Journal of Water and Soil
Year:2013 | Volume:27 | Issue:4|Papers Count:22

Damage or failure is an inevitable event which should be considered in all decisions taken at planning-, design-, operation-and maintenance-level for a water distribution network (WDN). So far several studies are conducted about reliability analysis in literature, but very little attention is paid to the damage tolerance analysis (DTA) of WDNs with different orders of failures. This may be due to the heavy and extremely time consuming computational workloads commonly required for DTA. In this study required relationships for DTA of WDNs with different orders of failure are derived. Additionally some equations are proposed to estimate the possible errors in these relationships. Then an attempt was made to evaluate the damage tolerance of sixteen designs of a hypothetical WDN with different orders of failure. The results indicate that application of the proposed equations of this study could significantly prevent redundant and unnecessary hydraulic simulations which may complicate the DTA of WDNs. Moreover the results reveal that the tolerance of the WDN to various orders of failures gradually decreases by decreasing the diameters of pipes. Comparing the damage tolerance of a network with different orders of failure, one could estimate the sensitivity of a WDN to simultaneous failures.

Population growth has caused increase of water demand for the drinking water, industry and agriculture. This condition needs the application of effective measures for optimal water management. So, in this research, a water allocation model is proposed for agriculture, industry and service sectors. In agricultural sector, production function of each crop is determined and then, objective function is specified based on the production function, and income of crops. In the industrial sector, the water demand of the product is function of water and other material prices and so, the demand function is determined based on these factors. Due to the necessity of water for the service sector, the total water demand of this section was fully allocated. Then, using innovative learning algorithms, a combination of genetic algorithms-Collective Intelligence (GAPSO), objective function is maximized and optimal allocation of water for agriculture and industry, were determined and compared. According to the result mentioned, use pattern of deficit irrigation model, changing crop pattern, remove the acreage of some crops and use of more water resources in the industry field can be effect on increase revenues to 114 billion Rls. In sum, the income of agriculture and industry in the Iran Central Kavir basin can be up to 56 percent of revenues of the current situation using water resource allocation for different sectors. In this case, the region will witness a remarkable progress. Therefore changes in the water resources allocation of the area seem to be necessary.

Increased use of drip irrigation systems in the country and farmer's tendency to use more efficient irrigation systems, has caused need to know about parameters and factors that affect irrigation efficiency. This Study was done to examine how water moves in the soil and soil moisturere distribution at Weather Station of FerdowsiUniversity of Mashhad. Inthisstudy, Hydrus 2D/3D Model performed by using data from laboratory and field analysis. Thes imulation results of soil moistureina 48 hour period were compared with the results offield measurements. The results showed that the model is very capable in simulating moisture contentin thesoil. Statisticalerroranalysiswas described to estimate model parameters using Maximumerror (ME), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Based on the results of RMSE parameter in volume tricsoil moisture, forallintervals and all discharges RMSE was less than 10 percent that it shows that model hashigh ability in simulation. Maximum Error was up to 5% of and Mean Absolute Error was up to 2.05% of volumetric moisture content.

In this study, Khanghag Sorkh watershed was selected to study on the effect of vegetation and slope changes on soil carbon sequestration. Therefore, three vegetation communities were recognized and soil sampling was done within 0-30 cm depth in two slopes (10-30% and 30-50%). Soil samples were analyzed to measure carbon sequestration rate and some of other physico-chemical characteristics. The results showed that the soil of Pteropyrum aucheri-Astragalus microcephulus, Astragalus microcephulus-Acanthophyllum microcephalum and Pteropyrum aucheri-Prangus uloptera communities has sequestrated 96.10, 73.84 and 52.85 ton carbon per hectare, respectively. The slope of 10-30% and 30-50% has sequestrated 96.11 and 126.68 ton carbon per hectare, respectively. In general, the slope of 10-30% had higher carbon sequestration compared with the slope of 30-50% with the exception of Pteropyrum aucheri-Astragalus microcephulus community. Our estimations revealed That the soil of Pteropyrum aucheri-Astragalus microcephulus, Astragalus microcephulus-Acanthophyllum microcephalum and Pteropyrum aucheri-Prangus uloptera had ca. 19220$ , 14768 and 10570$ economical values per hectare in respect to carbon fixation, , respectively. An investigation on other edaphic factors showed that most of soil factors were also significantly different between vegetation communities and slope classes (P<0.001). The results showed that in lower slopes, conservation and suitable utilization of vegetation could lead to conservation of soil organic carbon in dry and semi-dry regions.

