نشریه آب و خاک
سال سی و یکم شماره 1 (پیاپی 51، فروردین و اردیبهشت 1396)

Evaluations show the necessity of using optimization models in order to determine optimal allocation of water in different water conditions. Its use can be proposed according to developed model abilities in this study in order to optimize water productivity and provide sustainable management and development of water resources over irrigation and drainage networks. Basic needs of the earth growing population and limitation of water and soil resources remindnecessity of optimal use of resources. World’s more than 280 million hectare lands are covered by irrigation networks (Khalkhali et al., 2006). The efficiency of most projects is between 30-50 percent and studies show that performance of most irrigation and drainage networks is not desirable and they have not achieved their aims. Hirich et al. (2014) Used deficit irrigation to improve crop water productivity of sweet corn, chickpea, faba bean and quinoa. For all crops, the highest water productivity and yield were obtained when deficit irrigation was applied during the vegetative growth stage. During the second season 2011 two cultivars of quinoa, faba bean and sweet corn have been cultivated applying 6 deficit irrigation treatments (rainfed, 0, 25, 50, 75 and 100% of full irrigation) only during the vegetative growth stage, while in the rest of a crop cycle full irrigation was provided except for rainfed treatment. For quinoa and faba bean, treatment receiving 50% of the full irrigation during the vegetative growth stage recorded the highest yield and water productivity, while for sweet corn applying 75% of full irrigation was the optimal treatment in terms of yield and water productivity. Moghaddasi et al. (2010) worked examines and compares this approach with that based on the optimization method to manage agricultural water demand during drought to minimize damage. The results show that the optimization method resulted in 42% more income for the agricultural sector using the same amount of water allocated in the 1999 drought. This difference emphasizes the importance of water allocation with respect to growth stages rather than simply cutting allocations on an equitable basis to combat water scarcity. However, managing the system using the optimization method is more complex and requires a new framework and planning to make it operational.
Qazvin irrigation network in Qazvin province is located in 150 km West of Tehran, between 36˚ 20΄ north latitude and 49˚ 40΄ east longitude and 36˚ 00΄ north latitude and 50˚ 35΄ east longitude. Net water requirement of cultivated crops in the irrigation network is 109.798 million m3. According to the total efficiency of the irrigation network, an impure water requirement of cultivated crops will be 304.994 million m3. The inlet water from Taleghan dam into irrigation network is 274.8 million m3 that compared to impure water requirement decrease 10%. The current study was conducted in 5 options, including: option 1 (current conditions and supplied water volume of 274.8 million m3), option 2 (optimized current conditions using LINGO software and supplied water volume of 274.8 million m3), option 3 (30% water deficit and supplied water volume of 192.36 million m3), option 5 (40% water deficit and supplied water volume of 274.8 million m3). Water requirement of crops is determined using meteorological data with 30 years long term statistics and CROPWAT8 software.
Results Studying different scenarios of water deficit in network shows that products such as tomatoes, potatoes and alfalfa have the least changes in real production to potential production and yield ration in barely did not show significant difference in all options. In all of the options, tomatoes with water productivity indicator of 3029 rials/m3 have the maximum productivity index and sugar beets with water productivity indicator in options 2 to 5 as 479, 310, 307 and 268rials/m3, respectively has the minimum productivity index. Therefore, in water deficit conditions, the priority of water distribution in all options is for tomatoes and the last priority for sugar beets. In all of the options, wheat, barley and canola ascend in productivity index and corn and sugar beets descend in productivity index.
Studying water- production index shows that considering instructions will result in optimal productivity that in turn will increase production and network total income. Optimal model results show that drought effects can be satisfied with optimal and targeted management in allocating water, so that network total income has not reduced in stress occurrences compared to network net income. Optimization method in model development has been selected according to aim of model and it is proposed that model results to be assessed by non- linear optimization methods. It is proposed that, different scenarios of climate are studied in region according to climate changes and optimal allocation of water is prepared according to the effect of these scenarios on temperature increase, raining decrease and products water need increase in present cultivation method. For model efficiency increase, it is proposed that using neural networks capabilities, intelligent prediction of the input discharge to the network is done and the possibility of comprehensive management and timely combining of network with water allocation optimal model is provided.

The critical role of the rivers in supplying water for various needs of life has led to engineering identification of the hydraulic regime and flow condition of the rivers. Hydraulic structures such dams have inevitable effects on their downstream that should be well investigated. The reservoir dams are the most important hydraulic structures which are the cause of great changes in river flow conditions.
In this research, an accurate assessment was performed to study the flow regime of Karkheh river at downstream of Karkheh Reservoir Dam as the largest dam in Middle East. Karkheh River is the third waterful river of Iran after Karun and Dez and the third longest river after the Karun and Sefidrud. The Karkheh Dam is a large reservoir dam built in Iran on the Karkheh River in 2000. The Karkheh Reservoir Dam is on the Karkheh River in the Northwestern Khouzestan Province, the closest city being Andimeshk to the east. The part of Karkheh River, which was studied in this research is located at downstream of Karkheh Reservoir Dam. This interval is approximately 94 km, which is located between PayePol and Abdolkhan hydrometric stations. In this research, 138 cross sections were used along Karkheh River. Distance of cross sections from each other was 680m in average. The efficient model of HEC-RAS has been utilized to simulate the Karkheh flow conditions before and after the reservoir dam construction using of hydrometric stations data included annually and monthly mean discharges, instantaneous maximum discharges, water surface profiles and etc. Three defined discharges had been chosen to simulate the Karkheh River flow; maximum defined discharge, mean defined discharge and minimum defined discharge. For each of these discharges values, HEC-RAS model was implemented as a steady flow of the Karkheh River at river reach of study. Water surface profiles of flow, hydraulic parameters and other results of flow regime in HEC-RAS model were obtained for the conditions before and after the construction of the Karkheh Reservoir Dam and then it was reviewed and analyzed.
By exploiting the Karkheh Reservoir Dam, the river flow was changed from the natural condition to the regulatory situation. The results indicate that the river flow was considerably declined because the regulatory effect of the reservoir dam which has contributed to the great alternations at hydraulic parameters of the river. For example, the mean annual discharge of the Karkheh River shows 44pecent reduction during the time period of simulating (after the dam construction in comparison with the natural river flow before construction of reservoir dam) in PayePol hydrometric station. Flow velocity of Karkheh River is influenced by discharge, slope of the river channel and geometry of cross section. By increasing the river flow, the flow velocity has increased and there is a significant difference between pre and post-dam condition at the mean velocity of river flow in different sections. The flow area is directly influenced by river discharge and there is a significant difference in the maximum defined discharge before and after dam construction. The width of water surface is a parameter of the geometric situation of the river cross section that also shows the maximum width of the cross sections, passing discharge through the desired cross section. Since Karkheh River has a relatively large water surface width, it has a high wetted perimeter. For this reason, the Karkheh river hydraulic radius is usually low. The significant reduction of all these quantities is for reduction of flow rate by construction of Karkheh Reservoir Dam. Studying the water surface profiles represents reduction of water level in the longitudinal profile of Karkheh River and water level of hydrometric stations by construction of the Karkheh Reservoir Dam. Also, due to the reduction of the discharge in the downstream of Karkheh Dam, all hydraulic parameters of the river such as flow velocity, flow area, width of surface water, hydraulic depth, shear stress and the hydraulic radius have been changed. In general, it can be concluded that the construction of a large dam such as Karkheh Reservoir Dam has a significant effects on the flow regime conditions at river downstream. Our survey would be helpful for environmental, geological and ecological experiments on effects of dam construction and for engineering next hydraulic structures on such rivers.

In alluvial streams, water flow affects the sediment and transports them to the downstream constantly. In the meantime, bed forms will be created on stream bed with various dimensions and in different conditions. In this paper experiments have been done to study the influences of width reduced transitions on the height of ripple forms. These transitions are made with different angel 5, 10 and 15 degrees. Based on Van Rijn (7), when the sediment particles are smaller than 500 μm, if the flow velocity exceeds about 10 to 20 percent of critical velocity for starting the particle movement, small ripples grow on the bed surface. Ripple profiles have an asymmetric shape which has steep slope at the upstream and mild slope at the downstream. If the particles are bigger, flow velocity should be higher too in order to create taller ripples and in this situation a variety of bed form height and length will occur. There is a lot of research associated to bed form formation in alluvial beds like Van Rijn (4 and 7), Karim (2009), Omid and et al (2010), Chegini and Pender (2012) and Esmaili and et al (2009). But in none of them a width reduced transition has applied. The mail part of this research is specified to the effects of width reduced transitions on the dimension of ripple bed form.
Methods and Materials: Experiments were done in the hydraulic laboratory of water engineering faculty of Tabriz University. The flume had a 6 m long, 50 cm height and 50 cm wide flume. The α (angle of transition at the beginning) was different. The sediment particles had D_50=0.86 mm and ρ_s=2300gr.〖cm〗^(-3). The sediment flow was directly injected to the main flow from the upstream carefully. Water level was measured with scales installed on the glass wall of the flume and sediments were collected with the help of a sand trap located at the end of the flume. Experiments were classified in three discharges of 10, 12 and 14 L.S-1and in 0, 0.006, 0.009, 0.012 and 0.015 slopes of the channel. π Buckingham method was used to obtain a dimensionless relationship such as ∆/y=f(F_r,α). In which the ∆ is the bed form height, y is the flow depth, Fr is the Froud number and the α is the transition angle at the beginning part of it. To compare the situation of having transitions with the absence of any transition, was studied as a witness type. Totally, 136 experiments were done.
The changes in the bed form height based on different Froud Numbers, are exhibited in a series of curves. Basically, transitions which shortened the flow width, in low discharges, the initial walls of these transitions act like a barrier and absorb a significant amount of flow intensity. Therefore, when there is no such a transition, it is accepted that the flow has more freedom and as a result bed form height will grow bigger. Naturally, if the reduction of the channel width was milder, the barrier effect on the flow would be smaller slight. In study of bed form shaping and its height, in low discharges (e. 10 L.S-1) the flow intensity is not strong enough to conquer the barrier role of the transitions and however with increasing angle of the transition, the bed forms height in the transition area decreased. For the 12 L.S-1discharge the flow intensity is more and the power of entering flow to the transition is higher and ripples with taller height exist. But the point is that the 12 lit.s^(-1) is still a transition stage, it means that when the discharge reaches to 14 L.S-1, the bed form height has increased about 10 to 12 percent, comparing with no transitions. Another important issue is that, in any situation, transitions with α=15° have a strong barrier role against the flow and they always reduce the bed form height.
It can conclude that width reduced transitions can decrease scours slightly and therefore sediment transitions was reduced about 15 to 20 percent, compared with no transitions installed on the flume. The results show that if the discharge exceeds 14 L.S-1 or if steeper angles for the initial part of the transitions are used, the transition loses the barrier role and even they increases turbulences at the beginning and much more sediment would pass through the transition area due to higher velocities.

