Journal of Water and Soil Conservation
Year:2016 | Volume:22 | Issue:6|Papers Count:25

Background and Objectives: Several empirical models have been presented to describe water infiltration into soil. In order to make them applicable in different places, the mentioned models need to be calibrated in different conditions. Therefore, the current research was aimed to optimize parameters of different models using point measurements at Lighvan watershed located in east Azarbayjan.Materials and Methods: Current research was carried out in Lighvan watershed, East Azarbayjan, northwest of Iran which is located in longitudes of 46ᵒ 22' 23" E to 46ᵒ 28' 05" E and latitudes of 37ᵒ 43' 07" N to 37ᵒ 50' 08" N. Selected infiltration models include Green and Ampt, Kostyakov and modified Kostyakov, Philip, Horton and Philip’s triplex models. In order to fulfill this research, soil sampling and field measurements were conducted at late spring of 2012. In this regard, cumulative infiltration were measured in 135 different place of the study area using Disc infiltrometer.Results: Based on evaluation error (EE) ceriteria Philip’s triplex model (EE=4%), Kostyakov (EE=8%), modified Kostyakov (EE=10%), Horton (EE=13%), Green and Ampt (EE=36%) and Philip (EE=37%) models had the most to least accuracy for cumulative infiltration prediction, respectively. Among the different soil texture classes (clay loam, loam, sandy clay loam and sandy loam), all applied models in this research except Horton model showed the best conformity in clay loam soil texture class.Conclusion: The results revealed that the Kostyakov and modified Kostyakov models are more suitable for cumulative infiltration and infiltration rates predictions. Therefore, we suggested the mentioned model to be applied in simliar condtion of the Lighvan watershed.

Background and Objectives: This study was conducted to determine natural concentration of heavy metals and their pollution risk using pollution indices in a 2000 km2 area in central Zanjan.Materials and Methods: Soil samples (N=241) was taken from 0-10 cm depth based on gridding procedure in a completely randomized design. Geometric means of 53 natural soil samples were used to determine heavy metals background concentration in the area.Results: Results showed that the background concentration for Fe, Mn, Co, Cr, Ni, Cu, Zn, Pb and Cd were 16509, 628.4, 24.2, 20, 40.7, 27, 91.8, 57.8 and 0.25 mgkg-1, respectively. The means of enrichment factor for Cd, Zn, Pb, Cu, Ni, Cr, Co and Mn were found 4.20, 2.16, 1.69, 1.64, 1.19, 1.17, 1.04 and 1.02, respectively. The highest enrichment factor for Cd (12.07), Zn (5.26), Pb (4.82) and Cu (3.47) was observed in urban area. In all land uses studied, the geo-accumulation index was negative for the elements Fe, Mn, Co, Cr and Ni, indicating that the study area is categorized in non-polluted soil groups. However, the geo-accumulation index for Pb, Zn, Cd and Cu varied in urban land uses was positive. The pollution index for Cd and Zn under agriculture (3.01 and 1.83), rangeland (3.33 and 1.60) and urban (9.86 and 4.35) land uses were higher than other elements studied. Moreover, the lowest pollution indexes in all land uses were attributed to the metals Fe, Mn, Co and Cr. The mean of potential of ecological risk in agriculture, rangeland and urban land uses were 114.09, 122.08 and 339.62, respectively; in which the urban land use showed the highest potential of ecological risk for inhabitants of the area.Conclusion: The results show that urban land has the highest pollution index and this may be due to urbanization activities such as transport and traffic and nearby factories of Zanjan city.

Background and Objectives: Gates are among the most common hydraulic structures in open channels that are used for flow control and water level control. The vertical slide gates suffer from lower contraction coefficient and thus lower flow rate capacity. In this paper, the hydraulic performance of a new modified gate, combination of a vertical slide gate with a cylindrical edge (Drum gate), has been studied.Materials and Methods: Laboratory tests of this study are performed in Hydraulic Laboratory of Water Engineering Group from University of Ferdowsi in Mashhad, in rectangular flume with length of 10 cm, width 30 cm, height 50 cm. In this study, totally, from nine gates that include four cylindrical slide gates and four half-cylindrical slide gates with diameter of 63 mm, 90 mm, 125 mm and 200 were used. The dimensionless stage-discharge relationship was proposed based on dimensional analysis and using the incomplete self-similarity concept in free and submerged conditions. In these relationships, flow rate is related to the upstream depth, gate opening and the cylinder diameter.Results: Finally, the development of the relationship of Ferro and Buckingham theory and the Self-Similarity Theory, relationships to estimate the flow rate of a half and full cylindrical gates for free and submerged flow conditions were presented separately and with proposed correlation with experimental data and statistical evaluation of acceptable accuracy were examined and the experimental data were analyzed. The proposed equation is accurate and practical so that it removes the need to consider the discharge coefficient. Results showed that this equation can be fitted to laboratory data very well. The mean relative error for estimation of discharge in the free and submerged conditions was less than 2 and 5 percent, respectively. Therefore, these equations can be used as a design tool for slide gates with cylindrical edge.Conclusion: Since accurate estimate discharge increased management function of water distribution network and also leads to an increased executive certainty in gate design, it can be concluded that the combination of dimensional analysis and the self-similarity theory can estimate the discharge obtained with high accuracy.

