WATER AND SOIL SCIENCE (AGRICULTURAL SCIENCE)
Year:2011 | Volume:21 | Issue:3|Papers Count:12

The aim of this study was to evaluate the spatial variability and frequency distribution of some physical and chemical properties within and between various landforms of Tabriz plain in the northwest of Iran. For these evaluation 13 properties of 98 surface soil samples according to grid sampling design with 1000 meters interval based on soils variability were selected and analysed. Landforms in the study area included hill, piedmont plain, plain, river alluvial plain and lowland. The study of soil variables frequency distribution showed that Bd, CEC, CCE, pH, clay and silt followed normal distribution, and these variables were used in parametric statistical method. Variables such as MWD, total N, SAR, OC, EC, available P and sand showed log-normal distribution. The variables frequency distribution increased within landforms, in lowland, hill, and river alluvial plain they showed normal distribution. Only EC in piedmont plain and sand, OC and total  N in plain landforms land forms showed log-normal distributions. Results indicated significant differences in soil properties distribution among landforms. Clay, pH, EC, SAR and MWD, CEC, Bd, total N, OC, available P, sand, and silt were strongly and moderately spatial dependent, respectively, while CCE had no spatial dependence and it followed nugget model. These results indicated strong spatial dependence due to the effect of intrinsic factors such as parent material, relief and soil types. Also soil properties variations could result from variation in depositional environments and/or differences in pedogenic or hydrologic processes for different landforms. These environmental factors can be affected by flood water, irrigation, fertilizeir addition, high water table level or agriculture practices. They may affect data deviation from normal distribution and cause skewness (positive or negative) at soil mapping unit.

In several types of rainfall-runoff models, the unit hydrograph based methods are useful tools for flood estimation in many, except non-gauged, basins. In this study, unit pulse response functions (quick and slow runoff) derived, considering linear system theory concept and using tank conceptual model. The model parameters were estimated with direct search optimization method. The model applicability and validity were verified using observed rainfall-runoff data of Navrood basin in Gillan province. The results showed that the tank model could simulate rainfall-runoff process with acceptable precision by taking into account the antecedent soil moisture conditions and without need to define excess rainfall.

The recognition of climate and eco-physiology of agricultural plants can be regarded as one of the most imperative factor in the production of agricultural yield development, and promotion of agricultural activities in any region. This recognition may enhance the production level in one hand, and the reduction of damage resulting from incongruous climate factors in another. The current research has been carried out aiming at the determination of potentially suitable canola production zone in Kurdestan province. Climatic data from 34 existing climate stations, which had long term records were collected and analyzed. We considered climatic factors such as precipitation required for growth period, frostiness, minimum and maximum, mean annual temperatures. We also used total amount of sunshine hours, average relative humidity of phonologic stage of canola, and physical elements including the type of land uses. This was followed by the determination of different layers for each climatic demand through the application of geographical information system (GIS) function. After appropriate evaluation of canola growth requirements using weighted classification method, the layers were categorized. As a final step, all climatic and physical layers were combined in the GIS environment by overlaying of different indices and results indicated that about 6.8 percent of Kurdestan province is suitable for canola cultivation, including Divan Darreh, Dehgolan, and Marivan plains. The reason for such suitability is better climatic, topographic, and pedologic conditions in that area. About 39.4 percent of the whole area is unsuitable for canola cultivation due to inappropriate climatic conditions, and unsuitable physical environment. These areas include northeast and northern parts (Obatoo district), and parts of the central and north west of the province. The remaining areas were classified as average to appropriate occupying 29.3 and 24.5 percent of area, respectively.

Stilling basins are short lengths of paved channels placed at the end of spillways and any source of supercritical flow to control the hydraulic jump, therefore shortening the lengths of stilling basins will economically be feasible. The purpose of this study is to investigate the characteristics of hydraulic jump in divergent channels on inverse slopes. The results showed that the divergence and the inverse slope of the channel had noticeable effects on the hydraulic jump characteristics. It was shown that the divergence and inverse slope reduced sequent depth ratios and length of hydraulic jump and furthermore the channel divergence increased the relative head loss of the jump. However in channels with inverse slope there was not any remarkable change in relative head loss compared with the classical jump. Therefore, the role of channel divergence in the relative head loss of the hydraulic jump might be considered more than the role of inverse slope. The results also revealed that the reduction of 37.22 percent at sequent depth ratios and 61 percent at the length of hydraulic jump were evident compared with the classical jump. The relative head loss of the hydraulic jump in a divergent channel on inverse slope was 54 percent greater than the classical jump’s one. Therefore, the divergent channel with inverse slope could be used as an energy dissipator to control the hydraulic jumps.