Groundwater is the most important resource of providing sanitary water for potable and household consumption. So continuous monitoring of groundwater level will play an important role in water resource management. But because of the large amount of information, evaluation of water table is a costly and time consuming process. Therefore, in many studies, the data and information aren’t suitable and useful and so, must be neglected. The PCA technique is an optimized mathematical method that reserve data with the highest share in affirming variance with recognizing less important data and limits the original variables into to a few components. In this technique, variation factors called principle components are identified with considering data structures. Thus, variables those have the highest correlation coefficient with principal components are extracted as a result of identifying the components that create the greatest variance.
The study region has an area of approximately 962 Km2 and area located between 37º 21´ N to 37º 49´ N and 44º 57´ E to 45º 16´ E in West Azerbaijan province of Iran. This area placed along the mountainous north-west of the country, which ends with the plane Urmia Lake and has vast groundwater resources. However, recently the water table has been reduced considerably because of the exceeded exploitation as a result of urbanization and increased agricultural and horticultural land uses. In the present study, the annual water table datasets in 51wells monitored by Ministry of Energy during statistical periods of 2002-2011 were used to data analysis. In order to identify the effective wells in determination of groundwater level, the PCA technique was used. In this research to compute the relative importance of each well, 10 wells were identified with the nearest neighbor for each one. The number of wells (p) as a general rule must be less or equal to the maximum number of observations (n), here it is the number of years. So, for each well there are a 10 * 10 matrix. It should be noted in monitoring adjacent wells to a specific well, its dataset is not used. To quantify the effect of each well according to the number of its participation in the analysis and frequency of its effectiveness, each well is ranked. In the next step, the ineffective wells were recognized and eliminated using both the variation coefficient and Error criteria. Following, the procedure will be discussed.
Results In this study, at first step using PCA technique wells were identified with a more than 0.9 correlation coefficient. Then each well ranked based on the relative importance and according to the specified thresholds, the variation coefficient and error of monitoring was estimated. The wells remain in threshold 1 led to the lowest variation coefficient, considered as effective wells in the evaluation of aquifer parameters. By eliminating ineffective wells at each threshold, the variation coefficient is reduced because of the elimination of wells with a greater difference in water depth compared to the average of whole wells. To check the certainty of obtained results, the error criteria were calculated for each threshold. According to the results, both variation coefficient and standard error of monitoring in threshold 1 come to be at least. Thus, 12 wells remain in the threshold 1 are considered as the important wells in monitoring the water table of plain Urmia. Monitoring error for these 12 wells is equal to 5.1 % which is negligible and can be introduced as index wells in sampling and estimation of groundwater table in plain Urmia. Using this method, instead measurements of water table in 51 wells it can be performed exclusively in the 12 wells.
Due to reduction of precipitation and unauthorized uses of groundwater resources, water table monitoring is very important in the accurate management of these resources. Because of extensive aquifers and large number of wells, water sampling and data collection is very time consuming and costly process, that leads to no economic justification in the lot of proceedings. Principal component analysis technique is suitable method to reduce sampling points and summarize information. In this study, at first step using PCA technique wells were identified with a more than 0.9 correlation coefficient. Then each well ranked based on the relative importance and according to the specified thresholds, the variation coefficient and error of monitoring was estimated. The results showed that the 12 wells remain in threshold 1. In this way, the cost, time and manpower required to measurements and analysis process cut into quarters.

After wheat, rice and corn, potato is the fourth most important food plant in the world. In comparison with other species, potato is very sensitive to water stress because of its shallow root system: approximately 85% of the root length is concentrated in the upper 0.3-0.4 m of the soil. Several studies showed that drip irrigation is an effective method for enhancing potato yield. Fabeiro et al. (2001) concluded that tuber bulking and ripening stages were found to be the most sensitive stages of water stress with drip irrigation. Water deficit occurring in these two growth stages could result in yield reductions. Wang et al. (2006) investigated the effects of drip irrigation frequency on soil wetting pattern and potato yield. The results indicated that potato roots were not limited in wetted soil volume even when the crop was irrigated at the highest frequency while high frequency irrigation enhanced potato tuber growth and water use efficiency (WUE). Though information about irrigation and N management of this crop is often conflicting in the literature, it is accepted generally that production and quality are highly influenced by both N and irrigation amounts and these requirements are related to the cropping technique. Researches revealed that nitrogen fertilizers play a special role in the growth, production and quality of potatoes.
A factorial experiment in randomized complete block design with three replications was carried out during two growing seasons. Studied factors were irrigation frequency (I1:2 and I2:4 days interval) and nitrogen fertilizer levels (applying 100 (N1), 75 (N2) and 50 (N3) % of the recommended amount). Nitrogen fertilizer was applied through irrigation water. In each plot two rows with within-and between-row spacing of 45 and 105 cm and 20 m length. The amount of nitrogen fertilizer for the control treatment was determined by soil analysis (N1). In all treatments, nitrogen fertilizer applied in 5 times until flowering stage. Potassium, phosphorus and microelements applied according to the soil analysis results. The subsurface drip tape was used for irrigation. Tapes with 300 µm thickness, 30 cm dripper spacing and 4 lit/hour discharge were applied. Tapes buried at 20 cm soil depth before planting. Water amount was measured by the volume meter at each irrigation treatment. Water amount calculated based on crop water requirement and plot area and irrigation frequency. On maturity stage, 8 m of two central rows of each plot harvested for determining tuber yields. Water use efficiency was calculated as the ratio of the tuber yield to the total consumed water volume. Statistical analysis was performed using MSTAT-C software. Means were compared by Duncan's multiple range tests at 0.05 and 0.01 significant levels.
Results Results of combined analysis showed that yield and water use efficiency (WUE) did not affected by irrigation frequency. Yield and water use efficiency affected by nitrogen level (p

Dynamic nature of hydrological phenomena and the limited availability of appropriate mathematical tools caused the most previous studies in this field led to the random and the probabilistic approach. So selection the best model for evaluation of these phenomena is essential and complex. Nowadays different models are used for evaluation and prediction of hydrological phenomena. Damle and Yalcin (2007) estimated river runoff by chaos theory. khatibi et al (2012) used artificial neural network and gene expression programming to predict relative humidity. Zounemat and Kisi (2015) evaluated chaotic behavior of marine wind-wave system of Caspian sea. One of the important hydrological phenomena is evaporation, especially in lakes. The investigation of deterministic and stochastic behavior of water evaporation values in the lakes in order to select the best simulation approach and capable of prediction is an important and controversial issue that has been studied in this research.
In the present paper, monthly values of evaporation are evaluated by two different models. Chaos theory and artificial neural network are used for the analysis of stochastic behavior and capability of prediction of water evaporation values in the Urmia Lake in northwestern of Iran. In recent years, Urmia Lake has unpleasant changes and drop in water level due to inappropriate management and climate change. One of the important factors related to climate change, is evaporation. Urmia Lake is a salt lake, and because of existence valuable ecology, environmental issues and maintenance of ecosystems of this lake are very important. So evaporation can have an essential role in the salinity, environmental and the hydrological cycle of the lake.
In this regard, according to the ability of chaos theory and artificial neural network to analysis nonlinear dynamic systems; monthly values of evaporation, during a 40-year period, are investigated and then predicted. So that, 10 years of data are applied to model validation and a four-year time horizon is predicted by each model. In the present paper, a multi-layer perceptron network with a hidden layer are used. Number of neurons in the hidden layer is determined by try and error. Also different input combinations are used to find out the best artificial neural network model. Prediction accuracy of models is evaluated by three indexes. These three indexes are mean absolute error (MAE), root mean squared error (RMSE) and determination coefficient (R2).
Results of chaotic parameters such as a positive lyapunov exponent and the correlation dimension non-integer slope indicate that evaporation values in the Urmia Lake have chaotic behavior. So these values have not stochastic behavior and can be predicted by suitable models. Chaos theory and artificial neural network are used for prediction in this paper. Values of MAE, RMSE and R2 for validation data are 10.96, 14.67 and 0.97 for artificial neural network and 13.47, 16.92 and 0.97 for chaos theory, respectively. The determination coefficient is the same in the two models while the values of MAE and RMSE is lower in the artificial neural network. So error indexes indicate that the artificial neural network is slightly better than the chaos theory. In order to prediction by artificial neural network, The best input combination includes four time delays that they are values of a month ago, two months ago, eleven and twelve months ago. Because in the chaos theory only the evaporation time series is applied, in order to better comparison of artificial neural network and chaos theory, in the artificial neural network model only the evaporation time series is used. Results of the four-year time horizon indicate somewhat similar behavior of two models especially in the minimum and maximum values of time series. In the maximum and minimum value chaos theory and artificial neural network predict similar values while in the other values there are some difference and the artificial neural network model predicted values less than chaos theory.
The results obtained from the chaotic nature determination parameters of the evaporation data, positive lyapunov exponent and the correlation dimension non-integer slope; indicate the chaotic behavior of study time series. Therefore, the system has a hidden pattern (i.e., the system isn’t Stochastic). The verification results indicate the high accuracy of chaos theory and neural network models - a little more accurate - and it was found that both models have similar accuracy in prediction of the future evaporation values or data that havent been recorded in the past.

Rock fragments on soil surfaces can also have several contrasting effects on the hydraulics of overland flow and soil erosion processes. Many investigators have found that a cover of rock fragments on a soil surface can decrease its erosion potential compared to bare soil surface (1, 12 and 18). This has mainly been attributed to the protection of the soil surface by rock fragments against the beating action of rain. This leads to a decrease in the intensity of surface sealing, an increase in the infiltration rate, a decrease in the runoff volume and rate, and, hence, a decrease in sediment generation and production for soils covered by rock fragments. Parameters that have been reported to be important for explaining the degree of runoff or soil loss from soils containing rock fragments include the position and size (15), geometry (18), and percentage cover (11 and 12) of rock fragments and the structure of fine earth (16). Surface rock fragment cover is a more important factor for hydroulic properties of surface flows such as flow depth, flow velocity, Manning’s roughness coefficient (n parameter) and flow shear stress and geometrics properties of formed rill such as time, location, number, length, width and depth of rill. Surface rock fragment cover is directly affected soil erosion processes in dry area specially in areas that plant can not grow because of sever dryness and salinity. Also, Surface rock fragment prevent the contact of rain drops to aggregates, decreasing physical degradation by decreasing flow velocity. The objective of this study was to investigate the effect of different surface rock fragment cover on hydraulic properties of surface flows and geometrics properties of formed rill.
For this purpose, 36 field plots of 20 meter length and 0.5 meter width with 3% slope were established in research field of agricultural faculty, Shahrekord University. Before each erosion event, topsoil was tilled and smoothed with hand tools to remove soil irregularities and soil sealing, update aggregates which come from deeper soil. Then, for beginning the experiment, surface rock fragment cover is scattered randomly on plot surface. Experiment equipment such as collecting the runoff systems installed at the end of plots. In each experiment after setting the surface flow, surface runoff inter to soil surface and testing continued for 60 minutes after starting runoff. Flow velocity was measured using a dye-tracing technique (potassium permanganate) and depth, width and length of rill were measured using a ruler. Treatments were including four level rock fragment cover (0, 10, 20 and 30%) and three rate runoff (2.5, 5 and 7.5 L min-1) with three replications that experiments were done in a factorial with randomized complete block design. Surface runoff samples were oven-dried and weighed to determine sediment loads. Sediment concentration was determined as the ratio of dry sediment mass to runoff volume, while the erosion rate was calculated as the sediment yield per unit area per period of time.
The results of this study showed that surface rock fragment cover plays an important role in water distribution. Based on the results, the positive effects of rock fragment cover on Manning’s n and the negative effect on flow velocity. Increasing surface rock fragment cover increased hydroulic properties such as flow depth, Manning’s n and flow shear stress significantly (p

