جستجوی مقالات مرتبط با کلیدواژه « بهره وری آب » در نشریات گروه « اکولوژی »

The approach of water, energy and food correlation can be defined as an approach to evaluate the development and implementation of policies that emphasize the security of these things at the same time. The purpose of this research is to provide a method to analyze the relationship between water, food and energy in the crop production chain. Based on the proposed method and according to the amount of water and energy consumption, four indicators of water and energy consumption and water and energy productivity, and also based on these indicators, a combined index of water, food and energy nexus is proposed. This research has conducted on the Borkhor plain of Isfahan province and the MODFLOW model has used to simulate the watershed quantitatively and since the objective functions in this study are linear, multi-objective linear programming was chosen to solve the optimization problem. The goal of solving the optimization problem is 4 scenarios of water consumption minimization, energy consumption minimization, profit maximization, as well as water, food and energy maximization scenario. The results show that although each of the scenarios alone reflect the positive effects of reducing water and electricity consumption, but by using the scenario of combining water, food and energy, in addition to reducing water and electricity consumption, farmers' profits have also increased significantly, so that the amount of water consumption before optimization was 50 million cubic meters per year, but after optimization and applying the scenario of maximizing the correlation of water, food and energy, it decreased by 8% and reached 46 million cubic meters per year, and the amount of consumption Energy decreased by 9.7% from 13150330 kilowatt hours per year to 11867563 kilowatt hours per year and in addition, the profitability of the products before optimization was 6301966 million Rials, which after applying the scenario of correlation of water, food and energy with 21 The percentage of increase reached 8015264 million rials and on the other hand, with the continuation of the optimal scenario, the level of underground water in the state of maximizing the correlation of water, food and energy will decrease by 0.478 meters less than the existing conditions and and on the other hand, by continuing this trend in the long term, we will see a significant impact on the level of underground water.

Rice (Oryza sative L.) is an essential crop among cereals and shared a significant component in the global human diet, especially in developing countries. About 80% of water consumption in Asia is for the agriculture sector, and half of it would be used for rice production. Rice needs roughly 8000 to 1000 m3 of water per hectare and 1Kg of its dry matter needs to 700 liters of water. Rice farmers tend to keep their farms flooded continuously to make sure the product is more productive by too much water storage and, in this way, prevent against weeds. Up to the year 2050, rice production should increase by 50%, which requires improved cultivars and enhanced field management. For achieving high crop yield, applying fertilizers to maintain high soil fertility is quite necessary. Nitrogen is one of the main crop’s nutrient requirements and is a limiting factor for rice production. Nitrogen fertilizer affects the accumulation of dry matter and its allocation in different parts of the plants. The difference in the accumulation of dry matter in response to nitrogen arises from the difference in the amount of active radiation received by photosynthesis of vegetative canopy and plant efficiency in the use of solar radiation. Nitrogen deficiency reduces leaf growth, and leaves become less colorful since the amount of chlorophyll in the leaves decreases, accelerates aging leaves, therefore, reduce the amount of solar radiation, and it reduces the accumulation of dry matter in plants, finally. Nitrogen, plays an important and direct role in the development of grains by increasing the level of enzymes and enzyme activity, and this increases the transfer and processing of sucrose to seeds. Many studies have shown that increasing nitrogen up to a threshold has highly increased rice grain yield. Growth analysis indices are essential to realize how the crop yield may change in response to management and environmental factors. Therefore the application of appropriate management factors that have a positive effect on growth indices can enhance grain yield.

This study was conducted as split-plot based on a randomized complete block design in Rice Research Center of Rasht in 2014-2015 and 2015-2016. Irrigation with five levels (daily irrigation, rotational irrigation with 5, 8, 10, and 15 days interval) as main plot and nitrogen at six levels (0.0, 30, 45, 60, 75, and 90 kg.ha-1) as subplot were considered in this experiment. At flowering and harvest leaf and dry stem matter was measured. Then leaf area index (LAI), Crop Growth Rate (CGR), Net Assimilation Rate (NAR), Leaf Area Ratio (LAR), Relative Growth Rate (RGR) and Specific Leaf Area (SLA) were calculated.

