نشریه دانش آب و خاک
سال نوزدهم شماره 2 (پاییز و زمستان 1388)

The design storm is one of the main elements in flood estimation, as the choice of a design storm is an essential step in the many commonly used methods for estimation of design floods. Regarding to the existence of temporal variations in heavy storms, recognition of the storm temporal pattern is an important aspect. Application of storm temporal pattern in watershed hydrological modeling is a great necessity, as the main input, to gain more accurate results. In this research the dimensionless mass curves of intense storms of Tabriz station were extracted for different duration and average dimensionless mass curve were obtained using Pilgrim mean method. The mathematical model of each mass curve a general regression model for the average one as the temporal pattern of Tabriz storms were developed. The comparison of observed storms and those resulted from general regression model (temporal pattern model) indicated the closeness of them which confirmed the model goodness of fit.

Compost has been identified as an alternative chemical fertilizer to increase soil fertility and crop production. In this study the capacity of the compost produced from urban wastes to enhance seedling emergence grown in potting soil was investigated. Four treatments were compared based on the addition of increasing quantities of compost to soil (1:2.5, 1:5, 1:7.5, 1:10 compost to soil ratio, v/v). Physical and chemical analyses of the different mixtures were made. Plant growth, biomass production, macronutrients, micronutrients, and heavy metal contents of plant and soil were determined. The addition of compost increased pH, electrical conductivity (EC) of substrates, and macronutrients (N, P, K, Ca, Mg), micronutrients)Fe, Cu, Mn, Zn, B) and heavy metal (Pb, Ni, Cd, Cr, Co) of plants and substrates. The highest germination, growth rate, shoots and roots dry weights were obtained with the medium prepared by mixing rate of 1:5 compost and soil. The mixture with 1:2.5 rate had the lowest germination and growth of tomato seedling. Both toxic constituents and nutrient imbalances may be responsible for the growth-inhibiting effects of the municipal compost in the treatment. The addition of compost to growth media increased plant nutrient and heavy metal contents of plants. Excess adding of municipal compost to agricultural soil may lead to deleterious effects on crops.

Evaluation of suspended sediments and parameters affecting them is of great importance in river engineering. In this research the effects of water level and flow discharge fluctuations on suspended sediment load were studied using Artificial neural networks (ANNs). Ahar chay river basin, located in north of Iran, with area totaling about 2400 km2 as a sub-basin of Aras river was chosen. Data from Tazeh-Kand, Orang, Casein, Oshdologh and Bermice (upstream of Sattarkhan dam) stations were employed in ANNs method and the suspended sediment were predicted. The results showed that, suspended load forecasted by water level data had low accuracy than that forecasted by the flow discharge. The maximum and minimum coefficients of correlation for water level data were 0.69 and 0.08 in Orang and Oshdologh stations, respectively. The corresponding values for flow discharge were 0.84 in Oshdologh and 0.7 in Bermice. The main reason for the low coefficient of fittness in some stations probably were due to shortage of data, lack of temporal sequence and inaccuracy of water level fluctuations compared to the flow measurements. It appeared that, in this basin, in moving from high to low land with increasing discharge and sediment rates, the results of ANN became more reliable. Water level fluctuations did not show this trend.

Vermicompost as soil amendment is known for its large surface area and high nutrients holding capacity. A greenhouse trial was conducted to compare the municipal solid waste vermicompost and compost as potting media for the growth of corns. The mixing proportion of compost and vermicompost with soil were 0%, 1%, 3% and 5% of pot weights. Six corn seeds were planted in each pot and moisture contents of the pots were controlled close to filed capacity (FC). Plants were harvested at 60th day after planting. The results showed that all potted mixtures produced significantly higher biomass than the control (only soil). There was a positive significant relationship between the amount of compost and vermicompost added to the soil and the uptake of nutrients by corn. The optimum mixing proportion for vermicompost was 3% and for compost was 5% of pot weight. The results showed that the adding of 5% compost and 3% vermicompost to the soil, respectively, led to 178.82% and 178.42% increase in shoot dry weight and 49. 54% and 51.63% in root dry weight as compared to the control, respectively.