With developing of entropy theory and genetic programming based on maximum entropy and natural evolution, respectively, these methods have been applied extensively to the variety of engineering sciences such as fluid mechanics and hydraulics. In this study, entropy, genetic programming and conventional methods such as logarithmic, power law and Vanoni relations were used for estimation water flow velocity distribution in open channels. For comparing the mentioned methods, experiments were carried out in an experimental flume with a smooth bed in the hydraulic laboratory of the University of Tabriz. The flow discharges ranged from 4.8 to 32.89 Lit/s. For each flow discharge, the vertical velocity profiles were prepared with a precision of 0.1 cm/s and at 1 cm intervals from the channel bottom. Results showed that entropy and genetic programming methods were more accurate than the other methods for estimating the velocity distribution. Moreover the entropy method in comparison with the genetic programming showed higher accuracy and therefore it could be used for estimating the velocity profiles with a good accuracy in open channel flows.

Chemical immobilization is an operative approach to reduce detrimental effects of heavy metals in soils. The present study was conducted to test the usefulness of this procedure to decrease soluble and DTPA-extractable Zn in two Zn-spiked (addition of 200 mg Zn kg–1soil from zinc sulfate and incubation for two weeks at 25±1oC) acid and alkaline soils. In order to study the effect of submergence, two Zn-spiked acid and alkaline soils under two moisture conditions (field capacity [FC] and submergence [S], with and without 50 g cow manure/kg soil [M]) were incubated for one month. Results showed that S+M treatment caused a markedly decrease in soluble and DTPA-extractable Zn in both alkaline (97 and 75%, respectively) and acid (85 and 78%, respectively) soils. To evaluate the effect of phosphate amendments, 5 g P/kg soil from various sources (Ca (H2PO4)2.H20, Ca3 (PO4)2, H3PO4, K2HPO4 and KH2PO4) was added to the Zn-spiked acid soil. Results showed that the K2HPO4 treatment caused a markedly decrease in soluble Zn (88%). Neverthless DTPA-extractable Zn decreased (12.5%) in Ca3 (PO4)2 treatment. In another experiment the addition of calcium carbonate to acid soil (10 g CaCO3 kg-1 soil) caused a markedly decrease in soluble and DTPA-extractable Zn (97 and 43%, respectively).

Soil contamination with petroleum compounds since the petroleum exploration in the last century in Iran, and accumulation of these compounds in the environment threaten the health of soil and water resources of the country. The current research was conducted with the purpose of reaching to an efficient approach for the remediation of soils polluted with petroleum compounds. In this research the effect of five experimental treatments including various species of Bacillus and Pseudomonas bacteria with and without barely (Karron cv.) planting on the bio-degradation of those compounds in an artificially polluted loam soil was investigated. Analysis of the data indicated that the maximum purification belonged to the Bacillus 2 treatment. With barely planting this bacterium reduced soil total petroleum hydrocarbons up to %72.5 during 105 days. Without barely the reduction became %59.8 at the same period. The rate of bio-degradation was also highest at the same treatment, meaning that during a 20-day the reduction of catumination became %40. Degredation rate considerably increased with the presence of bacteria in the soil comparing to the barely planting alone. Inoculating of contaminated soil with bacteria without the need for particular nursery seems to be enough to control effectively the soil pollution. Among the several examined bacteria, Bacillus 2 turned to be the most suitable one for removing the petroleum- loased contamination.

Direct measurement of soil moisture curve (SMC) is time consuming, difficult and costly in laboratory. Therefore, many attempts have been made to predict SMC from soil physical and chemical properties indirectly. Arya - Paris model predicts SMC from soil particle size distribution data. The model estimates pore radius from the radius of spherical particles using a scaling parameter (a). The objective of this study was to evaluate estimation of a by six different methods to improve the predicted SMC from Arya - Paris model. Comparisons made on 14 soil samples with different textures collected from the eastern region of the Guilan province showed that the estimated SMC with different a produced different accuracy. It was highly depended on the selected parameter. In other words the method of determining a played a key role in the accuracy of SMC prediction. The results showed that linear a as described by Arya et al. and constant a of 1.38 as recommended by Arya - Paris were the best scaling parameters for estimation of SMC.