Chemical pollution of surface water is one of the serious issues that threaten the quality of water. This would be more important when the surface waters used for human drinking supply. One of the key parameters used to measure water pollution is BOD. Because many variables affect the water quality parameters and a complex nonlinear relationship between them is established conventional methods can not solve the problem of quality management of water resources. For years, the Artificial Intelligence methods were used for prediction of nonlinear time series and a good performance of them has been reported. Recently, the wavelet transform that is a signal processing method, has shown good performance in hydrological modeling and is widely used. Extensive research has been globally provided in use of Artificial Neural Network and Adaptive Neural Fuzzy Inference System models to forecast the BOD. But support vector machine has not yet been extensively studied. For this purpose, in this study the ability of support vector machine to predict the monthly BOD parameter based on the available data, temperature, river flow, DO and BOD was evaluated.
SVM was introduced in 1992 by Vapnik that was a Russian mathematician. This method has been built based on the statistical learning theory. In recent years the use of SVM, is highly taken into consideration. SVM was used in applications such as handwriting recognition, face recognition and has good results. Linear SVM is simplest type of SVM, consists of a hyperplane that dataset of positive and negative is separated with maximum distance. The suitable separator has maximum distance from every one of two dataset. So about this machine that its output groups label (here -1 to ), the aim is to obtain the maximum distance between categories. This is interpreted to have a maximum margin. Wavelet transform is one of methods in the mathematical science that its main idea was given from Fourier transform that was introduced in the nineteenth-century. Overall, concept of wavelet transform for current theory was presented by Morlet and a team under the supervision of Alex Grossman at the Research Center for Theoretical Physics Marcel in France. After the parameters decomposition using wavelet analysis and using principal component analysis (PCA), the main components were determined. These components are then used as input to the support vector machine model to obtain a hybrid model of Wavelet-SVM (WSVM). For this study, a series of monthly of BOD in Karun River in Molasani station and auxiliary variables dissolved oxygen (DO), temperature and monthly river flow in a 13 years period (2002-2014) were used.
To run the SVM model, seven different combinations were evaluated. Combination 6 which was contained of 4 parameters including BOD, dissolved oxygen (DO), temperature and monthly river flow with a time lag have best performance. The best structure had RMSE equal to 0.0338 and the coefficient of determination equal to 0.84. For achieving the results of the WSVM, the wavelet transform and input parameters were decomposed to sub-signal, then this sub-signals were studied with Principal component analysis (PCA) method and important components were entered as inputs to SVM model to obtain the hybrid model WSVM. After numerous run this program in certain modes and compare them with each other, the results was obtained. One of the key points about the choice of the mother wavelet is the time series. So, the patterns of the mother wavelet functions that can better adapt to diagram curved of time series can do the mappings operation and therefore will have better results. In this study, according to different wavelet tests and according to the above note, four types of mother wavelet functions Haar, Db2, Db7 and Sym3 were selected.
Compare the results of the monthly modeling indicate that the use of wavelet transforms can increase the performance about 5%. Different structures and sensitivity analysis showed that the most important parameter which used in this study was parameter BOD, and then flow, DO and temperature were important. This means that the most effective BOD and temperature with minimum impact. Also between different kernels types, RBF kernel showed the best performance. So, combined wavelet with support vector machine is a new idea to predict BOD value in the Karun River.

Outer bank region is always exposed to destruction and scour due to secondary flow. Different methods are generally used to protect the outer bank. One of the most common and economical ways is spur dike. As an obstacle in the flow, spur dikes protect the outer bank through decreasing the velocity and forming vortexes between them and as a result sedimentation along that area. However, the spur dike increases the shear stress and local scour around the spur, especially its nose.. This study investigates the scour hole dimensions around three types of spur dike including permeable, impermeable and bandal-like spur dike which is done as a combination of permeable and impermeable spur dike. Few studies were focused on field applications and laboratory experiments to investigate the practical applicability of the bandal-like structure in natural rivers. Rahman et al. (4) Studied the prediction of main channel degradation and local scour around hydraulic structures (impermeable and bandal-like spur dikes) under non-submerged condition. Teraguchi et al. (9) Investigated the influenced of submerged condition on flow characteristics and sediment transport process caused by bandal-like structures with different spacing and alignment under live-bed scour condition through laboratory experiments.
Experiments were carried out in the Physical Modeling Laboratory of Faculty of Water Science Engineering of Shahid Chamran University, Ahwaz. The main channel consisted of a 5m long upstream and a 3m long downstream straight reaches. A 90 degree bend was located between the two straight reach. The channel was of rectangular cross section, having a width of 0.7m and depth of 0.6m, with mild bends (ratio of radius to a width equal to 4) and it was filled with almost uniform sediment with a median particle size of D50=1.5 mm. The discharges were measured using an ultrasonic flow meter, which was installed on the pipe inlet of the flume. The water elevation was regulated using the sliding gate installed at the end of the flume. Plexiglas with a thickness of 0.01m was used for impermeable part of spurs and the permeable part prepared by using steel roll piles with 4mm diameter. The most erodible area along the bend was determined and after installing the spurs, the bed surface was leveled by a plate attached to the carriage mounted on the channel. Then the inlet valve was opened slowly and the gate at the end of the flume was first closed. The discharge increased to a predetermined value so that no scour occurs at the straight reaches of the flume. Each experimental case was carried out for 3 hours under clear-water scour condition. At the end of experiments, water was carefully drained out and measurement of bed topography was done using laser bed profiles.
The most erodible area along the bend was determined using the procedure described by the U.S. Army Corps of Engineers and in each experimental case specified the critical spur in terms of the maximum erosion around it that happened at the exit of the bend (sections of 80 to 90 degree of bend) and downstream straight reach in all conditions. The centrifugal force will occur has increased the water depth at the exit of the bend. This increase in flow depth is associated with longitudinal negative pressure gradient due to this maximum velocity occurs at the exit of the bend and by this high velocity flow the shear stress increases. The characteristics of the scour hole have been shown to be affected by Froude number and this parameter has a direct relation to maximum relative scour depth and dimensions of the scour hole. The results showed that by increasing the permeability percentage, the amount of maximum relative scour hole depth, length and width decreased. The amount of relative scour depth in permeable and bandal-like spur dike decreased (62% and 55%), and (87% and 76%) for permeability of 33% and 64%, respectively in comparison with impermeable spur dike.
The effect of hydraulic structures, with emphasis in the bandal-like structures, on the scour hole geometric dimensions were investigated in this study. Five types of structures (impermeable, permeable and bandal-like with a permeability of 33% and 64%) were tested experimentally. It was found that:The increase of permeability, reduced scour rate significantly, such that, the maximum amount of depth, width and length of scour-hole was related to impermeable spur dike (with permeability of 0.0%) and the minimum amount belonged to the permeable spur dike with 64% permeability. The performance of bandal-like structures considering the erosion process around the structures show close results compared with permeable spur dikes.

Introductionin current situation when world is facing massive population, producing enough food and adequate income for people is a big challenge specifically for governors. This challenge gets even harder in recent decades, due to global population growth which was projected to increase to 7.8 billion in 2025. Agriculture as the only industry that has ability to produce food is consuming 90 percent of fresh water globally. Despite of increasing for food demand, appropriate agricultural land and fresh water resources are restricted. To solve this problem, one is to increase water productivity which can be obtain by irrigation. Iran is not only exempted from this situation but also has more critical situation due to its dry climate and inappropriate precipitation distribution spatially and temporally, also uneven distribution of population which is concentrate in small area. The only reasonable solution by considering water resources limitation and also restricted crop area is changing crop pattern to reach maximum or at least same amount of income by using same or less amount of water. The purpose of this study is to assess financial water productivity and optimize farmer’s income by changing in each crop acreage at basin and sub-basin level with no extra groundwater withdrawals, also in order to repair the damages which has enforce to groundwater resources during last decades a scenario of using only 80percent of renewable water were applied and crop area were optimize to provide maximum or same income for farmers.
Materials and methods The Neyshabour basin is located in northeast of Iran, the total geographical area of basin is 73,000 km2 consisting of 41,000 km2 plain and the rest of basin is mountains. This Basin is a part of Kalshoor catchment that is located in southern part of Binaloud heights and northeast of KavirMarkazi. In this study whole Neyshabour basin were divided into 199 sub-basins based on pervious study.Based on official reports, agriculture consumes around 93.5percent of the groundwater withdrawals in Neyshabour basin and mostly in irrigation fields, surface water resources share in total water resource withdrawals is about 4.2percent, which means that groundwater is a primary source of fresh water for different purposes and surface water has a minor role in providing water supply services in the Neyshabour basin. To determine crop cultivation area, major crops divided into two groups. two winter crops (Wheat and Barley) and two summer crops (Maize and Tomato). To accomplish land classification by using supervised method, a training area is needed, so different farms for each crop were chosen by consulting with official agricultural organization expert and multiple point read on GPS for each crop. The maximum likelihood (MLC) method was selected for the land cover classification. To estimate the amount of precipitation at each 199 sub-basins, 13 station data for precipitation were collected, these stations are including 11 pluviometry stations, one climatology station and one synoptic station. Actual evapotranspiration (ETa) is needed to estimate actual yield (Ya). Surface Energy Balance Algorithm for Land (SEBAL) technique were applied on Landsat 8 OLI images. To calculate actual ETa, the following steps in flowchart were modeled as tool in ArcGIS 10.3 and a spreadsheet file. To estimate actual crop yield, the suggested procedure by FAO-33 and FAO-66 were followed. Financial productivity could be defined in differently according to interest. In this study several of these definition was used. These definitions are Income productivity (IP) and Profit productivity (PP). To optimize crop area, linear programing technique were used.
Results and discussion average actual evapotranspiration result for each sub-basin are shown in context. In some sub-basins which there were no evapotranspiration are shown in white. And it happens in those sub-basins which assigned as desert in land classification. In figures 8 and 9 minimum amount of income and profit productivity for wheat and barley is negative, this number means in those area the value of precipitation is higher than value of evapotranspiration, so lower part of eq. 21 and 22 would be negative and in result water productivity would be negative. Since most of precipitation occurs during cold season of the year these numbers are expected. Two sub-basins of 43 and 82 has the value of negative, it means in these two sub-basins groundwater are recharging during the year 2014-2015.The maximum value of income and profit productivity belong to wheat and barley which are winter crops and mostly rain fed, so amount applied water would be so low and in result productivity increased. Among the summer crops maize has the most income and profit income which can be interpret due to their growing period and the crop types. Maize has around 110 days to reach to maturity and harvest, on the other hand tomato needs 145 days to harvest. Some plant is C3 and some are C4. C4 plants produce more biomass than C3 crops with same amount of water which leads to more productivity. The results showed that tomato should have the most changes in area reduction (0.2) and maize should have no changes in both scenarios. Crop area should reduce to 66percent of current cultivation area to maintain ground water level and only 6percent reduction in cultivation area would result in 20percent groundwater recharging.
Conclusion to save groundwater resources or even retrieve the only water resource, cultivation area must reduce if the crop pattern will not change. In this study only four crops were studied. It seems best solution is to introduce alternative crop.