Background and Objectives: Groundwater modeling often is associated with uncertainty caused by incomplete knowledge of the underlying system or uncertainty due to natural variability in system processes and field conditions. Uncertainty in groundwater modeling has been evaluated in three main sources as parameter uncertainty, conceptual uncertainty and input uncertainty. So far, there are few studies for assessing groundwater uncertainty in the country and quantifying uncertainty has been limited to statistical methods. Due to the importance of the water resources in the country and the necessity of estimating the uncertainty in order to achieve reliable results, in this study, parameter uncertainty of an arid region’s groundwater flow model was assessed by using a Monte Carlo-based simulation technique.Materials and Methods: First, conceptual groundwater model of Birjand plain, located in the southern province, was developed based on collecting all available data, including topography, observed and withdrawal wells information, recharge information, hydrodynamic properties, surface elevation data. Then, the MATLAB -based MODFLOW model was used to simulate the groundwater flow. After initial calibration in steady state, for assessing parameter uncertainty in transient mode two scenarios were defined. Uncertainty analysis in the first scenario was performed by assuming the hydraulic conductivity as one of the major contributors to the model uncertainty. So the aquifer was divided into 17 homogenized zones according to initial calibration results and the parameter uncertainty was assessed using GLUE. In the second scenario, nine recharge zones were additionally considered as second parameters and their influence on hydraulic conductivity and total uncertainty were estimated by GLUE.Results: Posterior parameter plots of hydraulic conductivity in 17 homogeneous regions and recharge in nine inflow pathways and also, 95% confidence intervals for the simulated water table depth, were obtained as main results. The indices, as criteria for the comparison, were used to quantify the goodness of uncertainty performance and the sensitive regions were specified by implementing global sensitivity analysis of the model.Conclusion: Results indicate up to 86% of observed data bounded in the 95% confidence intervals that is emphatic the performance of the GLUE and the likelihood function in the assessment of parameter uncertainty in groundwater simulation model.

Background and Objectives: Rivers run in a sinus curve pattern usually and have a direct pathway rarely. Joining lateral channel to main channel at a bend location changes completely the conventional flow pattern at river bend. Recent flow pattern not only is affected by centrifugal force and stream and spin wise pressure gradient but also by momentum of lateral channel flow. Exact recognizing of this phenomenon needs extended studies.Materials and Methods: In this study using SSIIM1 model the effect of three position of straight lateral channel that is connected to a U bend at 45, 90 and 135 degree from the start of bend with a 90 degree confluence angle on flow velocity, variation of water surface elevation, shear stress distribution and helical flow strength was considered.Results: The results indicated by increasing the junction position from 45 to 135 degree from the bend start, stream wise flow velocity near the outer wall of the bend increases maximum %56 while near the inner wall of the bend decreases %8.Conclusion: Maximum difference between the upstream and downstream flow depth around confluence area at 45 degree position was equal to %6.15 of tail water depth. For position of 135 degree from the bend start this difference was about %5.4 of tail water depth. Additionally the results indicated shear stress at confluence area increases %8 when the position of junction angle change from 45 to 135 from start of bend.

