Research Article
seyed javad rasooli; Mohammad Taghi Naseri Yazdi; reza ghorbani
Abstract
Introduction: Environmental factors whichaffect crop yield areone of the most important factors in increasing yield.Accurate prediction of crop yield for economic management and farming systems is of particular importance.
Materials and Methods: This research was done in order to statistically model ...
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Introduction: Environmental factors whichaffect crop yield areone of the most important factors in increasing yield.Accurate prediction of crop yield for economic management and farming systems is of particular importance.
Materials and Methods: This research was done in order to statistically model and predict the canola growth and yield in Mashhad region based on 5 agricultural meteorology indicesand 12 climatic parameters during 1999 - 2014period. The date of planting determined with regard to the optimum temperature at planting with probability of 75% based on Weibull formula. Beginning and the end of the phenological stages of canola (germination, emergence, Single leaf, rosette, stemming, flower, poddingand ripening) were calculated on the basis of growing degree days (GDD) for each set. Calculation and statistical equations was done usingMinitab Ver. 13.0, 16.Ver SPSS and Excelsoftwares. Correlation analysis,statistical models andmultivariate models were used to determine the relationship between the annual yield of canolaand independent variables, includingclimaticparameters and agricultural meteorologyindices during the growing season between 1999- 2000 and2009-2010for each phenological stage (8stages).The bestmodel was selected with respect to the values of the coefficient of determination (R2) and root mean square error (RMSE).If the predictive power is estimated of the model RMSE values of less than 10% excellent, between 10 and 20% good, 20 to 30% average, and higher than 30% weak. The model tested by estimating the yield of canola for the 2010 to2014 years and the correction factor was calculated and the effect.
Results and Discussion: Canola planting date wascalculated for 23 September in Mashhad region. The phenology of canola was calculated based on growing degree days (GDD) above 5 ° C.Germination calculatedfor25 September, emergence in 3 October, appearance single leaf in 7 October, rosette in 6 March, stemming in 4 April, floweringin 21 April, podding in 15 May and ripening in 4 Jun. The time of the phenological stages of cereals is virtually the same time. Therefore, due to the water scarcity in the studied region -canola can be used in crop rotation. Average, the highest and the lowest yield of canola were1329.5, 2159 and 835.5 kg per hectare,respectively.Canola crop yield showed a rising trend during 1999 – 2014period due toimprovingfarming techniques and mechanization. All models are significant regression coefficients were tested normal, alignment and line.Each model in the absence of proof of any of these hypotheses was removed and the 9remaining models were compared.Model 1 predicted canola crop yield in the single leaf stagewith an average yield of canola evapotranspiration ((Mpet, absolute maximum wind speed (FFabsmax) and the sum of the vapor pressure deficit (VPD).Model 5 predicted canola yield in the floweringstage based on the absolute lowest temperature (Tabsmin), average daily wind speed (FF) and total sunshine hours (SH). Model 3 predicted canola yield in the rosette stage based on the average of daily minimum temperature (Tmin), the number of days with precipitation greater than 1 mm R (day) and total pressure loss water vapor (VPD). Model 7 predicted canola yield during the whole growing season based on the average of daily maximum temperature (Tmax) and total precipitation (R).After R2 models with higher coefficient of 1, 5, 7 and 3, respectively, with coefficients of determination 0.902, 0.902, 0.868 and 0.866 respectively.Then F and RMSE were evaluated forecasting models 1 and 7 excellent, 5 good model and version 3 was average. Model 7due to lower RMSE and the number of parameters during growing season was the most appropriate model. Model validatedby means ofrecordedcrop yieldsduring 2011 and2014 years. The simulated yieldswere 1470, 1639 and 1226 with average of 1445 kg per hectare. Error percent was 45.1, 9.3 and -7.1for the following years with an average of 15.7. RMSE was 9.4, 2.6 and 2.3 with average of 7.4. The predictive value of the model was excellent for all these years.
Conclusion: Model predicted the yield of canola based on the average maximum temperature (Tmax) and total precipitation (R)with error correction to reduce15.7. These variables described 86.8percent yield in the growing season and were significant at 5 percent. Canola planting date wascalculated for 23 September. Time phenology was germinated 25 September until ripening 4 Jun.
Research Article
azam gholamnia; mohammadhosein mobin; atefe jebali; hamid alipor
Abstract
Introduction: Solar radiation (Rs) energy received at the Earth's surface is measured usingclimatological variables in horizontal surface and is widely used in various fields. Domination of hot and dry climates especially in the central regions of Iran results from decreasing cloudiness and precipitation ...
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Introduction: Solar radiation (Rs) energy received at the Earth's surface is measured usingclimatological variables in horizontal surface and is widely used in various fields. Domination of hot and dry climates especially in the central regions of Iran results from decreasing cloudiness and precipitation and increasing sunshine hours, which shows the high potential of solar energy in Iran. There is a reasonable climatic field and solar radiation in most of regions and seasons which have provided an essential and suitable field to use and extend new and pure energy.
Materials and Methods: One of the common methods to estimate the solar energy received by the earthis usingtemperature variables in any place . An empirical model is proposed to estimate the solar energy as a function of other climatic variables (maximum temperature) recorded in 50 climatological, conventional stations; this model is helpful inextending the climatological solar-energy estimation in the study area. The mean values of both measured and estimated solar energy wereobjectively mapped to fill the observation gaps and reduce the noise associated with inhomogeneous statistics and estimation errors. This analysis and the solar irradiation estimation method wereapplied to 50 different climatologicalstations in Iran for monthly data during1980–2005. The main aim of this study wasto map and estimate the solar energy received in four provinces of Yazd, Esfahan, Kerman and Khorasan-e-Jonoubi.The data used in this analysis and its processing, as well as the formulation of an empirical model to estimate the climatological incident of solar energy as a function of other climatic variables, which is complemented with an objective mapping to obtain continuous solar-energy maps. Therefore, firstly the Rswasestimated using a valid model for 50 meteorological stations in which the amounts of solar radiation weren't recorded for arid and semi-arid areas in Iran. Then, the appropriate method was selected to interpolate by GS+ software and after that, the seasonal maps of the received solar energy over the ground surface were produced by GIS software. The best fitof the Gaussian model was determined in winter with the lowest residual error and the highest correlation 1.87 and 0.913respectively, in spring with the lowest RSS and highest R23.87 and 0.86 respectively and during summer with RSS and R2, 5.9 and 0.851 and the exponential model in autumn withthe RSS and R2, 3.61 and 0.88..
Results and Discussion: Naturally, some of the differences in the mean solar energy among the stations may be related to inter annual variability rather than to differences in the climatic, radiative regimes. If different periods for the climatological estimations are used, the resulting mean values can be representative of the regional climatic regime of solar energy. The results showed that 53% of Yazd province Received 26 Mj / m2.day, in summer.In winter, more than 80% of Yazd province received 15 Mj / m2.day radiation. Kerman compared to other provinces received high solar radiation, especially this feature wasmore pronounced in winter because in this season compared to Yazd, Kerman radiation didnot only showed greater range, but also about 40% of the province's total area received 16 Mj / m2.day radiation, whereas Yazd no radiation was received during this season. Because Kerman is located in the southeast of region and itreceived more solar radiation than other provinces.In this study, the amount of solar energy in surface of 4 provinces including Yazd, Esfahan, Kerman and South Khorasan in arid and semiarid regions of Iran was estimated by the geostatistic. Seasonal mean values of solar energy absorbed at the surface of 4 stationswascalculated. The results showed that Kerman with receiving 27.25 (Mj m-2. D-1) averagely has the most received solar energy and Esfahan with 21.54 (Mj m-2. D-1) during the summer has received the least solar energy. The limited records of solar energy used in thisanalysis madethe analysis of long-term variations impossible. This paper wasthe first stage of a more extensive study which involvedmonitoring the behavior of photocells under real environmental conditions, which allowedto obtain efficiency curves used in the mapping of actual photovoltaic potential inarid and semiarid regions of Central Iran. This analysis must be complemented by better, higher resolution estimates of the incident solar energy; a viable alternative for such a task is the use of satellite observations. However, a better photovoltaic prospection, with high quality data, is necessary.
Research Article
Keyvan Khalili; Mohammad Nazeri Tahrudi; Rasoul Mirabbasi Najaf Abadi; Farshad Ahmadi
Abstract
Introduction: Climate change in the current era is a very important environmental challenge. Our understanding of the impacts of human activities on the environment, especially those related to global warming caused by increased greenhouse gases indicates that, most probably, a number of hydro-climatic ...
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Introduction: Climate change in the current era is a very important environmental challenge. Our understanding of the impacts of human activities on the environment, especially those related to global warming caused by increased greenhouse gases indicates that, most probably, a number of hydro-climatic parameters are changing. Based on the scientific reports, the average temperature of the earth has increased about 0.6 degrees centigrade over the 20th century and it is expected that the amount of evaporation continues to rise. In this case, the atmosphere would be able to transport larger amounts of water vapor, influencing the amount of atmospheric precipitations (21). Low precipitation and its severe fluctuations in the daily, seasonal and annual time scales are the intrinsic characteristics of Iran’s climates. Based on the research background, it seems that no comprehensive study has been conducted on concentration of winter precipitation in Iran. The aim of this study is to calculate the concentration and Trend of precipitation of Iranian border stations over the last half-century.
Materials and Methods: Iran with an area of over16480000 square kilometers is situated in the northern hemisphere and southwest of Asia. Almost all parts of Iran have four seasons. In general, a year can be divided into two warm and cold seasons. In this study, 18 stations were selected among more than 200 synoptic stations existing in the country, for investigating the concentration and precipitation trend.
PCI Index The PCI index has been proposed as an index of precipitation concentration. The seasonal scales of this index are calculated as equation 1(18):
(1)
Where Pi is the amount of monthly precipitation in the ith month. Based on the proposed formula, the minimum value of theoretical PCI is 8.3, indicating absolute uniformity in the precipitation concentration (i.e. the same amount of precipitation occurs every month).
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.
Results and Discussion: The PCI index was calculated using the monthly precipitation of the selected stations at seasonal and winter time scales over a 50-year period. This period was then divided into two 25-year sub-periods for the investigation of changes in average values of PCI (7). In the first 25-year span, the irregular precipitation distribution has been observed in the Bandarabbas station and its surroundings in winter season. In none of the studied stations, highly irregular precipitation occurred. The highest share of PCI was relatedto the precipitation average distribution class, and the northern, northwestern, and northeastern parts of the country have a uniform precipitation distribution. In winter, within the first 25-year period, the country had ideal conditions in terms of precipitation and its concentration in the mentioned regions. Within the second 25-year period, the intensity of irregular precipitation concentration decreased, as the regions that had confronted strong precipitation irregularities wereadded to regions with uniform concentration. At the seasonal scale and in winter, the country’s share of uniform distribution diminished in the second 25 years, and overall most parts of Iran have been covered by average precipitation distribution. The uniform precipitation distribution in recent years (second 25 years) has decreased in winter in such a way that no uniform distribution has been observed in the northeast of the country and uniform distribution belongedto the Caspian sea border strip, southern regions of west and east Azerbaijan stations (Urmia, Khoy and Tabriz stations) along with Kermanshah, Sanandaj, and Zanjan stations.
Trend analysis of the PCI In winter the Abadan, Ahwaz, Bandarabbas, Birjand, Kermanshah, Sanandaj, Urmia and Zahedan stations experienced an insignificant decreasing trend in PCI. At other stations, an insignificant increasing trend was observed in the PCI series. Overall, 9 out of 18 considered stations, witnessed increasing PCI trend implying increased irregularities in winter precipitation.
The results of Mann-Kendall trend test for precipitation Based on the results it can be observed that in winter Ahwaz, Gorgan, Khoramabad, Kermanshah, Ramsar, Rasht and Sanandaj experienced an insignificant decreasing trend in precipitation. In Khoy, Sanandaj, Tabriz, Urmia, Zahedan, and Zanjan stations, the decreasing precipitation trend in winter was significant. Overall, 12 out of 18 studied stations have been afflicted with a decreasing precipitation trend in winter.
Conclusion: Precipitation Concentration Index (PCI) is an index for determining the precipitation variations in a certain region and PCI analysis can reveal the accessibility to water in an environment. In this study, the PCI was used to analyze the precipitation concentration at two annual and seasonal time scales throughout the Iran (from 1961 to 2010). The PCI zoning results at the seasonal scale demonstrated that precipitation concentration had the same trend within the two 25-year sub-periods. These results also revealed a high PCI in provinces with low precipitation such as Zahedan. These stations, according to Oliver (18) classification, have irregular and sporadic precipitation duringwinter. Overall, the PCI analysis at the seasonal scale indicated that the regions covered by polar-continental, Europe-originated polar-continental and North Atlantic ocean-originated polar-continental have the best precipitation concentration throughout the country. The results of this index provided valuable information for water resources managers in regions with low-precipitation, consistent with research by Gozzini et al (7). The results of modified Mann-Kendall (MMK) test for PCI in Iran revealed a decreasing trend over the last 50 years. Based on the obtained results in winter, the Khoy, Sanandaj, Tabriz, Urmia, Zahedan, and Zanjan stations experienced a significant decreasing trend. The existence of an increasing trend in PCI albeit insignificant reveals changes in Iran's winter precipitations confirmed by Mann-Kendall test for precipitations in 18 studied stations. Overall, it can be concluded that the decreasing trend in Iran's winter precipitation has resulted in increasing PCI and thereby increased irregularities in winter precipitations, especially in winter season.