Our results showed that the interaction of irrigation and nitrogen significantly (P≤0.01) affects stem and leaf dry matter, LAI, and NAR. Irrigation was significantly (P≤0.01) effective on CGR. Among irrigation levels, daily irrigation resulted in the highest LAI and NAR. Our results indicated that daily and every five days irrigation and considering almost no difference between 75 and 90 kg.ha-1 nitrogen, then 75 kg.ha-1 urea can be suggested as the optimum fertilization value. However, at higher irrigation intervals, 90 kg.ha-1 nitrogen would be recommended. Daily irrigation and 90 kg.ha-1nitrogen showed the highest water consumption (6663 m3.ha-1), but 15 days irrigation interval and 0.0 kg.ha-1nitrogen showed the lowest water consumption (4691 m3.ha-1). It seems that low rate release nitrogen fertilizers, along with suitable irrigation practice, would be the optimum management to achieve high yield and lowest possible irrigation water consumption.

The results of this study showed that applying nitrogen and irrigation increased LAI and crop productivity indices, which resulted in higher biomass yield production. Among irrigation levels, daily irrigation resulted in the highest LAI and CGR. Under daily irrigation and five days of interval irrigation, the application of 75 kg.ha-1 nitrogen can be recommended. Although there was not a significant difference between 70 and 95 kg.ha-1 nitroge, but due to environmental concerns, 75 kg.ha-1was recommended.

Rice is a global important food and in Asia alone is the source of food for 3.5 billion people. Such demand for rice imposes a plan to find new technology and approaches to replace old production methods. About 75% of global rice production is practiced on low lands. At field scale, rice compared to other plants receive two or three times more water and based on some calculations, about 34-43 percentage of global irrigation water or 24-30 percentage of drinking water consumed by rice plant. In this situation, the most important challenge with regard to rice production, water storage, increased water productivity and rice production is less than water. Recently, rice production systems such as rice alternate irrigation, where less water can be produced, has been considered as rice increasing demand for water in industry and cities have imposed the reduction of water consumption for agriculture. Rice is one of the most sensitive plants against water scarcity as a floodplain plant and has the most need for water in the cereals. Rice has the highest crop area than other irrigated plants.

This experiment was conducted as split-plot, using irrigation as main-plot at five levels (full irrigation, irrigation at ever 5, 8, 10, and 15 days), and planting distance as sub-plot at four levels (20x20, 25x25, 30x15, and 30x20 cm) within format of random complete block design with three replications. The study was performed in two years (2016-17, 2017-18) in national rice research center. Soil samples were taken to determine the soil tissue, soil water holding capacity, and some chemical characters including EC, PH, and amount of Ca, Na, and Mg. Within firs 15 days after transplanting, the rotation irrigation was not employed so the plant be able to establish in the field. The plowing was performed in two times. The first plow in the late autumn and early winter and the second plow were perpendicular to the first plowing in the spring. Fertilization was done based on long term local practice. Transplanting was done in may, 15 and at this time transplants were 20-25 cm height carrying 4-5 leaves. All traits including stem and leaf dry matter, leaf area index (LAI), crop growth rate (CGR), net assimilation rate (NAR), leaf area ration (LAR), relative growth rate (RGR) and specific leaf area (SLA) were measured and calculated. SAS and SPSS software’s were used for analysis of variance. Excel software was used for drawing slices.

ANOVA results showed that interaction of irrigation and planting distance were significantly (P <= 0.01) affected leaf and stem dry matter, LDW, TDW and CGR Individual effects of each treatment significantly affected the LAI and NAR but did not affect LAR, LWR, RGR, and SLA. As light absorption i a limiting factor in crops production, then where is no other environmental stress, increasing light absorb will increase crop production. In contrast to other crops light capture competitions a major issue for rice. Increasing panting density, vegetative growth and LAI would be lower and as planting density decreases, due to availability more spaces, both vegetative growth ad LAI increased.

 In general, this study results showed that rotation irrigation significantly affected the rice growth indexes, and reduction levels of study traits depends on irrigation timing at growth stage. Planting distances showed that planting at 20x20 cm, provided the most optimum conditions for rice plants under different stress, the worst conditions resulted in 25x25 cm planting distance. At lower planting density, due to lower competition between plants till flowering time but after this stage, competition for photosynthetic materials increased among the seeds which can result in small dead seeds.

Over the last two decades, Urmia Lake, the second largest hypersaline lake by area in the world, has been largely desiccated and its water volume and surface area have declined by 80%. Generally, this process is attributed to a combination of factors including climate change, water overuse for agriculture within the lake’s watershed, and mismanagement of water resources. One of the widely suggested solutions in restoration program of Urmia lake for sustainable use of land and water resources is the modification of cropping pattern within the lake’s watershed. Land suitability analysis helps planners and policy makers in the agriculture sector in deciding on the presence or absence of a specific plant in the optimal cropping pattern. The present study analyzed the cropping pattern and evaluated land suitability for major field and horticultural crops in the Urmia lake basin.