Background and Objectives: Long-term weather data is of particular importance in hydrometeorology studies. Unfortunately, the 60-years meteorological data record in Iran is not responsible for study of extreme weather events. Tree-ring width data from sensitive trees to weather conditions are good resources for reconstruction of past climate. In recent decades, unlike Iran many studies in this field have been done. According to simultaneous effect of short and long term moisture sources on annual tree-ring growth, the aim of this study is to investigate the effect of different moisture sources on tree-ring width and reconstruction of moisture conditions during the available tree-ring data period.Materials and Methods: In this study the tree-ring width chronology was obtained from Quercus Infectoria trees located in Javanroud (Kermanshah) at an altitude of 2300 m.a.s.l. which is in the period of 1818-2009. Required climate data was prepared from 7 meteorological stations (3 stations from Islamic Republic of Iranian Meteorological Organization and 4 stations from the Ministry of Energy). Simultaneous effect of short and long-term water resources was investigated on growth of trees by using multivariate standard precipitation index (MSPI), which is based on modified standardized precipitation index (SPImod). The index is based on principal component analysis technique (PCA).Results: Results of correlation between MSPI and tree rings width during 1968-2008 showed that the overall status of water resources in January to September had the greatest impact on growth of oak trees and the highest MSPI correlation with tree ring width was in July. Then based on linear relationship between tree ring width and MSPI of July, this index was reconstructed over the 1818-2008 periods. According to the results of this research, droughts average duration were 2 years, nevertheless severe droughts duration were 3 and 4 years. The most severe droughts during the past two centuries have occurred in the 1960-1963, 1827-1830 and 1999-2001 periods, respectively.Results have a good agreement with Iran’s historical famines and droughts records and also with neighbor countries research results, far east (China) and western countries (Turkey and the Mediterranean zone), especially in the case of severe drought. But the results of this research are most consistent with the results of research conducted in countries on the path of the Mediterranean air masses (south of Mediterranean Sea and Middle East region).Conclusion: The relationship of MSPI and tree ring width was performed for the first time in this study. The results showed that the correlation coefficient of annual tree ring width with MSPI was increased in comparison with rainfall data that is probably due to considering short and long-term water resources in this Index, simultaneously. Results of drought reconstruction in this study have good agreement with results of neighboring countries as well as historical reports. It seems that the results of this research can be used for investigation of Middle East past climate, confidently.

Background and Objectives: Groundwater is one of the most important and worthiest resources of the country, which recognizing and optimal utilizing of these resources cause economics efflorescence. Inaccurate management and groundwater overdraft make irrecoverable damage to these resources, environment and economy of the country. Marand plain is one of the fertile plains of East Azerbaijan Province which 80 percent of its water demands is supplied by groundwater. Therefore, qualitative protection of groundwater resources of this Plain is vital. In this Study, Statistical Methods and Saturation Indices are used for assessment of quality parameters.Materials and Methods: The study area is located in the north west of east Azarbaijan province, some 60 km far from the Tabriz city. The total Marand area is 1871 Km2 which 589 Km2 of this area covers the Marand plain aquifers.48 water samples were collected from groundwater resources and analyzed and measured for major and some minor ions and species such as NO3-, F- and SiO2 as well as pH and EC in University of Tabriz hydrology lab.Groundwater resources are separated by cluster analyzing in three distinct groups. In this research multivariate analysis methods were used for quality parameters evaluation.Results: Cluster analyzing puts the water types in three individual groups. In first group the water type is bicarbonate sodic and in second and third groups it is chloro sodic type. The results of factor analysis indicated that three factors such as salty geologic formations dissolve of minerals and increasing of evaporation control about 75% of the total samples variance. To identify geochemical processes governing to the aquifer, saturation indices of calcite, dolomite and gypsum of the samples were evaluated. The results showed that chemical composition of groundwater is highly affected by river recharged water, aquifer skeletal materials and evaporation from the groundwater.Conclusion: The results showed that the quality variations of groundwater is affected by salty evaporate formations, solution of minerals and aquifer materials, evaporation from the rivers waters which recharge to the aquifer, water and formation reactions and evaporation from the groundwater. Also, the results showed that the water quality for agricultural, drinking and industrial purposes in eastern and southeastern parts of the study area is more suitable than the north and northwestern parts of the plain.