Research Article
Niloofar Sadri; Hamidreza Owliaie; Ebrahim Adhami; Mahdi Najafi
Abstract
Introduction: Potassium is an essential element for plant growth and exists as four forms in soils: soluble, exchangeable, non-exchangeable, and mineral. Soluble and exchangeable K are considered as readily available and non-exchangeable K as slowly available. Organic matters and acids play an important ...
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Introduction: Potassium is an essential element for plant growth and exists as four forms in soils: soluble, exchangeable, non-exchangeable, and mineral. Soluble and exchangeable K are considered as readily available and non-exchangeable K as slowly available. Organic matters and acids play an important role in increasing the bioavailability of nutrients especially potassium in the soils. Organic acids are low-molecular weight CHO containing compounds which are found in all organisms and which are characterized by the possession of one or more carboxyl groups. Depending on the dissociation properties and number of these carboxylic groups, organic acids can carry varying negative charge, thereby allowing the complexation of metal cations in solution and the displacement of anions from the soil matrix.The ability of an organic acid to release K from soils depends on some factors such as: diffusion rate of the organic acid in soil, the diffusion capability of organic acid-element complexes, the contact time of the organic acid on a mineral surface, the ionization of the organic acid, the functional group of the organic acid and its position, and the chemical affinity between the organic acid and the mineral elements. This study was conducted in order to evaluate the effect of organic acids and vermicompost on transformation of K in some selected soils of Fars Province, southern Iran.
Materials and Methods: In this study, nine soils with enough diversity were selected from different parts of Fars Province. The experiment was done as a completely randomized design with three replications, consisting of three incubation times (5, 15 and 60 days) and four organic compounds (including 2% vermicompost, three acids of citric, malic and oxalic acid eachat a concentration of 250 mmolkg-1and one control). The samples were incubated at 50% of saturation moisture at 22°C. Routine physicochemical analyses and clay mineralogy were performed on soil samples. Soil reaction, texture, electrical conductivity, calcium carbonate, and gypsum were identified. Soluble, exchangeable, non-exchangeable and mineral potassium were measured. The amounts of K forms in each sample were determined. Total K was determined following digestion of soil (110°C) with 48 % HF and 6 M HCl. Water soluble K was measured in the saturated extract. Exchangeable K was extracted with 20 ml 1.0 M NH4OAc (pH 7.0) for 5 min. Nitric acid-extractable K was measured by extraction of a soil sample with boiling 1.0 M HNO3 for 1 h. Potassium was measured on all filtrated extracts by flame photometer. The content of clay minerals was determined semi-quantitatively, using peak areas on the diffractograms of ethylene glycol solvated specimens. Statistical analysis was accomplished using the SPSS 16.0 software and the comparison of mean values was done using the Duncan test at the 5% level of significance.
Results and Discussion: The amount of different forms of K including water soluble, exchangeable, HNO3-extractable, and mineral K are relatively high in the studied soils. Mineralogical analysis indicated that smectite, illite, palygorskite and chlorite were the major minerals in the clay fractions. The results also showed that exchangeable, non-exchangeable and total potassium were in the range of 166 to 378, 282 to 1694, and 2312 to 8437 mg/kg-1, respectively.Organic acids and vermicompostwere led toa significant increase in soluble K at all times compared to control and vermicompost treatment exhibited greater effect. These treatments also significantly increased exchangeable potassium compared to control. Significant differences between exchangeable potassium of organic acids and vermicompost treatments were not observed at 5 and 15 days, but significant differences were observed between treatments of mallic and oxalic acids at 60 days. Compared to the control, the non exchancheable K showed significant increase in all three organic acid treatments and vermicompost at 15 and 60 days.
Conclusion: Based on the results, while exchangeable and non-exchangeable (NEK) potassium showed a clear trend in treatments, solution potassium was first increased and then showed a decreasing trend due to the rapid changes in liquid phase compared to the solid phase. All treatments significantly increased soluble potassium in each 3 times. The greatest potassium increase associated with vermicompost. In general, oxalic acid> malic acid>vermicompost> citric acid, were increased exchangeable potassium, while the trend for NEK was in the order of oxalic acid> malic acid> citric acid>vermicompost, respectively. All treatments at all times (except for treatment 5 days of NEK), showed a significant increase in the exchange and NEK potassium compared to the control. The results also reflect the effect of the dominant soil clay mineral on transformation of exchangeable and NEK, so that the highest and lowest rate of increase was related to the soils with dominant palygorskite and illite, respectively. In general, it seems that the use of organic acids and organic matter leads to a rapid increase of potassium, which must be properly managed in the soils with high leaching. Due to the complexity of soil environment in terms of soil physical, chemical and biological aspects and the role of these factors on potassium transformation, repeating of this experiment in other soils is recommended.
Research Article
Yousef Hasheminejhad; Mahdi Homaee; Ali Akbar Noroozi
Abstract
Introduction: Monitoring and management of saline soils depends on exact and updatable measurements of soil electrical conductivity. Large scale direct measurements are not only expensive but also time consuming. Therefore application of near ground surface sensors could be considered as acceptable time- ...
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Introduction: Monitoring and management of saline soils depends on exact and updatable measurements of soil electrical conductivity. Large scale direct measurements are not only expensive but also time consuming. Therefore application of near ground surface sensors could be considered as acceptable time- and cost-saving methods with high accuracy in soil salinity detection. . One of these relatively innovative methods is electromagnetic induction technique. Apparent soil electrical conductivity measurement by electromagnetic induction technique is affected by several key properties of soils including soil moisture and clay content.
Materials and Methods: Soil salinity and apparent soil electrical conductivity data of two years of 50000 ha area in Sabzevar- Davarzan plain were used to evaluate the sensitivity of electromagnetic induction to soil moisture and clay content. Locations of the sampling points were determined by the Latin Hypercube Sampling strategy, based on 100 sampling points were selected for the first year and 25 sampling points for the second year. Regarding to difficulties in finding and sampling the points 97 sampling points were found in the area for the first year out of which 82 points were sampled down to 90 cm depth in 30 cm intervals and all of them were measured with electromagnetic induction device at horizontal orientation. The first year data were used for training the model which included 82 points measurement of bulk conductivity and laboratory determination of electrical conductivity of saturated extract, soil texture and moisture content in soil samples. On the other hand, the second year data which were used for testing the model integrated by 25 sampling points and 9 bulk conductivity measurements around each point. Electrical conductivity of saturated extract was just measured as the only parameter in the laboratory for the second year samples.
Results and Discussion: Results of the first year showed a significant correlation between electrical conductivity and apparent conductivity with a regression coefficient of 0.78. Although multiple linear regression by inclusion of soil moisture and clay content as independent variables improved the regression coefficient to 0.80 but the effect of clay content was not significant in this multiple model. Sensitivity analysis by maintaining one variable at its average value and changing the second variable also showed greater sensitivity of the model to soil moisture in comparison with soil clay content. Generally under estimation of soil moisture and over estimation of soil clay content produced about 63 to 65 percent Mean Bias Error (MBE) while over estimation of soil moisture and under estimation of soil clay content produced about 35- 37 percent of MBE. So the model is quite sensitive to both parameters and they cannot be estimated in the field by feeling and the other field methods. Simple linear regression model between ECe and EMh was tested on the second year because the errors in estimating soil moisture could be imposed a significant error on estimating soil salinity. Once the model was tested for estimation of soil salinity in the central point based on EMh reading at the center and then it was tested for estimation of soil salinity based on the average EMh of 9 points in each location. Results showed that the correlation between soil salinity and apparent soil electrical conductivity could be improved to 0.98 using the average of 9 measurements instead of 1 measurement.
Conclusion: Based on the results the electromagnetic induction device is sensitive to soil moisture. Although its sensitivity to clay content is less than the sensitivity to moisture content, but the total model error as a result of over estimating soil moisture is about equal to its error resulted from under estimating clay content and vice versa. So the field and feeling methods could not be implemented as inputs for the multiple regression models but these methods have enough accuracy to divide soil samples into two groups of dry and wet soils or sandy or clayey soils, on the other hand measurements of these parameters imposes more cost and time to soil salinity surveys. Results also showed that the repeated EM measurements around each sampling point could improve the strength of the regression. Therefore regarding to the sensitivity of the technique to soil moisture three methods are suggested to improve accuracy of calibration: a)- measurement and calibration under the same moisture conditions; b)- field approximation of soil moisture and dividing soil samples into two groups of dry and moist soils and deriving two different groups of calibration equations.
Research Article
alireza yazdanpanah; mohammad reza bakhtiyari
Abstract
Introduction: Corn is one of the most important agricultural products withhigh consumption different forms of usage asfood and fodder. Corn yield and its cultivation needs improvement especially in developing countries. In conventional fertilizing methods with centrifuge machines or hand fertilization, ...
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Introduction: Corn is one of the most important agricultural products withhigh consumption different forms of usage asfood and fodder. Corn yield and its cultivation needs improvement especially in developing countries. In conventional fertilizing methods with centrifuge machines or hand fertilization, parts of the fertilizer lost through volatilization, leaching and weeds absorption. Leaf burning is also reported in this method. Fertilizer placement in bands is a method that does not show these disadvantages and improves fertilizer use efficiency for the crop. Therefore using new machines and new methods for fertilizing the crop,the cultivation area and mean of yield productioncan improved, for example the yield of corn in this research.
Material and Methods: This research was conducted in Lak Lak research farm in Asadabad district. Moldboard plowing plus disking was used for bed preparing the seeds anda 4 rows crop planter was used for planting the seeds.
For treatments conducting Combination machine that had designed in thisresearch station workshop was used. This machine was able to place Urea fertilizer with different methods (fertilizer drilling in the rills, fertilizer placement in one side and two sides of plants). The variety of corn that used for this experiment was SC704 with65000 plants in one hectareas plant density. After soil sampling nitrogen, phosphorous and potassium fertilizers and other fertilizers demands by means of soil testwere determined. Half of the nitrogen was used at planting time from source of urea and the other half was used as top dressing duringgrowth season due to treatments as follow:
90 kgha-1 nitrogen as broad costing
60 kgha-1 nitrogen as broad costing
30 kgha-1 nitrogen as broad costing
90 kgha-1 nitrogen as drilling in the rills
60 kgha-1 nitrogen as drilling in the rills
30 kgha-1 nitrogen as drilling in the rills
90 kgha-1 nitrogen as band placement in one side of the plants
60 kgha-1 nitrogen as band placement in one side of the plants
30 kgha-1 nitrogen as band placement in one side of the plants
90 kgha-1 nitrogen as band placement in two sides of the plants
60 kgha-1 nitrogen as band placement in two sides of the plants
30 kgha-1 nitrogen as band placement in two sides of the plants
The treatments were conducted through 7-9 leaf bearing stage of corn growth. After harvesting, the mean yield of each plot and other data of plant attributes were collected through growth season and leaf samples were collected for nitrogen analysis. All data were analyzed usingmeans of Duncan's test.
Result and Discussion: The results of experiment showed that, fertilizing method had no significant effect on plant height, maize height and percentage of corn cob at 1% level, but had a significant effect on corn yield at 1% level and on the weight of thousand kernels at 5% level. Also the effect of fertilizer amount on plant height, maize height and percentage of corn cob was not significant at 1% level. The interactional effect of method-amount was not significant on the corn attributes and weight of thousand kernels but was significant on the net yield of corn at 5% level. Comparison of means showed that although the treatment of fertilizer placement in two sides of plants with the amount of 90 kgha-1net nitrogen produced 10.98 tha-1corn yield but its difference with one side fertilizer placement, with the amount of 60 kgha-1 net nitrogen that produced 9.463 tha-1 corn yield, was not significant in 1% level. According to mean comparison table (table 3 and 4) it was clear that using 90 kgha-1 net nitrogen as band placement in two sides of plant row, produced the maximum yield of corn that was in the same group with 60 kgha-1 as band placement in one side of plant row. Therefore the treatment of 60 kgha-1as band placement waspreferred to othertreatments that reduces fertilizer usage and produces good amount of yield. The results of leaf analysis of corn in two years of experiment showed that the treatments effect on nitrogen concentration in corn leaf was significant.
