each crop in the periods of 2011-2045, 2065-2046, 2066-2079 and 2080-2099. In the final stage, a positive mathematical programming model was utilized to investigate the impact of climate change scenarios on Jiroft City's planting patterns using predicted climate change results. The cultivation pattern of Jiroft city today and the predicted effects of climate change parameters during the periods 2011-2045, 2046-2065, 2066-2079, and 2080-2099 are examined in this section. The current cultivation pattern will be discussed in the previous step. A positive mathematical programming model and GAMS25 software have been employed in this regard. Separate information about the area under cultivation, production, and performance of selected agricultural products, as well as the consumption of inputs, for the agricultural year 2021-2022 is presented in the table.

The results indicate that the performance of selected products is significantly affected by the climatic parameters of temperature and precipitation. Also, by applying the forecast of climate variability in the cultivation pattern model of all selected crops in the periods 2011-2045, 2046-2065, 2066-2079 and 2080-2099 based on the noses of the HadCM3 model are affected by different climate scenarios. The improvement of agricultural productivity and climate change are both negative effects of this phenomenon. The findings of this investigation can be advantageous for agricultural planning and economic development in Hamadan province.

Nowadays, agro-industrial complexes play an important role in food security, especially in developing countries, due to their advantages such as facilitating planning, increasing food production, reducing consumer costs, encouraging innovation and technological development, creating job opportunities, and enhancing food availability. The current study was performed to develop a cultivation program that would minimize water consumption and maximize income at Khorramdareh agro-industrial complex covering an area of 1262 ha in Zanjan Province. The ordinary least squares method (POLS) due to Peykani (سال انتشار؟) was used in Lingo v.18 to analyze the economic data sets (the 2100-2020 time series) on irrigated crops including wheat, barley, corn, canola, and alfalfa at the complex under study. The results indicated an increase of 118.18% in the area under barley cultivation. In contrast, the areas under wheat, canola, maize, and alfalfa cultivations decreased by 33.33%, 73.19%, 34.79%, and 20.44%, respectively. It was also found that the optimized cropping pattern developed for the complex would decrease the total cultivated area (by 25.87%), water consumption (25.32%), machine working hours (25.70%), labor (25.87%), as well as fertilizer (30.50%) and pesticide (39.45%) consumptions compared to those measured for the current cropping pattern although the current net income would remain almost invariable (showing an increase of only +0.09%) while no crop would be removed from the current pattern. It was, therefore, concluded that the estimations seemed realistic.

Monitoring the quality parameters of the river is very important in the management of surface water resources. One of the effective methods in this field is entropy theory which has a very good capability in designing quality monitoring network. In this research, discrete entropy theory has been studied and monitored in order to qualitatively evaluate the temporal and spatial frequencies of the network of hydrometric stations in Kermanshah province with 16 stations and a 29 years common statistical period. The amount of data transfer between each station and all other stations is calculated in two to determine the information coverage between the network stations. The results showed that Bavleh station on The Gavehrud River in Kermanshah province is the most efficient network station in terms of potential of data giving by getting the highest amount in border entropy ranking. Pirsalman, Ghorbaghestan, Doab-mereg and Khersabad stations were also in good condition in terms of potential for information capture, but Totshami station is in poor condition. Polchehr, Biar, Sarpol-e Zahab and Kamish Road Bridge stations have poor status in terms of potential of giving information, bridge stations, Quantified road bridges and biyar in terms of quality indicators are not suitable and the information coverage of qualitative variables in almost all stations in the field is weak. Information transfer index is deficient throughout the study area and there is a need to revise the network. . In terms of optimal sampling distances, EC variable can maintain the effective quality of this index, considering that it is in a state of severe lack of information transmission (current network situation) up to 50 km distance.  Esp index is less sensitive to distance than Ec index and according to data transfer index and distance, the variability of this index is less at distances and distance of 55 km is suitable and for Cl the distance of less than 50 km was obtained for sampling. According to the data transfer index for mg quality variable, there is appropriate information coverage in the network at a distance of 55 km.

In the last decade, various aspects of groundwater resource depletion have gained a special place among water sector experts and decision makers. Research in this area is relatively new in most parts of the world. Groundwater depletion, which has been in a concerning state for most plains in Iran in recent years, has various consequences which impede sustainable development. One of the most important consequences of the dropping groundwater table is its impact on the economy of the agricultural sector. A problem that, despite its obviousness and bi-directionality, has rarely been quantified. In this research, it is attempted to simulate the status of groundwater resources under the influence of continued groundwater overdraft until 1420 (2041), on the basis quantitative (harvestable water) and qualitative (electrical conductivity) effects on the economic status of agricultural sector using cultivation area indices. We examine agricultural products, their performance, farmers’ income, and labor force. Questionnaires were used to estimate costs and incomes and the results of combined modeling of surface and groundwater in Neishaboor plain were used to estimate the amount available water. The model predicted a decrease of up to 24 m in water table and an average increase in salinity of 5500 mmhos/cm for the Neishaboor plain. The effects of the occurrence of these events was then modeled. Based on models for cropping patterns, water-yield equations, and salinity patterns, we estimated a 30% reduction in area under cultivation, a 65% decrease in crop yields, and a 28% decrease in labor force by 2041. Over the next 20 years, these impacts will significantly reduce revenues in the agricultural sector in Neishaboor plain, which will pose important secondary problems and consequences.