Sediments transported by river may cause damages to cultivated land and hydraulic structures. Accurate estimation of sediment load for hydraulic structures (e.g. dam) can prevent extra costs. Because of the existence of many rivers, our country, Iran, has high potential for dam construction. On the other hand, flood disaster causes huge damage every year. The main reason for magnifying the effects of this disaster can be related to the reduction of water conveyance capacity of the rivers because of sediment deposition. Therefore, the correct estimation of the transported sediment will be highly important. Prediction of the suspended sediment load can be accomplished by the Artificial Neural Networks (ANNs). In this study, ANNs are used to estimate suspended sediment load in Akhola station, located on the Ajichay River in East Azarbaijan, Iran. The available data for this station were daily discharge and sediment load The ANN sensivity for these parameters was examined in the modeling. In order to evaluate the effect of the upstream stations load, the data of Markid and Vanyar stations were also used to train the network, which led to more accurate result. The classic rating curve method was also used to estimate the sediment load at this station. To optimize the coefficients of the rating curve, the genetic algorithm was employed, its result of caerse did not show superiority on the classic optimization method. Regarding these results, multi-station estimation using ANNs has better efficiency.

Determining of the coefficients in infiltration models often is accomplished by fitting experimental data (cumulative infiltration and time) to the models; the two important soil parameters, soil bulk density (Db), and Initial water content (W0) are overlooked. In the current study it was aimed to find out to what extent the coefficients in Kostiakov, modified Kostiakov and Philip infiltration models would depond on Db and W0 and by entering those two variables into the models how much the predicting accuracy may be improved. For this purpose soil columns using PVC tubes with 23 cm in diameter and 80 cm length were prepared with four Db ranging from 1.11 to 1.42 gcm-3 and three W0 of 0.106, 0.131 and 0.147 gg-1. Infiltration tests were run with each combination of Db and W0 with two replicates, and the cumulative infiltratoion (I) were recorded at various times (t). Constant presure head of 2.1 cm water was maintained on the soil surfuce during all tests until approaching steady infiltration rate when tests were terminated. At the first step of data analysis, I and tdata were fitted to Kostiakov, modified Kostiakov and Philip models and their coefficients were computed. Then, the coefficients were regressed against Db and W0 and the regression equations were constructed. An the second step by applying those equations, the coefficients in the models were substitueted in terms of Db and W0 and cumulative infiltration, (Ip) were predicted by using three variables of t, Db and W0. Comparing the corresponding set of I and Ip through computing linear correlation coefficient (R) and root mean square deviation (RMSD) was the final step of data analysis. Results indicated that the dependence of the coefficients of these models on Db was quite greater than on W0. Entering Db and W0 into the models inspite of making them relatively complicated, resulted in better prediction of cumulative infiltration at most combinations of Db and W0. In this respect Kostiakov model with Db and W0 entered to it, produced more accurate prediction comparing to Philip and modified Kostiakov models.

The aim of this research is the application of two dimensional Saint-Venant equations for determenation of isochronal areas over the Kamanaj Olia watershed, a sub-watershed of Ajichay, located in East Azarbaijan Province, Iran. For this purpose watershed area was divided into 250×250 meters cells using GIS, then digital elevation model was prepared. Kostiokov infiltration model, as the best fitted model to measured infiltration data was selected for expressing infiltration component in Saint-Venant equations. Saint-Venant equations were solved using explicit method of finite difference numerical technique. Flow trajectory was calculated cell to cell to reach the outlet. Considering the momentary infiltration, the cell to cell flow rate was simulated using diffusive model for the purpose of spatial and temporal analysis.The equilibrium time for each cell was calculated to achieve the drivation isochronal maps for any rainfall event. Based on these maps the relation of concentration time with rainfall intensity as well as that of drainage area with rainfall intensity were developed.The eqiuilibrium time increased as the cell size changed from 250×250 to 300×300 and 350×350 meters, because of topographic and hydraulic parameters variation.

This research work is aimed to investigate temperature and precipitation changes in Aidoghmoush basin considering uncertainty of AOGCM models that may occur due to climate change in time period 2040-2069 (2050s). At first, monthly temperature and precipitation data of TAR-AOGCM models were provided for baseline period (1971-2000) and future period (2040-2069) under the SRES emission scenario, namely A2. Then, these data were downscaled spatially and temporally to Aidoghmoush basin. Results show temperature increase of 1 to 6˚C in 2050s relative to the baseline period. On the other hand, in 2050s precipitation shows substantial increase in autumn and winter and decrease in other seasons relative to the baseline. Monthly probability distribution function, of temperature and precipitation in the period 2050s were established by weighting method. Results indicated that the HadCM3 model has the most weighing for simulation of temperature and precipitation than the other models.