Conclusion: Band placement of urea fertilizer from distance of 10 cm of plants and 5 cm in soil depth with amount of 60 kgha-1 as band placement in one side of plant row is recommended for corn through growth season. Band placement of urea is preferred to broadcasting method.
Research Article
Mohammad Ali Monajjem; Ahmad Heisari; Gholam Bagheri Marandi
Abstract
Introduction: Nanoclays, due to their high specific surface area (SSA) chemical and mechanical stabilities, and a variety of surface and structural properties are widely applied. Some of their applications are using them as nano composite polymers, heavy metal ions absorbents, catalysts, photochemical ...
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Introduction: Nanoclays, due to their high specific surface area (SSA) chemical and mechanical stabilities, and a variety of surface and structural properties are widely applied. Some of their applications are using them as nano composite polymers, heavy metal ions absorbents, catalysts, photochemical reaction fields, ceramics, paper fillings and coatings, sensors and biosensors. Nano clays and Clays are the most important components constructing soil ecosystems. The physical and chemical properties of soils are mainly depending on the type and amount their clay fraction pertaining to considerable nanoclays. Nano clays have been frequently used to eliminate environmental contaminants from soil and water. Nano clays have also an effective role in the phosphate sorption and desorption from soil solution. Phosphate retention is highly affected by the chemical bonds of the materials, cristalographic properties and pH. In clay size particles there are different structures of nano particles such as alominosilicates with nano ball and nano tube construction. Soils with andic properties have amorphous clay minerals such as allophone. Allophane has a diameter of 3 to 5 nano meter under a transmission electron microscope (TEM) and its atomic Si/Al ratio ranges between 0.5 and 1. Allophane shows variable charge characteristics and high selectivity for divalent cations, and is highly reactive with phosphate.
Materials and Methods: The objective of this research was to inspect the effect of soil components particularly clay and nanoclay on the sorption of phosphate. To achieve this goal, we studied the amount of phosphate sorption by the natural nanoclays. Samples with andic and vitric properties which were previously formed on volcanic ash in Karaj were chosen in 5 pedons as two Andic ( > 5 percent volcanic glass, > 25 percent P retention, pH NaF > 8.6 and Alo +½ Feo > 0.4) and non Andic soils.. After removal of organic materials, soluble salts, carbonates and iron oxides from the soil, clay fraction was prepared for X-ray diffraction analyses. The nanoclay fraction was extracted using the method described by Li and Hu (2003). The specific surface area were determined using EGME method. Different forms of extractable aluminum, including pyrophosphate (Alp) and ammonium oxalate (Alo) extractable forms, as well as silica extractable by ammonium oxalate (Sio) were measured. Routine chemical analyses for organic carbon (OC), cation exchange capacity (CEC) were determined by standard methods. Particle size distribution was determined by the hydrometer method (after ultrasound dispersion). Allophane percentage was calculated using the formula provided in the soils under study by Mizota and Van Reeuwijk (1989). Nano particles were inspected using scanning electron microscope (SEM).
Results and Discussion: The studied soils were classified as Entisols, Andisols and Inceptisols. The results showed that the bulk of soil mineralogy was consisted of combination of illitic, chloritic, smectite and hydroxy interlayer minerals. In addition to sesquioxides, the crystallization degree of soil minerals was also important in phosphate retention. Results of SEM studies of Andisols implied the existence of different types of aluminosilicate nano particles as nano ball (Allophane), nano tubes (imogolite) and smectitic minerals. Hollow spherical structure was proposed for allophane. According to the SEM results, nano particles extracted from non andic soils were dominated by layered silicates (probably montmorillonite). Among physical properties which are effective on phosphate retention, the shape, size and porosity of the particles can be mentioned, all of which have impacts on the specific surface area of the particles. Soils with higher amounts of Alp and Sio were comprised more nanoclay (25,8 g per kg) and higher phosphate retention (%55). Various mechanisms were suggested by soil scientists for phosphate sorption on allophane (Nanoclays). Some of are ligand interchange, silicate replacing by phosphate in high phosphate concentration, and replacing phosphate by weak silicon bonds. There was a positive and significant relation between Sio and Alo amounts (R2= 0,976). The ratio of Alp/Alo in andic soils increased by increasing organic material (at least 0,02 and at most 0,11).
Conclusions: Phosphate retention in the studied soils had a significant relation with Alo (R2 = 0,991).The more percentage of nanoclay showed higher phosphate retention thus the highest amount of phosphate retention was determined in the sample containing highest nanoclays. Nanoclay shows high performance in removal of phosphate from solutions. Little amounts of nanoclays can remove great amounts of phosphate from solution.
Research Article
Nasrin Ansari; Mehdi Hassanshahian; MohammadReza Khoshro
Abstract
Introduction: Petroleum hydrocarbons are widespread pollutant that enters to soil by some pathwayssuch as: Transportation of crude oil, conservation of oil compounds, crude oil spill and treatment process on refineries. Oil pollution has some ecological effect on soil that disturbed composition and ...
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Introduction: Petroleum hydrocarbons are widespread pollutant that enters to soil by some pathwayssuch as: Transportation of crude oil, conservation of oil compounds, crude oil spill and treatment process on refineries. Oil pollution has some ecological effect on soil that disturbed composition and diversity of microbial community. Also this pollution has some effects on microbial activity and enzymes of soil. Forests ecosystems may be polluted with petroleum hydrocarbons via different ways such as transportation and spill of crude oil from resource of petroleum storage. Industrial soil defined as the soils that located in industrial area such as petrochemical plant, mine, chemical factories and etc. These soils always contaminated to many pollutant such as: oil, diesel and heavy metals. These pollutants have some effects on the texture of the soil and microbial community. The aim of this research is to understand the effect of oil pollution on two different soils.
Material and Methods: In order to evaluate the effect of crude oil on soil microbial community, two different soil samples were collected from industrial and forest soils. Six microcosms were designed in this experiment. Indeed each soil sample examined inthree microcosms asunpolluted microcosm, polluted microcosm, and polluted microcosm with nutrient supply of Nitrogen and PhosphorusSome factors were assayed in each microcosm during 120 days of experiment. The included study factors were: total heterotrophic bacteria, total crude oil degrading bacteria, dehydrogenase enzyme and crude oil biodegradation. For enumeration of heterotrophic bacteria nutrient agar medium was used. In this method serial dilutions were done from each soil and spread on nutrient agar medium then different colonies were counted. For enumeration of degrading bacteria Bushnel-Hass (BH) medium were used. The composition of this medium was (g/lit): 1 gr KH2PO4, 1gr K2HPO4, 0.2 gr MgSO4.7H2O, 0.02 gr CaCl2, 1 gr NH4NO3, and two drops of FeCl3 60% , the pH was 7. The carbon source of this medium was crude oil (1%). In MPN method microplates (24 well) were utilized and turbidity was calculated as positive index.
Results and Discussion: The results of this study showed that the highest quantity of heterotrophic bacteria was related to forest soil (8 × 108). The quantities of degradative bacteria significantly were lower than heterotrophic bacteria in all soil microcosms. This result may be expected because heterotrophic bacteria can use other carbon sources instead of crude oil such as organic carbon, suger and some nutrients that exist in the soil, but degrading bacteria have some limit in the use of organic carbons and only capable to use crude oil hydrocarbons. Sothe quantity of these bacteria is lower than heterotrophic bacteria. The quantity of degradative bacteria have decrement pattern until 60th day of experiment but after this day these bacteria have increment pattern. This result can be interpreted as from beginning of experiment until 60th day of experiment the bacteria adapted to toxic effect of crude oil and after this time the quantity of bacteria increased and have ability to use pollutant in the soil. The best deydrogenase activity between different microcosms related to polluted microcosm with nutrient. This result confirms that nitrogen and phosphorus can decrease the damage effect of crude oil on soil microbial community. The mechanism of this attenuation of toxicity effect of crude oil on microbial community can be related to enhance bioavailability of essential elements for bacteria in the soil. So after oil pollution of an area, soil supply upto nitrogen and phosphorus demand must be mentioned as a necessary practice to decrease the toxicity effect of pollutants. The highest biodegradation of crude oil in all studied soils belonged to industrial microcosm (95 %). It can be explained by adaptation theory because the bacteria in the industrial soil were better adapted to different pollutants and these bacteria have more capability for biodegradation of crude oil. By this reasonthe rate of degradation of crude oil in the industrial soil were higher than forest soil. Statistical analysis of the results showed that there was a significant correlation between MPN quantity of heterotrophic bacteria and other assayed factors. Also, forest soil seemed to have significant difference with other soils.
Conclusion: according to the obtained results by this study, it can be possibly proposed appropriate strategies for bioremediation of different studied soil types. The selection of best bioremediation strategies belong to specific types of soil. Just as this research confirmed that the type of soil plays significant role in the percentage of degradation.
Research Article
parvane mohaghegh; Mahdi Naderi; jahangard mohammadi
Abstract
Introduction: The mismanagement of natural resources has led to low soil quality and high vulnerability to soil erosion in most parts of Iran. To have a sustainable soil quality, the assessment of effective soil quality indicators are required. The soil quality is defined as the capacity of a soil to ...
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Introduction: The mismanagement of natural resources has led to low soil quality and high vulnerability to soil erosion in most parts of Iran. To have a sustainable soil quality, the assessment of effective soil quality indicators are required. The soil quality is defined as the capacity of a soil to function within natural and/or managed ecosystem boundaries. Among approaches which are suggested for soil quality assessment like soil card design, test kits, geostatistical methods and soil quality indices (SQIs), SQIs are formed by combination of soil indicators which resulted from integration evaluation of soil physical, chemical and/or biological properties and processes complement by existing/measureable data, sensitive to land use changes, management practices and human activities and could be applied in different ecosystems. As the measurement and monitoring of all soil quality indicators is laborious and costly, many researchers focused on limited soil quality indicators. There are many methods for identification and determination of minimum data set that influence on soil quality such as linear and multiple regression analysis, pedotransfer functions, scoring functions, principle component analysis and discriminant analysis. Among these methods, principle component analysis is commonly used because it is able to group related soil properties into small set of independent factors and to reduce redundant information in original data set. The objective of this research was to investigate the effects of land use change on soil quality indicators and also the determination of minimum effective soil quality indicators for assessment of soil quality in Choghakhor Lake basin, Chaharmahal and Bakhtiari province, Iran.
Materials and Methods: To meet the goal, Latin hypercube sampling method was applied by using slope, land use and geological maps and 125 composite soil samples were collected from soil surface (0-20 cm). After pretreatments, 27 physical and chemical soil properties like clay, sand and silt content, bulk density (ρb), porosity, organic carbon (OC), particulate organic carbon in macro aggregate (POCmac), particulate organic carbon in micro aggregates (POCmic), proportion of particulate organic carbon in macro aggregates to micro aggregates (POCmac/mic), mean weight diameter (MWD), macro porosity (Mac pore), air content, available water content (AWC), relative water content (RWC), effective porosity (Feff), Dexter index (S), porosity, acidity (pH), electrical conductivity (EC), Nitrogen (N), Phosphorous (P), Iron (Fe), manganese (Mn), Zinc (Zn), Cadmium (Cd), lead (Pb), Copper (Cu) and Cobalt (Co) were measured using appropriate methods.
Results and Discussion: The impact of different land use types on soil quality was evaluated by measuring several soil properties that are sensitive to stress or disturbance and comparison of them. The results showed that measured values of OC, POCmac, POCmic, POCmac/mic, P, Fe, Zn, Mn, Cu, ρb, MWD, AWC, air content and S were in order orchards > crop land > good rangelands > dry lands > weak rangelands. In this region, land use changes have different effects on soil quality. The alternation of good pasture lands to orchard and crop lands caused to enhancement of soil quality parameters. The variation of good pasture to dry land and degradation of good pasture in this area led to decreasing of soil quality. The principle component analysis (PCA) was employed as a data reduction tool to select the most appropriate indicators of site potential for the study area from the list of indicators. Based on PCA, 8 components with eigenvalues ≥ 1 were selected that explained 99.96 percent of variance. The prominent eigenvectors in components were selected using Selection Criterion (SC). The results revealed that the most important component, was the first component with the most dominant measured soil property of Cu. 12 soil quality parameters base on SC were determined in the first component. Stepwise discriminate analysis also was applied for determination significant soil quality indicators from 12 soil parameters. Our result showed that the minimum data set influencing on soil quality were Zn followed by POCmac/mic, clay %, Cu, Mn and P, respectively.
Conclusion: The results suggested that the permanent crop management (Orchard and crop land) had generally a positive impact on soil quality, while dry land and degradation of good pasture had a negative impact on soil quality. Our study suggested that the PCA method and stepwise discriminant analysis for determination of minimum data set can be used in Chughakhur lake basin. In this study from27 of physical and chemical soil properties, the fertility factors such as the content of Zn, Cu, Mn and P and the proportion of particle organic carbon in macro aggregate to micro aggregate and also soil texture components can be used to the minimum data set that evaluates soil quality. These parameters mostly depend on soil management system.