Background and Objectives: Precipitation is one of the most important meteorology elements and recognition of its amount, its variation and prediction, are necessary to have an actual planning in agricultural, economic and social management. So the hydrologists and climatologists are paying attention to it. Due to precipitation importance in planning and crisis management, the goal of this research leads to the implementation of neural network and wavelet conversion hybrid model to monthly precipitation prediction of Kermanshah synoptic station.Materials and Methods: In this research to predict monthly precipitation time series of Kermanshah’s synoptic station, five parameters namely: monthly precipitation average, relative humidity average, Maximum temperature average, minimum temperature average and wind speed average, were used within the forty years period (1970-2010). In order to quality control of given statistic and information, sequencing test is used. The results showed that given information is significantly homogeneous and according to nonlinear specifications of multiple time scales, neural network and wavelet model is used to precipitation prediction.Results: In order to precipitation prediction, four parameters of relative humidity average, maximum temperature average, minimum temperature average and wind speed average, were used and using wavelet alternation decomposed into 8 sub-series and then these series were used to future monthly precipitation prediction as the entrance neural network model data. The correlation coefficient (R=0.874) of next month prediction denoted the relatively low efficiency of the neural network while the wavelet-neural network model correlation coefficient is 0.94.Also, both model prediction precision decreases by increasing the number of output neurons delays. It should be noted that Meyer wavelet is used to wavelet- neurotic network prediction which has a high precision. Regarding the F statistic, variance analysis of homogeneity and heterogeneity indices of observed and predicted precipitation, is homogeneous in the confidence level of %99 (P<0.008).Conclusion: The comparison between the driven results from wavelet conversion-neural network and driven results from a neural network application, showed that wavelet-neural network method had higher predicting precision than neural network and also predicting precision in both models decreases through increasing the number of delays of exit neurons. It is noteworthy that Meyer wavelet was used to neural network predicting which its simulated results had high precision.

Background and Objectives: Qualitative and quantitative management of water resources to meet the demand for different usages is the major approach in each country policy. In this regard, dam reservoirs water quality monitoring is an important step in the management of these resources. Previous researches described in this study, show that, artificial neural network based models can be used to predict the qualitative indices of water resources efficiently. The objective of this study is to develop an efficient model in order to predict the concentration of dissolved oxygen in the dam reservoir.Materials and Methods: The data used in this study consisted of monthly dissolved oxygen data from January 1998 to December 2007 were obtained from Boulder reservoir, Colorado, (USA). This study investigated the prediction of dissolved oxygen in a gauging station in the reservoir by artificial neural network, multi linear regression and conjunction of wavelet analysis and artificial neural network models. In the proposed wavelet analysis and artificial neural network model, observed time series of dissolved oxygen was decomposed at different scales by wavelet analysis. Then, total effective time series of this water quality index was imposed as inputs to the artificial neural network model for prediction of one month ahead dissolved oxygen.Results: Results showed that the wavelet analysis and artificial neural network combined model performance were better in prediction rather than the artificial neural network and multi linear regression models. Using wavelet analysis improved the modeling results considerably. In the combined model, E, and RMSE is obtained 0.96 and 0.22 respectively. Artificial neural network and the combined wavelet with artificial neural network models produced reasonable predictions for the minimum values that lead anaerobic condition in reservoir.Conclusion: The results showed that using wavelet analysis in conjunction with artificial neural network, improved the modeling performance. Also the results of this research indicate that the wavelet analysis and artificial neural network combined model is a promising model for dissolved oxygen predicting in reservoirs such as those found in Boulder reservoir.

Background and Objectives: Since the river flow forecasting is an important issue in water resources engineering, the researchers have considered and applied different methods in this field. In recent decades the artificial intelligence (AI) methods emerge as a powerful tool for detecting the relationship among different variables of hydrological systems. Support Vector Machine and Bayesian networks are two types of artificial intelligence methods which are widely used in recent years for river flow forecasting.Materials and Methods: In this study, Support Vector Machines (SVM) and Bayesian networks (BNs) methods were used to forecast daily discharge of the Baranduz Chai River. The support vector machine was a novel neural network algorithm and originally applied to pattern recognition problems and regression. In recent years, decision support systems (DSS) have been developed to integrate the best available knowledge for making appropriate decision. Among the various kinds of DSS, Bayesian networks have proven quite useful since this modeling approach can integrate quantitative information and data as well as qualitative expert knowledge.Results: The daily discharge data of the Baranduz Chai River measured at the Dizaj hydrometric station during 2006 to 2010 were used for modeling, which 80% of the data were used for training and remaining 20% used for testing of models. In order to model river flow by SVM and BNs methods, the river flow discharge of over 5 days with daily time steps were used and the results evaluated based on root mean square error (RMSE), correlation coefficient (R) and Nash-Sutcllife (NS) criteria. The results showed that at first, the accuracy of models increased with increasing of memory, as the most accuracy obtained for combination #3 of input variables in both of the methods. Comparing the performance of SVM and BNs models indicated that the accuracy of the SVM method with the R=0.976, RMSE=1.80 (m3/s) and NS=0.949 was slightly more than BNs method with R=0.964, RMSE=1.96 (m3/s) and NS=0.921.Conclusion: According to obtained results, it can be concluded that the performance of SVM and BNs models are close together, but both of considered models had a remarkable error in estimating high discharge values. However, the SVM model had better performance than BNs in forecasting average and the minimum discharge values.

