A. Khashei Siuki; B. Ghahraman; M. Kouchakzadeh
Abstract
Nayshabour plain in Khorasan Razavi with arid and semi-arid climate, have an important role in agricultural production by using groundwater resources. In this study, by using groundwater balance model the equations which are required for estimating water table variations is obtained for plain. afterwards ...
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Nayshabour plain in Khorasan Razavi with arid and semi-arid climate, have an important role in agricultural production by using groundwater resources. In this study, by using groundwater balance model the equations which are required for estimating water table variations is obtained for plain. afterwards since, there are too many variables in the objective function of water consumption(optimized crop pattern and intensification) a meta heuristic method which require less computation of effect while it is more efficient will be used. In this research PSO optimization algorithm (Particle Swarm Optimization) is used. Model results based on a normal year (2008) showed that can earn highest income from the aquifer with 30 percent reduced spring cultivation, and increased 30 percent of wheat, barley and calona. Among the spring crops, corn and tomato ratio to another crops have largest increase area. The results showed that can obtain 7500 (thousands rial /hec)more benefit with increasing 20,591 hectares to autumn crops and reduced 10,970 spring products
S. Khazaei; H. Ansari; B. Ghahraman; A.N. Ziaee
Abstract
With increasing population and scarcity of fresh water,one of possible solutions is, using marginal waters (saline and sodic water). Using marginal waters should be taken into consideration and special studies. Since most processes related to soil and water, take place in unsaturated field condition, ...
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With increasing population and scarcity of fresh water,one of possible solutions is, using marginal waters (saline and sodic water). Using marginal waters should be taken into consideration and special studies. Since most processes related to soil and water, take place in unsaturated field condition, The purpose of this research is evaluation of saline and sodic water effect on diffusivity and unsaturated hydraulic conductivity.for this purpose, two soil types include loamy and sandy, two levels of SAR, 5 and 20, two levels of EC, 4 and 12 ds/m and distilled water were used. NaCl, CaCl2 and MgCl2 salts at Ca:Mg=2:1 were used to prepare treatments. Diffusivity was measured by one step out flow method at the suction of 15 bar. Unsaturated hydraulic conductivity calculated by using the diffusivity and the slope of the soil moisture charactristic curve. At both soils with increasing SAR and decreasing EC, diffusivity and unsaturated hydraulic conductivity decreased and this reduction was more at low moistures. Sandy soil was affected less than loamy soil. In comparison of treatments that cause the least and the most dispersion, diffusivity and hydraulic conductivity for loamy soil, decreased 100% and for sandy soil at low moistures, diffusivity and hydraulic conductivity decreased about 91% and 99%, respectively.
mehri shahedi; S.H. Sanaiinejad; B. Ghahreman
Abstract
The purpose of this study is regional frequency analysis of Annual Maximum 1-day Rainfall (AM1R) and Annual Maximum 2-day Rainfall (AM2R) using L-moments theory in Khorasan Razavi Province. For this purpose, the basic statistical tests include: homogeneity, independency and outlier data for AM1R and ...
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The purpose of this study is regional frequency analysis of Annual Maximum 1-day Rainfall (AM1R) and Annual Maximum 2-day Rainfall (AM2R) using L-moments theory in Khorasan Razavi Province. For this purpose, the basic statistical tests include: homogeneity, independency and outlier data for AM1R and AM2R were surveyed in 123 rainfall stations. The province was divided into four regions based on cluster analysis, topography and spatial pattern of precipitation. Hydrology homogeneity was also controlled by running heterogeneity test for each region. generalized extreme value (GEV), generalized logistic (GLO), Pearson type III (PE3) and Log Normal type III (LN3) probability distributions were estimated for every region. To select the appropriate distribution of AM1R and AM2R data, the fitness was judged using an L-moment ratio diagram and the Kolmogorov–Smirnov test and GEVdistribution select . The regionally quantile estimateions for GEV distribution were also calculated for AM1R and AM2R data. In all of the Homogeneous regions, the estimated values of AM1R and AM2R from the obtained relations are close enough to the real data of return periods less than 200 years (The largest MAE was 0.0386). The average absolute error between the estimated and the observation values in each region is favorable, showing a high accuracy of the estimation.