Research Article
Mehdi Zangiabadi; manoochehr gorji; Mehdi Shorafa; Saeed Khavari Khorasani; Saeed Saadat
Abstract
Introduction: Soil is the main source of water retention and availability for plant uptake. The supplement of water is completely dependent on soil physical properties. The soils with higher values of available water are generally more productive because they can supply adequate moisture to plants during ...
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Introduction: Soil is the main source of water retention and availability for plant uptake. The supplement of water is completely dependent on soil physical properties. The soils with higher values of available water are generally more productive because they can supply adequate moisture to plants during the intervals between irrigation or rainfall events. Generally according tothe spatial and temporal distribution of precipitation, Iran has an arid climate in which most of the relatively low annual precipitation falls from October through April. Thus, water deficiency along with the lack of organic carbon in the soil justifies the necessity of studying the soil, water and plant relationships that may improve the efficiency of water consumption in agricultural practices. For that reason, this research was conducted to investigate the relationship between some soil physical properties and Integral Water Capacity (IWC) index as one of the soil physical quality indices.
Materials and Methods: This study was conducted in Torogh Agricultural and Natural Resources Research Station in Khorasan-Razavi province, north-eastern Iran during 2013-2014. This station is located in south-east of Mashhad city with a semi-arid climate, annual precipitation of 260 mm and mean air temperature of 13.5 °C. The soil was classified in Entisols and Aridisols with a physiographic unit of alluvial plain that generally had medium to coarse textures in topsoil. Thirty points with different soil textures and organic carbon contents were selected as experimental plots. In order to measure different properties of the soil, two soil cores (8 cm diameter × 4 cm length cylinder for bulk density and 5 cm diameter × 5.3 cm length cylinder for sandbox measurements) and one disturbed soil sample (for other measurements) were collected from 0-30 cm depth of each plot. After conducting required laboratory analysis and field measurements using standard methods, the soil moisture curve parameters (RETC program), Porosity (POR), Air Capacity (AC), Relative Field Content (RFC) and Integral Water Capacity (IWC) index, were calculated. In this regard, integration calculations were done by Mathcad Prime 3 software. Finally, the relationship between the measured properties and IWC index were analyzed using Pearson correlation coefficient and stepwise multiple linear regression by SAS (9.1) statistical software.
Results and Discussion: Laboratory analysis results showed that the soil texture classes of samples were loam (40%), silt loam (23%), silty clay loam (17%), clay loam (13%), and sandy loam (7%). On average, very fine sand particles were dominant between five size classes of sand and the lowest values were devoted to very coarse sand particles. Soil porosity and air capacity calculation results indicated that on average bulk soil porosity (PORt) and bulk soil air capacity (ACt) were 0.46 and 0.20 (cm3cm-3), respectively. According to the results, RFC of 60% of studied soil samples were lower than 0.6, 7% were higher than 0.7 and only 33% were between 0.6-0.7 (optimal range). IWC index calculations were resulted in 0.13-0.25 (cm3cm-3) in different soil textures. The highest IWC were related to Loam and Clay Loam textures, respectively. Statistical analyses indicated that there were no significant relationship between soil particles (sand, silt and clay) and organic carbon content with IWC index. The factors of soil bulk density and RFC were negatively correlated with IWC index that means decreasing the soil bulk density and RFC would lead to the reduction of the effects of water uptake limitation factors by increasing the values of weighting functions (IWC calculations), and improvement of soil physical quality. High significant (P < 0.001) positive correlation coefficients were observed between IWC index and the factors of soil PORt, ACt and soil matrix air capacity (ACf) in this study. Multiple regression analysis results showed that IWC index could be estimated by the factors of ACt and PORt with the determination coefficient of 0.63. The partial determination coefficients indicated that ACt factor accounted for 50% and PORt accounted for 13% of IWC index variations.
Conclusion: The results indicated that in medium to coarse-textured soils, IWC index could be estimated using the bulk soil air capacity (ACt) and bulk soil porosity (PORt) factors that are derived from soil volumetric water content at saturation and field capacity points.
Research Article
zahra amirpour; salar rezapour; behnam dovlati
Abstract
Introduction: Multiple biological and physiological processes in the plant, including carbohydrates and proteins formation, activation of 50 enzymes for energy transmission as well as reducing water losses from leaf pores, are mostly affected by the presence of potassium in the plant. In order to test ...
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Introduction: Multiple biological and physiological processes in the plant, including carbohydrates and proteins formation, activation of 50 enzymes for energy transmission as well as reducing water losses from leaf pores, are mostly affected by the presence of potassium in the plant. In order to test this hypothesis, five soil subgroups (TypicCalcixerepts, FluventicHaploxerepts, TypicEndoaquepts, TypicHalaquepts and VerticEndoaquepts) belonging 15 series of gardened and adjoining virgin soils were described and sampled. The studied soils had been influenced under horticultural practices for over five decades.
Materials and Methods: The soil samples were analyzed for different K forms, K adsorption and physico- chemical properties after air drying and grinding to pass through a 2 mm-sieve. The particle-size distribution was determined by the hydrometer method (Bouyoucos, 1962). The total carbonate in the soil expressed as the calcium carbonate equivalent (CCE) was determined by a rapid titration method (Nelson, 1982). Organic matter (OM) was measuredby the Walkley and Black (1934) dichromate oxidation method. The pH of the soil was analyzed in 2:1 CaCl2/soil suspension using glass electrode pH meter (Crockford and Norwell, 1956) and EC was detected in a saturated extract. The cation exchange capacity (CEC) was measured using sodium acetate (1 M NaOAc) at pH 8.2 (Chapman, 1965). Water soluble K was extracted with deionized water (1: 5 w/v) after shaking for 30 minutes on a mechanical shaker and later contents were centrifuged to separate clear extract (Jackson 1973). Exchangeable K was determined by extracting the soil with neutral normal ammonium acetate, Non-exchangeable K was estimated as the difference between boiling 1N HNO3 –K and neutral normal ammonium acetate K (Thomas 1982).
Results and Discussion: The result showed that for most of the studied soils, long-terms horticultural practices decreased the amount of different K forms as a result of changes in soils types, agricultural practices and soil properties. In Comparing to the virgin soils, long-term horticultural and irrigation activities caused a decrease?? in soluble K from 0.05 (a drop of 15% with depletion factor of 0.85) to 1.48 mmol l-1(a drop of 95% with depletion factor of 0.05), potassium absorption ratio (PAR) from 0.08 (a drop of 31% with depletion factor of 0.69) to 1.17 mmol l-1(a drop of 97% with depletion factor of 0.03), exchangeable K from 12.01 (a drop of 3% with depletion factor of 0.97) to 285.98 mg kg-1 (a drop of 97% with depletion factor of 0.43),exchangeable potassium percentage(EPP) from 0.49 (a drop of 12% with depletion factor of 0.88) to 3.47% (a drop of 59% with depletion factor of 0.41), available K from10.42 (a drop of 3% with depletion factor of 0.97) to 180.65 mg kg-1(a drop of 53% with depletion factor of 0.47) and non-exchangeable potassium from 43.05 (a drop of 8% with depletion factor of 0.92) to 114.65 mg kg-1 (a drop of 19% with depletion factor of 0.81). Isotherm studies showed that the uptake of potassium in gardened series were more than virgin soils. The highest adsorption values were observed in VerticEndoaquepts (gottape) subgroup.In this series of soil, amount of available k (potassium soluble + exchangeable K) and expandable clay increased by long-term horticultural practices which can be effective in increasing K buffering capacity.
Conclusion: long-term horticultural practices decreased K in soil solution and potassium adsorption ratio. The main reasons for the decline of soluble K can be explained by possible movement of K into the depths, dense cultivation and harvesting crops as well as high levels of calcium and magnesium in irrigation water of study area.In comparison with adjoining virgin soils, horticultural practices caused significant decrease in the amount of exchangeable K, exchangeable K percentage (EPP) and available K. The most important cause of reduced exchangeable potassium may be related toK uptake by apple trees (The study area is generally under the apple orchard user) which had the great need for K. Consequently, due to lack of fertilizers application and agricultural practices,the amount of available K declined in soils about 80percent. On the other hand, In the Non-exchangeable K amount with long-term horticultural practices non- significant reduction occurred. Since the amount of exchangeable and available k in these soils is high, it seems to be enough to satisfy the needs of the regional products.
Research Article
shahrzad karami; mehdi zarei; jafar yasrebi; najafali karimian; s.Ali Akbar Moosavi
Abstract
Introduction: Heavy metals such as cadmium (Cd) are found naturally in soils, but their amount can be changed by human activities. The study of the uptake and accumulation of heavy metals by plants is done in order to prevent their threats on human and animal’s health.Cadmium is a toxic element for ...
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Introduction: Heavy metals such as cadmium (Cd) are found naturally in soils, but their amount can be changed by human activities. The study of the uptake and accumulation of heavy metals by plants is done in order to prevent their threats on human and animal’s health.Cadmium is a toxic element for living organisms. Cadmium competes with many of nutrients to be absorbed by the plant and interferes with their biological roles. Water stress affects the cell structure and the food is diverted from its normal metabolic pathway. It also reduces the availability and uptake of nutrients by the plant. One reason for the reduction of plant growth under drought stress is the accumulation of ethylene in plants. There are ways to mitigate the negative effects of drought stress that one of which is the use of Plant Growth Promoting Rhizobacteria(PGPRs) to increasing the availability of nutrients. Soil beneficial bacteria play an important role in the biological cycles and have been used to increase plant health and soil fertility over the past few decades.The aim of this study was to investigate theeffect of PGPRson the concentration and uptake of macro nutrients by corn in a Cd-contaminated calcareous soil under drought stress.
Materials and Methods: A greenhouse factorial experiment was conducted in a completely randomized design with three replications. The treatments were two levels of bacteria (with and without bacteria), four levels of Cd (5, 10, 20, and 40 mg kg-1), and three levels of drought stress (without stress, 80, and 65% of field capacity). The pots were filled with 3 kg of treated soil. Cd was treated as its sulfate salt in amounts of 5, 10, 20, and 40 mg kg-1. The soil was mixed uniformly with 150 mg N kg-1 as urea, 20 mg P kg-1 as Ca (H2PO4)2, 5 mg Fe kg-1 as Fe-EDDHA and 10, 10 and 2.5 mg Zn, Mn and Cu kg-1, respectively as their sulfate salt in order to meet plant needs for these nutrients. Six seeds of Zea mays (var. HIDO) were planted at each pot. Each seed of maize was inoculated with 2 mL (1×108 colony-forming units (cfu) mL-1) of Micrococcus yunnanensis (a gram positive bacterium with the ability of production of sidrophore and phosphate dissolving characteristic). Each pot was irrigated daily with distilled water to near field capacity by weight, until 15 days after corn planting. Then corn was thinned to 3 plants per pot and irrigation was started with different levels of drought stress (without stress (F.C), 80, and 65% of field capacity) by weight. At harvest (8 weeks after planting), the aerial parts of the plants was cut at the soil surface. The harvested plants were washed with distilled water, dried to a constant weight at 65C. Representative samples were dry-ashed and analyzed for macro nutrients.
Results and Discussion: The results indicated that the inoculation of bacteria increased shoot dry weight (DW) and total uptake of nitrogen (N), phosphorus (P), and potassium (K). Drought stress decreased DW, total uptake of N, P, and K, concentrations of N and K in corn shoots, and concentration of K in the soil. The application of biological fertilizers, such as plant growth promoting rhizobacteria, increase plant growth through increasing microorganism’s activities and population in the soil and so increase macro nutrients uptake by the plant. Phosphate solubilizing rhizobacteria increase plant growth and phosphate availability with production of organic acids and secretion of phosphatase enzymes or protons and conversion of non-soluble phosphates (either organic or inorganic phosphates) to the forms that are more available for the plants and improve their nutrition and increase their growth. Drought stress decreases Dry Matter Weight(DMW) through decreasing relative humidity of the air of plant growth environment and increases evaporation, transpiration, plant temperature and light intensity of the sun. It prevents normal development of roots, water uptake, and plant growth by reducing the moisture content of the soil. It also decreases uptake and availability of Phosphorus in arid soils because plant growth and root activity in arid soils are lower from those of wetlands and as phosphorus is immobile in the soil, its uptake by the plant will decrease. N concentration of plants will increase drought stress conditions through rapid accumulation of amino acids that had not been converted into protein. The combined effects of drought stress and inoculation of bacteria on decomposition of silicates, cause the release of nutrients such as potassium. Increasing levels of cadmium in both cases, with and without bacterial inoculation, decreased DW, N and K uptake by corn because of its toxicity and its competition and interactions with these nutrients.