All required data were obtained from the Ministry of Agriculture - Jihad. Weighted goal programming (WGP) model was applied to optimization of cropping pattern with considering three goals including maximizing net return (NR), maximizing economic water productivity (EWP) and minimizing water consumption (WC). GAMS software were used to solve the optimization model. Land suitability evaluation was done using Parametric Method for 22 field crops including wheat, barley, grain maize, bean, soybean, sunflower, canola, safflower, alfalfa, forage sorghum, potato, carrot, cotton, sugar beet, garlic, tobacco, tomato, onion, watermelon, saffron and cucumber and 12 horticultural crops including almond, apricot, peach, nectarine, sour cherry, sweet cherry, plum, apple, pear, grape, walnut and pistachio.     

The results revealed that during the past 10 years (from 3-years average of 2004-2006 to 2014-2016), cultivated area of irrigated field crops in the study area had declined in contrast to increasing trend of cultivated area for irrigated horticultural crops. Comparison of field crops for this period shows that area of wheat (from 151000 to 110000 ha), alfalfa (from 97000 to 82000 ha), sainfoin (from 15000 to 5000 ha) and onion (from 9800 to 4800 ha) had reduced while the corn silage (from 1354 to 5000 ha) and tomato (from 7382 to 8781 ha) cultivated area had increased in that period. Comparatively, the area of apple (from 62000 to 69000 ha), apricot (from 5800 to 7300 ha), plum (from 840 to 3000 ha) and peach (from 3523 to 5667 ha) had increased between two-time interval (from 3-years average of 2004-2006 to 2014-2016) in contrast to decrement of grape (from 38000 to 34000 ha) cultivated area. Results of land suitability evaluation showed that among the studied field crops, the highest suitable order area (including S1, S2 and S3 classes) were related to wheat and barley by more than 375000 ha followed by canola and alfalfa with more than 350000 ha, sunflower with more than 340000 ha, grain maize with more than 330000 ha and potato, onion and tomato with 330000 ha. Among the horticultural crops, the highest area of suitable order was related to sweet cherry, sour cherry, apricot and apple with more than 350000 ha followed by walnut with more than 340000 ha and peach by about 330000 ha. Results of cropping pattern optimization showed that total water consumption about 378 MCM (11.7%) reduced compared to current cropping pattern however, total net return and economic water productivity increased about 27.1% and 43.9%, respectively. Crops characterized with relatively higher water requirements and lower economic benefits (viz. apricot, cotton, plum, safflower, and etc.) eliminated from cropping pattern. By contrast, area under crops such as saffron, pistachio, sorghum, sweet cherry, garlic and cucumber crops recommended to optimal cropping pattern mainly because of relatively lower water consumption and higher economic benefits.

In the present study, geographical distribution of suitable areas and main limiting factors for cultivation of each crop was determined. Generally, in the optimal cropping patterns, total water consumption decreased against an increase in net return and economic water productivity.