The rate of Zn desorption from soil surfaces into soil solution is a dynamic factor that regulates it continuous supply to growing plants. To ascertain the pattern of Zn desorption and the effective soil characteristics, the kinetics of Zn desorption from 20 selected soils of Iran by diethylentriaminepentaacetic acid (DTPA) were investigated. Eight kinetic models were evaluated to describe the rate of desorption of soil Zn by DTPA, which was rapid initially but gradually declined with time. The simple Elovich, the parabolic double diffusion and the two constant rate equations adequately described Zn desorption from soils. Rate constants for the parabolic double diffusion equation (K1 and K2), the two constants (a and ab), and parabolic diffusion (Kd) were closely correlated with soil pH, calcium carbonate equivalent, Olsen-P and DTPA-Mn, which are the soil characteristics that affect solubility, desorption and diffusion of Zn in soils. Rate constant for the simple Elovich equation (βs) was correlated with Olsen-P and rate constant for two-constant equation (b) was correlated with CEC, organic carbon and FC. The ratio of initial Zn desorption (rapid desorption) to total Zn desorption of soils decreased significantly with increase in calcium carbonate equivalent of soils.

Water movement through the root zone has attracted an increasing interest during the last few decades. In this research, the spatial and temporal patterns of root water uptake were studied in the root zone of an apple tree. An important part of the root water uptake model is root length density which was measured by sampling soil cores in the one quarter of the root zone. A 2D model of root water uptake was established, which included root density distribution function, potential transpiration and soil water stress-modified factor. Root water uptake distribution was measured by an array of TDR probes and the model parameters were optimized, by minimizing the residuals between the measured and simulated data. Studies showed that the maximum root water uptake occurred at depth 10-30 cm. The results also showed an excellent agreement between the measured data and the simulated outputs, indicating that the developed root water uptake model was efficient and feasible.

In the last decades, researchers had high consideration on the presence of chemical anomalies in water, soil and air which threat human health. Anomalies in fluoride concentration values exceeding standard limit (>1.5 mg/l) in drinking water have high importance, because of direct influence on physiology of human body. Fluoride concentration values of water resources in Bazargan and poldasht plains exceed standard limit (WHO). The aim of this research is spatial prediction of fluoride concentration in these plains. For this purpose Artificial Neural Networks (ANNs) model was utilized as a nonlinear model. For spatial prediction of fluoride concentration in the study area, different structures of these models were tested and the best structure (FNN-BFG) was determined. Spatial modeling was carried out by this structure and using fluoride ion concentration, correlated ions values and position of each sample, for which the determination coefficients of training and test steps were equal to 0.9625 and 0.9019 respectively. Then, results of the model were compared to those of the geostatistical methods of kriging and cokriging and the determination coefficients for test steps were 0.7285 and 0.8556, respectively. The best results of the three developed models were related to ANNs models.

Estimation of regional rainfall is one of important problems of water resources studies that can be accomplished by different methods. In this research, based on GIS capability and application of some geostatistical methods such as Kriging (simple, ordinary and universal) and radial basis functions (RBF), the spatial distribution of annual rainfall characteristics of Hamedan province were evaluated. In this regard, the observed data of 11 years in 36 meteorological stations and digital elevation model of the study area were used. To evaluate the methods, the cross validation technique was applied by error estimation. The results show that rainfall of the area varies between 206.7 and 494.8 mm. They also illustrate that the simple Kriging (with exponential model variogram) is the best method for average annual rainfall interpolation based on the mean bios error, mean absolute error and root mean squared error. They were 0.002, 16.53 and 21.04, respectively. Based on the estimated errors, in the case of maximum data, simple Kriging (with circular model) was identified as the reliable estimation method. The ordinary and universal Kriging methods (with Gaussian model) were also recognized as the most precise methods for the minimum rainfall data estimation. These results can be used to local estimation of rainfall characteristics of the region.

In this study, the effect of shape of roughness elements on the bed shear stress and sequent depth of hydraulic jump have been investigated. Experiments are conducted in a rectangular flume 0f 7.5 m long and 0.3 m wide in the hydraulic laboratory of Shahid Chamran University, Ahwaz, Iran. For the purpose of this study, prismatic roughness elements with different shapes: rectangular, triangular, circular, lozenge and hexangular were tested. The roughened elements are glued on the bed of flume downstream of ogee spillway in such a way that the incoming water jet is just above the element surface. The incoming Froude number was in the range of 4.5 to 12. During each tests the water surface profile, the roller length and the jump length were measured. In few tests the longitudes and vertical flow velocity were measured. The results indicated that the presence of rough elements can reduce the sequent depth ratio. The amount of reduction would depend on the Froude number and the roughness shape. The triangular element can produce lesser sequent depth ratio. Relations have been presented in this study for the sequent depth of hydraulic jump and shear force coefficient of bed as a function of the Froude number for each roughness shape.