V. Yazdani; B. Ghahreman; K. Davari; M.E. Fazeli
Abstract
One of the important aspects of soil is, knowing the relationships between spatial features of soil and quantity in statistical model. The goal of this research is to estimate saturated hydraulic conductivity by regression and Co-Active Neuro-Fuzzy Inference System (ANFIS) with using the parameters of ...
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One of the important aspects of soil is, knowing the relationships between spatial features of soil and quantity in statistical model. The goal of this research is to estimate saturated hydraulic conductivity by regression and Co-Active Neuro-Fuzzy Inference System (ANFIS) with using the parameters of Bulk density, real density, porosity, Fractal dimension of particle size, and clay percent, silt percent, sand percent. So experiment related to saturated hydraulic conductivity calculation and soil physical properties calculation of soil in 54 points which were specified 5 by 5 meters. Also, amount of bulk density based on paraffin Hunk, Fractal dimension of particle size by wet sieve method, the percentage of sand, clay and silt by Hydrometry and saturated hydraulic conductivity above water table by double rings method was measured. The best regression model for Pedo transfer function (PTF) was chosen according to minimized the goal function based on statistical parameters R2, RMSE and MAE. Parameters sand and silt percent, bulk density, real density, Fractal dimension of particle size, and porosity were chosen as input. In PTF amount of R2, RMSE, NRMSE and MAE, are 0.65, 0.017, 0.96 and 0.012 respectively. ANFIS with four layers input includes bulk density, real density, porosity and Fractal dimension of particle size and an output layer with the best performance. In this research, the amount of R2 in the presented ANFIS model in training and test is 0.88 and 0.86 respectively, and RMSE values will be 0.012 and 0.02 respectively. Noticing to sensitivity analysis result, PTF has the least sensitivity than changes in porosity and Fractal dimension of particle size, on the other hand, it has the most sensitivity than changes in the values of bulk density, silt and sand percent. ANFIS model is like PTF is more sensitivity than changes in values of bulk density. In addition, the outcome shows more effect on ANFIS than PTF. Evaluation of models show that estimation in clay soil is not acceptable, in contract contrast its model for estimate saturated hydraulic conductivity in soil texture (lom sandy, lom and silt lom) is suitable.
E. Amini; B. Ghahraman; K. Davary; M. Mousavi Baygi
Abstract
Abstract
Agricultural scientists have developed considerable interest in modeling and generation of rainfall as new ways of analyzing rainfall data and assessing its impact on agriculture. A combination of Markov chain and gamma distribution function is recognized as a simple approach and is demonstrated ...
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Abstract
Agricultural scientists have developed considerable interest in modeling and generation of rainfall as new ways of analyzing rainfall data and assessing its impact on agriculture. A combination of Markov chain and gamma distribution function is recognized as a simple approach and is demonstrated to be effective in generating daily rainfall data for many environments. Thus the availability of the weather data limits the applicability of the simulation method. When these model parameters are evaluated over time and at different places, however, certain general characteristics are revealed. First, the transitional probability of a wet day followed by a wet day tends to be greater but parallel to the transitional probability of a dry day followed by a wet day. This phenomenon leads to a linear relationship of the transitional probabilities to the fraction of wet days per month. Second, the beta parameter, which is used to describe the amount of rainfall, is related to the amount of rain per wet day owing to the positive skew ness of the rainfall distribution. Based on these relationships, a simple method is introduced, by which model parameters can be estimated from monthly summaries instead of from daily values. The suggested method, therefore, provides a convenient vehicle for applying weather simulation models to areas in which its use had been impossible because of the unavailability of long series of daily weather data.
Keywords: Modeling, Markov chain, Gamma distribution function
B. Ghahraman; M. Sadeghi; J. Mohammadi
Abstract
Abstract
Spatial variability of soils makes difficult analysis of soil water flow phenomena especially in a large area such as a watershed. Using scaling methods is a solution in variability problems. The objective of this study was to investigate the effect of the non-linear variability on performance ...
