N. Afshar Bakeshloo; K. Zarafshani; B. Farhadi Bansouleh
Abstract
Introduction: Kermanshah Province with one million hectares of arable land play an important role in food security and economy of Kermanshah province. For example, Kermanshah province holds third in wheat yield per hectare; second in chickpea production; third in maize production; third in sugar beet ...
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Introduction: Kermanshah Province with one million hectares of arable land play an important role in food security and economy of Kermanshah province. For example, Kermanshah province holds third in wheat yield per hectare; second in chickpea production; third in maize production; third in sugar beet yield per hectare; and seventh in tomato production. However, unsustainable behavior of farmers in one hand and overuse of water consumption have depleted water reserves which in turn has developed “prohibited plains” in the region. For example, several regions such as Mahidasht, Islamabad, and Kangavar are consider as forbidden areas and still extending in size. In addition, with the continued overuse of water resources we will soon experience huge sinkholes across the province. Therefore, there is a need to study the content and value of virtual water in order to zone cultivated areas based on virtual water. This could be an effective way to maintain water resources and prevent environmental crises.
Materials and Methods: This study used quantitative documentary research method. Using secondary data source, we collected data from various sources such as FAO data bank, Agricultural Jihad Organization data source, Meteorological organization, Agricultural Research Center, and Department of Soil and Water Management. This documentary research sought to investigate the content and value of virtual water used in irrigated and rainfed farming across wheat, barley, chickpea, maize, sugar beet, and tomatoes during 2014-2015 using CROPWAT, AGWAT, and EXCEL software. In addition, the share of green and blue virtual water was estimated in the study. Finally, 12 provinces were zoned from classes A to Z based on virtual water content and value of the products.
Results and Discussion: Results revealed that wheat with 1.96 to 3.68 m3/kg is the most consumable product that about 60 percent of the cultivated areas of wheat are located in areas of the province that are inappropriate in terms of content and value of virtual water. Also, tomato with the value of 0.09 to 0.38 m3/kg had the lowest virtual water content and average value of virtual water. According to the results, the sugar beet product is in desirable condition in terms of virtual water content and had moderate conditions in virtual water value. Finally, about 80% of maize produced in areas that are not in a desirable position in terms of virtual water content and value.
Results of green and blue virtual water showed that spring products such as sugar beet, tomatoes and maize received their water requirement from surface and groundwater resources. In addition, the largest blue component of wheat was related to Harsin city and the lowest was related to Javanrod city. For irrigated barley, the smallest and the largest share of blue virtual water were related to cities of Qasr Shirin and Sahne respectively.
Conclusion: Overall, the results of this study revealed that irrigated wheat and barley have a poor condition in terms of the content and the value of virtual water. However, since wheat and barley are considered as a strategic products policymaker should take appropriate measures in order to provide sustainable cultivation of wheat and barley. For example, improved farming, plant breeding, changing the growing season according to climatic conditions, developing cultivation in suitable areas, as well as applying appropriate pricing and support policies, including training of beneficiaries, and improving insurance policies could provide appropriate measures if Iran is to be self-sufficient in wheat and barley production.
Results of this study has practical significance for agricultural policymakers in Iran in general and Kermanshah province in particular. For example, zoning of crop cultivation based on the content and value of virtual water provided in this study can be an effective tool in modelling cropping pattern and sound water management policies. In addition, effective cropping pattern as well as sound water management resources would encourage farmers to engage in climate smart agriculture. Moreover, cultivation zoning based on content and value of virtual water is considered as a climate smart agriculture technique. This in turn would create resilient farming system in the study area. Through resilient farming system, farmers better adapt to climatic condition more effectively.
Sheyda Kaboodi; farzin shahbazi; Nasser Aliasgharzad; nosratola najafi; naser davatgar
Abstract
Introduction: Understanding soil biology and ecology is increasingly important for renewing and sustainability of ecosystems. In all ecosystems, soil microbes play an important role in organic matter turnover, nutrient cycling and availability of nutrients for plants. Different scenarios of land use ...
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Introduction: Understanding soil biology and ecology is increasingly important for renewing and sustainability of ecosystems. In all ecosystems, soil microbes play an important role in organic matter turnover, nutrient cycling and availability of nutrients for plants. Different scenarios of land use may affect soil biological properties. Advanced information technologies in modern software tools such as spatial geostatistics and geographical information system (GIS) enable the integration of large and complex databases, models, tools and techniques, and are proposed to improve the process of soil quality and sustainability. Spatial distribution of chemical and biological properties under three scenarios of land use was assessed.
Materials and Methods: This study was carried out in Mirabad area located in the western part of Souldoz plain surrounded by Urmieh, Miandoab, Piranshahr and Naghadeh cities in the west Azerbaijan province with latitude and longitude of 36°59′N and 45°18′E, respectively. The altitude varies from 1310 to 1345 with average of 1325 m above sea level. The monthly average temperature ranges from -1.4 °C in January to 24.6 °C in July and monthly precipitation ranges from 0.9 mm in July to 106.6 mm in March. Apple orchard, crop production field and rich pasture are three selected scenarios in this research work. Soil samples were systematically collected at 65 sampling points (0-30 cm) on mid July 2010. Soil chemical and biological properties i.e. microbial community, organic carbon and calcium carbonate equivalent were determined. The ArcGIS Geostatistical Analyst tool was applied for assessing and mapping the spatial variability of measured properties. The experimental design was randomized complete blocks design (RCBD) with five replications. Two widely applied methods i.e. Kriging and Inverse Distance Weighed (IDW) were employed for interpolation. According to the ratio of nugget variance to sill of the best variogram model three following spatial dependence conditions for the soil properties can be considered: (I) if this ratio is less than 25%, then the variable has strong spatial dependence; (II) if the ratio is between 25% and 75%, the variable has moderate spatial dependence; and (III) otherwise, the variable has weak spatial dependence. Data were also integrated with GIS for creating digital soil biological maps after testing analysis and interpolating the mentioned properties.