Conclusion: The inoculation of bacteria mitigated the negative effects of drought stress and cadmium contamination by increasing dry weight of corn and increasing uptake of macronutrients by aerial parts. Drought stress in both cases (with and without bacterial inoculation) reduced shoot dry weight, total uptake of macro nutrients, N and K concentrations in corn shoots and post-harvest potassium concentration in the soil. Cadmium levels decreased shoot dry matter and N and K uptake by the plant. The use of bacteria was more effective at low cadmium and drought stress levels.
Research Article
zohreh mosleh; mohammad hassan salehi; azam jafari; Isa Esfandiarpoor Borujeni
Abstract
Introduction: Soil classification generally aims to establish a taxonomy based on breaking the soil continuum into homogeneous groups that can highlight the essential differences in soil properties and functions between classes.The two most widely used modern soil classification schemes are Soil Taxonomy ...
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Introduction: Soil classification generally aims to establish a taxonomy based on breaking the soil continuum into homogeneous groups that can highlight the essential differences in soil properties and functions between classes.The two most widely used modern soil classification schemes are Soil Taxonomy (ST) and World Reference Base for Soil Resources (WRB).With the development of computers and technology, digital and quantitative approaches have been developed. These new techniques that include the spatial prediction of soil properties or classes, relies on finding the relationships between soil and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. These approaches are commonly referred to as digital soil mapping (DSM) (14). A key component of any DSM mapping activity is the method used to define the relationship between soil observation and auxiliary information (4). Several types of machine learning approaches have been applied for digital soil mapping of soil classes, such as logistic and multinomial logistic regressions (10,12), random forests (15), neural networks (3,13) and classification trees (22,4). Many decisions about the soil use and management are based on the soil differences that cannot be captured by higher taxonomic levels (i.e., order, suborder and great group) (4). In low relief areas such as plains, it is expected that the soil forming factors are more homogenous and auxiliary information explaining soil forming factors may have low variation and cannot show the soil variability.
Materials and Methods: The study area is located in the Shahrekord plain of Chaharmahal-Va-Bakhtiari province. According tothe semi-detailed soil survey (16), 120 pedons with approximate distance of 750 m were excavated and described according to the “field book for describing and sampling soils” (19). Soil samples were taken from different genetic horizons, air dried and grounded. Soil physicochemical properties were determined. Based on the pedon description and soil analytical data, pedons were classified according to the ST (20) and WRB (11). Terrain attributes, remote sensing indices, geology, soil and geomorphology map were considered as auxiliary information. All of the auxiliary information were projected onto the same reference system (WGS 84 UTM 39N) and resampled to 50×50 m according to the suggested resolution for digital soil maps (14). Four modeling techniques (multinomial logistic regression (MLR), artificial neural networks (ANNs), boosted regression tree (BRT) and random forest (RF)) were used for each taxonomic level to identify the relationship between soil classes and auxiliary information in each classification system. The models were trained with 80 percent of the data (i.e., 96 pedons) and their validation was tested by remaining 20 percent of the dataset (i.e., 24 pedons) that split randomly. The accuracy of the predicted soil classes was determined by using overall accuracy and Brier score.For each classification system, the model with the highest OA and the lowest BS values were considered as the most accurate model for each taxonomic level.
Results and Discussion: The results confirmed that ST showedmore accessory soil properties compared to WRB. The ST described the cation-exchange activity, soil depth classes, temperature and moisture regime. The different models had the same ability for prediction of soil classes across all taxonomic levels based on ST. Among the studied models, MLR had the highest performance to predict soil classes based on WRB. For all the studied models and both classification system, OA values showed a decreasing trend with increasing the taxonomic levels. Predicted soil classes based on the ST had the higher accuracy. Different models selected different auxiliary information to predict soil classes. For most of the models and both classification systems, the terrain attributes were the most important auxiliary information at each taxonomic level.
Conclusion: Results demonstrated that although ST showed more accessory soil properties compared to WRB, the DSM approaches have not enough accuracy for prediction of the soil classes at lower taxonomic levels. More investigations are needed in this issue to make a firm conclusion whether DSM approaches are appropriate for prediction of soil classes at the levels that are important for soil management. Prediction accuracy of soil classes can be influenced by the target taxonomic level and classification system, soil spatial variability in the study area, soil diversity, sampling density and the type of auxiliary information.
Research Article
shahrokh fatehi; jahangard mohammadi; Mohammad Hassan Salehi; aziz momeni; Norair Toomanian; Azam Jafari
Abstract
Introduction: Spatial scale is a major concept in many sciences concerned with human activities and physical, chemical and biological processes occurring at the earth’s surface. Many environmental problems such as the impact of climate change on ecosystems, food, water and soil security requires not ...
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Introduction: Spatial scale is a major concept in many sciences concerned with human activities and physical, chemical and biological processes occurring at the earth’s surface. Many environmental problems such as the impact of climate change on ecosystems, food, water and soil security requires not only an understanding of how processes operates at different scales and how they can be linked across scales but also gathering more information at finer spatial resolution. This paper presents results of different downscaling techniques taking soil organic matter data as one of the main and basic environmental piece of information in Mereksubcatchment (covered about 24000 ha) located in Kermanshah province. Techniques include direct model and point sampling under generalized linear model, regression tree and artificial neural networks. Model performances with respect to different indices were compared.
Materials and Methods: legacy soil data is used in this research, 320 observation points were randomly selected. Soil samples were collected from 0-30 cm of the soil surface layer in 2008 year. After preliminary data processing and point pattern analysis, spatial structure information of organic carbon determined using variography. Then, the support point data were converted to block support of 50 m by using block ordinary kriging. Covariates obtained from three resources including digital elevation model, TM Landsat imagery and legacy polygon maps. 23 relief parameters were derived from digital elevation model with 10m × 10m grid-cell resolution. Environmental information obtained from Landsat imagery included, clay index, normalized difference vegetation index, grain size index. The image data were re-sampled from its original spatial resolution of 30*30m to resolution of 10m*10m. Geomorphology, lithology and land use maps were also included in modelling process as categorical auxiliary variables. All auxiliary variables aggregated to 50*50 grid resolutions using mean filtering. In this study Direct and point sampling downscaling techniques were used under different statistical and data mining algorithms, including generalized linear models, regression trees and artificial neural networks. The direct approach was implemented here using generalized linear models, regression trees and artificial neural networks in following three steps, (i) creating the spatial resolution of 50m*50m averaged over 10m*10m grid resolution environmental variables within each coarse grid resolution, (ii) establishing relationships between these coarse grid resolutions of 50m*50m environmental variables and soil organic carbon using GLMs, regression tree and neural networks and (iii) using parameter values gained in step 2 in combination with the original 10m*10mgrid resolution environmental variables to produce predictions of soil organic carbon with10m*10m grid resolution. In point sampling approach, within each coarse resolution (50m*50m), a fixed number of fine grid resolution (10m*10m) were randomly selected to calibrate models at high resolution. In this study, 5 fine grid resolutions (20% fine grid cell within each coarse grid cell) randomlywere sampled at. Then, each selected point overlied on an underlying fine-resolution grid and recorded its environmental variables and averaged fine grid resolution (10m*10m) within their corresponding coarse grid resolution (50m*50m). To calibrate model parameters, these averaged environmental variables were used. The calibrated parameters applied to fine-resolution environmental data in order to predict soil organic carbon at spatial resolution of 10m*10m. The prediction accuracy of the resulting soil organic carbon maps was evaluated using a K-fold validation approach. For this purpose, the entire dataset was divided into calibration (n = 240) and validation (n = 80) datasets four times at random. Prediction of soil organic carbon using calibration datasets and their validation was conducted for each split, and the average validation indices are reported here. The obtained values of the observed and predicted SOC were interpreted by calculating Adjusted R2 and the root mean square error (RMSE).
Results and Discussion: Point pattern analysis showed the sampling design is, generally, representative relative to geographical space .A semi-variogram was used to drive the spatial structure information of soil organic carbon. We used an exponential model to map soil organic carbon using block kriging. Grid resolution block kriging map was 50m*50m. Since the distribution of organic carbon variable and covariates were normal or close to normal for run generalized linear models selected Gaussian families and identity link function. The validation results of this model in point sampling was slightly (Adjusted R2=0.57 and RMSE=0.22) better than the direct method (Adjusted R2 =0.47 and RMSE=0.26).The results of modelling using regression tree in point sampling approach (Adjusted R2 =0.57and RMSE=0.22) is very close to the direct method (Adjusted R2 =0.57 and RMSE=0.23).In implementation of neural networks, the combination of the number of neurons and learning rate for direct downscaling method were obtained 10 and 0.10, respectively and for point sampling downscaling method were, 20 and 0.1 The results of validation obtained from the implementation of this model in point sampling approach (Adjusted R2 =0.45 and RMSE=0.27) is very close to the direct method (Adjusted R2 =0.47 and RMSE=0.28).Validation results indicated that in both downscaling approaches, regression tree (Adjusted R2=0.57, root mean square root (RMSE) =0.22-0.23) has higher accuracy and efficiency better than generalized linear models (Adjusted R2=0.49-0.57, RMSE=0.22-0.26) and neural network (Adjusted R2=0.45-0.47, RMSE=0.27-0.28).
Conclusion: In general, the results showed that the efficiency and accuracy of the sampling point approach is slightly better than the direct approach. Validation results indicated that in both downscaling approaches, regression tree has higher accuracy and performed better than neural network and generalized linear models. However, it is required to perform more research on the different ways of downscaling digital soil maps in the future.
Research Article
Ehsan Sayad; Shaieste Gholami; Mohammad Reza Askarpour
Abstract
Introduction: Sustainability and maintenance of riparian vegetation or restoring of degraded sites is critical to sustain inherent ecosystem function and values. Description of patterns in species assemblages and diversity is an essential step before generating hypotheses in functional ecology. If we ...
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Introduction: Sustainability and maintenance of riparian vegetation or restoring of degraded sites is critical to sustain inherent ecosystem function and values. Description of patterns in species assemblages and diversity is an essential step before generating hypotheses in functional ecology. If we want to have information about ecosystem function, soil biodiversity is best considered by focusing on the groups of soil organisms that play major roles in ecosystem functioning when exploring links with provision of ecosystem services. Information about the spatial pattern of soil biodiversity at the regional scale is limited though required, e.g. for understanding regional scale effects of biodiversity on ecosystem processes. The practical consequences of these findings are useful for sustainable management of soils and in monitoring soil quality. Soil macrofauna play significant, but largely ignored roles in the delivery of ecosystem services by soils at plot and landscape scales. One main reason responsible for the absence of information about biodiversity at regional scale is the lack of adequate methods for sampling and analyzing data at this dimension. An adequate approach for the analysis of spatial patterns is a transect study in which samples are taken in a certain order and with a certain distance between samples. Geostatistics provide descriptive tools such as variogram to characterize the spatial pattern of continuous and categorical soil attributes. This method allows assessment of consistency of spatial patterns as well as the scale at which they are expressed. This study was conducted to analyze spatial patterns of soil macrofauna in relation to tree canopy in the riparian forest landscape of Maroon.
Materilas and Methods: The study was carried out in the Maroon riparian forest of the southeasternIran (30o 38/- 30 o 39/ N and 50 o 9/- 50 o 10/ E). The climate of the study area is semi-arid. Average yearly rainfall is about 350.04 mm with a mean temperature of 24.5oc. Plant cover, mainly comprises Populus euphratica Olivie and Tamarix arceuthoides Bge and Lycium shawii Roemer & Schultes. Soil macrofauna were sampled using 175 sampling point along parallel transects (perpendicular to the river). The distance between transects was 100m. We considered distance between samples as 50 m. tree canopy were measured in 5* 5 plots. soil macrofauna were extracted from 50 cm×50 cm×10 cm soil monolith by hand-sorting procedure. All soil macrofauna were identified to family level. Evenness (Sheldon index), richness (Menhinich index) and diversity (Shannon H’ index) by using PAST version 1.39, were determined in each sample. Classical statistical parameters, i.e. mean, standard deviation, coefficient of variation, minimum and maximum, were calculated using SPSS17 software. For analysis of the relationship between Soil macrofauna diversity indices and tree canopy (Total canopy, Populous canopy, Tamarix canopy and Serim canopy) we calculated the correlation among soil properties and macrofauna using the Pearson correlation coefficient. Next, to determining the spatial structure, we calculated the semivariances. Semivariance quantifies the spatial dependence of spatially ordered variable values. In order to gather information about the spatial connection between any two variables, and to compare the similarity of their spatial structure patterns, cross-variograms were constructed. Cross-variograms are plots of cross-semivariance against the lag distance.