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Abstract
Spatial variability of soils makes difficult analysis of soil water flow phenomena especially in a large area such as a watershed. Using scaling methods is a solution in variability problems. The objective of this study was to investigate the effect of the non-linear variability on performance of the scaling methods of Richards’ equation for modeling infiltration in a watershed. The method of Warrick et al. by adopting van Genuchten hydraulic functions was used and variability of n values (power of van Genuchten hydraulic functions) was considered as the nonlinear variability. Marghmalek watershed, a sub watershed of Zayanderoud, with 97 Sq. kilometers was studied. In addition, ten virtual watersheds with various degrees of variability of n were evaluated which were generated by stochastic method of Monte Carlo. Using HYDRUS-1D model, original and scaled Richards’ equations were solved for infiltration condition with constant hydraulic head and uniform initial soil water content. The results indicated that coefficient of variations of n values in the Marghmalek watershed (equal to 2.57%) is small enough that the scaling method can be used efficiently in modeling infiltration. Therefore, in this watershed, generalized solutions of Richards’ equation can be adequately used instead of individual solutions for every points of the watershed. Evaluations in the virtual watersheds indicated that variability of n values considerably affect the error between the generalized and individual solutions. Based on the result of this study, it can be concluded that scaling methods of Richards’ equation can be adequately applied in the watersheds in which coefficient of variations of n values does not exceed 3%.
Keywords: Scaling, Richards’ equation, Infiltration, Nonlinear variability, Marghmalek watershed
S. Zarrinfar; B. Ghahraman; K. Davary
Abstract
Abstract
Saturated hydraulic conductivity (Ks) is one of the most important physical properties of soils which is expensive and time-consuming to directly measure. Hence, indirect methods, such as pedotransfer functions (PTFs), were developed to predict the Ks. Previous studies showed that most of the ...
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Abstract
Saturated hydraulic conductivity (Ks) is one of the most important physical properties of soils which is expensive and time-consuming to directly measure. Hence, indirect methods, such as pedotransfer functions (PTFs), were developed to predict the Ks. Previous studies showed that most of the PTFs common in the literature can not suitably predict the Ks. Hence, this study was conducted to develop some new PTFs. In this study, some physical properties of 49 gravel soils, including Ks, bulk density and particle size distribution, were measured in a land in the campus of ferdowsi university of mashhad. The measurements were performed in a regular quadrangular grid with 4 meters distances. To measure the Ks, inverse hole method was used. To derive some PTFs, 8 arbitrary sets of independent variables were selected. For each set, the best subset of independent variables was selected using best subset regression method. Then, this PTF was found using partial least square regression method. To evaluate the validity of the derived PTFs, we used cross-validation method. The results showed that the PTF that used d50, geometric mean and standard deviation of the particle size distribution as independent variables could more precisely predict the Ks. For this PTF, R2, RMSE, MAE and R2pred are 0.4, 0.245, 0208 and 0.3 respectively.
Keywords: Pedotransfer function, Saturated hydraulic conductivity, Gravel soils, Inverse hole
A. Haghverdi; K. Mohammadi; S.A. Mohseni Movahed; B. Ghahraman; M. Afshar
Abstract
Abstract
Soil salinity within plant root zone is one of the most important problems that cause reduction in yield in agricultural lands. In this research, salinity in soil profile was simulated in Tabriz irrigation and drainage network using SaltMod and Artificial Neural Networks (ANNs) models. Based ...
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Abstract
Soil salinity within plant root zone is one of the most important problems that cause reduction in yield in agricultural lands. In this research, salinity in soil profile was simulated in Tabriz irrigation and drainage network using SaltMod and Artificial Neural Networks (ANNs) models. Based on initial spatial distribution of salinity in soil profile, studying area was divided to 4 different soil and water groups and for two seasons in one year salinity was predicted. The SaltMod model was calibrated and then was applied to generate 2400 data sets for training ANN models. Some of the input data of SaltMod were used in ANN models including irrigation water depth, evapotranspiration, water table depth, rainfall, and initial soil salinity. Efficiency of genetic algorithm in training phase of ANNs was analyzed. The mean of correlation coefficient (R2) and root mean square error (RMSE) of estimated salinity in all groups was 0.8 and 0.032 respectively. In conclusion ANNs could perform well in simulation of soil salinity and it could be replaced SaltMod with enough accuracy. The results showed that overall performance of ANN models improve by applying genetic algorithm.