Electrokinetic removal of heavy metals from the contaminated soils seems an innovative approach for their remediation. This technique may require much less time for the removal particularly in the soil with lower permeability comparing to the conventional leaching methods. In the current study electrokinetic remediation of a calcareous soil contaminated by three heavy metals (Zn=1400 mg kg-1, Cd=15 mg kg-1 and Pb=250 mg kg-1) due to the release of sludge's from mining industry around Zanjan city north west of Iran, was investigated in disturbed soil columns. Treatments imposed during the experiment were three moisture contents (saturated, FC and 0.7 FC), and two voltage gradients (1.3 and 2.66 volts per cm of the column length). Effects of three electrolytes (distilled water, Acetic acid, EDTA), electrolyte circulation and anodes displacement on the removal efficiency were also studied. Experimental data showed that raising voltage gradient and water content both enhanced ion migration through the column and thus led to considerably grater removal. After 10 days imposing the above voltage gradient under saturation condition, the removal of Cd, Zn and Pb achieved to 32.6%, 31.3% and 18.9%, respectively. Reducing water content to 0.7 FC reduced the removal percents to 21%, 18.4% and 12.3%, respectively. The largest removal belonged to Cd; with Zn and Pb being the second and third in this respect.

In this study, the performance of two different artificial neural network software's named neuro solution (NS) and neural works professional II (NW) in estimation of crop reference evapotranspiration (ET0) were evaluated. For models evaluation, some statistical parameters such as root mean square error (RMSE), mean absolute error (MAE) and coefficient of determination (R2) were calculated for different arrays, learning rules and transfer functions. For the NS software the best fitted array characterizing with lowest values of RMSE, MAE and highest R2 were found to be 0.08, 0.07 (mm day-1) and 0.87, respectively. Results showed that the NS software with the best fitted network array of: learning rule of conjugate gradient and transfer function of sigmoid type, which required shorter computational time and less iteration loops, can perform better prediction. The results indicated that using two hidden layers did not improve the accuracy of ET0 predictions, in comparison with the results obtained by one hidden layer layout. The sensitivity analysis of neural network model revealed that ET0 is very sensitive to maximum air temperature (Tmax). In contrast, the estimated daily ET0 showed the lowest sensitivity to minimum relative humidity (RHmin).

In order to introduce a sustainable soil fertility system in Kurdistan province (Sanandaj), a field experiment was carried out in 2007 and 2008 growing season. In this research effect of different fertilizers including farm yard manure, compost, biofertilizers, chemical phosphorus and green manure was investigated on grain yield and quality of chickpea (Cicer arietinum, Pirouz cultivar). Experimental units were arranged in split-split plots design based on randomized complete blocks with three replications. Main plots consisted of (G1): establishing a mixed vegetation of Vicia panunica and Hordeum vulgare and (G2): control, as green manure levels. Also, five methods for obtaining the base fertilizer requirement including (N1): 20 t.ha-1 farm yard manure; (N2): 10 t.ha-1 compost; (N3): 75 kg.ha-1 triple super phosphate; (N4): 10 t.ha-1 farm yard manure & 5 t.ha-1 compost and (N5): 10 t.ha-1 farm yard manure & 5 t.ha-1 compost & 50 kg.ha-1 triple super phosphate were considered in split plots. Four levels of biofertilizers were (B1): Bacillus lentus and Pseudomonas putida; (B2): Trichoderma harzianum; (B3): Bacillus lentus and Pseudomonas putida & Trichoderma harzianum; and (B4): control, (without biofertilizers). Results showed that green manure increased pod number/plant and number of fertile pods per area. Integrating biofertilizers (B3) and green manure (G1) produced the highest rate of pod number per plant. G1×N5 interaction obtained the highest amount of yield component (p≤0.01). However sole application of chemical phosphorus and phosphate solubilizing bacteria (PSB) has not significant effect on 100 grain weight. Regarding to significant differences between experimental treatments in all two and three way interactions G1N5B3 was determined as the superior treatment. Significant increasing of N, P, K, Fe and Mg in chickpea leaves and grains emphasized on superiority of mentioned treatment. Highest amount of protein and starch were obtained under (N5) treatment. Also, this treatment having low crude fiber, high total sugar content and reduced cooking time, increased the quality of chickpea grains.