Results and Discussion: Soil macrofauna communities were dominated by earthworm, diplopods, coleoptera, gastropoda, araneae, and insect larvae. Correlation analysis of soil macrofauna and tree canopy indicated weak relationships between them. Weak, but significant relationships were found between macrofauna diversity, evenness, richness and total canopy, Populous canopy and Tamarix canopy (positive). Macrofauna indices and tree canopy(excepted Tamarix canopy) were spatially structured; the variograms revealed the presence of spatial autocorrelation. The variograms of variables especially tree canopy, were characterized by relatively large nugget values, which can be explained by sampling error, short range variability, random and inherent variability.Soil macrofauna diversity indices and tree canopy were moderately spatially dependent. Spatial similarity between variables, indicating potential relationships between macrofauna and tree canopy, was evaluated by cross-variograms for pairs of macrofauna indices and measured tree canopy. According to the cross-variograms, using RSS as criterion for model performance, macrofauna diversity were spatially closely related to total tree canopy, Populus canopy. Spatial distribution of soil macrofauna may be influenced by factors like gradients in soil properties and vegetation cover structure. These factors together with intrinsic population processes constitute proximate controlling factors of population structure.
Conclusion: The relationship between macrofauna indices and tree canopy was further explored by means of spatial analyses. Macrofauna indices and tree canopy (excepted Tamarix canopy) were spatially structured. Tree canopy distribution is important for the spatial variability and structure of Soil macrofauna diversity.
Research Article
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.
Research Article
naser boroumand; saleh sanjari
Abstract
Introduction: Soil and geomorphology are closely related to each other. That is why considering geomorphic concepts in soil genesis and classification studies may cause a better understanding of soil genesis processes. Paleosols with argillic horizons were investigated on stable pediment surfaces in ...
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Introduction: Soil and geomorphology are closely related to each other. That is why considering geomorphic concepts in soil genesis and classification studies may cause a better understanding of soil genesis processes. Paleosols with argillic horizons were investigated on stable pediment surfaces in Jiroft area, central Iran, by Sanjari et al. (2011). They found that secondary gypsum and calcium carbonate were accumulated in mantled pediments, but moving down the slope toward lowlands, salts more soluble than gypsum have been accumulated.
Clay mineralogy in soil researches helps to better studying soil genesis and development. A quantitative and qualitative study of clay minerals together with their structural composition provides valuable data on the absorption, fixation, and desorption of different cations in soils. Smectite, chlorite, illite, vermiculite, kaolinite, palygorskite, and sepiolite were reported as dominant clay minerals found in arid and semi-arid areas. The objectives of the present study are to evaluate the clay mineralogy of Jabalbarez-Jiroft soils on different geomorphic surfaces.
Materials and Methods: The study area was located in Jabalbarez, 200 Km south Kerman, Central Iran. Fig. 1 showed the exact location of study area. Soil temperature and moisture regimes of the area were thermic and aridic, respectively. Hill, rock pediment, mantled pediment and piedmont alluvial plain landforms were identified, using aerial photo interpretation, topography and geological map observation, in addition to detailed field works. Air-dried soil samples were crushed and passed through a 2-mm sieve. Routine physicochemical analyses wereperformed on the samples. Undisturbed soil samples from the Bt horizon of pedons 4, 5 and 6 were chosen for micromorphology investigations. Beside, eight samples including A and C2 horizons of pedon 1, A and Bt horizon of pedon 3, Bt and Bw horizons of pedon 4, and Bt and C horizon of pedon 5 were selected for clay mineralogy.
Results and Discussion: Argillic horizon found in mantled pediment and piedmont alluvial plain surfaces and stable hill, respectively. In thin horizons coating of clay were observed. Pedofeatures formed in this geomorphic surface, seemed to have been buried in the soil, due to the favorable conditions in terms of the time factor and the presence of moisture in the past. Fig. 2 showed clay coatings in the Bt horizon of pedons 4,5 and 6. The presence of argillic horizons in the arid climate of the research area is attributed to a more humid paleoclimate, which was also reported by Farpoor et al. (2002), Khademi and Mermut (2003), and Sanjari et al. (2011) in Rafsanjan, Isfahan and Jiroft, central Iran, respectively. Clay minerals illite, smectite, chlorite and kaolinite were identified by using X-ray diffractometer. Similar results were also obtained by Sanjari et al. (2011) in the Jiroft area. Kaolinite and illite in soils of arid and semi-arid environments of Iran have been reported with an inherited origin (Khormali and Abtahi, 2003; Sanjari et al., 2011). As the environmental conditions are not favorable for the pedogenic formation of such minerals in soils of this study area , it is proposed that they might be inherited from their parent material. Just as previously stated by other researchers that the origin of the kaolinite minerals in the dry climate regionsis due to itsinheritance from parent materials (Farpoor et al., 2002; Khormali and Abtahi, 2003). The dominant of smectite minerals in soils on stable geomorphic surfaces ofhills and mantled pediment can be cause of stable level and more moisture content in the past and the present, which may be resulted to smectite formation from illite and chlorite transformation. Also, chlorite minerals on stable surface of mantled pediment were not observed. High amount of leaching, low pH level (
Research Article
Mohammad Reza Khaleghi; Vahid Gholami; Ghorbanali Khodabakhshi
Abstract
Introduction: In the last century, dams have constructed with the objective of water supplies for agriculture, drinking water and industry. However, the results from the performance review of dams show adverse effects on the downstream environment and the availability of water resources. The purpose ...
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Introduction: In the last century, dams have constructed with the objective of water supplies for agriculture, drinking water and industry. However, the results from the performance review of dams show adverse effects on the downstream environment and the availability of water resources. The purpose of the Chashm dam construction on the TalarRiver's tributaries is the water supply for Semnan city.
Materials and Methods: This study was conducted in TalarRiver watershed. TalarRiveroriginatesfrom AlborzMountains in Mazandaran province, in the southern Caspian Sea basin, in north of Iran and flows parallel with the Firouzkooh-Ghaemshahr road and it arrives to the Caspian beach area in the Malek Kala village. In order to supply the water requirements of Semnan city, the construction of Chashm dam on the TalarRiver's tributaries placed on the agenda of the Ministry of Energy. However, because of the uncontrolled exploitation of agricultural streams and invasion of privacy riverbed, the TalarRiver has acute and critical conditions from the point of hydrologic and environmental. To study the hydrological impacts of Chashm dam, Talar watershed was considered with an area of approximately 1057 square kilometers of the Pole Sefid gauging station using a rainfall-runoff model.
Results and Discussion: Simulation of the study area hydrological behavior shows that the Chashm Dam average water discharge is near to 8.6 million m3. This figure will be significant changes during wet and droughtperiods. The minimum and maximum monthly discharge of the Chashm Dam watershed in August and February is equal to 0.31 and 0.55 m3/s respectively. The minimum and maximum monthly water demand in turn in October and August is equal to 0.015 and 0.4 m3/s respectively and this shows that the river discharge in June is lower than the downstream water demand. Based on confirmed studies of the Kamandab Consulting Engineers, drinking water requirement of Semnan province, water rights users' requirement and downstream environmental requirements are 4.54, 2.164 and 2.448 million m3, respectively. This is despite the fact that the volume of annual input water is slightly lower than this figure in normal.
Conclusion: Simulation of the study area hydrological behavior shows that the Chashm Dam average water discharge is near to 8.6 million m3. This figure will be significant changes during wet and drought periods. The minimum and maximum monthly discharge of the Chashm Dam watershed in August and February is equal to 0.31 and 0.55 m3/s respectively. The minimum and maximum monthly water demand in turn in October and August is equal to 0.015 and 0.4 m3/s respectively, and this shows that the river discharge in June is lower than the downstream water demand. Based on confirmed studies of the Kamandab Consulting Engineers, drinking water requirement of Semnan province, water rights users' requirement and downstream environmental requirements are 4.54, 2.164 and 2.448 million m3, respectively. This is despite the fact that the volume of annual input water is slightly lower than this figure in normal. In addition, the Chashm Dam area is about 110 hectares and given the minimum annual actual evaporation equal to 700 mm, about seven hundred thousand cubic meters of water stored in the reservoir will be lost. Due to the simultaneous occurrence of the maximum water requirement, maximum evaporation and a minimum of water inlet to the Chashm Dam reservoir in warm seasons, it seemsthat, it is not possible to provide needs based on these studies and no doubt, in the case of water supply in Semnan province, we have to stop the flow of the river in downstream of the dam. The results of this study suggest that on many rivers large headwater dams have reduced the frequency and duration of floodplain inundation downstream and these changes lead to changes in downstream ecosystems. The results from the simulation and analysis of the Chashm Dam in downstream are as follows: a) stop of the river flow in downstream of the dam site, b) the sharp decline in river discharge in minimum (varied) flows, c) reduce in the rate and volume of maximum flows, d) changes in the hydrological regime of the river such as base flow, flow stop, the frequency of the river full section and competency which will make dramatic changes in the morphology of the river and downstream ecosystems. Note that is not verified by modeling and forecasting studies, is how to manage the reservoir. The amount of water stored in the reservoir and discharge to downstream is directly a function of the reservoir management.
Research Article
Alireza Moghaddam; Majid Montaseri; Hossein Rezaei
Abstract
Introduction: The reservoir operation is a multi-objective optimization problem with large-scale which consider reliability and the needs of hydrology, energy, agriculture and the environment. There were not the any algorithms with this ability which consider all the above-mentioned demands until now. ...
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Introduction: The reservoir operation is a multi-objective optimization problem with large-scale which consider reliability and the needs of hydrology, energy, agriculture and the environment. There were not the any algorithms with this ability which consider all the above-mentioned demands until now. Almost the existing algorithms usually solve a simple form of the problem for their limitations. In the recent decay the application of meta-heuristic algorithms were introduced into the water resources problem to overcome on some complexity, such as non-linear, non-convex and description of these problems which limited the mathematical optimization methods. In this paper presented a Simple Modified Particle Swarm Optimization Algorithm (SMPSO) with applying a new factor in Particle Swarm Optimization (PSO) algorithm. Then a new suggested hybrid method which called HGAPSO developed based on combining with Genetic algorithm (GA). In the end, the performance of GA, MPSO and HGAPSO algorithms on the reservoir operation problem is investigated with considering water supplying as objective function in a period of 60 months according to inflow data.
Materials and Methods: The GA is one of the newer programming methods which use of the theory of evolution and survival in biology and genetics principles. GA has been developed as an effective method in optimization problems which doesn’t have the limitation of classical methods. The SMPSO algorithm is the member of swarm intelligence methods that a solution is a population of birds which know as a particle. In this collection, the birds have the individual artificial intelligence and develop the social behavior and their coordinate movement toward a specific destination. The goal of this process is the communication between individual intelligence with social interaction. The new modify factor in SMPSO makes to improve the speed of convergence in optimal answer. The HGAPSO is a suggested combination of GA and SMPSO to remove the limitation of GA and SMPSO. In this paper the initial population which caused randomly in all metha-heuristic algorithms consider fixing for the three mentioned algorithms because the elimination of random effect in initial population may make increase or decrease the convergence speed. The objective function is the minimum sum of the difference between the downstream demand reservoir and system release in the period time. Also the constrains problem is continuity equation, minimum and maximum of reservoir storage and system release.
Results and Discussion: The performance of GA, SMPSO and HGAPSO evaluated based on the objective function for Dez reservoir in the south east of Iran. In this study the programming of GA, SMPSO and HGAPSO was written in Matlab software and then was run for the time period with a maximum of 400 iterations. The minimum of the objective function for GA, SMPSO and HGAPSO was obtained 1.19, 1.05 and 0.9 respectively, and the maximum of objective function was calculated 1.66, 1.26 and 1.10 respectively. The results showed that the minimum of the objective function by HGAPSO was estimated 32 and 16 percent lower than the counts which calculated by GA and SMPSO. The standard deviation of SMPSO and HGAPSO were near to each other and less than GA which shows the diversity between solutions for SMPSO and HGAPSO are much less than GA. Also the HGAPSO had the better performance rather than previous method in terms of minimum, maximum, average and standard deviation. The convergence speed of HGAPSO for finding the optimal solution is much faster of GA and SMPSO. The difference graphs between system release and monthly demand in HGAPSO is much less than GA and SMPSO. Also the storage calculated in HGAPSO and SMPSO is highly close to each other but in GA method the storage calculated more in the first and second years.
Conclusions: The convergence speed in finding the optimal solution in SMPSO in more than GA but in other hand the probability of caughting in local optima for SMPSO is great whereas GA can make the diverse optimal solutions. For this reason, in this paper was trying to improve the performance of the GA and SMPSO and remove their disadvantage based on combining them and presenting a new hybrid method. The results showed the HGAPSO method which presented in this paper to use without any complexity and additional operator to GA and SMPSO has the ability to use for reservoir operation with large-scale. In addition it is suggested which the HGAPSO apply to other water resources engineering problems.