Keywords: Tabriz plain, Soil profile salinity, Genetic Algorithm, Artificial Neural Networks, SaltMod
A. Haghverdi; B. Ghahraman; A.A. Khoshnood Yazdi; Z. Arabi
Abstract
چکیده
ظرفیت زراعی و پژمردگی دائم مهمترین نقاط پتانسیلی در مدل سازی و مدیریت آب مورد نیاز محصولات کشاورزی می باشند. روش های مستقیم تعیین میزان رطوبت هزینه بر و گران می ...
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چکیده
ظرفیت زراعی و پژمردگی دائم مهمترین نقاط پتانسیلی در مدل سازی و مدیریت آب مورد نیاز محصولات کشاورزی می باشند. روش های مستقیم تعیین میزان رطوبت هزینه بر و گران می باشد. بنابراین استفاده از توابع انتقالی برای تبدیل خصوصیات زودیافت خاک به خصوصیات هیدرولیکی یک راهکار مناسب برای حل این مشکل است. در این پژوهش کارایی مدل های شبکه عصبی مصنوعی (NNs) آموزش داده شده با نمونه های خاک منتج از جریان خروجی چند مرحله ای (NeuroMultistep outflow) و مدل های نزدیک ترین K همسایه (KNN) در اشتقاق توابع انتقالی به منظور تعیین میزان رطوبت در ظرفیت زراعی و پژمردگی دائم برای 122 نمونه خاک از شمال و شمال شرق ایران مورد بررسی قرار گرفت. همچنین تاثیر عوامل ورودی مختلف و نوع داده به کار رفته برای اشتقاق هر دو روش معین شد. نتایج حاصله نشان دادند که در کل روش KNN (027/0RMSE= ) نسبت به NNs (037/0RMSE= ) نتایج بهتری داشت. همچنین می توان گفت که حساسیت مدل های شبکه عصبی به کیفیت و نوع داده های به کار رفته برای آموزش بسیار بالاست و همگن نبودن داده ها باعث کاهش کارایی مدل های شبکه عصبی و افزایش 100 درصدی خطا می شود. همچنین نتایج نشان دادند که در نظر گرفتن خصوصیات هیدرولیکی به عنوان متغیرهای ورودی در شبکه عصبی باعث ارتقاء نتایج مدل سازی می شود.
واژه های کلیدی: نزدیک ترین K همسایه، شبکه های عصبی مصنوعی، توابع انتقالی، ظرفیت زراعی، پژمردگی دائم
M. Sadeghi; B. Ghahraman
Abstract
Abstract
Scaling methods, which are based on similar media theory, are used to simplify the statistic description of soil spatial variations. To simulate the water flow in heterogeneous soils, simultaneous scaling of soil hydraulic functions, including soil water retention and unsaturated hydraulic ...
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Abstract
Scaling methods, which are based on similar media theory, are used to simplify the statistic description of soil spatial variations. To simulate the water flow in heterogeneous soils, simultaneous scaling of soil hydraulic functions, including soil water retention and unsaturated hydraulic conductivity functions, is highly desirable. In the similar media theory, the simultaneous scaling is expected for geometrically similar soils. In this paper, it is indicated that although the geometric similarity is a necessity, it is not sufficient for validation of the similar media theory in the reality. It is shown that, in addition, the values of Kshm2 (β) must be identical in all similar soils (where Ks is the saturated hydraulic conductivity and hm is the median suction head in the water retention curve). To evaluate the theory, method of Tuli et al. (13) was used which applies the similar media theory to the similar soils of Kosugi and Hopmans (4) with identical σ (standard deviation in the log-normal hydraulic models). The method was also generalized such that it can well scale the soil hydraulic functions of the similar soils even where the β values are not identical. The theoretical descriptions were tested by data of 26 soils from UNSODA database. The soils were classified into six groups of similar soils based on the equality of their σ. As it was expected, the method of Tuli et al. did not perform well in the groups in which β values were significantly different. The results also showed that the proposed method can considerably improve the performance of the method of Tuli et al. It was indicated that the performance of the proposed method do not depend on β values and the geometric similarity is the only condition for that.