Results and Discussion: Spherical model was the best isotropic model fitted to variograms of all examined properties. The value of statistics (R2 and reduced sum of squares (RSS)) revealed that IDW method estimated calcium carbonate equivalent more reliably while organic carbon and microbial community was estimated more accurately by Kriging method. The minimum effective range (6110 m) was found for microbial community which had the strong spatial dependence [(Co/Co+C)
Mohammad Nazeri Tahrudi; Farshad Ahmadi; Keivan Khalili
Abstract
Introduction: Given the fact that Iran is located in the center of the dryland of earth and is significantly influenced by the deserts of Central Asia and hot dry deserts of Arabia and Africa, is one of the most arid and low rainfall land areas.So is the proper management of water resources is of critical ...
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Introduction: Given the fact that Iran is located in the center of the dryland of earth and is significantly influenced by the deserts of Central Asia and hot dry deserts of Arabia and Africa, is one of the most arid and low rainfall land areas.So is the proper management of water resources is of critical importance. The first step in the proper management of water resources is studying the factors that affected these resources including climate change. In fact climate change is a dynamic process in terms of time and place. Large parts of the Earth's climate as part of their normal variability in short-term and long-term experience. Short-term climate changes due to the difference in terms of average annual values of specific climate variables in average periods such as 30 years. Causes and effects of regional climate change in several parts of the world have been widely studied from various aspects. Among hydrological parameters, precipitation is the most important parameter in the complex hydrologic cycle. Follow the phenomenon of global warming on the Earth's surface, the rainfall pattern has changed.Trends of rainfall in different parts of the world have been studied by many researchers. Due to climate change in Iran and climate change in the Basin of Urmia Lake it seems that evaluation the trend of monthly and annual precipitation and its time of change point in the basin of Urmia Lake changes is important. The goal of this study is evaluatingthe trend and time of the change point trend of monthly and annual precipitation of rain gage stations in Urmia Lake basin.
Material and methods: Lake Urmia is the focus of surplus accumulation of surface currents all the rivers of the basin, with an area of approximately 5750 square kilometers and the average elevation of 1276 m above sea level and is located in the middle of the northern basin. Around of Lake Urmia there are 16 wetlands with an area of 5 to 120 hectares (some have dried up) that mostly have sweet or salty and fresh water and a high value of ecosystems.Urmia Lake Basin is situated in eastern of 44-14 to 47-53 and north of 40-35 to 30-38 coordinates. Urmia Lake Basin rainfall changes is 220 to 900 mm and have mean precipitation about 263 mm that added in central parts of the basin to the highlands.
Trend analysis: The aim of process test is to specify whether an ascending or a descending trend exists in data series. Since parametric tests have some assumptions including normality, stability, and independence of variables, where most of these assumptions do not apply to hydrologic variables, the nonparametric methods are more preferred in meteorological and hydrological studies. The nonparametric methods are less sensitive to extreme values compared to parametric tests in the examination of trends. Nonparametric tests can also be utilized for data time series regardless of linearity or nonlinearity of the trend (Khalili et al. 2014). One of the most well-known nonparametric tests is Mann-Kendall test (Mann 1945; Kendall 1975).
The modified Mann-Kendall test (MMK): The main assumption of Mann-Kendall test is that the sample data has no significant autocorrelation. However, some hydrological series might have a significant autocorrelation coefficient. When a series has a positive autocorrelation coefficient, there is an increased chance for Mann-Kendall test to reveal the existence of a trend in this series. In this case, the null hypothesis i.e. lack of trend is rejected, yet this hypothesis should not actually be. The modified Mann-Kendall test was presented by Hamed and Rao (1998) and has been used by Kumar et al (2009) for the analysis of the trend of Indian rivers. In this method, the effect of all significant autocorrelation coefficients is removed from the time series and is appliesto a series whose autocorrelation coefficients are significant in one or more cases.
Change point test: Pettittest is a non-parametrictest that was developedin 1979byPettit. Themethod is used in order tofind change points ina time series(Salarijazi et al 2012).In this study,thestatisticwas usedtofind asudden change intemperaturedata.Thisstatistic isatest with rank basis and without a distributionin orderto detectsignificantchangesin the mean of the time seriesanditis importantwhenthereis noassumptionabout the change time.
Results and discussion: In this study the trend of monthly and annual precipitation of rain gage stations that located in Urmia Lake basin were investigated using modified Mann-Kendall test. Z values of case study were calculated in two monthly and annual scales. The results of evaluation the trend of precipitation of rain gage stations of Urmia Lake basin showed that in October, December, January, February and March (five months of the year) the trend of precipitation is decreasing and the mean of Z values showed the less than zero values. In April and May there is no sensible changing in precipitation trend. Also the results showed that the March, April and May have a low failure rate and February, December and July have a most of change point of monthly precipitation data. About 60 percentages of the time of change point in precipitation trend are between 1992 and 1998. Also the results showed that two months of May and November there is no changing point in west Urmia Lake rain gage stations. In annual scale the time of changing trend is between 1992 and 1998.
Conclusion: The results of evaluation the trend of Lake Urmia precipitations showed that the Urmia Lake basin has a combination of decreasing and increasing trend in studied time period. The decreasing trend in precipitation often seen in west stations of the basin and west and south-west of Urmia Lake. The increasing trend also seen in south and north-east of Urmia Lake basin. Also the results of zoning the Z values of Mann-Kendall test showed that in annual scale the regions that influenced by polar-continental air mass that they entered Iran have a decreasing trend.
