Yavar Pourmohamad; Mohammad Mousavi baygi; Amin Alizadeh; Alinaghi Ziaei; Mohammad Bannayan
Abstract
Introductionin current situation when world is facing massive population, producing enough food and adequate income for people is a big challenge specifically for governors. This challenge gets even harder in recent decades, due to global population growth which was projected to increase to 7.8 billion ...
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Introductionin current situation when world is facing massive population, producing enough food and adequate income for people is a big challenge specifically for governors. This challenge gets even harder in recent decades, due to global population growth which was projected to increase to 7.8 billion in 2025. Agriculture as the only industry that has ability to produce food is consuming 90 percent of fresh water globally. Despite of increasing for food demand, appropriate agricultural land and fresh water resources are restricted. To solve this problem, one is to increase water productivity which can be obtain by irrigation. Iran is not only exempted from this situation but also has more critical situation due to its dry climate and inappropriate precipitation distribution spatially and temporally, also uneven distribution of population which is concentrate in small area. The only reasonable solution by considering water resources limitation and also restricted crop area is changing crop pattern to reach maximum or at least same amount of income by using same or less amount of water. The purpose of this study is to assess financial water productivity and optimize farmer’s income by changing in each crop acreage at basin and sub-basin level with no extra groundwater withdrawals, also in order to repair the damages which has enforce to groundwater resources during last decades a scenario of using only 80percent of renewable water were applied and crop area were optimize to provide maximum or same income for farmers.
Materials and methodsThe Neyshabour basin is located in northeast of Iran, the total geographical area of basin is 73,000 km2 consisting of 41,000 km2 plain and the rest of basin is mountains. This Basin is a part of Kalshoor catchment that is located in southern part of Binaloud heights and northeast of KavirMarkazi. In this study whole Neyshabour basin were divided into 199 sub-basins based on pervious study.Based on official reports, agriculture consumes around 93.5percent of the groundwater withdrawals in Neyshabour basin and mostly in irrigation fields, surface water resources share in total water resource withdrawals is about 4.2percent, which means that groundwater is a primary source of fresh water for different purposes and surface water has a minor role in providing water supply services in the Neyshabour basin. To determine crop cultivation area, major crops divided into two groups. two winter crops (Wheat and Barley) and two summer crops (Maize and Tomato). To accomplish land classification by using supervised method, a training area is needed, so different farms for each crop were chosen by consulting with official agricultural organization expert and multiple point read on GPS for each crop. The maximum likelihood (MLC) method was selected for the land cover classification. To estimate the amount of precipitation at each 199 sub-basins, 13 station data for precipitation were collected, these stations are including 11 pluviometry stations, one climatology station and one synoptic station. Actual evapotranspiration (ETa) is needed to estimate actual yield (Ya). Surface Energy Balance Algorithm for Land (SEBAL) technique were applied on Landsat 8 OLI images. To calculate actual ETa, the following steps in flowchart were modeled as tool in ArcGIS 10.3 and a spreadsheet file. To estimate actual crop yield, the suggested procedure by FAO-33 and FAO-66 were followed. Financial productivity could be defined in differently according to interest. In this study several of these definition was used. These definitions are Income productivity (IP) and Profit productivity (PP). To optimize crop area, linear programing technique were used.
Results and discussionaverage actual evapotranspiration result for each sub-basin are shown in context. In some sub-basins which there were no evapotranspiration are shown in white. And it happens in those sub-basins which assigned as desert in land classification. In figures 8 and 9 minimum amount of income and profit productivity for wheat and barley is negative, this number means in those area the value of precipitation is higher than value of evapotranspiration, so lower part of eq. 21 and 22 would be negative and in result water productivity would be negative. Since most of precipitation occurs during cold season of the year these numbers are expected. Two sub-basins of 43 and 82 has the value of negative, it means in these two sub-basins groundwater are recharging during the year 2014-2015.The maximum value of income and profit productivity belong to wheat and barley which are winter crops and mostly rain fed, so amount applied water would be so low and in result productivity increased. Among the summer crops maize has the most income and profit income which can be interpret due to their growing period and the crop types. Maize has around 110 days to reach to maturity and harvest, on the other hand tomato needs 145 days to harvest. Some plant is C3 and some are C4. C4 plants produce more biomass than C3 crops with same amount of water which leads to more productivity. The results showed that tomato should have the most changes in area reduction (0.2) and maize should have no changes in both scenarios. Crop area should reduce to 66percent of current cultivation area to maintain ground water level and only 6percent reduction in cultivation area would result in 20percent groundwater recharging.