Keywords: Similar media, Simultaneous scaling, Retention curve, Hydraulic conductivity function
M. Sadeghi; M.R. Gohardoust Monfared; B. Ghahraman
Abstract
Abstract
To estimate spatial variability of soil hydraulic functions, scaling methods were developed and have been widely used. Among these functions, physically based methods have been found more desirable because of possibility of estimating soil hydraulic functions from soil physical properties. ...
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Abstract
To estimate spatial variability of soil hydraulic functions, scaling methods were developed and have been widely used. Among these functions, physically based methods have been found more desirable because of possibility of estimating soil hydraulic functions from soil physical properties. In this paper, a new and physically based method has been described for scaling soil hydraulic conductivity function. In this method, use of effective capillary drive (hcM) has been proposed for scaling of soil water suction axis in the hydraulic conductivity function. Using this method, data of all natural soils, from sand to clay, can be presented by a unique exponential curve as reference curve. The approach was validated by 396 sets of hydraulic conductivity data, including all soil texture classes, taken from UNSODA database. To determine hcM, fitting Brooks-Corey and Gardner-Philip models and also a model-free method were used. The results indicated an acceptable performance of the proposed method. Brooks-Corey and Gardner-Philip models and the model-free method results showed the average absolute error of relative hydraulic conductivity between the scaled data and the reference curve as 0.019, 0.056, and 0.059, respectively. In the employed methods, fitting capability of the mentioned models can be taken into account as the only limitation. Thus scaling performance would be well if the mentioned models could fit well the hydraulic conductivity data and vice versa.
Keywords: Scaling, Soil unsaturated Hydraulic conductivity, Effective capillary drive, Unique exponential reference curve
K. Davary; S.H. Nemati; B. Ghahraman; N. Sayari; P. Shahinrokhsar
Abstract
This experiment was conducted at research greenhouse of college of agriculture, Ferdowsi University of Mashhad in 1381-1382. The experiment was designed based on the splitted plots in the form of completely randomized design and in four replications. Irrigation intervals were in three levels of 12, 4, ...
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This experiment was conducted at research greenhouse of college of agriculture, Ferdowsi University of Mashhad in 1381-1382. The experiment was designed based on the splitted plots in the form of completely randomized design and in four replications. Irrigation intervals were in three levels of 12, 4, and 2 times per day at primary plots, and three substrates of new perlite, used perlit, and rice bran at secondary plots. We used Paris Island as the lettuce seed. Wet weight, dry weight, and height were influenced from irrigation interval. Accordingly which 4- and 12-day irrigation intervals resulted in 466.39 and 386.94 g corresponding to highest and lowest dry weight, respectively and 12-day irrigation interval arose increase in lettuce height. Significant differences for wet and dry weights were found under different substrates. High wet and dry weights were due to used perlit and rice bran substrates, respectively. There were no significant interactions between irrigation interval and substrate on all of the growth properties of lettuce.
R. Moazenzadeh; B. Ghahraman; K. Davary; A.A. Khoshnood Yazdi
Abstract
Soil moisture retention curve (SMRC) is an important soil property which expresses reaction between matric potential and moisture of soil. Direct measurement of soil matric potential and moisture is labour- and time-consuming. In order to prevail this problem, indirect methods are used for SMRC prediction. ...