Background and Objectives: Already many studies have been done on the mechanism of scour around hydraulic structure especially bridges and methods for control or reduction of scour around them have been investigated and evaluated. In the field of scour around bridges, researches are more focused on scour of piers in compare with abutment. While the review of available information on the bridge required cost, the major problems are related to abutment. Therefore most costs has been spent in this part.Materials and Methods: In this study, the performance of vane attached to the bridge abutment and the influence of parameters such as height and angle of the vane installing in the reduction of local scour around bridge abutment were investigated.Results: The results showed that the installing angle and height of vane had a significant impact on the reduction of abutment scour. By increasing of the vane height, the performance of vane will be improved. Also the results showed that installing angle of 40° for vane is most appropriate angle. Following this research, three-dimensional components of velocity were determined with electromagnetic velocimeter around abutment with attached vane.Conclusion: Investigation of flow pattern around bridge abutment in case of using submerged vane showed that, this structure had an effective role on reduction of local scour by creating a low velocity zone around bridge abutment and control of primary vortexes.

Background and Objectives: The ways of dealing with density include control of soil moisture during tillage, the control of vehicle's traffic on the soil, weight reduction and vehicle's contact pressure with soil and changing of soil structure by adding organic material.Materials and Methods: In order to study the effect of organic materials and zeolite and their mutual effect at different moisture stages on resistance to pentrometer penetration, organic material factor in four levels (0, 0.5, 1 and 1.5 percent), zeolite factor in four levels (0, 8, 16 and 24 tons per hectare), also soil moisture levels which are in two dry and wet stages at five levels (saturation, capillary crack, final crack, return final crack to capillary crack and when the crack have destroyed) were examined in three replicates as the factorial based on complete randomized blocks design in Rice Research Institute.Results: The results showed that adding plant residues has increased resistance to pentrometer penetration in soil to 37 percent, the reason of increased resistance to pentrometer penetration in treatments containing plant residues, is the levels of plant residues which aren' t decomposed. While adding plant residues causes reduced resistance to pentrometer penetration will accelerate in wet process. It was also found that resistance to pentrometer penetration with subsidence of soil, volume shrinkage of soil, bulk density and soil moisture content highly correlated (0.7811-0.9916).Conclusion: Finally it's recommended that in order to reduce of the resistance to pentrometer penetration, plant residues must be added to the soil for long time.

Background and Objectives: Regarding the recent droughts, water resources management and prioritization of water allocation to different demands are important and essential issues. The amount of water allocation in storage dams at different months is determined based on reservoir storage. Therefore, the objective of this study is to determine the suitable operation policy regarding the sum squares of water deficit.Materials and Methods: In this study the Standard Operation Policy (SOP) and Yield models were developed for planning and water resources management. In these models amount of water release from reservoir is determined by storage volume at beginning of the period. For assessment of models efficiency in development of rule curve, Shahid Rajaei dam was studied.In mentioned models, river discharge in dam site and middle basin between Shahid Rajaei dam and Tajan diversion dam were used. By means of these models, five operation scenarios consisted of supplying 100 percent of drinking, industrial and environmental demands; with 40 to 80 percent of agricultural demand from the reservoir were simultaneously investigated.Results: In the first, second and third operation scenarios, deficit sum squares in Yield model compared to SOP model was less, equal to 83.72, 63.32 and 34.70 percent; respectively. In the fourth and fifth operation scenarios this parameter in the Yield model was greater than SOP model. Average annual water deficit in the SOP and Yield models was 23.6 and 15.16 MCM; respectively. Average and minimum reliability in Yield model were 3.81 and 52.29 percent more than SOP model; respectively; whereas, maximum vulnerability in Yield model was 80 percent less than SOP model.Conclusion: First, second and third operation scenarios with the aim of supplying 100 percent drinking, industrial and environmental demands and 60, 70 and 80 percent agricultural demand were acceptable with sum squares of water deficit of 3.97, 2.23 and 0.99; respectively. Fourth and fifth operation scenarios with the aim of supplying 100 percent drinking, industrial and environmental demands, and 40 and 50 percent agricultural demand were not acceptable with sum square of water deficit of 8.93 and 6.20; respectively.