Agricultural activity in Varamin plain has been faced with many challenges in recent years, due to vicinity to Tehran the capital of Iran (competition for Latian dam reservoir), and competition with Tehran south network in allocation of Mamlou dam reservoir and treated wastewater of south wastewater treatment plant. Mamlou and Latian dam reservoirs, due to increase of population and industry sectors, allocated to urban utilization of Tehran. Based on national policy, the treated wastewater should be replaced with Latian dam reservoir water to supply water demand of agricultural sector. High volume transmission of wastewater to Varamin plain, will be have economical, environmental, and social effects. Several factors effect on wastewater management and success of utilization plans and any change in these factors may have various feedbacks on the other elements of wastewater use system. Hence, development of a model with capability of simulation of all factors, aspects and interactions that affect wastewater utilization is very necessary. The main objective of present study was development of water integrated model to study long-term effects of irrigation with Tehran treated wastewater, using system dynamics modeling (SD) approach.
Varamin Plain is one of the most important agricultural production centers of the country due to nearness to the large consumer market of Tehran and having fertile soil and knowledge of agriculture. The total agricultural irrigated land in Varamin Plain is 53486 hectares containing 17274 hectares of barley, 16926 hectares of wheat, 3866 hectares of tomato, 3521 hectares of vegetables, 3556 hectares of alfalfa, 2518 hectares of silage maize, 1771 hectares of melon, 1642 hectares of cotton, 1121 hectares of cucumber and 1291 hectares of other crops. In 2006 the irrigation requirement of the crop pattern was about 690 MCM and the actual agriculture water consumption was about 620 MCM (supplying 90 percent of the demand), 368 MCM of which was supplied through groundwater and 252 MCM was supplied by surface water. In recent years supplying water from Latyan Dam to the agriculture in Varamin Plain due to water supply of Tehran and the recent droughts has been reduced to lower than half (the average 68.8 MCM). On the other hand, shortage of surface water resources has caused an additional pressure to the groundwater resources of the Plain. Excessive groundwater withdrawal and use of brackish reused waters in the southern parts of the plain has caused the quality loss in groundwater resources, so that groundwater salinity has increased about 0.5 dS/m from the year 2000 to 2011. Obviously, by continuing the present situation, in less than two decades the groundwater resources in Varamin will be either quite destroyed or unable to be used due to inappropriate quality. Another source of surface water is allocated to the Varamin Plain is treated wastewater produced from Tehran Wastewater Treatment Plant. Utilizing the phases 1 to 4 of this treatment plant, about 80 MCM (2.5 up to 4 m3/s) of wastewater is annually transferred to Varamin Plain. According to the projections, it is assumed that wastewater will be used in near future as the most important water resource to Varamin Plain. In this study, SD was applied as the system analysis method for the Varamin wastewater management. The spatial boundary of the SD model for Varamin model was the whole Varamin area, which is 1584 km2. The historical review period was from 2001 to 2011, the simulated period was from 2011 to 2036, and the simulation time interval was one year. The most important scenarios evaluated consisted of four wastewater allocation scenarios [(i) keeping the excising condition, (ii) complete allocation of Latian dam reservoir water to Tehran domestic use, allocation of 200 MCM treated wastewater during growing season to agricultural sector and 40 MCM to artificial aquifer recharge during non-growing season starting year 2016, (iii) similar to scenario number two w/o artificial aquifer recharge and (iv) similar to scenario number two plus allocating 50 MCM starting year 2021]. Mass flow or convection method by considering surface adsorption of solute was used to survey movement and adsorption of elements in soil. Adsorption isotherms delineated and determined by field and experimental measurement.
The result indicated that if raw wastewater be used till 2031, Cadmium and Copeer concentration will be outstanding and will have harmful effects on farmer’s health. Utilization of treated wastewater will be safe and will have not harmful effects on farmer’s health by heavy metals, to about 150 future years. Also, simulating result showed that Nitrate concentration in groundwater will exceed from allowable limitation for potable water in all scenarios to 2031. Application of scenarios (iv) and (iii) lead to the lowest and the highest Nitrate concentration, respectively.
In this model a systems system dynamics approach was applied to understand how various factors related to operation of wastewater and water sustainability interrelate. The developed model is capable to simulation of all factors, aspects and interactions that affect wastewater utilization. Result of this study demonstrated that SD is a useful decision support tool for sustainable wastewater management. By considering severe water shortage problems in the study area, and safe utilization of treated wastewater, treated wastewater transmission of Tehran plant to Varamin Plain can help to solve water shortage problems. Increase of treated wastewater allocation lead to decrease of raw sewage and hereby decreasing hygienic harmful effects.

Plants can uptake, bioaccumulate and immobilize different metals in their tissues. Phytoremediation technique has been used to remove hazardous substances including heavy metals from the environment. Assisted phytoremediation is usually the process of applying a chemical additive to heavy metal contaminated soils to enhance the metal uptake by plants. The main objective of present study was to investigate the effectiveness of plant growth regulators (PGRs) and a humic substance (HS) on Ni phytoremediation by maize in a Ni-pollutrd calcareous soil.
The experiment designed as a 5×3 factorial trial arranged in a completely randomized design with three replicates. Three kilograms of soil was placed in plastic pots and pots were watered with distilled water to field capacity and maintained at this moisture level throughout the experiment by watering the pots to a constant weight. The soils were polluted with 250 mg Ni Kg-1 as Ni-nitrate Ni (NO3)2. Six maize (Zea mays L.) seeds were planted 2 cm deep in soil and thinned to three uniform stands 1 week after emergence. Treatments consisted of three levels of soil application of commercially humic substance, HS, (0, 3, and 6 mg kg as Humax 95-WSG containing about 80% humic acid, and about 15% fulvic acid) and five levels of PGRs (0 or 10 µM GA3, IAA, BAP and SA). The HS was applied as split doses in three times at 15 day intervals along with irrigation water. The seedlings were exposed to aqueous solutions of HS 16 days after sowing for the first time. Prepared solutions of PGRs were sprayed three times at 15 day intervals from emergence. Seven weeks after planting, shoots were harvested and roots were separated from soil carefully, both parts were rinsed with distilled water and dried at 65°C for 72 h, weighed, ground, and dry meshed at 550°C. Root and shoot dry matter and Ni concentration and uptake and phytoremediation criteria were considered as plant responses. Data were statistically analyzed using SAS and SPSS software packages. Application of different PGRs had no considerable effect on phytoextraction or translocation efficiencies. Among the four PGRs studied application of SA and BA significantly increased mean uptake efficiency.
Among four PGRs evaluated, application of GA3 increased mean shoot dry matter yield and application of SA increased mean root dry matter yield. Application of the highest HS level (6 mg kg-1) decreased both mean root and shoot dry weight. Application of SA increased Ni concentration in both maize root and shoot. Application of BA only increased Ni concentration in maize root. Although application of the highest HS level (6 mg kg-1) caused an increase in Ni concentration in maize shoot, this effect was attributed to the influence of HS on the decrease in decreasing dry weight of maize shoot. Application of all PGRs except GA3 increased leaf greenness criterion. Addition of HS had no significant effect on leaf greenness. Application of PGRs enhanced root concentration factor (RCF) and decreased translocation factor (TF). Among PGRs evaluated, BA was the most effective on TF, and SA or BA was the most effective on RCF. However HS were not significantly influenced these phytoremediation criteria, as compared with control. The efficiency of PGRs in root Ni uptake was in the order of SA > BA > GA3 > IAA. Application of BA had a significant effect on Ni distribution among root and shoot, in comparison with other PGRs, and caused an increase and a decrease in root and shoot uptake of Ni, respectively. However HS had a negative effect on tolerance index and its application decreased root and shoot dry weights. Results showed that the values of Ni in maize root was considerably higher than that of maize shoot demonstrated that phytostabilization was the main mechanism involved in the phytoremediation of Ni by maize and application of PGRs was effective on this mechanism.
Results reported here indicated that although the addition of HS did not cause a significant effect on Ni phytoremediation, application of most studied PGRs had a positive effect on Ni phytoremediation by maize. Application of SA and BA increased uptake efficiency and RCF and application of GA3 increased shoot dry matter and tolerance index. The fact that Ni uptake by roots was significantly higher than that of shoots demonstrated that phytostabilization was the main mechanism involved in the phytoremediation of Ni by maize. According to results reported herein the addition of PGRs especially SA is likely to be promising in phytostabilization of Ni in calcareous soils polluted with this metal.

Water shortage in arid and semiarid regions is the most serious factor in limiting agricultural activities as it leads to the rapid reduction of yields from both a quantitative and qualitative perspective. Under conditions of water scarcity, leaf temperature rises, which causes plant wilting and premature senescence of leaves and, eventually, severes reduction of dry matter production. Use of high-efficient irrigation practices, improvement of soil's physical properties, and use of soil amendments such as superabsorbent polymers are some ways of compensating for water shortage, especially during the growing season. Some materials such as plant residues, manure, various types of compost, and superabsorbent polymeric hydrogels can store various amounts of water and thus increase water retention and storage capacity of soils. Superabsorbent hydrogels, which are also called superabsorbent polymers (SAPs) or hydrophilic polymeric gels, are hydrogels that can absorb substantial quantities of water. Hydrogels are a class of polymeric materials having network structures (with physical or chemical crosslinks) that are very capable of swelling and absorbing large amounts of water. These materials are formed from water-solublepolymers by crosslinking them either using radiation or a crosslinker. Superabsorbents are widely used in many products such as disposable diapers, feminine napkins, soils for agricultural and horticultural purposes, gel actuators, water blocking tapes, medicine for the drug delivery systems and absorbent pads where water absorbency or water retention is important. Water is a major constraint for crop growth in arid and semi-arid regions, as the precipitation is low and uncertain in these areas. Efficient utilization of meager soil and water resources necessitates the adaptation of appropriate water management techniques. Suitable soil moisture increases the biological activities as result of physical and chemical condition of soil improving the crop production finally.
Material and This experiment was conducted under greenhouse conditions in Shushtar city at northern Khuzestan Province using the randomized complete block design using 13 treatments and with 3 replications. Soil samples were taken from a field in the study area, air dried, and passed through a 2 mm sieve. Seven concentration (0, 0.25, 0.5, 0.75, 1.0, 1.25, and 1.5 percentage) of superabsorbent polymers (Aquasorb and Accepta) were used in greenhouse condition. Superabsorbent and 10 Kg soil thoroughly mixed in each pot. All treatments were irrigated when the plants at control showed sign of wilting. There were three replications of each treatment. NPK fertilizers were applied as urea, diammonium phosphate (DAP) and potassium sulphate (K2SO4) based the soil test. Soil samples were again collected which were analyzed for nitrate-N, total organic carbon (TOC), phosphorus and potassium, bulk density, particle density and saturation percentage.NPK of plant samples were also determined. Data were statistically analysed by Duncan test using SPSS.
Results had shown that the highest bulk density (1.515 gr/cm3) seen in control treatment and with increasing the polymer, bulk density decreased significantly to 0.91 gr/cm3 in treatment No.2. Also the treatments No. 4 and 11 shown decreasing EC significantly from 0.9 in control treatment to 0.68 in No.4. Adding superabsorbent had significant effect on Potassium amount of soil. Using superabsorbent had no significant effect on real density, pH, N amount, Phosphorous, soil organic carbon after yield harvesting in soil and amount of Phosphorous in plant. Significant increasing in number of leaves, branches, fresh weight of plant, and fruit weight with using superabsorbent polymers and the highest used polymer level (treatments No. 7 and 13) had the highest effect on fresh weight of plant which reported 47.2 g for No.7 and 90.47 g for No.13. Also using 1 percentage of Accepta superabsorbent (No.12) caused the significant increasing of fruit weight (502.9 g) instead of control (73.5 g). Based on the presented results No. 2 and 9 had the most effects on N of plants, which the N amount in control was 1.31 percentage and in No.2 and 9 were 2.88 and 2.82 measured respectively. Treatments No. 7, 8, 9, and 11 had the most measured plant potassium. Final results had shown the number of bacteria and fungi increased significantly using superabsorbent and the number of bacteria increased to 215 × 104 in No.13 and the number of fungi to 176500 in each gram of soil.
The overall results of this research had shown the promotion of physical, biological, and finally increase the yield as results of using superabsorbent especially Accepta type. Using these superabsorbent polymers in farms need more studies because of more effective climate parameters.