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Soil moisture retention curve (SMRC) is an important soil property which expresses reaction between matric potential and moisture of soil. Direct measurement of soil matric potential and moisture is labour- and time-consuming. In order to prevail this problem, indirect methods are used for SMRC prediction. Pedotransfer functions (PTFs) are one of these indirect methods. This study was carried out to evaluate three internal pedotransfer functions, first and second models of Ghorbani and Homaee (1381) and Sepaskhah and Bondar (2002) derived in Iran, to predict SMRC in some Iranian soils. Also we tried to develop new different PTFs with better performance using the available information. Therefore 42 soil samples with spatial distribution from northern region of Iran, Amol, Babol and Karaj were selected and divided in Loam (20 samples) and Clay Loam (22 samples) texture classes. In evaluation of all existing PTFs, all 42 soil samples, and in developing new PTFs, 36 soil samples were used. The remaining six samples (three samples in each texture class) were used for validation of the new developed PTFs. In evaluation of the existing PTFs, results showed that the first and second models of Ghorbani and Homaee had alike and appropriate prediction of moisture in whole range of matric potential, whereas Sepaskhah and Bondar did not show an appropriate prediction. By the way, none of these PTFS had noticeable preference in specific texture classes in comparison with the others. New developed PTFS were highly significant (p
M. Sadeghi; B. Ghahraman; K. Davary
Abstract
Abstract
In recent years, many researchers have attempted to estimate the soil hydraulic functions (e.g. soil moisture characteristics curve, and hydraulic conductivity function) using particle-size distribution (PSD) curve. In these studies, an accurate mathematical representation of PSD is required ...
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Abstract
In recent years, many researchers have attempted to estimate the soil hydraulic functions (e.g. soil moisture characteristics curve, and hydraulic conductivity function) using particle-size distribution (PSD) curve. In these studies, an accurate mathematical representation of PSD is required for fitting the observed data. So far, some mathematical models were developed with different limitations. The goodness of fit is directly related to the number of the model parameters. However, estimating the parameters for higher-parameter models which have no mathematical or physical significance is a problem. Among the current models, 2-parameter Log-normal distribution model with mathematical significant parameters has been considered as a basis for many studies. In this study, it is indicated that the 2-parameter Log-normal distribution model can not be very accurate for representation of the PSD for all of soil textural classes. As an alternative, 2-parameter Gamma distribution model is proposed for more accurate representation of the PSD that its two parameters also are mathematical significant and readily computable. These two models have been compared in fitting the observed PSD data of 461 soil samples from UNSODA soil database. Gamma distribution model indicated a pronounced improvement in representation of the PSD. Based on Coefficient of determination (R2), in 362 samples and based on RMSE, in 323 samples, Gamma distribution model showed a better representation of the PSD than Log-normal. To evaluate the significance of the difference between two models, a t-test was performed. The results showed that, at confidence level of 1%, the R2-values of the Gamma model are significantly greater than those of Log-normal model. Also, at confidence level of 5%, a significant difference between the RMSE-values of two models was shown. Therefore, 2-parameter Gamma distribution model is judged to be better than 2-parameter Log-normal model for representation of PSD.
Key words: Particle-size distribution (PSD), Log-normal distribution, Gamma distribution, UNSODA
R. Moazenzadeh; B. Ghahraman; F. Fathalian; A.A. Khoshnood Yazdi
Abstract
Abstract
Pedotransfer functions (PTFS) are useful means of prediction many properties of the soil, and especially the hydraulic characteristics of this porous media. The main advantages of this functions, as compare to conventional methods used to directly estimate soil hydraulic properties, is that ...
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Abstract
Pedotransfer functions (PTFS) are useful means of prediction many properties of the soil, and especially the hydraulic characteristics of this porous media. The main advantages of this functions, as compare to conventional methods used to directly estimate soil hydraulic properties, is that they are not time-cost consuming. Different approaches such as classic linear and non linear regressions, artificial neural networks and regressions tree are being employed to develop the PTFS. Rosetta is a software package to predict soil hydraulic properties making use of artificial neural networks- based PTFS. In the present study, the impacts of the type and count of input variables to this software, on the prediction of the moisture retention curve and saturated hydraulic conductivity were evaluated in some soils from northern region of Iran, classed as of Loam and Clay Loam textures (USDA). Our results indicated that addition of bulk density as input variable decreased the performance of moisture retention curve prediction in both textural classes. Addition of bulk density showed on RMSE, ME, GMER and GSDER a positive and negative effect in Loam and Clay Loam textures, respectively. Addition of one or two moisture retention point(s) (the moisture content at matric potential of -33 and -1500 kpa) significantly decreased the RMSE at the medium range of matric potential (i.e. -33 to -500 kpa) and especially at -33 kpa. All of the studied PTFS tended to underestimate both saturated hydraulic conductivity and moisture content at different matric potential.