Background and Objectives: Optimizing the operation of reservoirs is the most important issue in water science and engineering which has been resolved through a variety of traditional optimization methods. One of these methods is optimizing using the meta-heuristic algorithms.The researchers around the world show the performance of meta-heuristic algorithms performance has been far better than procedures such as linear programming. The aim of this study is to evaluate the performance of imperialist competitive algorithm (ICA) and ant colony algorithm (ACO) with application of chain constraints.Materials and Methods: In this research, ICA, is used to solve the optimization problem of reservoirs operation. The approach taken in this research is application of relationship continuity in determining the initial position of countries, which has been proposed as a chain constraints.The results of applying the chain constraints and lack of application of the chain constraints have been compared and consequently these results have been compared with one of well -known algorithm named as ant colony algorithm.Results: The results indicated that imperialist competitive algorithm without considering the continuity equation, was rarely able to find possible answer and applying the chain constraints to determine the initial position of countries, enhanced the performance of algorithm more efficiently and it leads to even better performance compared to ant colony algorithm and find an appropriate value for the objective function, so that after running ten times, the mean for objective function for imperialist competitive algorithm was 15.822 and for ant colony algorithm was 48.008.Conclusion: Result have shown with chain constraints the ICA and ACO algorithms have been unable to find feasible solution and their performance is fairly high. Therefore the chain constraints can be applied as an essential element in enhancing the efficiency of these algorithms. Also the results of the comparison between the algorithms has shown that ICA algorithm performance has been far better than ACO algorithm.

Background and Objectives: Complexity, variety and improper management of agricultural contaminants and high volume of water losses due to improve design and management of irrigation and drainage systems increase share of agriculture in water resources, soil and environment contamination. Control and reducing of nitrogen pollution caused by fertilizer is needed to understand the biological cycle in the ecosystem. Simulation models are effective tools for understanding complex processes such as the nitrogen cycle in soil. The aim of this study was to simulate nitrogen cycle and evaluate the impact of soil moisture content on denitrificaton rate under furrow fertigation systems using HYDRUS–1D model.Materials and Methods: To achieve the aim of this study, field experiments were conducted under constant furrow fertigation in the furrow with 83 meters length and clay loam soil texture in Karaj in 2007. HYDRUS-1D was used to simulate nitrogen cycle in fertigation. The conversion coefficients of nitrogen cycle included dispersion coefficient and order conversions from the parameters of nitrogen cycle based on observational data, soil moisture and nitrate concentrations using inverse modeling techniques that were obtained. To study plant effect on the nitrogen cycle, the model is studied in presence and absence of plant.Results: The results showed that modified Van Genuchten method performance with mean of soil nitrate concentration (mg/l) and moisture (%) RMSE=0.02879 and R2=0.9899, considering presence of plants better estimate of parameter values of nitrogen cycle concentrations in corn furrow irrigation. Also, maximum soil moisture that denitrificaton occurred, was obtained in 50% of the saturation moisture. Using denitrificaton coefficient in the simulation of the nitrogen cycle in corn fertigation led to improve in results.Conclusion: The results showed that soil hydraulic properties and plant had more effect on nitrate changes to nitrite and nitrogen gas forms than anaerobic percentage of soil profile.

Background and Objectives: To increase productivity of paddy fields, a suitable management of midseason drainage can be considered. Due to the effect of soil moisture and dry duration on the characteristics of soil cracks, this study was conducted to investigate the effect of surface midseason drainage duration in paddy fields of Tarom-Hashemi rice cultivar on surface cracks of soil.Materials and Methods: A field experiment was done with the six surface drainage duration treatments of 0, 5, 7, 9, 11, 13 days and three replications at Haraz Extension and Technology Development Center. The planted area was 360 m2. The values of daily soil moisture were measured during midseason drainage for different treatments. Also, there were identified 12 points of each plot on a 1´1 network and the soil cracks characteristics (length, width and depth) were measured in these points. After harvesting, the soil bearing capacity in experimental plots were measured using a cone penetrometer in five depth (5, 10, 15, 20 and 25 cm).Results: Base on the results, the effects of surface midseason drainage duration on length, width and depth of the soil cracks were significant. Maximum width and length of the soil cracks were 7 mm and 10 cm, respectively, which were gained by 13-day drainage duration treatment.Application of the 11 and 13 days drainage duration treatments significantly increased the depth of soil cracks. Also, for the values less than FC, a little decrease in soil moisture resulted in a considerable increase in soil cracks length and width. For different depth of soil from 0 to 25 cm, the mean difference between the highest (13-day drainage duration treatment) and lowest (control) measured soil bearing capacity was gained 228.8 kPa.Conclusion: With considering the maximum soil crack depth be less than hardpan depth, applying 17-day midseason drainage duration in study area is recommended. Increasing soil bearing capacity at the harvesting time will make the land ready to apply agricultural machines that minimizes energy consumption and working hours. Therefore, the conditions will be more suitable for the cultivation of secondary products.