Land application of organic wastes and biosolids such as municipal sewage sludge has been an important and attractive practice for improving different properties of agricultural soils with low organic matter content in semi-arid regions, due to an increase of soil organic matter level and fertility. However, application of this organic waste may directly or indirectly affect soil bio-indicators such as microbial and enzymatic activities through a change in the activity of other soil organisms such as earthworms. Earthworms are the most important soil saprophagous fauna and much of the faunal biomass is attributed to the presence of these organisms in the soil. Therefore, it is crucial to evaluate the effect of earthworm activity on soil microbial and biochemical attributes, in particularly when soils are amended with urban sewage sludge. The purpose of this study was to evaluate the earthworm effects on biochemical and microbiological properties of a calcareous soil amended with municipal sewage sludge using Factor Analysis (FA).
In the present study, the experimental treatments were sewage sludge (without and with 1.5% sewage sludge) as the first factor and earthworm (no earthworm, Eiseniafoetida from epigeic group, Allolobophracaliginosa from endogeic group and a mixture of the two species) as the second factor. The study was setup as 2×4 full factorial experiment arranged in a completely randomized design with three replications for each treatment under greenhouse conditions over 90 days. A calcareous soil from the 0-30 cm layer with clay loam texture was obtained from a farmland field under fallow without cultivation history for ten years. The soil was air-dried and passed through a 2-mm sieve for the experiment. Sewage sludge as the soil organic amendment was collected from Wastewater Treatment Plant in Shahrekord. Sewage sludge was air-dried and grounded to pass through a 1-mm sieve for a uniform mixture with soil matrix.Heavy metals concentrations were found to be below the maximum permissible limits for municipal sewage sludge. After applying sewage sludge treatments, the pots were irrigated (70% soil field capacity) for three months to achieve a relative equilibrium condition in the soil. Eight adult earthworms with fully-developed clitellum were added to each pot. In the pots with both earthworm species, 4 specimen of each earthworm species was added. At the end of the experiment (90 days), soil samples were collected from treatments and were separately air-dried for chemical analysis or kept fresh and stored (4oC) for microbial analysis. Finally, data obtained from the study were analyzed using multivariate analysis.
Factor analysis led to the selection of three factors with eigen value greater than 1. The first, second and third factors were accounted for 62, 17.7 and 9.2% of the variability in soil data, respectively. The three factors together explained 89% of the original variability (i.e., variance) in the soil dataset. Consequently, three factors were retained to represent the original variability of the dataset. The first factor had 16 highly weighted variables with a negative loading for soil pH and positive loadings for other variables. The first factor, which included most soil indicators as input variables, clearly separated sewage sludge treatments. Most of the soil microbial characteristics were increased by sewage sludge application due to the high contents of organic matter and nutrients in sewage sludge, as well as low concentrations of heavy metals. Fungal respiration, bacterial respiration and microbial biomass carbon loaded heavily on the second factor with a negative loading for fungal respiration and positive loadings for bacterial respiration and microbial biomass carbon. The second factor, which included microbial biomass and community composition, noticeably discriminated earthworm treatments. In sewage sludge treatments, the dependence of E. foetidaspecies on soil microorganisms as a food source declined, because of the consumption of organic waste by this epigeic species. However, the activity and impact of A. caliginosa species from endogeic group was only related to soil microbial biomass probably due to selective feeding of soil microorganisms.
Factor analysis was used successfully in discriminating the effects of sewage sludge and earthworm either alone or in combination on soil microbial and biochemical parameters. A. caliginosa species in soils amended with sewage sludge had a positive effect on microbial community and biomass, while E. foetidaspecies had no such effect. A. caliginosa species indirectly benefited from sewage sludge application following the increase of soil microbial biomass. In summary, A. caliginosa species positively affected microbiological and biochemical properties in soils amended with sewage sludge due to its less dependence on this organic resource.

Natural environments, including soils and sediments, are open and complex systems in which physico-chemical reactions are in semi equilibrium state. In these systems, bioavailability of plant nutrients, like phosphate, is influenced by environmental conditions and concentrations of other ions such as calcium and magnesium. Magnesium is a dominant cation in irrigation water and in the soil solution of calcareous soils. Recent evidences show relative increase in the concentration of magnesium in irrigation water. Because of the importance of chemical kinetics in controlling concentrations of these ions in the soil solution and for understanding their effects of adsorption kinetics of magnesium and phosphate ions, in this research, adsorption kinetics of these two ions on goethite is investigated as function of time and pH in single ion and binary ion systems. The experimental data are described by using the adsorption kinetics equations. These data are of the great importance in better understanding adsorption interactions and ion adsorption mechanism.With respect to the importance of these interactions from both economical and environmental point of view, in this research, the kinetics and thermodynamics of phosphate and Mg2adsorption interactions were investigated as function of pH on soil model mineral goethite in both single and binary ion systems.
Kinetics experiments were performed in the presence of 0.2 mM magnesium and 0.4 mM phosphate in 0.1 M NaCl background solution and 3 g L-1 goethite concentration as function of pH and time (1, 5, 14, 24, 48. 72 and 168 h) in single ion and binary ion systems. After reaction time, the suspensions were centrifuged and a sample of supernatant was taken for measuring ions equilibrium concentrations.Phosphate concentration was measured calorimetrically with the ammonium molybdate blue method by spectrophotometer (Jenway-6505 UV/Vis). Magnesium concentration was determined by atomic absorption spectrophotometer (AA-670Shimadzu AA/FE). The amounts of adsorbed ions were calculated from the difference of the initial and the equilibrium concentrations. The experimental data were described by using the several widely-used kinetic models. Models performance was evaluated based on their ability to describe experimental data and obtained values for coefficient of determination (R2) and standard error of the estimate (SE).
The results demonstrate that phosphate and magnesium adsorption on goethite reached equilibrium within the 24 h equilibration time. The equilibration time is, however, pH-dependent. No systematic differences are observed among time-dependent adsorption isotherms for phosphate at pHpHPZC. It seems that the effect of pH on kinetics of phosphate and magnesium adsorption is related to the mineral surface charge, which influences electrostatic interactions between the ions and the surface charges.thus electrostatic attractive and repulsive forces dominantly control the reaction. The equilibration time for phosphate and magnesium adsorption on goethite was calculated to be ≤1 h when electrostatic forces are attractive and approximately 24 h when electrostatic forces are repulsive. In binary ion systems, phosphate and magnesium enhanced the amount and accelerated the adsorption rate of each other. Adsorption of phosphate could reverse electrostatic forces from repulsive to attractive for the adsorption of magnesium and vice versa. Also, because of the smaller ionic radius of magnesium (0.065 nm) in comparison with phosphate (0.22 nm), reduction in equilibration time of magnesium adsorption in the presence of phosphate could be partly diffusion-controlled. Fitting different kinetic models on experimental data showed that pseudo-second order model can successfully describe phosphate and magnesium adsorption data in both single and binary ion systems with highest determination coefficient (R2~0.99) and lowest standard error of the estimate (SE

In recent years, because of the presence of industrial factories around the Isfahan province of Iran and high concentrations of heavy metals in the vicinity of them, and the gradual accumulation of heavy metals from various sources of pollution in urban areas over time, including gasoline combustion, and use of urban waste compost and sewage sludge as fertilizer, there has been widespread concerned regarding the human health problems with increasing heavy metals in soils around the Isfahan city. The variation of composition in the soil matrix may lead to variation of composition and behavior of soil heavy metals. Soil is a heterogeneous body of materials and soil components are obviously in interaction. Studies tacking this complexity often use aggregate measurements as surrogates of the complex soil matrix. So, it is important the understanding soil particle-size distribution of aggregates and its effects on heavy metal partitioning among the size fractions, the fate of metals and their toxicity potential in the soil environment. Therefore, the present study aimed to determine the Cu release potential from different size fractions of different polluted soils by different extractants and their availability for corn plant.
Five soil samples were collected from the surface soils (0–15 cm) of Isfahan province, in central of Iran. The soil samples were air-dried and ground to pass a 2-mm sieve for laboratory analysis. Air dried samples fractionated into four different aggregate size fractions 2.0–4.0 (large macro-aggregate), 0.25–2 (small macro-aggregate), 0.05–0.25 (micro-aggregate), and

Soils form from the interplay of five main factors namely parent material, time, climate, relief (topography) and organisms. Topography is one of the local factors that has direct and indirect effects on soil formation, physical and chemical properties of soils. To understand the mutual relationship between topographic properties, soil properties and plant community (phytocoenosis), it is necessary to decide on the appropriate method for properly managing the soil resources. In addition to the soil properties, topography may affect the soil production indices as well. Soil production index and consequently its productivity will in turn affect the growth and fruiting. Insight about the pattern the spatial variability of soil properties can be used to manage the lands properly. This study was performed to investigate the spatial variability of soil properties regarding aspect and also the relationship of these changes with the quality and quantity of peach production in Saman region in Chaharmahal-Va-Bakhtiari province, Iran.
The study area contained 1.5 hectare of 200-hectare peach gerdens belong to BaghGostaran Company located in Saman, Chaharmahal-Va-Bakhtiari Province. The soil moisture and temperature regimes are xeric and mesic, respectively. 136 soil samples were collected from 0-30 and 30-60 cm depths. Two peach trees around the soil samples were also selected. Then, soil physical and chemical properties including soil texture, percentage of calcium carbonate equivalent, organic carbon, plant available potassium, phosphorous, iron and zinc, pH and electrical conductivity were determined and fruit properties including branch length and diameter in the current year, number of fruits, total yield, average of fruit weight, TSS, tissue strength, pH, acid and extract percentage were measured. Finally, the dataset were analyzed using Statistica 6.0 software. Analysis of spatial data was calculated via variogram and performed using Variowin, 2.2 software package. After determination of the best model, kriging maps of the soil and fruit properties were prepared by Surfer 8 software.
The statistical results revealed that among the soil properties, pH of the surface and subsurface horizons in both aspects had the lowest CV. Plant available phosphorous and iron showed the highest CV at surface and subsurface horizons of eastern aspect, respectively. Among the soil variables, plant available iron showed the highest CV for both horizons at western aspect. Regarding peach properties, the tissue strength showed the highest and pH showed the lowest variation in both slopes, respectively. The results of mean comparisons revealed that the soil of eastern slope has more clay percentage, silt, organic carbon, plant available potassium, phosphorous, and iron in comparison with western aspect. Peach yield was higher in eastern aspect than the western one. Correlation coefficient among soil and peach propertied did not show a similar trend for two aspects. Amount of clay and plant available potassium in subsurface horizon showed a positive significant correlation with yield in western and eastern aspects, respectivelty. Variography showed that all variables except pH of subsurface horizon have spatial structure. The pattern of spatial variability of the yield and the number of fruits was also approximately the same as that of clay particles and organic carbon, plant available potassium, phosphorous and iron in both depths. The spatial variability of the branch length and diameter in the current year was similar to the spatial variability of clay particles percentage and the plant available potassium. The results suggested the significant effect of soil properties, especially clay particles percentage and the plant available potassium on the performance and vegetative properties of peach. However, the peach qualitative properties showed no significant correlation with the soil properties.
The results suggest that the significant effect of aspect on the soil and fruit properties. It seems that the aspect caused the formation of soil with different properties. Significant differences observed among some soil properties including texture components, the amount of organic carbon and nutrients in both aspects. The trees on the eastern slope had higher yield due to having more organic carbon and nutrients and consequently higher soil quality, while the trees on the western slope had fruits with higher quality which may be due to the climatic factors such as receiving more light, or other soil properties like the mount of available nitrogen. More investigation is needed to understand the effect of NPK and iron fertilizers and climate properties on peach properties in the orchards of the area. The effect of climatic factors on the peach qualitative and quantitative characteristics should be investigated as well.