Cation Exchange Capacity (CEC) is an important characteristic of soil in view point of nutrient and water holding capacity and contamination management. Measurement of CEC is difficult and time-consuming. Therefore, CEC estimation through other easily-measurable properties is desirable. The purpose of this research was to investigate CEC estimating using easily accessible parameters with Artificial Neural Network. In this study, the easily accessible parameters were sand, silt and clay contents, bulk density, particle density, organic matter (%OM), calcium carbonate equivalent (%CCE), pH, geometric mean diameter (dg) and geometric standard deviation of particle size (sg) in 69 points from a 1´2 km sampling grid. The results showed that Artificial Neural Network is a precise method to predict CEC that it can predict 82% of CEC variation. The most important influential factor on CEC was soil texture. The sensitivity analysis of the model developed by using of Artificial Neural Network represented that clay%, silt%, sand%, geometric mean diameter and geometric standard deviation of particle size, OM% and total porosity were the most sensitive parameters, respectively. The model with clay%, silt%, sand%, geometric mean diameter and geometric standard deviation of particle size as inputs data was selected as the base model to predict CEC at studied area.

In order to investigate the effect of humic acid (HS) on P adsorption behavior, an experiment carried out with three levels of HS (0, 100, 200 mg/L) and various P concentration (0 to 30 mg/L) at two ionic strengths (IS) of 0.1 and 0.01 M. Adsorption data were fitted to Langmuir, Freundlich and Temkin equations, and Langmuir was better fitted than others (R2=0.91 to 0.98). Results indicated that HS application significantly lowered the adsorption isotherm curves and Langmuir maximum mono layer adsorption (qmax) decreased up to %50 in comparison to control. Also sorption parameters including Langmuir bonding energy parameter (KL), Freundlich capacity and intensity factors (KF, n), and Temkin retention parameter (KT) decreased significantly by adding HS. Maximum buffering capacity (MBC), equilibrium buffering capacity (EBC) and standard buffering capacity (SBC) decreased more than %50 in HS200. Application of HS increased equilibrium phosphorus concentration (EPC) in both ionic strength, as EPC increased from 0.28 to 0.40 mg/L (IS=0.01 M) and 0.21 to 0.39 mg/L (IS=0.1 M). Finally, it was concluded that HS reduced P sorption due to competition on sorption sites and resulted in increasing P availability to plants.

Aluminosilicates such as K-feldspar and micaceous minerals are the main source of potassium in soils. The objectives of this study were to investigate the release of K from micaceous minerals (biotite, phlogopite, muscovite) and K-feldspars (Zanjan and Yazd) using sequential extraction by 0.05 M BaCl2 and determine the effect of mineral grain size and application of kinetic models to describe K release. For this purpose, sequential extraction with BaCl2 was conducted on two sizes of 50-100 and less than 50 micron for the periods of 2-600 hours. The amount of K released into the solution was measured by flame photometer. The results indicated that after 13 times of extraction, in the both sizes, biotite and muscovite had the highest and lowest values of K release, respectively. Meanwhile, the released K increased by decreasing the mineral size. The kinetics of K release from minerals consisted of two phases, the first phase was relatively rapid and then continued with a slow rate to end of the experiment. Regarding the high determination coefficient (R2) and low standard error of the estimate (SE), parabulic diffusion and exponential function equations could reasonably describe the K release kinetics. Therefore, it may be concluded that the release of K is controlled by diffusion process from the surface of the study minerals.

Sewage sludge uses as a low coast fertilizer to rectify deficit of elements such as zinc (Zn). A suitable extractant for estimation of bean-available Zn in calcareous soils amended with sewage sludge has not yet been introduced. The aim of this research was to assess several chemical extractants for the estimate of available Zn in sewage sludge-amended calcareous soils. For amended soils, 1% (w/w) of sewage sludge was added to 10 calcareous soils, and the soils (amended and un-amended) were incubated at field capacity for 30 days. At the end of incubation, soils were air-dried and available Zn was determined using 7 chemical extractants (DTPATEA, AB-DTPA, Mehlich 1, Mehlich 2, Mehlich 3, 0.1 N HCl and 0.01 M CaCl2). Zinc concentration in shoots, Zn uptake, and shoot dry weight of bean were determined in a pot experiment in amended and un-amended soils. The results show that Mehlich 3 and Mehlich 1 extractants extracted the highest and the lowest concentrations of Zn in both amended and un-amended soils, respectively. Furthermore, all three studied indices and Zn extracted by using different methods increased in amended soils. In addition, results indicated that significant correlations were found between extracted Zn using AB-DTPA, DTPA-TEA and Mehlich 3 and plant indices in un-amended soils. On the contrary, in sewage sludge-amended soils only the correlation between extracted Zn using DTPATEA and Mehlich 1 with Zn uptake and shoot dry weight and Mehlich 2 with Zn concentration was significant. The results of this study showed that DTPA-TEA could estimate bean-available Zn in the sewage sludge-amended And-un-amended calcareous soils.