Key words: Pedotransfer Functions, Hydraulic properties, Moisture retention curve, Saturated hydraulic conductivity, Rosetta, Iran
H. Sharifan; B. Ghahraman; A. Alizadeh
Abstract
Evaluation of Rainfall Effect on Programing of Agricultural Management (Case Study: Golestan region)
Abstract
Securing of water need in agricultural is important. Precipitation are one of the most important of water resources in agricultural, in Golestan province, especially , because Alborze mountains ...
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Evaluation of Rainfall Effect on Programing of Agricultural Management (Case Study: Golestan region)
Abstract
Securing of water need in agricultural is important. Precipitation are one of the most important of water resources in agricultural, in Golestan province, especially , because Alborze mountains are in Golestan south. In research has investigated effects of rainfall to cropping pattern and intensification in Golestan farms. Rainfall used: a) have forecasted rainfalls by Minitab-13 program, b) Different probabilities of rainfalls by LST Program. Then estimated effective rainfall (by USDA method). For optimization used Lingo-8 program. Evaluations shown that in southern region (climate is: smi wet), if rainfall decreased, area of tomato and potato decreased , but canola area increased. In central and north regions (climates are: semi dried to dried), if rainfall decreased, watermelon area decreased, but canola area increased. Also if drought conditions, planting of canola, watermelon and cotton crops are important.
Key words: Cropping pattern, Intensification, Precipitation, Golestan
H. Shamkoeian; B. Ghahraman; K. Davary; M. Sarmad
Abstract
Abstract
Natural disasters threatening and endangering human communities has resulted in the study and research of such disasters through the related sciences and present methods of forecasting their behavior with time and place and also from a qualification and quantity viewpoint. To this end, numerous ...
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Abstract
Natural disasters threatening and endangering human communities has resulted in the study and research of such disasters through the related sciences and present methods of forecasting their behavior with time and place and also from a qualification and quantity viewpoint. To this end, numerous methods for the determination of the maximum flood in various return period has been made available which can be refered to as flood frequency analysis methods. One of these methods is the regional flood frequency analysis in which instead of using the data from a single station, it considers the data and characteristics of a group of similar stations. In the case under the research this method uses L-Moments and Index Flood in North, Razavi and South Khorasan water basins and MATLAB software. Maximum annual flood statistics were used from 68 Hydrometric stations with minimum and maximum statistical periods of 6 and 39 years. Using Cluster analysis the region under study was divided to 7 partitions. Discordance test has conducted and only one station in region C was found as discordance station. Because of knowing the homogeneity of the regions, the parameter of Kappa distribution were estimated and with using the simulation method of Monte Carlo with 500 times, the homogeneity measure was tested in 7 regions. Using homogeneity test all regions was found homogen. Using goodness-of-fit measure z and Kolmogrove-Smirnov the Log normal 3 parameters distribution were selected for two regions of A and B, GEV for C, Generalized Pareto for D and E, Generalized logistic for F and Pearson III for G. Besides, GEV distribution was found appropriate for all of the regions, only their parameters are different in any regions. For estimating of index flood a logarithmic model has found for each region with 4 variables of area, height, average slop and form factor. Using of these models, the index flood can be estimated in each region and it can be used for standardize the statistics of maximum flood values.
Keywords: Regional flood frequency analysis; L-Moments; Index Flood; Cluster analysis; Khorasan
B. Ghahraman; K. Davary; A.R. Astaraei; M. Majidi; S. Tamassoki
Abstract
Abstract
Irrigation planning and management requires continious monitoring and measurements of soil moisture content. Application of Gypsum blockes (GB) are common in soil moisture measurements. GB readings are subjected to its geometry and soil solution concentration. This study was carried on 90 ...
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Abstract
Irrigation planning and management requires continious monitoring and measurements of soil moisture content. Application of Gypsum blockes (GB) are common in soil moisture measurements. GB readings are subjected to its geometry and soil solution concentration. This study was carried on 90 GB in research greenhouse of Faculty Agricultural, Ferdowsi University of Mashhad. At the begining, all GB were calibrated in distilled water. Further, readings were collected in four solutions of 2, 6, 10 and 18 dS/m salinity. Then, three soil media with different textures (sandy loam, loam, clay loam) at 5 levels of salinity rate (trace, 2, 6, 10 and 18 dS/m of saturated extract) were studied, as 15 treatments. GB readings, at different soil moisture contant, were made by ELE-5910A. For each treatment, readings vs. soil moistures were plotted. These curves were compared with that of standard (same soil texture with trace salinity). Finally, some corrector functions were developed to eliminate the salinity effects from GB readings.