Conclusion to save groundwater resources or even retrieve the only water resource, cultivation area must reduce if the crop pattern will not change. In this study only four crops were studied. It seems best solution is to introduce alternative crop.
javad seyedmohammadi; leila esmaeelnejad; Hassan ramezanpour
Abstract
Introduction: With regard to increasing population of country, need to high agricultural production is essential. The most suitable method for this issue is high production per area unit. Preparation much food and other environmental resources with conservation of biotic resources for futures will be ...
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Introduction: With regard to increasing population of country, need to high agricultural production is essential. The most suitable method for this issue is high production per area unit. Preparation much food and other environmental resources with conservation of biotic resources for futures will be possible only with optimum exploitation of soil. Among effective factors for the most production balanced addition of fertilizers increases production of crops higher than the others. With attention to this topic, determination of soil fertility degree is essential tobetter use of fertilizers and right exploitation of soils. Using fuzzy logic and Analytic Hierarchy Process (AHP) could be useful in accurate determination of soil fertility degree.
Materials and Methods: The study area (at the east of Rasht city) is located between 49° 31' to 49° 45' E longitude and 37° 7' to 37° 27' N latitude in north of Guilan Province, northern Iran, in the southern coast of the Caspian sea. 117 soil samples were derived from0-30 cm depth in the study area. Air-dried soil samples were crushed and passed through a 2mm sieve. Available phosphorus, potassium and organic carbon were determined by sodium bicarbonate, normal ammonium acetate and corrected walkly-black method, respectively. In the first stage, the interpolation of data was done by kriging method in GIS context. Then S-shape membership function was defined for each parameter and prepared fuzzy map. After determination of membership function weight parameters maps were determined using AHP technique and finally soil fertility map was prepared with overlaying of weighted fuzzy maps. Relative variance and correlation coefficient criteria used tocontrol groups separation accuracy in fuzzy fertility map.
Results and Discussion: With regard to minimum amounts of parameters looks some lands of study area had fertility difficulty. Therefore, soil fertility map of study area distinct these lands and present soil fertility groups for better management of soil and plant nutrition. Weight of soil parameters was0.54, 0.29 and 0.17 for organic carbon, available phosphor and potassium, respectively. Fuzzy map of study area includes five soil fertility groups as: 22.9% very high fertility, 27.7% high fertility, 35.53% medium fertility, 10.48% low fertility and 3.39% very low fertility. Consequently, a separated map for soil fertility prepared to evaluate soil fertility of study area for rice cultivation. Toinvestigatethe efficiency of fuzzy model and AHP in increasing the accuracy of soil fertility map, soil fertility map with Boolean method prepared as well. Boolean map showed 58.88% fertile and 41.12% unfertile.15 soil samples from different soil fertility groups of study area were derived fromcontrol of maps accuracy. 13 renewed samples of 15 and 9 soil samples have matched with fuzzy and Boolean map, respectively. Comparison of parameters mean in fuzzy map fertility groups showed that parameters mean amounts of very high and high fertility groups are higher than optimum level except potassium that is a few lower than optimum level in high fertility group, therefore, addition of fertilizers in these groups could not be useful to increase rice crop production. Phosphorus parameter amount is lower than the critical level in very low, low and medium fertility groups, then in these groups phosphorus fertilizer should be added to the soil toincreaserice production. The amount of potassium parameter is higher than the critical level and lower than optimum limit in very low, low, medium and high fertility groups, then in these groups addition of potassium fertilizer will results in theincrease of production. Organic carbon amount is lower than optimum level in very low and low fertility groups. With regard to the relation between organic carbon andnitrogen and phosphorus, therefore, the addition of organic carbon fertilizer could compensate deficit of nitrogen and phosphorus in these groups as well. Attention to the presented explanations and comparison of fuzzy and Boolean maps using parameters amounts in renewed sampling points for control of maps accuracy, it is distinct that fuzzy logic could influencetheoptimum using of fertilizers with increasing map efficiency and accuracy. In addition, relative variance and correlation coefficient amounts showed that fuzzy map has separatedquite wellparameters changes.
Conclusion: Effective parameters in soil fertility, includingorganic carbon, phosphorus and potassium were used topreparesoil fertility map for rice cultivation. With regard to the minimum amounts of parameters looks some lands of study area had fertility difficulty. Therefore, soil fertility map of study area distinct these lands and presents soil fertility groups tobetter management of soil and plant nutrition. Fuzzy and Boolean methods were used topreparesoil fertility map. Comparison of these two approaches showed that fuzzy method with AHP caused to increase theefficiency and accuracy of fertility map for rice. Separated and distinguish soil fertility groups in fuzzy map help suitable distribution and optimum use of fertilizers for rice production.
s. nazaryan; Ali Najafi nejad; N. Nura
Abstract
Introduction : Given its low and sparse precipitation both in spatial and temporal scales, Iran is nestled in an arid and semiarid part of the world. On the other hand, because of population growth, urbanization and the development of agriculture and industry sector is frequently encountered with increasing ...