Because most of the methods that have been proposed for estimating statues drought generate point estimate, so researchers were always looking for ways to achieve regional estimates for better manage this gradually creeping phenomenon. Recently, remote sensing and techniques proposed base on it could estimate drought inregional scale well. In this paper, it’s tried to estimate drought and evaluation performance of the Temperature Vegetation Dryness Index (TVDI) and the Modified Temperature Vegetation Dryness Index (MTVDI) using the vegetation and temperature MODIS products in Northern Khorasan during two years 2004 and 2008 (as normal and dry years respectively). The results showed that MTVDI index has performed better than TVDI index. The result of linear correlation analyzed between indices and the cumulative precipitation of the currently 16 days, early 16 days and early 1 month, 2 month, 3 month, 5 month and 7 month showed the indices, specially MTVDI, had a close relationship with early 1 month precipitation than the others. This is due to the delayed response of vegetation to precipitation.

Many of irrigated agriculture problems are resulting from chemical and physical composition of irrigation water. The irrigation water quality is effective on soil moisture characteristic curve by effect on soil structure, pore size distribution and continuity of them. The aim of this study was to evaluate the effect of different water salinity in the presence of constant turbidity on the soil moisture curve. The salinity treatments at five levels (1, 2, 4, 6 and 8 dS/m) with constant turbidity (200 NTU) were applied. These treatments were investigated at three depths of soil (0 to 15, 15 to 30 and 30 to 45 cm) with a silt-loam texture with three replications in a randomized complete block design. Soil water retention curve was determined by using pressure plate method. The results were statistically analyzed with MSTATC software. The results showed that the water percent of the soil of S2, S3, S4, S5 treatments of irrigation water quality increased to values 13.65, 20.20, 23 and 30 percent compared to S1 treatment. Comparison of water percent of soil at various depths showed that the depth of the second and third compared to the first decreased to 1.40 and 2 percent.

In this research, replacement of hydraulic models with statistical models and artificial neural networks were studied in order to estimate the criteria of pressurized irrigation systems hydraulic performance. The Coefficient of Uniformity of Christiansen (CU) was accepted as a hydraulic performance index. Using an automated algorithm, the values of this index were calculated for different combinations of inlet pressure, number and spacing of outlets, pipe roughness coefficient, inside diameter, slope, outlets nominal outflow and pressure and the exponent of the formula of outlet outflows (x) (4320 different combinations). Two different architecture of artificial neural networks were studied including a multi-layer perceptron (MLP) model and a generalize regression model (GRNN). Again, K-nearest neighbor (KNN) algorithm, as a nonparametric regression model was analyzed too. The results showed that MLP model could estimate the CU values of pressurized irrigation system laterals very closely (2-3% error) using its hydraulic and physical characteristics. The performance of GRNN model was also acceptable, especially related to the whole data set. But, the KNN algorithm was unable to predict standard deviation of CU values, although it was capable in estimating the mean value. The deviations of the KNN algorithm were the largest among all the models. The lowest values of error indices of the KNN algorithm was related to the K values of 10 and 15. The results of this study revealed the possibility of simplification of sophisticated hydraulic models by replacing the whole or some parts of these models with simpler statistical models and artificial neural networks. This is very interesting because of the complexity of hydraulic models, especially in optimization processes of irrigation systems.