Research Article
maryam mohammadi; farzad hassanpour; Majid azizpour pirsaraie
Abstract
Introduction: Poor performance of irrigation and drainage networks causes to reduce the transfer and distribution throughputs and in result comes useless water and makes too much consumption in forming. A significant portion of water losses in irrigation and drainage networksis related to transmission ...
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Introduction: Poor performance of irrigation and drainage networks causes to reduce the transfer and distribution throughputs and in result comes useless water and makes too much consumption in forming. A significant portion of water losses in irrigation and drainage networksis related to transmission and distribution. Therefor more consideration in thrirrigation network management, improve irrigation efficiency and also the exploitation of water resources, especially in the agricultural sector is necessary. Controlling and adjusting structures of water level in the direction of drainage and irrigation canals can influence on increasing of throughput and decrease the use of water. So, right choosing and recognition of the deficiencies of these structures helps carry up the throughput of the networks and prevents to waste water. It is hard to solve equations of water flow in canals and related institutions by using analytic methods. For this reason, this research was done with HEC-RAS hydraulical model in the main channelof irrigation and drainage network of Sistan plain.
Materials and Methods: Sistan plain is located in southeastern of Iran with good potential for agricultural production because of the alluvial sediments from Hirmand River. 23820 ha of the Sistan plain is covered by 5 blocksof the Shibab irrigation and drainage network. While Sistan’sShibab irrigation network efficiency is low, HEC-RAS Hydraulics model in unsteady condition was performed to control and adjust this network’s main canal in approximately 19 Km length. In this research, the evaluation model in the canal was performed for more suitable intakingwater in the quadruple order 2 canals . So, the existing structure’s operation was analyzed on controlling structures in management and lack of management situations.This research was assessed during a 15-day impounding period using hydraulic model of HEC-RAS with the aim of performance and operation evaluation of existing structures on the Shibab main canal. HEC-RAS model was prepared by United States army corps of engineers which is developed by the hydrologicengineering center.HEC-RAS analyzes river system and runs under the Windows operating system. This software package is of hydraulic analysis program series, where the user communicates with the system via a graphical user interface (GUI). The system is capable of performing steady and unsteady flow water surfaceprofile calculations. HEC-RAS software is designed to perform one dimensional hydraulic calculation for a full network of natural and synthetic channels. Visits were made before and after the beginning of irrigation, and during the Operation, in order to record the data of the flow and observe the way of utilization of canal, and existing structures. Then, the model was calibrated on the basis of depth and discharge measurement and simulation data in real condition of operation for 10 days impoundment during 21 to 30 April, and the Statistical parameter values:RMSE, EF, MBEand R2 were calculated. Then the objective functionwas evaluatedusingoperational performance indexes of adequacy, efficiency, equity and reliability of Molden and Gates regarding to HEC-RAS simulation results in unsteady condition.
Results and Discussion: According to the simulation results in existing condition,theerror of delivery dischargeis equal to 0.54 while applying the management onthe adjustment structure of irrigation networkdeclined theerror to 0.42. By the canal routstructuremanagement in HEC-RAS model, on the basis of proposed operation option, according to existing operation condition, delivery discharge loss in comparison to the total discharge of the network 0.12 value decreases.Based on the simulation results, the mean percentage of improvementin performance indexes of adequacy,efficiency, equity and reliability, as well as objective functionofdelivery discharge are equal to 19.7, 20.90, 66.07, 65.24and54.81. Therefore based on simulation results of different scenarios and investigation of the effective factors onto the flow, onthe forms of charts and tables show that without management on controlling structures, it isn`t possible to appropriate of flow rate onto second class canals and traditional streams branched out main canal and also streams branched out second class canals, properly.
Conclusion: The results show that the model of HEC-RAS is proper for hydraulic simulation of main canal in the irrigation and drainage network of Sistan plain. Based on the simulation results of different scenarios of this research, the mostimprovements intheobjective functionare allocated toequity and reliability indexes in the Shibab main canal with the proposed management method.
Research Article
majid montaseri; Negar Rasouli Majd; Javad Behmanesh; Hossein Rezaei
Abstract
Introduction: The water footprint index as a complete indicator represents the actual used water in agriculture based on the climate condition, the amount of crop production, the people consumption pattern, the agriculture practices and water efficiency in any region. The water footprint in agricultural ...
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Introduction: The water footprint index as a complete indicator represents the actual used water in agriculture based on the climate condition, the amount of crop production, the people consumption pattern, the agriculture practices and water efficiency in any region. The water footprint in agricultural products is divided to three components, including green, blue and gray water footprint. Green water footprint is rainwater stored in soil profile and on vegetation. Blue water refers to water in rivers, lakes and aquifers which is used for irrigation purposes. Gray water footprint refers to define as the volume of contaminated water. The water footprint in arid and semiarid regions with high water requirement for plants and limited fresh water resources has considerable importance and key role in the planning and utilization of limited water resources in these regions. On the other hand, increasing the temperature and decreasing the rainfall due to climate change, are two agents which affect arid and semiarid regions. Therefore, in this research the water footprint of agriculturalcrop production in Urmia Lake basin, with application of climate change for planning, stable operating and crop pattern optimizing, was evaluated to reduce agricultural water consumption and help supplying water rights of Urmia Lake.
Materials and Methods:Urmia Lake basin, as one of the main sextet basins in Iran, is located in the North West of Iran and includes large sections of West Azerbaijan, East Azerbaijan and Kurdistan areas. Thirteen major rivers are responsible to drain surface streams in Urmia Lake basin and these rivers after supplying agriculture and drinking water and residential areas in the flow path, are evacuated to the Lake. Today because of non-observance of sustainable development concept, increasing water use in different parts and climate change phenomena in Urmia Lake basin the hydrologic balance was perturbed, and Urmia Lake has been lost 90% of its volume and has a critical condition. Therefore, planning, managing and optimizing utilization of water resources in the basin have a high research priority and this requires the concentration on the consumption of water resources. In this study five major products including, wheat, sugar beet, tomato, alfalfa and corn, were studied. For this purpose, seven synoptic meteorological station data including,Salmas, Urmia, Mahabad, Takab, Tabriz, Maragheh and Sarab were used to calibrate the downscaling atmospheric-ocean general circulation model LARS.WG5 and forecast meteorological data in the future periods time (2011-2030) and (2046-2065) with the A2 scenario.The reason to selectA2 scenario was the most critical situation for the mentioned scenario. Then the obtained data were used to estimate the water requirement and water footprint of mentioned plants separately blue and green water footprint in the future periods.
Results and Discussion:The resultsof themeteorological data prediction showed thatall synoptic stations except for Tabriz station the average annual predicted rainfallvalues had the deviationfromhistoricalvalues.The mentioneddeviation in the south (Tekab, Mahabad) and West (Urmia, Salmas) ofUrmia lake basin will showincreaseanddecrease in theannual rainfallin the future, respectively.Moreover,the average annual of predicted temperature values for all studied stations showed that the temperature will increase about1°Cduring2011-2030 period and 2°C during 2046-2065 period. Potential evapotranspiration, as another important meteorological parameter has essentialrole in the estimation of crop water requirements which will be slightly affected by climate change phenomena and it will increase in the summer. The results of agricultural products water footprint show that the maximum amount of green water footprint in all studied stations was related to wheat and alfalfa, and this water footprint depend on the time and growth period. For corn, tomatoandsugar beetproducts the ratio of blue and green water footprint is greater 9. By comparing the water footprint of products it can be seen that in Urmia, Salmas and Tekab stations water footprint is decreased with decreasing rainfall and this decrease during 2065 – 2045 periods is higher than 2030 – 2011 periods.
Conclusions: According to the results, annual precipitation in southern and western regions of the Lake Urmia basin will be increased and decreased, respectively in the future periods. However, increasing approximately one Celsius degree in temperature is expected for each of the periods all over the basin. In addition,the results showed that the amount of potential evapotranspiration will be increased in the warm months (June to September) in the future periods, and agricultural water consumption pattern will be changed affected by evapotranspiration variations. In the future periods, the blue and green water footprint of most agricultural products will be increased and decreased, respectively.
Research Article
Mohammad Nazeri Tahrudi; Keivan Khalili; Javad Behmanesh; Kamran Zeinalzadeh
Abstract
Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes ...
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Introduction: Drought from the hydrological viewpoint is a continuation of the meteorological drought that cause of the lack of surface water such as rivers, lakes, reservoirs and groundwater resources. This analysis, which is generally on the surface streams, reservoirs, lakes and groundwater, takes place as hydrological drought considered and studied. So the data on the quantity of flow of the rivers in this study is of fundamental importance. This data are included, level, flow, river flow is no term (5). Overall the hydrological drought studies are focused on annual discharges, maximum annual discharge or minimum discharge period. The most importance of this analysis is periodically during the course of the analysis remains a certain threshold and subthresholdrunoff volume fraction has created. In situations where water for irrigation or water of a river without any reservoir, is not adequate, the minimum flow analysis, the most important factor to be considered (4). The aim of this study is evaluatingthe statistical distributions of drought volume rivers data from the Urmia Lake’s rivers and its return period.
Materials and Methods: Urmia Lake is a biggest and saltiest continued lake in Iran. The Lake Urmia basin is one of the most important basins in Iran region which is located in the North West of Iran. With an extent of 52700 square kilometers and an area equivalent to 3.21% of the total area of the country, This basin is located between the circuit of 35 degrees 40 minutes to 38 degrees 29 minutes north latitude and the meridian of 44 degrees 13 minutes to 47 degrees 53 minutes east longitude. In this study used the daily discharge data (m3s-1) of Urmia Lake Rivers.
Extraction of river drought volume The drought durations were extracted from the daily discharge of 13 studied stations. The first mean year was calculated for each 365 days using the Eq 1 (14).
(1) (For i=1,2,3,…,365)
That Ki is aith mean year, Yijis ith day discharge in jth year and n is number of period years. After the extraction the 1 to ndays drought duration, the years with no data were complete with Regression or interpolation methods. After the extraction, data initial evaluation (Trend, Independence and Stationarity) and completed the drought volume data, these data were fitted by the common distribution functions and select the best function based on Kolmogorov-Sminnov test. To read more information about the data initial evaluations see the NazeriTahroudi et al (15).
Log Pearson type 3 distribution Log Pearson type 3 distribution and its parameters is (7 & 12):
(2)
After selectingthe best distribution function based on Kolmogorov - Smirnov test, estimated the selected function parameter to evaluate the return period. For this purpose, there are many methods such as moments, Sundry Average method (SAM), Logarithm of applied moments observations and maximum likelihood that in this study were compared.
Results and Discussion: In this study, using daily flow data fromstations studied; the drought volume of days 1 to 60 was extracted, corrected, and completed. Before fitting the extraction drought volume river data with distribution function, the mentioned data were investigated with Wald-Wolfowitz (Independence and Stationary), Kendall (Trend) and Wilcoxon (Homogeneity) tests and the results of these tests were accepted in two significant levels of 1 and 5 percentages. Before estimatingthe Log Pearson type III parameters, first the drought volume river data were modeled by the Easy Fit software and common distribution functions and Log Pearson type III was selected by the Kolmogorov – Smirnov test as the best function. Results of two Anderson Darling and Chi Squared tests foraccurate evaluation were added. After initial evaluation of data and statistic tests, the time series of drought Volume River data of the studyarea were fitted by log Pearson type III. To estimatethe Log Pearson type III parameters used the sundry average method and to investigatethe accuracy of this method, 3 methods (moment, maximum likelihood and Logarithm of applied moment observations) were used and 4 mentioned methods for all of rivers were calculated. The most river drought relating to Gadar-Chai river with 1742 million cubic meters low volume and the lowest of it relating to Mardoq-Chai river with 68 million cubic meters low volume in 10000 year return period. After Gadar-Chai river the most low volume of discharge relating the Zarineh-rood river. Two Zarineh-rood and Gadar-Chai rivers among other rivers have a higher average discharge. Log Normal III, Gamma, Wikeby and GEV distributions have a good fitting on river flows data and no difference in investigation models that corresponded with Mosaedi et al (13) and NazeriTahroudi et al (15). The results of Grifits (7) also introduced the Wikeby distribution has a better than Beta distribution. Lee (12) also with evaluation the rainfall frequency in the study the rainfall concentration properties in Chia-Nan (Taiwan) introduced the Log Pearson type III as the best distribution function between the common distribution function. Results of Chi-Squared test in methods of parameter estimation showed that all methods are acceptable.