Soil water erosion on the slope lands involves detachment, transport and deposition of soil materials due to erosive forces of raindrops and surface runoff. Surface runoff can produce relatively high soil loss and is often the dominant hillslope erosion process. The rate of surface runoff which controls surface erosion on the uniform areas in the hillsolpes, is dependent on rainfall intensity and slope steepness. In various studies, the relationships between rainfall characteristics and surface runoff were well known. Many studies have been performed on the relationship between runoff and rainfall characteristics and soil loss.The effects of slope steepness on the surface runoff and soil loss were also investigated by many researchers. In a few studies, the transportation of soil particles has been studied. For examples, some studies showed that the soil particles have different susceptibility to transport by surface flow . However, limited information is available on the effects of rainfall intensity and slope steepness on the transportability of soil particles by surface runoff in the semi-arid areas. Therefore, the objective of this study was to investigate the effects of rainfall intensity and slope steepness on the transport rate of soil particles by surface runoff in a medium soil texture in semi-arid region.
A clay loam soil with similar particle size distribution (33.15% sand, 33.22% silt and 33.63% clay) was provided to study the detachability of soil particles by surface runoff. Soil loss and particle size distribution of eroded material were determined in the soil under zero, 10%, 20%, 30% and 40% slope steepness using simulated rainfall with 10, 20, 30, 40, 50, 60, 70, 80 and 90 mm h-1 in intensity. Soil samples were filled to 32 cm  50 cm flumes with 7 cm depth and exposed to simulated rainfalls. Surface runoff, surface soil erosion and particle size distribution (PSD) of eroded material were determined in the slopes under simulated rainfalls. A total of 135 trials were carried out on 45 soil samples using the factorial completely randomized design with three replications. Data of surface soil erosion and transportation of soil particles were compared using the Duncan's test among the rainfall intensities and slope steepness.
No surface runoff and surface soil erosion were observed in 10 mm h-1 rainfall intensity. Rainfall intensity of 20 mm h-1 appeared to be the threshold rainfall intensity to make surface runoff and surface soil erosion. Based on the results, surface runoff, surface erosion and kind of eroded soil particles were significantly affected by rainfall intensity (P Rainfall intensity was the more important factor than the slope steepness in the soil loss and transportation rate of soil particles by surface runoff. Silt was the most susceptible soil particle to erosion by surface runoff in the rainfall intensities and the slope steepness. The transportation of very coarse sand and clay didn’t appear significant differences for both the rainfall intensities and the slope steepness. Protection of soil surface from raindrop impact is essential for prevention of runoff and soil loss in steep slopes especially for intensive rainfalls.

Effective and sustainable soil management requires knowledge about the spatial patterns of soil variation and soil surveys are important and useful sources of data that can be used. Prior knowledge about the spatial distribution of the soils is the first essential step for this aim but this requires the collection of large amounts of soil information. However, the conventional soil surveys are usually not useful for providing quantitative information about the spatial distribution of soil properties that are used in many environmental studies. Recently, by the rapid development of the computers and technology together with the availability of new types of remote sensing data and digital elevation models (DEMs), digital and quantitative approaches have been developed. These new techniques relies on finding the relationships between soil properties or classes and the auxiliary information that explain the soil forming factors or processes and finally predict soil patterns on the landscape. Different types of the machine learning approaches have been applied for digital soil mapping of soil classes, such as the logistic and multinomial logistic regressions, neural networks and classification trees. In reality, soils are physical outcomes of the interactions happening among the geology, climate, hydrology and geomorphic processes. Diversity is a way of measuring soil variation. Ibanez (9) first introduced ecological diversity indices as measures of diversity. Application of the diversity indices in soil science have considerably increased in recent years. Taxonomic diversity has been evaluated in the most previous researches whereas comparing the ability of different soil mapping approaches based on these indices was rarely considered. Therefore, the main objective of this study was to compare the ability of the conventional and digital soil maps to explain the soil variability using diversity indices in the Shahrekord plain of Chaharmahal-Va- Bakhtiari province.
The soils in the study area have been formed on Quaternary shale and foliated clayey limestone deposits. Irrigated crops such as wheat, barley and alfalfa are the main land uses in the area. According to the semi-detailed soil survey, 120 pedons with approximate distance of 750 m were excavated and described according to the “field book for describing and sampling soils”. Soil samples were taken from different genetic horizons and soil physicochemical properties were determined. Based on the pedons description and soil analytical data, pedons were classified according to the Soil Taxonomy (ST) up to subgroup level. Using aerial photo interpretation, geology map, google earth image and field observations primary soil map was created. With considering the taxonomic level, the representative pedons were determined and soil map was prepared. Multinomial logistic regression was used to predict soil classes at great group and subgroup levels. The map units that have the highest frequency were selected as indicator to calculate diversity indices in the conventional soil map at each taxonomic level. The selected map units were overlay to digital soil map and further diversity indices were calculated. Diversity indices including the Shannon’s diversity, evenness and richness index. In order to know whether the means of Shannon’s diversity for two approaches are significantly different, means comparison was done.
The results confirmed that the Shannon's diversity index was higher in the digital soil map than the conventional soil map for most soil map units. At great group and subgroup levels, a significant difference was observed for the Shannon's diversity index at 0.05 and 0.001 probability levels, respectively. Comparing the conventional and the digital soil maps showed the numbers of soil map units with significant difference regarding the Shannon's diversity index decreased from great group to the subgroup level. Although the conventional soil map did not show a good efficiency to explain the soil variability in this region considering more soil information to select the representative pedons at subgroup level in the conventional soil mapping could increase the ability of this approach.
A significant difference for the Shannon's diversity index between the conventional and the digital soil maps demonstrated that conventional soil mapping has not enough ability to explain the soil variability. It is recommended to test the effect of soil mapping approaches on explanation of the soil variability in other areas. Despite the deficiencies of traditional soil survey, it is still difficult to state about their replacement by digital methods.

Introduction Some methods of contaminated soils remediation reduces the mobile fraction of trace elements, which could contaminate groundwater or be taken up by soil organisms. Cadmium (Cd) as a heavy metal has received much attention in the past few decades due to its potential toxic impact on soil organism activity and compositions. Cadmium is a soil pollutant of no known essential biological functions, and may pose threats to soil-dwelling organisms and human health. Soil contamination with Cd usually originates from mining and smelting activities, atmospheric deposition from metallurgical industries, incineration of plastics and batteries, land application of sewage sludge, and burning of fossil fuels. Heavy metal immobilization using amendments is a simple and rapid method for the reduction of heavy metal pollution. One way of the assessment of contaminated soils is sequential extraction procedure. Sequential extraction of heavy metals in soils is an appropriate way to determine soil metal forms including soluble, exchangeable, carbonate, oxides of iron and manganese, and the residual. Its results are valuable in prediction of bioavailability, leaching rate and elements transformation in contaminated agricultural soils.
Materials and Methods The objective of this study was to synthesize magnetite nanoparticles (Fe3O4) stabilized with sodium dodecyl sulfate (SDS) and to investigate the effect of its different percentages (0, 1, 2.5, 5, and 10%) on the different fractions of cadmium in soil by sequential extraction method. The nanoparticles were synthesized following the protocol described by Si et al. (19). The investigations were carried out with a loamy sand topsoil. Before use, the soil was air-dried, homogenized and sieved (

sustainable development and the environment are interconnected. Sustainable agriculture is continuous utilization of a farm with respect to various aspects of environmental conditions by using fewer inputs (other than Bio-fertilizers). Phosphorus is one of the essential elements for the plants. Management of soil is possible by using biological fertilizers pillar of sustainable agriculture and providing some of the phosphorus needed by plants via bio-fertilizers. Phosphorus deficiency is extremely effective on the plant growth and productivity. The application of phosphorus fertilizers is expensive and dangerous. In addition, phosphorus in the soilmay become insoluble and will be unavailable to the plants. Studies showed that phosphate solubilizing bacteria in the soil rhizosphere are active and by root exudates solve insoluble phosphates such as tricalcium phosphate, and form absorbable P for plant. Consequently, the use of microbial fertilizers could reduce excessive use of chemical fertilizers and lead to decrease their harmful effects and protect the environment and conservation of available resources. The biological phosphate fertilizer industry uses sugar beet molasses as a binder and drying granules at high temperatures. Therefore, it is important to evaluate the durability of the bacteria in molasses at high temperature.
This study was designed as completely randomized design in a factorial arrangement.10 isolates were selected and the ratios of 50%, 25%, 15% and 10% of the apatite, organic matter, sulfur and soluble granule (ratio 1: 1 and 2: 1 bacteria and molasses), respectively, for each isolate was prepared. The final product was dried at 28 and 40 °C and remained for 4 months and population counted at first day and 10, 20, 30, 60, 90 and 120 days after the preparing. The population was counted by the serial dilution technique and cultured at Sperber media.
Comparing the average logarithm of population of bacteria in the granules indicated the highest proportion in the granules on the first day and the lowest population on 120 days (4 months), andthe ratio of 1: 1 inoculant and molasses had the largest population than the 2:1. The highest population was observed in 1:1 dried granules at 28 °C, but, some of 1:1 dried granules at 40 °C were consistent with the defined standards. Overall, bacteria I2-4, Z4 and C5-1 showed the greatest amount of population and the population had more power to maintain the standards among the isolates. The granules produced according to the defined standard (two-month period, 105 cell per gram of fertilizer) are dried at 28 °C in both 1: 1 and 2: 1 to the end of 4 months in the standard population. Granules dried at 40 °C for 1: 1 ratio of the population by the end of 4 months in the standard range. In the case of the most isolated granules at the ratio of 2:1 until the end of the second month, the population were within the standard range but at the end of the third month, they come lower than standard except I2-4, Z4 and C5-1. The total population of the granules was as following: Granules 1: 1, 28 °C> 2: 1, 28 °C> 1: 1, 40 °C> 2: 1, 40 °C. Considering to the fact that this standard is undefined for four months, but in this study, the population was 104 granules in the fourth month.
Based on the results, some of these conditions could keep their population and population decline was less. In general, it can be concluded that the granular organic fertilizer phosphorus in the industry of phosphate solubilizing bacteria with sugar beet molasses as a binder and drying at 40 °C can be used The results were positive and the granules can be cited to the production of this type of microbial fertilizer. Considering to the results, it was found that the proportion of molasses and inoculant, drying temperature and storage time were effective on viability of bacteria. Also, instead of using a train of bacteria, phosphate solubilizing bacteria, a combination of any of these bacteria in a field lead to better results. It is clear that by a comprehensive study, the molecular identification of bacteria, and detection of desire genetic loci and then gene transfer between bacteria for increasing of high temperature resistance by spour production and also, gene transfer between bacteria with high population and non-tolerance to sugerbeet molasses and tolerant bacteria to sugar beet molasses but low population; we can achieve bacteria with high population and high tolerance to sugar beet molasses and consequently achieve to favorable results. This result could decrease chemical phosphate fertilizers usage and their harmful effects and help to protect the environment and available resources.