A major challenge facing sustainable agricultural production is that of selecting cropping patterns that observe the restrictions on such natural local capacities as soil, climate, and renewable water resources. This important issue has also been reflected with due emphasis in the state laws and national documents on water and agriculture as evidenced by the number  of laws and national documents (13) approved/adopted on the cropping pattern issue, standing second only to that of “Efficient use of water” (with 25 laws/documents). In this paper, a comprehensive analytical review and a SWOT analysis are initially conducted of the laws and national documents on cropping pattern practices before recommendations and suggestions are formulated for the practical implementation of a national cropping scheme at the state level. Among the important conclusions to be drawn from this review is that despite the legally binding requirements (such as The Enhancing Productivity in Agriculture and Natural Resources Sectors Act), no serious and effective measures have yet been taken in this filed except in such cases as greenhouse crop production and extraterritorial farming. In the few cases where actions have been taken, they have been mostly restricted to those within a specific sector in the absence of an integrated approach or coordination with other sectors or organizations involved. It is also observed that little attention has been paid in the relevant laws and regulations to capacity building and training on cropping pattern issues while the published research and field studies in the this area are quite scant as well. Another area neglected in the development of a national cropping scheme is the inclusion of indigenous and under-utilized crops in such schemes, or introduction of exotic crops with low water demand but high economic value for adaptation to the present climate at the state level that ensure sustainable agricultural production. Finally, a long time has elapsed since these laws and legal documents were adopted/passed during which time the climate has drastically changed and new farm technologies have emerged. These considerations necessarily require revisions in the existing laws and regulations or development of brand new ones.

Crop pattern has significant effect on optimum use of water resources and agricultural ýmanagement. Present research accomplished to achieve optimum crop pattern in Aharchai Basin ýlocated in the downstream of Sattarkhan Dam. The study area is about 3000 ha using ýtraditional irrigation method, wherein low irrigation efficiency and water shortage are the most ýimportant problems. In order to determine optimum crop pattern and to provide a suitable way ýto increase agricultural benefit and productivity, a linear programming model in both cases of ýthe current and improved irrigation system conditions was simulated in the Mathematica ýsoftware. After simulation, in order to maximize benefits, the area of each product was ýdetermined through two different simulation states. Results showed that if agricultural lands ýemploy modern irrigation methods, the benefit of agricultural activities would increase by 30%, ýi.e. it would rise from 98 to 128 billion Riyals in a year.ý

In order to determination of suitable cropping pattern for agricultural lands of Golestan province, were used geographical information system (GIS) and analytical hierarchy process (AHP).
At first, agroecological requirements of crops were identified from scientific resources then classified and required thematic maps were provided. The digital environmental layers overlaid and integrated in GIS media with AHP weights, then zoning of lands were done in 4 classes for any crops. In future step, the crops feasibility maps and land type and unit maps (as management unit) were overlaid then were identified the high suitable and suitable classes in each unit for crops cultivation and suitable cropping pattern was selected with respect to parameters such as plant water requirements, water resources status, the net benefit and the other economic and development factors. In introduced patterns for south lands of province, were suggested dry farming of high net benefits and autumn crops. In the most agricultural lands in southern and central of province were proposed crops such as wheat, canola, beans, chickpea, berseem clover in the patterns. The results showed that the north and northeastern lands of this province, has more adapted to cropping pattern of chickpea and barley due to environmental constraints. Also, cultivation of spring and summer crops is possible in high suitable areas, in the south and southwestern province as rainfed farming with supplementary irrigation.

Nowadays the methods that for determining the optimal planting crops are used often in order to increase farmer's prosperity and Take steps to maximize their profits, while the neglect of damaging effects environmental can adverse consequences and a lot of problems for future generations of mankind create. Therefore, choice a method that could help saves the environment multiple manager's goals to achieve to suited cultivation patterns leave in a model is necessary and important. Therefore in this study to achieve the objectives comprehensive above, especially in determining the optimal pattern planting Rudbar Alamot Western Qazvin Province and also reducing water pollutions river basin Shahrud that resulting from the more using of chemical fertilizers Lexicographic goal programming was used. This study data from premier farmers of this section, field studies, surveys, Statistical yearbook 1389 and also Statistics released by Agriculture Jahad organization of Qazvin province was collected and to analyze data and solve the proposed model Excel software was used. The results showed that the current pattern of farming in this section is not optimal and production inputs Non-efficient used. Therefore, we can take effective steps with using the proposed model in addition to choosing the appropriate pattern and optimum use of region resources, in order to increase farmer's incomes and reduce environmental degradation removal.

Soil and water conservation are a key of sustainable agriculture. Conservation of soil and water are the most important component of sustainable agricultural strategies. There are some methods for Conservation of soil and water that cropping pattern is one of method for conservation of soil and water. The main objective this research is to determine the optimum cropping pattern of watershed with minimizing soil erosion. For this objective، a model is introduced that showed how we can minimize erosion with changing cropping pattern in Atrak watershed. The model is used a linear programming (LP) with objective function Minimization of soil erosion. The result showed the erosion is controlled by 60% with changing cropping pattern. But if farmers accept this crop planning they will loss their profit. These plants in cropping pattern should be supported by government. The policy such as price-induced encourages farmers to move from more erosive crops and cropping systems to less erosive crops and cropping systems.