Agriculture development heavily relies on chemical inputs such as synthetic fertilizers, pesticides, fossil fuels and other energy-intensive inputs. This development is having a serious impact on public health and the environment. Therefore, efficient use of resources is a primary and most vital implications for sustainable agriculture development. Sustainability indices are quantitative values that can be used to evaluate the efficiency and quality of agroecosystems and are useful tools for making suitable decisions in its management. These including energy flow indices, global warming potential (GWP), economic indices, environmental impact quotient (EIQ) of pesticides, efficiency of land, water and fertilizers use and etc. Alfalfa and corn silage as the main source of feed for livestock, have a notable area in the cropping pattern of Maragheh-Bonab plain. Therefore, evaluation of sustainability for these crops will help the sustainable management of agroecosystems in the study area. The present study was conducted to: (a) determine energy efficiency and global warming potential; (b) determine the environmental impacts of pesticides; (c) assess input use efficiency and; (d) economic analysis of alfalfa and corn silage production systems in East Azerbaijan province of Iran. In the present study, the sustainability of alfalfa and corn silage production systems lies in the Maragheh-Bonab plain in southern East Azerbaijan province in northwestern Iran were evaluated using quantitative indices such as energy efficiency and productivity, greenhouse gas (GHG) emission; economic indicators; pesticide risk (field environmental impact—FEIQ); tillage impact (TI); fertilizer, labour, land and water use efficiency, and the eco-efficiency index. For this purpose, data was collected from 110 farmers by survey to determine crop production in the region. Secondary data including climate characteristics and products sale price was obtained from previous studies and organizations such as the Agricultural Ministry of Iran. The results showed that the values of input energy, output energy and net energy in alfalfa production system (48151, 432920 and 384768 Mj.ha-1, respectively) were higher than corn silage production system (35557, 217350 and 181792 Mj.ha-1, respectively). Also, it was observed that the values of energy use efficiency and specific energy of alfalfa (9 and 15.8 MJ.kg−1, respectively) were higher than that of corn silage (6.1 and 4.1 MJ.kg−1, respectively). In terms of economic indices, despite of lower total cost of production in corn silage (1089 $.ha-1), the highest values of gross production value (6447 $.ha-1) and net return (4193 $.ha-1) were related to alfalfa production system. In terms of GWP and EIQ, alfalfa production had the higher values with compared to corn silage production. However, eco-efficiency (ratio of economic value to the environmental impact) values based on of GWP and EIQ was significantly higher for alfalfa (1.75 $.kg -1 CO2eq-1 and 35.3 $.EIQ-1) than corn silage (1.5 $.kg-1 CO2eq-1 and 26 $.EIQ-1). Land production efficiency, economic land production efficiency, irrigation water productivity, economic irrigation water productivity, nitrogen use efficiency, phosphorous use efficiency and potassium use efficiency were 140 kg.ha-1.day-1, 21.5 $.ha-1.day-1, 4.1 kg.m-3, 0.63 $.m-3, 335 kg.kg-1, 1191 kg.kg-1 and 1826 kg.kg-1 in alfalfa production system and 583 kg.ha-1.day-1, 22.9 $.ha-1.day-1, 8 kg.m-3, 0.31 $.m-3, 656 kg.kg-1, 3553 kg.kg-1 and 65525 kg.kg-1 in corn silage production system, respectively. It can be concluded that environmental impacts of pesticides and global warming effect per area in alfalfa production system were higher than corn silage production system. However, in terms of economic indices and energy use efficiency, alfalfa production system was superior to corn silage production system.

One of the key issues in the practical planning for water resources is the existence of uncertain factors. One of the approaches for decision making under such circumstances is interval programming. The aim of the study is to develop an interactive optimization model for water and crop area allocation. The developed model comprises four objectives that take into account socio-economic factors, the virtual water content of crops, and meeting environmental water requirements. For solving the model, four crop area scenarios (assumptions) were considered. Results showed that by raising the level of satisfaction threshold on the constraints, the amount of water allocated to each water user is declined. So that from the satisfaction level of 0.65 to the level of complete satisfaction, the model allocates only the minimum amount of water (40 MCM) to meet the environmental water needs. Based on considered scenarios for solving the model, the largest cultivation areas are allocated to wheat and maize for autumn and spring cultivations, respectively. Solving the model in the absence of upper bound for crop areas revealed that the greatest difference between optimal crop area and the highest cultivation area happened was belong to rice with 2777 and 5821.6 hectares in Dorudzan and Korbal districts, respectively. The main advantage of the developed model in the present study is the linear formulation as well as its ability to deal with uncertain parameters. Outcomes of the model provide information required for the assessment of risk and reliability of planning options for water allocation.

To illustrate the impact of various levels of deficit irrigation on yield and yield components of maize (Zea mayz L.) cultivar, a study was conducted based on randomized complete block as a split plot design with 3 replicates and two treatments for three crop seasons. Four levels of deficit irrigation including: conventional, 100, 80, and 60% of water level use were considered as main plots and two varieties 704 and 647) as subplots in a experimental site located in Shahid Fozveh research station. Significant differences (P 0.05) were noticeable in grain yield, as well as depth and column of kernel among the irrigation treatments. In addition, the effects of cultivars on grain yield, 1000 kernel weight, number of kernel per ear row, number of kernel per column, and depth of kernels were non-significant. Results showed that, a decrease of 36 percent water applied (60% irrigation level treatment) compared to full irrigation, yield declined 11.4% and a decrease of 20 percent water applied (80% irrigation level treatment) compared to full irrigation, yield declined only 2. Based on the results and considering the quantitative characteristics of the crop, it was established that for the deficit irrigating of maize, the 80% irrigation level is the most advantageous treatment when water is not limited. However, when higher water productivity and the possibility of using the water saved are taken into consideration during severe drought conditions, 60% irrigation level treatment is recommended.