Deficit irrigation is an essential optimization method for water consumption in irrigated lands and is feasible by irrigating only half of the furrows either constantly or alternatively. In order to evaluate yield, yield components, and water use efficiency of tomato (Super Strain B), this study was carried out at the field of Agriculture and Natural Resources, College of Karaj, Iran. The experiment was performed as a randomized full block design with three replicates including three treatments: full irrigation, variable and constant alternative furrow irrigation. Irrigation interval was calculated based on MAD=0.5 using a TDR moisture meter device. At the end of the growth season characteristics such as yield, plant height, number of fruit, fruit diameter, length of root and root dry weight were determined. Totally, deficit irrigation produced significant effect (p<0.01) on yield and yield components. Yield reductions were determined to be about 10.17 and 34.46 percent respectively for variable and constant alternative furrow irrigation as compared to full irrigation. Reduction values were 16.67 and 30 percent for root length, 12 and 32.17 percent for root dry weight, 17.87 and 38.76 percent for plant height and 14.74 and 34.52 percent for number of fruit in alternative furrow irrigation treatment as compared to full irrigation, respectively. Water use efficiency was 1.8 and 1.3 times greater in variable and constant alternative furrow irrigation compared to full irrigation treatment. The results show that under conditions that land is not limiting factor area under cultivation can be nearly doubled by practicing deficit Irrigation so that total yield may increase considerably compared to that of full irrigation practice. In this context, constant alternative furrow irrigation compared to variable alternative furrow irrigation seems be economically more affordable because water use efficiency would be increased to as much as 1.8 times.

Based on the sugar beet high value and due to prolongation of growth period and relatively high water requirement, irrigation of sugar beet with new methods such as ordinary and alternative tape and furrow irrigation is of great importance. This study was conducted with three and two treatments for tape and furrow irrigation, respectively. In each treatment, there were four rows of crops. The plots were irrigated as ordinary, and alternative methods of tape and furrow irrigation and providing 70 and 100 percent of plant water requirement. The rate of water use, white sugar content, gross sugar content, sugar beet yield (root), white sugar yield, WUE of root yield, white sugar yield and WUE of gross sugar yield were compared in all treatments. The lowest and highest rates of water use were observed in the alternative and the ordinary furrow irrigation, respectively. The highest root yield was also obtained from plots with ordinary furrow irrigation. The amount of water use in drip (Tape) irrigation was about 50% of furrow irrigation, while the WUE of root yield, WUE of white sugar yield and WUE of gross sugar yield in alternative irrigation treatment and 70% of plant water supply were highest and they were lowest in the ordinary furrow irrigation treatment. alternative furrow irrigation having 30% less water use than ordinary furrow irrigation caused 15% reduction in root yield, but water use efficiency in root yield in alternative furrow irrigation was more than that in ordinary furrow.

In order to develop a simple and rational relationship between air temperature and soil temperature at different depths and to compare to Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) a study was conducted during 1992-2005. Air temperatures and soil temperature at depths of 5, 10, 20, 30, 50 and 100 centimeters were measured at Kermanshah station. To determine the optimum functional relationships between parameters the statistical criteria of correlation coefficient, RMSE and MAE were used. Based on correlation coefficient and error parameters, results showed that the regression methods of the third and second degree equations, linear, power and logarithmic had the best estimations, respectively. Also, results showed that the best and worst estimations between air temperature and soil temperature were observed, at 5 and 100 cm soil depths respectively. Results of this study produced a second degree equation and a linear equation (noting their simpticities of application in comparison with the third degree equation) for each soil depth. Based on the correlation coefficients and errors if can be said that obtained this equation is usable for soil depth of 100 cm with poor precision, but in the case of other depths has to high accuracy. The comparisons of regressions, ANN and ANFIS results indicated that ANN estimated more accurately soil temperature.

Using artificial neural networks (ANNs) and regression pedotransfer functions to predict the surrogate soil properties such as aggregate stability reduces time and cost needed for their direct measurements. In this research, 100 soil samples were collected from the forest soils of Guilan province. Organic matter, bulk density, equivalent carbonate calcium, particle density, porosity, soil mechanical resistance, clay, sand, silt, pH and electrical conductivity all were measured as independent variables. Geometric mean diameter (GMD) was computed as dependent variable by appropriate method. The samples were divided into two data subsets randomly: 80 for model calibration and 20 for model test. Regression pedotransfer functions were generated by stepwise method. For establishing ANNs we used Marquardt-Levenburg training algorithm and a 3-layer perceptron structure with 6 neurons in one hidden layer. According to the correlation matrix between GMD as dependent variable and independent variables, 10 groups input variables were selected. The were employed once by multi-variate regression pedotransfer functions and once by artificial neural networks. According to the adjusted coefficient of determination (R2ady), root mean square error (RMSE) and relative improvement (RI) a model resulted from applying ANNs and using input variables of pH, particle density, silt and soil mechanical resistance turned to be the best model for predicting GMD of the examined soils.