The objective of this research was to evaluate the rhizospheric effects of wheat on phosphorus (P) release kinetics in 10 calcareous soils under rhizobox conditions. The kinetics of P release in the bulk and the rhizosphere soils were determined by successive extraction with 0.5 M NaHCO3 in a period of 2 to 840 h at 25±1oC. The results of kinetics study showed that mean of released P after 840 h of extraction period in the rhizosphere soils (192 mg/kg) was significantly lower than the bulk soils (207 mg/kg). A plot of cumulative amount of P released from both the rhizosphere and the bulk soils showed a discontinuity in slope at 168 h. Thus, two equations were applied to segments of the total reaction time (2 to 168 and168 to 840 h). Release kinetics of P from the rhizosphere and the bulk soils conformed fairly well to parabolic diffusion, simplified Elovich, power function and first order models in two segments. The correlation results showed that P released after 168 and P release rate constants of simplified Elovich, parabolic diffusion and first order equations in the rhizosphere and the bulk soils were significantly correlated (p£0.05) with wheat plant indices. In second segment, P release rate constants of Elovich, and parabolic diffusion equations in the rhizosphere and the bulk soils were significantly correlated with wheat plant indices (p£0.1). The results of this research indicated that wheat rhizosphere caused decrease of the P release rate and P release amount and release rate of P are important factosr in supplying available P to plants.

Marls have been recognized as susceptible formations against water erosion. Polyvinyl acetate (PVAc) is a biodegradable polymer which can be currently applied in soil conservation programs. The study was conducted to investigate effect of the PVAc on hydraulic conductivity and runoff and sediment production in a marl soil. The PVAc was applied in soil surface at five levels consists of zero (control), 50, 100, 150 and 200 kg ha-1 with three replications. The polymerized soils were putted into fifteen flumes with a dimension of 0.5m´1m and15cm depth. The flumes were placed in 9% slope and affected by five simulated rainfall events (40 mm h-1 in intensity and 30 min duration) with seven days interval. Based on the results, soil infiltration and hydraulic conductivity significantly affected by the PVAc application with a statistical level of 0.05 and 0.01, respectively. Analysis of runoff and sediment data showed that the runoff and sediment production was remarkably influenced by the PVAc application. There was found that 50 kg per hectare of the PVAc have the highest effect in improving infiltration rate and hydraulic conductivity, and consequently decreasing runoff and sediment production. The infiltration rate in 50 kg per hectare of the PVAc was 16.6% higher than zero treatment (control). The study reveled that the PVAc can be successfully used in the marl areas to improve soil structure and control runoff and sediment.

The operation dredging of river bed and also creating a cut off for removing sharp meander and maintain proper alignment is effective non-structural methods for decreasing the flood level. This study compared the effects of 1) Dredging karoon river at ahvaz range, 2) Removing heterogeneity height in order to make uniformly downstream slope, 3) Removing ahvaz downstream horseshoe Meander, which has been analyzed by HecRas4 model. Data modeling analysis showed that dredging in the form of bed dig in ahvaz range will not have significant effect on water level profile. This method only increase sedimentation and erosion rate in ahvaz range. Achieving to better results, the idea of dredging ahvaz downstream between two meander in order to regulate hydraulic gradient through removing heterogeneity height was proposed. Findings showed that this method has significant effect on improving of Hydraulic of flow and dredging effectiveness. Finally, it will be found that removing of the ahvaz downstream horseshoe meander is the most effective method for reducing level of flood and sedimentation rate in ahvaz range.

Management and chemical quality of groundwater is very important in arid regions. Fasa plain (in Fars province) is an arid-semi arid region in Iran, that almost all of its residents are using groundwater in agricultural activities. Recent water shortages resulted in deepens water table, salinization and reduced groundwater quality in this area. Studying the spatial variability and zoning of the chemical quality attributes of water in order to optimum utilization and management of soil and water resources is one of the practical methods in conservation of these resources. Therefore, the spatial variability for some of groundwater quality attributes in 80 wells located in Fasa plain of Fars province including total hardness, total dissolved solids, electrical conductivity, pH, soluble cations (calcium, magnesium, sodium, and potassium) and anions (sulfate, chloride, and bicarbonate) concentration was studied and attributes were estimated by applying geostatistical methods. The suitable estimation method was determined and zoning of the studied area was done for each studied attributes. The spatial variability structure of studied attributes followed the spherical and exponential models having the range parameters of 6700 to 140600 m belonging to the moderate to strong spatial correlation classes. The Ordinary Point Kriging was determined as the suitable estimating method that used for preparing the maps of water quality zoning. The quality of groundwaters in the southern half of the studied area was lower than that of the northern half, therefore, the more sensitive management in utilization of water resources and in using of agricultural systems is needed in order to avoiding the deterioration of water quality and worsening of groundwater status that is directly related to the residents livelihood.