Key words: Gypsum block, Salinity, Salinity effect correction, electrolytic concentration of soil solution
S.R. Khodshenas; B. Ghahraman; K. Davary; H. Nazerian
Abstract
Abstract
Sediment load-discharge data of hydrometric stations in the north of Great Khorasan province were studied. Twenty nine stations were selected and the mean annual sediment yield was computed using sediment rating curves. The total annual sediment yield for these catchments (61.5 to 16800 km2) ...
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Abstract
Sediment load-discharge data of hydrometric stations in the north of Great Khorasan province were studied. Twenty nine stations were selected and the mean annual sediment yield was computed using sediment rating curves. The total annual sediment yield for these catchments (61.5 to 16800 km2) varied between 4.8 to 19500 M ton/year and the specific sediment yield varied between 62 to about 4000 ton/year/km2. Due to large variations in the total and specific sediment yield, 29 selected catchments were divided in two groups: 17 large catchments (area>500 km2) and 12 smaller ones (area
A. Emami; B. Ghahraman; K. Davary; M. Hashemi nia; S. Tamassoki
Abstract
Abstract
Deficit irrigation is a method to promote water use efficiency (WUE) in a farm under water shortage conditions, however, the consequences is that yield per area decreases. To determine production functions for three cotton cultivars, an experiment was conducted during 1381 growing season on ...
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Abstract
Deficit irrigation is a method to promote water use efficiency (WUE) in a farm under water shortage conditions, however, the consequences is that yield per area decreases. To determine production functions for three cotton cultivars, an experiment was conducted during 1381 growing season on a silty clay loam soil in HashemAbad Agricultural Research Station in Gorgan. This study was performed using a split-plot design with 3 replications on three cotton cultivars. A line-source sprinkler irrigation system was used with 54 plots in each side of the line (3cultivars* 6treatments* 3replications). To estimate root zone water deficit, climatic data and cotton crop coefficients during the growing season were used. For each cultivar second order equations were derived to relate yield and applied water. However, linear relationships were established to relate yield and evapotranspiration. In addition, based on Doorenbos and Kassam formula yield response factors were found to be 1.02, 0.96 and 1.01 for Sahel, Say Ocra, and 818-312 cultivars, respectively. Such yield response factors can be used to optimize irrigation planning under water shortage conditions.
Key words: water production function, yield response factor, line source irrigation, Gorgan
M. Sadeghi; B. Ghahraman; K. Davary
Abstract
Abstract
The rate and duration of downward flow during redistribution process determines the effective soil water storage at any time. This property is vitally important, particularly in arid and semi-arid regions where plants must rely for long periods of time on the remained soil water of the root ...
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Abstract
The rate and duration of downward flow during redistribution process determines the effective soil water storage at any time. This property is vitally important, particularly in arid and semi-arid regions where plants must rely for long periods of time on the remained soil water of the root zone. In this study a new approach for scaling of soil moisture redistribution process based on the Green-Ampt redistribution theory was developed. Using the scaled results of numerical solution of the general flow (Richards’ equation), an empirical equation for predicting the soil moisture profile during redistribution process was derived. An important advantage of the empirical equation is adopting the effect of hysteresis in soil retention curve on redistribution process. To validate the proposed empirical equation, its outputs were compared with those of Richards’ solution for 11 soil textural classes (from sand to clay). The comparison showed negligible amount of error for all of the 11 soil textural classes and for a wide range of initial conditions. However, some deviations from results of Richards’ solution were observed under high initial infiltrated water depth and/or high initial soil water content. Therefore, a model which can estimate the soil moisture content at any depth and time during redistribution phase with accuracy of numerical models and simplicity in application of analytical models was obtained.
Key words: Scaling, Soil moisture profile, Redistribution phase, Green and Ampt equation, Richards’ equation