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Introduction : Given its low and sparse precipitation both in spatial and temporal scales, Iran is nestled in an arid and semiarid part of the world. On the other hand, because of population growth, urbanization and the development of agriculture and industry sector is frequently encountered with increasing water demand. The increasing trend of water demand will widen the gap between water supply and demand in the future. This, in turn, necessitates urgent attention to the fundamentals of economic planning and allocation of water resources. Considering the limited resources and the declining water table and salinization of groundwater, especially in semi-arid areas forces us to exploit surface waters. When we evaluate the various methods of collecting rainwater, surface water that is the outcome of rainfall-runoff responses in a basin, is found to be a potential source of water and it can be useful to meet some of our water demand if managed properly. Water shortages in arid areas are critical, serious and persistent. Thus, water harvesting is an effective and economic goal. The most important step in the implementation of rain water harvesting systems is proper site selection that could cause significant savings in time and cost. In this study the potential of surface waters in the Aq Emam catchment in the east Golestan province was evaluated. The purpose of this study is to provide a framework for locating areas with water harvesting potential.
Materials and Methods: For spatial evaluation of potential runoff, first, the amount of runoff is calculated using curve number and runoff potential maps were prepared with three classes: namely, the potential for low, medium and high levels. Finally, to identify suitable areas for rain water harvesting, rainfall maps, soil texture, slope and land use were weighted and multiplied based on their importance in order to determine the appropriate areas to collect runoff
Results and Discussion : The results of runoff production potential indicated that May and June accounted for the highest runoff and it can be inferred from these results that both of these months are characterized with storms which was confirmed by interviewing local residents and as range-land covers the largest land use in the basin as well as low vegetation density in the spring and summer due to overgrazing, much more runoff has been produced which is in line with the studies conducted by the Department of Natural Resources of the Golestan province in Aq Emam watershed (2003) as well as findings of Eftekhari et al. The results showed that the highest areas of the sub watershed 8, and 3 were suitable for rain water harvesting. Thus, the appropriate areas for rain water harvesting in the sub watersheds do not have a uniform spatial distribution according to the results. It can be argued that these sub basins are characterized by 4 criteria to be appropriate for rain water harvesting, which is in confirmation with Miliniai et al. Also according to the results, the areas suitable for rainwater harvesting in each sub-basin have heterogeneous spatial distribution as confirmed by the results of Eftekhari and Jin et al. Given the final map from integrating data layers, it was found that the central part of the study area has a good potential for rainwater harvesting and as results show, suitable area for water harvesting in the watershed coincides with range-lands that have a moderate crown cover as confirmed by the results reported by Tabatabaii et al.
Conclusion: Finally it can be said that spatial evaluation and identification of proper areas for rain water harvesting is an important and necessary step in the application of rain water harvesting systems.
Keywords: Surface water harvesting, Spatial evaluation, Sub watersheds priority, GIS, SCS
Z. Lotfi Arpachaei; Abazar Esmali; kazem hashemimajd; n n
Abstract
In modern agriculture, the preparation of soil fertility map seems to be necessary to plan for appropriate using of fertilizers for crops. This study was conducted to prepare a distinct map for evaluating soil fertility according to soil chemical properties in 136 soil samples of Ardabil plain in Ardabil ...
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In modern agriculture, the preparation of soil fertility map seems to be necessary to plan for appropriate using of fertilizers for crops. This study was conducted to prepare a distinct map for evaluating soil fertility according to soil chemical properties in 136 soil samples of Ardabil plain in Ardabil province. To achieve this purpose, the available K and P, total N, EC, pH and organic matter of soil were mapped using geostatistical Kriging estimator into Geographic Information System (GIS) by ArcGIS9.3 software. The Analytical Hierarchy Process (AHP) was used for weighting soil fertility factors as the input data. Then a membership functions was defined for each factor by factorial scoring and the map of soil fertility was prepared and classified for wheat and potato by using AHP technique into GIS program. The results showed that 74.84, 3.59, 19.3 and 2.32 percentage of lands for wheat cropping were classified based on soil fertility into groups of weak, moderate and suitable, respectively while for potato it was 24.88, 27.57, 7.19 and 40.34 percentage, respectively. As a final result, this type of distinct soil fertility map for different crops could assist us to manage the appropriate using of lands and fertilizers.