Dispersivity is an important property of a porous medium and Advection-Dispersion equation (ADE). It is used in solving problems related to pollutants migration by groundwater. Numerical models are frequently used for simulation of water movement in soils. In the present study, the dependence of NaCl dispersivity on thickness of the aquifer materials has been investigated. In orther to perform it, 5 different thickness of soil column (20, 40, 60, 80 and 100 cm) selected. The physical model used in the study consisted of a cylindrical tank with inner diameter of 6cm and 5 thicknesses 20, 40, 60, 80 and 100 cm of soil column designated by T1, T2, T3, T4 and T5 respectively. Sodium chloride with an electrical conductivity (EC) of 3 dSm-1 was selected as conservative pollutant. For calculation of dispersivity Brigham model and for simulation of NaCl movement HYDRUS software used. Results of the study indicated that the dispersivity of sandy porous was not dependent on the thickness. The result of HYDRUS showed that with increase of aquifer length, dispersivity increased but it was not significant.

Crop coefficient (Kc) is one of the important factors in the irrigation planning and crop water allocation. The current study was carried out in order to calculate Kc for grain maize in the lysimetric station of Jihad-e-Agriculture and Natural Resource of Kermanshah, in Mahidasht. Kc was calculated as the ratio of crop evapotranspiration (ETc) to potential reference crop evapotranspiration (ETo). Actual crop evapotranspiration was measured based on lysimetric experiment and potential of reference crop evapotranspiration was calculated using Penman-Monteith equation based on daily weather data in Mahidasht weather station. During the growing season Leaf Area Index (LAI) was measured 14 times. The relation between Kc and number of Days After Sowing (DAS) and also LAI was investigated. In both cases the relation was made in a polynomial equation in order of 5 with the coefficient of determination over 0.9 and confidence level 0.001. Total amount of ETo and ETc in the growing period were 913 and 743 mm respectively. The initial, mid and late Kc for the maize determined a 0.5, 1.22 and 0.89, respectively. Comparing the calculated Kc values in the current study with the FAO values for Kc shows acceptable match except small differences in the late season that can be because of climate change and its impacts on crop water requirement.

Instantaneous velocity fluctuations are very important insuspended sediment load transportation. In this study experiments were performed toinvestigate the effects of artificial bed roughness on the instantaneous velocity fluctuations of saline density currents. Conic and cylindrical shapes of roughness with three heights were used. Velocity profiles were measured with an acoustic profiler velocity meter. Velocity and concentrationprofiles were measured in 3 and 4 cross-sections, respectively. The results show that increasing inrelative roughness height has a little impact on instantaneous velocity fluctuations in the entrainment region of the body of current. Also results of theinstantaneous velocity fluctuations profile on the rough bed show that turbulence intensity at the boundary of the ambient fluid and body of the current for cylindrical and conic roughness were 48 and 32 percent of shear velocity, respectively.

Fractional Gaussian noise (fGn) is an important and widely used self-similar process, which is mainly parametrized by its Hurst exponent (H) to specify its long-term persistence (LTP). Many researchers have proposed methods for estimating the Hurst exponent of fGn. But there is only a few researches that has compared different methods for different time series covering different length of records. In this paper, we have compared the performance of 7 different methods covering rescaled range (R/S), 3 different approaches of aggregated standard deviation method (ASD[0], ASD[rec], ASD[opt]), variance method (VAR), and 2 approaches of autocorrelation method (r[1] and r[2]). Seven different time series including Mashhad annual temperature (127 and 66 years), yearly minimal water levels at the Nile River (660 years), two global phenomena of North Atlantic Oscillation (NAO) (62 years) and two Pacific Decadal Oscillation (PDO) series (112 and 331 years), and concentration of atmospheric CO2 measured at Mauna Loa, Hawaii (55 years) were considered. The results showed that NAO and CO2 series do not have LTP (H<0.5). The VAR method failed to satisfy the scaling relationship, r[1] and r[2] failed to have good correlation, ASD[rec] failed to work under T66 and CO2 series, both ASD[rec] and ASD[opt] yielded inconsistently high H and standard deviation. R/S and aggregated standard deviation showed to be suitable methods for computing H. It was shown that H decreases as record length increases where includes historic data.