Background and Objectives: Mineral weathering and the release of nutrients such as potassium increase in the presence of microorganisms. Arbuscular mycorrhizal fungi and plant growth promoting bacteria in addition to improved plant growth and nutrition and physical, chemical and biological soil properties can support host plants against environmental stresses such as drought. Considering the limited information, this greenhouse study was carried out to evaluate the effects of microbial and environmental agents on different forms of potassium in a calcareous soil and also potassium absorption by maize plant.Materials and Methods: A greenhouse experiment was set up with a completely randomized design and factorial arrangement in three replications. The factors were consisted of arbuscular mycorrhizal (AM) fungus at two levels: G0 (not inoculated with fungus) and G1 (inoculated with Glomus intraradices), bacteria at two levels: B0 (not inoculated with bacterium) and B1 (inoculated with Pseudomonas fluorescence) and drought stress at four levels: S0 (without stress), S1 (%75 FC), S2 (%50 FC) and S3 (%25 FC). After plant harvesting, shoot dry weight, potassium concentration and uptake in aerial parts and root colonization with standard methods were measured. The soil samples were air- dried and used for determination of different forms of potassium and then the results analyzed.Results: As drought stress increased, the concentration of potassium different forms and uptake increased and root colonization percent decreased. Co-application of mycorrhizal fungus and bacterium significantly increased root colonization percent. With increasing drought stress levels, single using of fungus and co-application of mycorrhizal fungus and bacterium in comparison with non inoculated treatments increased the concentration of potassium different forms in soil and its uptake by plant.Conclusion: Plant growth promoting bacterium, mycorrhizal symbiosis and their interactions have significant positive effects on potassium uptake and their different forms in soil.

Background and Objectives: The main cause of collapse of bridges is scour around bridge piers. Therefore, knowledge about the effective parameters and estimation of maximum scour depth has an important role on the safe design of bridges in rivers. The aim of this research is evaluation of optimized ANFIS parameters with GA on prediction of maximum scour depth and comparison with all FIS generator of Matlab Toolbox ANFIS.Materials and Methods: To evaluate prediction of scour depth around inclined bridge piers located on rectangular foundation using optimized ANFIS parameters with GA and Matlab ANFIS, 48 sets of experimental data of scour around incline bridge piers were used. To compare the performance of results, R2 and RMSE were utilized.Results: Analysis of results showed that GENFIS1 generator of ANFIS toolbox in Matlab had the best performance, which could predict maximum scour with R2 and RMSE, 0.976 and 0.053, respectively. Comparison of the predicted scour depths indicated that optimization of ANFIS parameters had better desired parameters prediction with R2 and RMSE, 0.992 and 0.02537 in comparison of ANFIS toolbox in Matlab.Conclusion: Comparison of results indicated that both ANFIS toolbox in Matlab and optimized ANFIS could predict desired output, but the study are encouraging and suggest that an optimized adaptive neuro-fuzzy approach is a powerful tool to model scour depth around inclined bridge piers group which could reduce RMSE from 0.053 to 0.0254.

Background and Objectives: Due to limited water resources, only 8.7 million hectares of total 165 million hectares of total area of Iran can be used for production of irrigated crops. Increasing human population and scarcity of water resources have resulted in more attention for rainwater harvesting. Based on climate, topography, soil type, soil permeability and different types of agricultural products rainwater harvesting methods are different. The rainwater harvesting technique has been used for cultivation of fruit trees in the 200 to 250 mm rainfall per year and obtained suitable results. Rainwater harvesting also increase the establishment ability of seedlings of rangeland plants. So, the rainwater harvesting method can be used as a convenient method to increase water resources in natural resources and agriculture land to increase the available water. Locating the appropriate field is the most important step in the implementation of rainwater harvesting system. The considerable time and money savings has been made with the identification of suitable sites for this purpose. The aim of this research is to develop a framework to locate the areas for water harvesting.Materials and Methods: To assess the potential for runoff generation, a conceptual model of rainfall- runoff has been applied. Integrating this conceptual model and Arc GIS, spatial distribution of runoff potential across the study area has been estimated. Then, prioritization of areas and sub watershed for surface water harvesting purposes has been carried out based on physical and economic index. The benefit/cost indicator has been used in the economic analysis.Results: The results showed that these economically prioritized sub watersheds are those with higher total amount of surface water harvesting potential while have lower establishment costs.Conclusion: Water harvesting can be used to minimize water loss and augment water supplies in watershed systems. Water scarce countries such as some parts of Iran are facing to poor rainfall distribution. Recent initiatives focus to explore more efficient alternatives to water supply and recognition of numerous opportunities to implement runoff harvesting as a means to supplement water availability. The most important step in making use of rainwater harvesting systems is appropriate site selection. Identifying appropriate areas for water harvesting systems results. The aim of this research is developing a framework for spatial assessment of rain water harvesting potential. It worth to mention that an extensive data set has been used for the spatial assessment purpose. The proposed methodology improve the capability for water resource management in the Golbahar and other similar watersheds. The proposed methodology in this study, has utilized the Geographical Information System as a powerful and useful tool in prepering processing, in integrating, and extracting required information from various data layer for spatial assessment. Therefore, by identification and allocation water harvesting system to the most suitable areas, while increasing efficiency of this system a remarkable saving in the time and cost is gained.