Conclusion: Drought occurrence can be estimated bythe analysis of historical data for different regions and using the results of predicting problems can be reduced. In this research daily river flow of Lake Urmia basin applied to calculate drought volume of rivers. Log Pearson III distribution selected among current hydrological distribution functions for fitting drought volume of rivers. Using selected distribution function and Sundry Average Moment method for estimating parameters return period of drought from 2 to 10000 years extracted. Results showed that volume of drought for Shahar-chai , Barandoz-chai, Nazlu-Chai, Mahabad-Chai, Rozeh-Chai, Gadar-chai, Simineh-rood, Zola-chai, Aji-chai, Sofi-chai, Leilan-chai and Mardoq-chay rivers in the return period of 10000 years will be 92, 125, 228, 150, 110, 1742, 90, 77, 690, 280, 65, 68 Mm3 respectively.
Research Article
rahim motalebifard
Abstract
Introduction: With 12 million tons production per year, garlic is the fourth important crop in world. In addition to its medical value, it has been used in food industry. The Hamedan province with 1900 ha cultivation area and 38 percent of production is one of the most important garlic area productions ...
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Introduction: With 12 million tons production per year, garlic is the fourth important crop in world. In addition to its medical value, it has been used in food industry. The Hamedan province with 1900 ha cultivation area and 38 percent of production is one of the most important garlic area productions in Iran. Few studies on water use and management of garlic exist in the world. Garlic is very sensitive to water deficit especially in tubers initiation and ripening periods. The current research was done because of scarce research on garlic production under water deficit condition in Iran and importance of plant nutrition and nutrients especially nitrogen on garlic production under stressful conditions. Nitrogen is necessary and important element for increasing the yield and quality of garlic. Application of nitrogen increases the growth trend of garlic such as number of leaves, leaf length and plant body. Reports have shown that garlic has high nitrogen requirement, particularly in the early stages of growth.
Materials and Methods: This study was conducted for evaluating the combined effects of nitrogen and irrigation on the yield and quality of garlic (Allium sativumL.). The study was performed as a split-block based on randomized complete blocks design with factors of irrigation at four levels (0-3(normal irrigation), 3-6 (slight water deficit), 6-9 (moderate water deficit) and 9-12 (sever water deficit) meters distance from main line source sprinkler system), nitrogen at four levels (0, 50,100 and 150 kg nitrogen per ha) using three replications and line source sprinkler irrigation system. The total water of irrigation levels was measured by boxes that were fixed in meddle of each plot. The statistical analysis of results were performed using themethod described by Hanks (1980). The chlorophyll index was measured using the chlorophyll meter 502 (Minolta, Spain). The chlorophyll a and bwas measured by the method described by Arnon (1946) and Gross (1991) in fresh leaf samples using spectrophotometer at 645 and 663 nm. Data were subjected to analysis of variance using MSTATC and SPSS softwares. Duncan’s multiple range test at p≤0.05 probability level was applied to compare the mean values of measured attributes. The Excel software (Excel software 2007, Microsoft Inc., WA, USA) was used to draw Figures.
Results and Discussion: The results showed that, the application of nitrogen significantly affected most of measured attributes. The application of 150 kg N per ha showed highest stem height (40.5 cm), dry weight of stem (5.34 g),wet weight of stem (69.5 g), chlorophyll index (49.7),chlorophyll a (9.8 mg.g-1dw) and chlorophyll b (4.04 mg.g-1dw) and increased stem height, dry and wet weight of stem, chlorophyll index and chlorophyll a and b around 7, 6, 7, 12, 22 and 36 percent, respectively. The irrigation levels significantly affected most of measured attributes similar to the nitrogen levels. The application of 409 mm irrigation water per growing season resulted to maximum stem height (41.9 cm), leaf number (7.5), dry weight of stem (5.39 g) and wet weight of stem (70.1 g), chlorophyll index (50.5) and chlorophyll a (10.2 mg.g-1dw) and chlorophyll b (4.04 mg.g-1dw). The severe water deficit (application of 138 mm irrigation water per growing season) decreased stem height, leaf numbers, dry and wet weight of stem, chlorophyll index and chlorophyll a and b about 13, 36, 12, 12, 19, 42 and 44 percent, respectively. The two way interaction of nitrogen and irrigation was significant and mostly synergistic on wet and dry weight of stem. The highest amounts of stem wet weight (73.2 g) and stem dry weight (5.63 g) were resulted from application of 150 kg nitrogen per ha under full irrigated condition that increased dry and wet weight of stem 17 and 25 percent respectively comparing with without nitrogen application under sever water deficit condition. Application of 409 mm irrigation and 100 kg N per ha is suitable for condition that enough irrigation waterexists. However in water deficit condition, the application of 150 kg nitrogen per ha could be recommended.
Conclusion: In general, to achieve the optimum growth of garlic in similar soils and climatic conditions, application of 100 kg nitrogen per ha would be recommended under normal irrigation conditions while at water deficit conditions the application150 kg nitrogen per ha could be recommended that had only two percent difference with the mentioned treatment and this difference was not significant.
Research Article
mostafa yaghoobzadeh; Saeid Boroomand Nasab; Zahra Izadpanah; Hesam Seyyed Kaboli
Abstract
Introduction: Accurate estimation of evapotranspiration plays an important role in quantification of water balance at awatershed, plain and regional scale. Moreover, it is important in terms ofmanaging water resources such as water allocation, irrigation management, and evaluating the effects of changing ...
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Introduction: Accurate estimation of evapotranspiration plays an important role in quantification of water balance at awatershed, plain and regional scale. Moreover, it is important in terms ofmanaging water resources such as water allocation, irrigation management, and evaluating the effects of changing land use on water yields. Different methods are available for ET estimation including Bowen ratio energy balance systems, eddy correlation systems, weighing lysimeters.Water balance techniques offer powerful alternatives for measuring ET and other surface energy fluxes. In spite of the elegance, high accuracy and theoretical attractions of these techniques for measuring ET, their practical use over large areas might be limited. They can be very expensive for practical applications at regional scales under heterogeneous terrains composed of different agro-ecosystems. To overcome aforementioned limitations by use of satellite measurements are appropriate approach. The feasibility of using remotely sensed crop parameters in combination of agro-hydrological models has been investigated in recent studies. The aim of the present study was to determine evapotranspiration by two methods, remote sensing and soil, water, atmosphere, and plant (SWAP) model for wheat fields located in Neishabour plain. The output of SWAP has been validated by means of soil water content measurements. Furthermore, the actual evapotranspiration estimated by SWAP has been considered as the “reference” in the comparison between SEBAL energy balance models.
Materials and Methods: Surface Energy Balance Algorithm for Land (SEBAL) was used to estimate actual ET fluxes from Modis satellite images. SEBAL is a one-layer energy balance model that estimates latent heat flux and other energy balance components without information on soil, crop, and management practices. The near surface energy balance equation can be approximated as: Rn = G + H + λET
Where Rn: net radiation (Wm2); G: soil heat flux (Wm2); H: sensible heat flux (Wm2); and λET: latent heat flux (Wm2). Simulations were carried out by SWAP model for two different sites in Faroub and Soleimani fields. The SWAP is a physically based one-dimensional model which simulates vertical transport of water flow, solute transport, heat flow and crop growth at the field scale level. The period of simulation covered the whole wheat growing season (from 1st of December2008 to 30th of July2009. 16 MODIS images was used to determine evapotranspiration during wheat growing season. Inverse modeling of evapotranspiration (ET) fluxes was followed to calibrate the soil hydraulic. While SWAP model has the advantage of producing the right amount of irrigation and evapotranspiration at high temporal resolution, SEBAL can estimate crop variables like leaf area index, NDVI index, net radiation, Soil heat flux, Sensible heat flux and evapotranspiration athigh spatial resolution.
Results and Discussion: Actual and potential evapotranspiration were estimated for SWAP Model during the whole wheat growing season around669.5 and 1259.6 mm for Farub field and 583.7 and 1331.2 mm for Soleimani field, respectively. In contrast with NDVI and net radiation,spatial distribution of SEBAL parameters indicated that soil heat flux, sensible heat flux, and surface temperature of land have the same behavior. At the planting date, evapotranspiration was low and about 1 mm/day, but at the peak of plant growth, it was about 9 mm/day. Moreover, evapotranspiration declined at late growing season to about 3 mm/ day. SWAP model has been calibrated and validated with meteorological data and the data of field measurements of soil moisture. The amount of RMSE of 0.635 and 0.674 (mm/day) and MAE of 0.15 and 0.53 (mm/day) and also coefficient of determination (R2) of 0.915 and 0.964 obtained from comparison of SEBAL algorithm with SWAP model for Farub and Soleimani fields showed that no significant differences was seen between results of two models.
Conclusion: The present study supports the use of SEBAL as the most promising algorithm that requires minimum input data of ground based variables. Results of comparison of SEBAL and SWAP model showed that SEBAL can be a viable tool for generating evapotranspiration maps to assess and quantify spatiotemporal distribution of ET at large scales. Also, it feels that SEBAL and SWAP models can be applied in a wide variety of irrigation conditions without the need for extensive field surveys. This helps significantly in identifying performance indicators and water accounting procedures in irrigated agriculture, and to obtain their likely ranges.
Research Article
Farshad Fathian; Ahmad Fakheri Fard; Yagob Dinpashoh; Seyed Saeid Mousavi Nadoshani
Abstract
Introduction: Time series models are one of the most important tools for investigating and modeling hydrological processes in order to solve problems related to water resources management. Many hydrological time series shows nonstationary and nonlinear behaviors. One of the important hydrological modeling ...
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Introduction: Time series models are one of the most important tools for investigating and modeling hydrological processes in order to solve problems related to water resources management. Many hydrological time series shows nonstationary and nonlinear behaviors. One of the important hydrological modeling tasks is determining the existence of nonstationarity and the way through which we can access the stationarity accordingly. On the other hand, streamflow processes are usually considered as nonlinear mechanisms while in many studies linear time series models are used to model streamflow time series. However, it is not clear what kind of nonlinearity is acting underlying the streamflowprocesses and how intensive it is.
Materials and Methods: Streamflow time series of 6 hydro-gauge stations located in the upstream basin rivers of ZarrinehRoud dam (located in the southern part of Urmia Lake basin) have been considered to investigate stationarity and nonlinearity. All data series used here to startfrom January 1, 1997, and end on December 31, 2011. In this study, stationarity is tested by ADF and KPSS tests and nonlinearity is tested by BDS, Keenan and TLRT tests. The stationarity test is carried out with two methods. Thefirst one method is the augmented Dickey-Fuller (ADF) unit root test first proposed by Dickey and Fuller (1979) and modified by Said and Dickey (1984), which examinsthe presence of unit roots in time series.The second onemethod is KPSS test, proposed by Kwiatkowski et al. (1992), which examinesthestationarity around a deterministic trend (trend stationarity) and the stationarity around a fixed level (level stationarity). The BDS test (Brock et al., 1996) is a nonparametric method for testing the serial independence and nonlinear structure in time series based on the correlation integral of the series. The null hypothesis is the time series sample comes from an independent identically distributed (i.i.d.) process. The alternative hypothesis arenot specified. Keenan test has also been proposed for assessing the linearity or nonlinearitybehavior of a time series in time series analysis. Keenan (1985) derived a test for nonlinearity analogous to Tukey’s degree of freedom for nonadditivity test. Keenan’s test is motivated by approximation a nonlinear stationary time series by a second-order Volterra expansion. While Keenan’s test for nonlinearity is designed for detecting quadratic nonlinearity, it may not be sensitive to threshold nonlinearity. Here, we applied the likelihood ratio test (TLRT) with the threshold model as the specific alternative.The null hypothesis of the TLRT approach for threshold nonlinearity is the fitted model to the series is an AR (p) model, and the alternative hypothesis is the fitted model to the series is a threshold autoregressive (TAR) model with autoregressive order p in each regime.
Results and Discussion: Because both the ADF and KPSS tests are based on linear regression, which has the normal distribution assumption, logarithmization can convert exponential trend possibly present in the data into a linear trend. In the case of stationary analysis, the results showed the standardized daily streamflow time series of all stations are significantly stationary. According to KPSS stationary test, the daily standardized streamflow time series are stationary around a fixed level, but they are not stationary around a trend stationaryin low lag values. Based on the BDS test, the results showed the daily streamflowseries have strong nonlinear structure, but based on the Keenan test, it can be seen the linear structure in thembyusing logarithmization and deseasonalization operators, and it means the coefficients of the double sum part are zero. It should be considered the Keenan test is used to detect quadratic nonlinearity, and it cannot be adequatelyfor threshold autoregressive models since they are linear in each regime.
Conclusion: Streamflow processes of main rivers at 6 stations located in the southern partof Urmia Lake basin were investigated for testingthenonstationarity and nonlinearity behaviors. In general, streamflowprocesses have been considered as nonlinear behaviors. But, the type and intensity of nonlinearity have not been detected at different time scale due to the existence of several evaluation tests. In this study, all daily streamflow series appear to be significantly stationary and have the nonlinearity behavior. Therefore, to model the daily streamflow time series, linear and nonlinear models can be used and their results can be evaluated.