World's population growth and limited water resources and needing to more food production led to interest farmers to use nitrogen fertilizer more than soil requires and subsequently Nitrate leaching causes groundwater and environmental pollution. Therefore, researches has concentrated on improvement of nitrogen use efficiency, which numerical simulation is the effective solutions to optimize the management of water and fertilizer in the field in order to achieve the maximal yield and minimal nitrate pollution of soil, groundwater and drainage in water deficiency crisis condition. For this reason, the evaluation of new user friendly models in correct estimation of soil moisture and nitrogen content distribution and recognition of water and solutes movement in the soil and choosing the best management option for increasing productivity and economic performance and also reduction of nitrate pollution of soil and ground water source with the least limitations and high accuracy is necessary. The Eu-Rotate-N model has been developed for simulation of nitrogen use and specifically for optimization of nitrogen use in variation of vegetables in a wide range of conditions, which without the need to calibration has presented satisfactory results in many areas. So this study was conducted to evaluate the efficiency of Eu-Rate-N model in assessment of moisture and nitrogen distribution and yield under different nitrogen fertigation management for pepper plant.
Sweet pepper was planted at density of 8.33plant per m2 in a row planting method. 150kg per hectare per year of fertilizer was used during the season. Crop yield, soil water and nitrogen content were measured on a regular basis. The treatments consisted of three fertilizer level: zero (N0), the ratio of ammonium to nitrate 20:80 (N1) and 40:60 (N2), which was conducted in a completely randomized block with three replications in Isfahan. Irrigation based on daily monitoring of humidity was used with drip irrigation system. The irrigation Depth was calculated and applied with aim of replacing the water content deficiency in the root zone up to field capacity (FC) for the no water deficit treatment.
Coefficients were modified only for plant coefficients and length of each growth stage according to the area. To compare simulated data with measured data in field, indices of statistical root mean square error (RMSE), normalized root mean square error (NRMSE), coefficient of determination (r2) and index of agreement Wilmot (d) were used.
The NRMSE index for nitrate and soil water content was 11.45, 12.08, the RMSE was 0.89, 0.022, the r2 was 0.998, 0.996 and the d was 0.667, 0.66 respectively. All calculated indices for soil water and nitrate content were in the acceptable range. NRMSE index was less than 20 percent in all treatments which was indicating good ability of model in simulating soil water and nitrate content and r2 was more than 90 percent which pointed out to well process of simulation of the model. The simulation accuracy was greater at the end of the growing season. Comparing of RMSE statistical index for different depths showed that the simulation accuracy was increased by increasing depth which can be due to changes in surface evaporation and also the effect of environmental factors on surficial layers more than other layers. Generally the best simulation was related to the layer of 80 to 100 cm. And the average RMSE was 0.019 cm3 per cm3 for soil moisture content and 0.22 mg per kg for soil nitrate.In the layer of 80-100 cm the best simulation of soil moisture and nitrate content between treatments was related to N0 by the RMSE equal to 0.024 cm3 per cm3 and 0.21 mg per kg respectively and the weakest simulation was related to N3.The simulated yield in all treatments was less than its actual value. Comparison of simulations between three treatments demonstrated the usefulness of EU-Rotate N to examine the effects of management on, nitrate leaching.
The Eu-rotate-n model without calibration for site location was well capable of estimating soil water and nitrate content under different fertilizer management for Isfahan climatic conditions nevertheless it is suggested to use to calibrate yield functions to improve the yield simulation. Generally we can use Eu-rotate-n model for simulation of water and nitrogen content and eventually approach to integrated and optimal management in the farm in the hot, dry conditions of Isfahan.

Land suitability evaluation is a process to examine the degree of land fitness for specific utilization and also makes it possible to estimate land productivity potential. In 1976, FAO provided a general framework for land suitability classification. It has not been proposed a specific method to perform this classification in the framework. In later years, a collection of methods was presented based on the FAO framework. In parametric method, different land suitability aspects are defined as completely discrete groups and are separated from each other by distinguished and consistent ranges. Therefore, land units that have moderate suitability can only choose one of the characteristics of predefined classes of land suitability. Fuzzy logic is an extension of Boolean logic by LotfiZadeh in 1965 based on the mathematical theory of fuzzy sets, which is a generalization of the classical set theory. By introducing the notion of degree in the verification of a condition, fuzzy method enables a condition to be in a state other than true or false, as well as provides a very valuable flexibility for reasoning, which makes it possible to take into account inaccuracies and uncertainties. One advantage of fuzzy logic in order to formalize human reasoning is that the rules are set in natural language. In evaluation method based on fuzzy logic, the weights are used for land characteristics. The objective of this study was to compare four methods of weight calculation in the fuzzy logic to predict the yield of wheat in the study area covering 1500 ha in Kian town in Shahrekord (Chahrmahal and Bakhtiari province), Iran.
In such investigations, climatic factors, and soil physical and chemical characteristics are studied. This investigation involves several studies including a lab study, and qualitative and quantitative land suitability evaluation with fuzzy logic for wheat. Factors affecting the wheat production consist of climatic conditions like mean, maximum and minimum air temperatures during growing period as well as edaphologic properties like EC, pH, ESP, percent of clay, silt, sand, gravel, gypsum and CaCO3 content. Climatic data collected from the Shahrekord synoptic station were used to assess climatic land suitability for wheat. Qualitative land suitability evaluation was carried out using the fuzzy approach. Potential yield was calculated using the method proposed by FAO. Using MATLAB software, qualitative and quantitative land evaluation were classified based on fuzzy logic approach. In fuzzy method, climatic factors are used to achieve climatic index. Clay and sand percent were applied to calculate soil texture. To determine the membership degrees,bell membership functions were used. Parameters of function shapes were transformed to equations with variable coefficients and the best coefficients were eventually chosen based on the model determination coefficient. In evaluation method based on fuzzy logic, the weights are used for land characteristics. In fuzzy logic method, weights were calculated by four methods. These methods consist of neural network using 1 neuron and 4 neurons, multivariate and Partial Least Squares (PLS) regressions. Comparison of the coefficient of determination results of multivariate regression and RMSE is carried out between observed and predicted yield. Weight calculations were conducted by using MINITAB software to PLS and multivariate regression. Also, Neurosolution 5 was used for weight calculation based on neural network.
The calculated weights were differed by using the four applied methods. In all methods, the maximum weight was related to gravel, and minimum weight was related to clay. The results of land index and predicted yield calculation were different in some points (3, 6, 7, 13, 14, 19, and 21) for four methods. The coefficient of determination of calculated weights were 0.595, 0.56, 0.6 and 0.56 for neural network, 1 neuron, 4 neurons, multivariate regression and PLS and RMSE values in these methods were 6.38, 6.4, 6.38 and 6.38 Ton/ha, respectively. The correlation coefficient between the observed and predicted yield indicated the partially appropriate selection of the factors and evaluation approach.
The results of weight calculation were not showed significant difference in three methods (neural network, PLS, regression). The predicted yield was somewhat closer to the observed yield when 1 neuron was introduced to the neural network than 4 neurons. The maximum coefficient of determination as well as the minimum RMSE was achieved for weights calculated by multivariate regression. Because the method is almost accurate and easy to use, it is recommended in this study. The coefficient of determination generally became low because different traditional management practices were carried out in the study area. Finally, in regard to achieved results about the used methods, it is suggested to take into account the management factors in land suitability processes and compare the other weight calculated methods in land suitability evaluation based on fuzzy logic.

Selecting the right source of nutrient in a particular cropping situation requires a consideration of economic, environmental, and social objectives. One of the objectives is to keep all nutrient losses to a minimum. Since the use of nitrogen chemical fertilizers began more than 100 years ago, it has been recognized that it can be lost as gaseous ammonia when an ammonical fertilizer is applied to calcareous soil. A process by which nitrogen exit from the soil in form of ammonia and enter to the atmosphere is called volatilization. Agricultural practices (use of chemical and animal fertilizers) are known as major sources of ammonia volatilization into the atmosphere. Nitrogen losses not only economically but also in terms of environment pollution is important. Ammonia volatilization is one way of the nitrogen losses from agricultural and non-agricultural ecosystems. A variety of soil chemical properties interact with environmental conditions at the site of the fertilizer application to determine the extent of NH3 loss. This article study some of the major factors that contribute to NH3 loss from N fertilizer. The aims of this study were to evaluate the impacts of concentrations of soil calcium carbonate (experiment 1), plant residue application (experiment 2), nitrogen fertilizer rate and source on volatilization of ammonia from soil.
Two factorial experiment with 36 treatments, three replications and 108 experimental unit for 25 days at a constant temperature of 30 ° C were conducted using a completely randomized design. The experimental treatments were three concentrations of soil calcium carbonate (20, 27 and 35% in experiment 1), three alfalfa plant residue application rates (0, 2.5 and 5% w/w in experiment 2), three rates of nitrogen (0, 200 and 400 kg/ha), four sources of nitrogen (urea, ammonium nitrate, ammonium sulfate and urea- sulfuric acid). Fertilizers were added to soil samples in form of solution and the moisture of soils was brought to field capacity. Samples were placed into special jars and amount of nitrogen volatilization were measured.
The results showed that ammonia volatilization from soil increased as the concentration of soil calcium carbonate, rates of nitrogen and alfalfa plant residues application increased. In first experiment the highest amount of nitrogen volatilization rate, as ammonia (33.21 µgr N/gr soil) was measured from 400kgN/ha soil for urea fertilizer and 35 percent calcium carbonate. Also the lowest amount (11.99 µgrN/gr soil) was obtained from 20 percent calcium carbonate without application of any nitrogen fertilizer. In this experiment, with an increase in the amount of soil calcium carbonate by 15%, the amount of volatilized nitrogen in the form of ammonia were six times. By increasing the amount of soil calcium carbonate of from 20 to 27% the amount of nitrogen losses as ammonia slightly increased but with a further increase of calcium carbonate (from 27 to 35%) the amount of nitrogen losses increased a lot and this increase was higher than the initial increase. The presence of calcium carbonate in the soil increase soil pH and ammonia volatilization. In second experiment the highest amount of nitrogen volatilization rate, as ammonia (32.28 µgr N/gr soil) was measured from 400kgN/ha soil for urea- acid sulfuric fertilizer and 5 percent of plant residues. Also the lowest amount (0.33 µgrN/gr soil) was obtained from soil without application of any nitrogen fertilizer and plant residues. The most of nitrogen losses in the form of ammonia in the amount of 15.34 micrograms per gram of soil was obtained from level of 5% of alfalfa residue. With the 2.5 percent increase in the alfalfa residue rate, ammonia volatilization from soil increased in rate of 3.24 micrograms per gram of soil and by increasing it from 2.5 to 5%, nitrogen volatilization increased in the amount of 8.88 micrograms per gram of soil.
The loss of nitrogen as ammonia with application of nitrogen fertilizers and without application of residues was as urea> ammonium sulfate> ammonium nitrate > urea-sulfuric acid and with application of crop residues was as urea-sulfuric acid