Background and Objectives: Nowadays, investigations to forecast the hydrological variables behavior and the effective climatological factors on it in the time domain are considered by researchers. Therefore, the usage of time dependent data analysis in the prediction of river discharge rates is statistically valid and so that the results can be used in the planning and management of water resources and infrastructure design.Materials and Methods: The study area was Atrak River which is one of the most important water resources in economic, agricultural and environmental point of view in the North East of Iran. In recent years, this river had overflow or decline of the water levels that certainly affected on river discharge rates. In this paper, we use the data of the six hydrometric stations from 51-52 years till 81-82 years of the catchment Atrak River.Results: First we have paid attention to the descriptive analysis of data and then we fitted a suitable model to the discharge time series data of considered stations after removing trend and the seasonal variations. Finally, through estimating the parameters of the model, we predicted the distribution behavior of the river flow rate. We used Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) and Mean Square Error (MSE) for fitting model and estimating the parameters of the fitted model. After fixing the variance of the data and remove the trend and seasonality variations and by using the Auto-correlation and Partial Auto-correlation plots, ARIMA (1, 0, 2) (1, 1, 2) 12 model was admitted. Finally, using this model, future values Atrak river discharge rates were forecasted for the year.Conclusion: Since Atrak river basin has been both mountainous and plain, as well as its climate is constantly changing, therefore special attention to changes in trends and seasonal variations in hydrometric stations in this area before fitting a time series model and forecasting is necessary. Otherwise the statistical analysis of time series analysis may yield to the bias results.

Background and Objectives: Trees play an important role in all terrestrial ecosystems. Trees can have a main impact by their root system and canopies on conservation, fertility and improve quality of soil. Studies conducted in context of the effect of trees on soil properties indicate that presence of trees have been an important role in improving soil properties under their canopy. Considering the importance and role of trees on the surrounding soil properties, trees management is essential in Programs principles of soil conservation and fertility. One thing that should be considered in this context is the canopy of trees. Therefore, in this study has been paid to investigate of effect of olive trees canopies in an agroforestry system on soil organic matter and nutrient.Materials and Methods: For this study was considered the land under agroforestry system (wheat cultivation in between olive trees) and land under wheat cultivation (control area). In agroforestry system, was considered three treatments of canopy cover: canopy cover with small area, canopy cover with moderate area and large canopy cover. Organic matter was used titration method and soil nitrogen was calculated by using correlation between nitrogen and organic matter. Soil soluble phosphor was determined by Olsen method and spectrophotometer. Measurement of potassium was determined by using ammonium acetate method and flame photometry. Mean weight diameter was measured by wet sieving. To analyze the data from laboratory results were used by SPSS and Excel. For comparison of means were used by test least significant difference (LSD).Results: The results show that different treatments of canopy cover have a significant effect on organic matter, phosphorous and mean weight diameter at 1% and 5% level of significance. Significant correlations have not been observed between different treatments of canopy cover and soil potassium. As a result of the implementation of agroforestry system, increased amount of organic matter from %0.22 to %1.49, nitrogen from %0.01 to %0.074, phosphorus from 0.79 to 1.22 mgL-1, potassium from 4.94 to 6.95 mgL-1 and mean weight diameter from 0.04 to 0.15 mm.Conclusion: The presence of litter fall and wheat debris under trees increased soil organic matter and nutrient and improve soil properties. Agroforestry system can be as an approach to increase of soil fertility and help to prevent of soil erosion especially in arid zone because of combination of several different systems (trees, crops and pasture). Today, due to increase of population has followed increasing demand for food. This led to increased utilization of agricultural land and loss of soil fertility. Agroforestry system as a sustainable agricultural can increase soil fertility in long term.