Amongst different habitats, fire is an ecological factor and determinant that affects many physico-chemical soil factors. In addition, among natural disturbances, fire plays an important role in plant diversity conservation and in some areas around the world, the presence of some plant species depends on natural fire. The extension of fire influences on soil is related to the fire severity. In fact, fire severity encompasses of two characteristics: extension and time of burning. On the other hand, fire extension and burning time are affected by humidity, air temperature, wind speed, topographical characteristics. Despite high frequency of fire in natural habitats and high level of fire effectiveness on soil parameters, study of fire impacts on soil characteristics were rarely reported in Iran. In addition, most previous studies were conducted in forest habitats, ignoring the severity of fire on soil.
In order to investigate the effect of fire severity on some soil physico-chemical characteristics, Yeylagh Dasht area (rangeland habitats) was selected in southern-east of national Golestan Park with three different plant covers, viz. grass, shrub and cushion. Many fires occurring have been reported in this park in each year. For the current study, we tried to select the habitats in which the fire was occurred at least one year before. A control area without burning with similar ecological parameters was also selected adjacent to the burnt area. in fact unburnt area was isolated by a road from burnt area, unable to extend the fire into unburnt area due to the road. Fire had been occurred in the burnt area in September, 2014. Soil samples with 15 replications in burnt area and 15 replications in unburnt were collected within a depth of 0-5 cm and then transported to the soil laboratory to measure some qualitative soil characteristics i.e. soil organic matter (SOM), particulate organic matter (POM), total nitrogen (TN) and aggregate stability (AS). All statistical analyses were done by R software. Before ANOVAs (one and two-ways) and unpaired t-test, we tested data for normal distribution by Shapiro-Wilk test and homogeneity of variance by Flinger Test.
The results of two-way ANOVA showed that the main effect of fire on soil was not significant while the main effect of fire severity and the interaction of fire and fire severity on SOM and POM were significant (Table 1). The results of one-way ANOVA showed that the content of SOM was significantly different between three different treatments in unburnt area (control area) while there were no significant differences between the three treatments (three fire severities) in burning areas. Therefore it can be discussed that the kind of vegetation (grassland, shrub or cushion) could affect SOM while the fire increased the spatial homogeneity of SOM. The same pattern of SOM was occurred for POM in burnt and unburnt areas. However, the results of unpaired t-test showed that POM was drastically decreased after high and intermediate fire severities. Aggregate stability and POM were significantly decreased in the intermediate and high severities of fire (cushion and shrub plant cover). Fire in the intermediate and high severities increased TN (Figure 1). We concluded that fire occurring by plants might be decreased POM and AS significantly. In addition, mineralization probable increased TN after burning. We also compared soil characteristics among three fire severities in burnt area and in unburnt area separately.
This study showed that the variation of soil characteristic was mainly affected by different fire severities. Therefore, we emphasized that fire severity should be considered in the studies of the impact of fire on soil in different habitats. Fire can decrease the spatial heterogeneity of soil parameters among different sites. We showed that soil POM is a characteristic more sensitive than total SOM in confronting with fire.

The analysis of extreme events such as first frost dates are detrimental phenomena which influence in various branches of engineering, such as agriculture. The analysis and probability predicting of these events can decrease damage of agriculture, horticulture and the others. Furthermore, this phenomenon can have a relation with other thermal indexes. The analyzing of first frost dates of all synoptic stations of Khorasan Razavi province is subject of this article. The frequency analysis applied to eight distributions. Then the relationship between first frost dates and thermal index were studied. Best relation was between minimum temperature and return periods of first frost dates.
The analyzing of first frost dates (origin is March 21) of all synoptic stations of Khorasan Razavi province is subject of this article. At first data of each station were screening. The basic properties such as homogeneity, randomness, stationary, independence and outliers must be tested. The eight distribution Normal, Gumbel type 1, Gamma 2-parameter, Log normal 2 or 3 parameters, Generalized Pareto, Generalized extreme values and Pearson Type 3 fitted to data and the parameters estimated with 7 methods by the name of the several types of Moments (5 methods), maximum likelihood and the maximum Entropy. The Kolmogorov – Smirnov goodness of fit test can be used to compare the best distribution. The return periods of first frost dates are major application in frequency analysis. There is maybe a relationship between periods and thermal index such as min, max and mean temperature. This relationship can be adapted by regression methods.
The statistical analysis for prediction probabilities and return periods of the first frost dates for all synoptic stations in Khorasan Razavi province and the relationship between annual temperature indicators and this phenomenon is the aim of this article. The origin date of this phenomenon is March 21. First, data were screened. Then basic hypothesis test were applied which including the Runtest (randomness), the Mann-Whitney test (homogeneity and jump), the Wald-Wolfowitz test (independence and stationary), the Grubbs and Beck test (detection Outliers) and the three sigma methods (Outlier). The results were: 1-The Sabzevar, Mashhad and Gonabad had lower Outliers that will not cause any problem in data analysis by their skewness. The first frost data of all station were without upper outlier. 2- The independence of all stations was accepted at the 10% level. 3-All stations were Randomness, Independence and homogeneous and lack of jump. Eight probability distributions (Normal, Gumbel type 1, 2-parameter gamma, 2 and 3 parameters log-normal, the generalized Pareto, the generalized extreme values and the Pearson type 3) were applied. The skewness coefficients for all stations were more than 0.1 so Normal distribution was rejected. Also the7 methods of estimation (five different methods of moments, maximum likelihood and maximum entropy methods) were used. The ks fit test was applied. The ks for some stations were closed together at several estimations methods. The results are as follows: GPA (4 times), PT3 (4 times), LN2 (4 times), GA2 (3 times). Generalized Pareto distribution had the best fitted to data (60% of cases compared to the other functions). The results significantly indicated that the occurrence of first frost on the first day of process is in place. The first frost in the period of 2 years at all stations, not occur earlier than Aban(October 28). The 100-year return period event does not occur earlier than first of Mehr(September 22). There is no significant relationship between first frost in the period of 2 years with other factors such as altitude, latitude, longitude, temperature and precipitation as well.
Date of the first fall frost is one of the unfavorite climate influences that cause reduction in crop products. The purpose of this paper is to analysis the frequency occurrence of first frost day in several Khorasan’s synoptic stations as study area. Screening and initial basic tests such as randomness homogenity, independence, etc. were done. Eight distribution function, namely Normal, Gumbel type 1, Gamma 2 parameters, Log normal 2 and 3 parameters, Generalized Pareto and Pearson type III were fitted to data with five probability distributions methods (Ordinary Moments, Maximum Likelihood method, Modified Moments, Probability Weighted Moment and Maximum Entropy). Goodness of fit test was Kolmogorove-Smirnov test. PWM and ModM methods revealed relatively superior results compared to the rest of methods. Generalized Pareto distribution had the best fitted to data (60% of cases compared to the other functions). The results significantly indicated that the occurrence of first frost on the first day of process is in place. The first frost in the period of 2 years at all stations, not occur earlier than Aban. The 100-year return period event does not occur earlier than first of Mehr. There is no significant relationship between first frost in the period of 2 years with other factors such as altitude, latitude, longitude, temperature and precipitation as well.

Solar radiation on the earth surface has a wide range of applications in hydrology, agriculture and meteorology. Solar radiation is an important parameter of estimated models of reference crop potential evapotranspiration such as the Penman–Monteith equation. Also, total sunshine hours are one of the most important factors affecting climate and environment, and its long-term variation is of much concern in climate studies. Reference crop potential evapotranspiration is one of the most important parts of water cycle in the nature but, direct measurement of this crop parameter is so difficult and not practical. Therefore, equations that can estimate the value of evapotranspiration only by using meteorological data are necessary. As mentioned before, the Penman–Monteith equation can be used for estimating reference crop potential evapotranspiration, however this equation needs solar radiation data, and the measurement of solar radiation is done in a limited numbers of weather stations in Iran, and also in Fars province, south of Iran. Since, the measurement of solar radiation is expensive, therefore many models have been derived for its estimation in different climates of the world., Many investigators also have been tried to estimate solar radiation for different locations of the world based on more simple measured weather data such as air temperature (minimum, maximum or mean) and sunshine hours. Hence, the derived equations for estimating solar radiation based on other weather data can be used for estimating reference crop potential evapotranspiration with the Penman–Monteith equation.
In this study, solar radiation was estimated in Shiraz, central part of the Fars province in south of Iran. For this purpose, the daily measured of solar radiation data in Shiraz synoptic station were used. Also, other needed weather data were used. All available data was for the years 2006 to 2010. Measured data of years 2006 to 2008 were used for calibrating fourteen estimated models of solar radiation in seasonally and annual time steps and the measured data of years 2009 and 2010 were used for evaluating the obtained results. The equations were used in this study divided into three groups contains: 1) The equations based on only sunshine hours. 2) The equations based on only air temperature. 3) The equations based on sunshine hours and air temperature together. On the other hand, statistical comparison must be done to select the best equation for estimating solar radiation in seasonally and annual time steps. For this purpose, in validation stage the combination of statistical equations and linear correlation was used, and then the value of mean square deviation (MSD) was calculated to evaluate the different models for estimating solar radiation in mentioned time steps.
The mean values of mean square deviation (MSD) of fourteen models for estimating solar radiation were equal to 24.16, 20.42, 4.08 and 16.19 for spring to winter respectively, and 15.40 in annual time step. Therefore, the results showed that using the equations for autumn enjoyed high accuracy, however for other seasons had low accuracy. So, using the equations for annual time step were appropriate more than the equations for seasonally time steps. Also, the mean values of mean square deviation (MSD) of the equations based on only sunshine hours, the equations based on only air temperature, and the equations based on the combination of sunshine hours and air temperature for estimating solar radiation were equal to 14.82, 17.40 and 14.88, respectively. Therefore, the results indicated that the models based on only air temperature were the worst conditions for estimating solar radiation in Shiraz region, and therefore, using the sunshine hours for estimating solar radiation is necessary.
In this study for estimating solar radiation in seasonally and annual time steps in Shiraz region, three groups of equations were used (1: based on only sunshine hours. 2: based on only air temperature, and 3: based on sunshine hours and air temperature). Final results of this study for estimating solar radiation in Shiraz region were: 1) For autumn season the best equation was based on the extraterrestrial radiation, the ratio of daily actual sunshine hours to daily maximum sunshine hours, and minimum and maximum air temperatures. 2) For annual time step the best equation was based on the extraterrestrial radiation and the ratio of daily actual sunshine hours to daily maximum sunshine hours.

The range of meteorological parameters, such as temperature, are different at different scales. Fractal geometry is a branch of mathematics that has many applications in the field of discrete and continuous domains. Downscaling may be done by different methods, including univariate, multivariate regression functions, splined function and fractal function. Finding the best model for fractal downscaling, is needed to implement the distance between measured and modeled data sets. This distance may be estimated by different methods, including Euclidian. For temporal downscaling, the data are two-dimensional, i.e. time and that of principal variable (e.g. temperatures).In such a case, the dimensionality problem arises in Euclidean space. In these cases, data are usually changed to non-dimensional forms which are referred to standardization, normalization, scaling, or non-dimensionalizing. So, in addition to imbalance of data calculating distance between two sets, we are also considering the impact of standardized data on the number of interpolation points, run time, and accuracy of downscaling the temperature of Mashhad synoptic station.
In this paper, fractal model was used for modeling and downscaling temperature datasets for the period of 2007- 2009 at Mashhad Synoptic stations with two approaches of Hasdurf distance to determine the interpolation points (first approach: in first approach original data was used. Second approach: in second approach the data were standardized). We adopted some criteria, such as root mean squared error, correlation, and Akaike information criteria to assess the accuracy of fractal downscaling.
Mashhad is the second most populous city in Iran and capital of Razavi Khorasan Province. It is located in the northeast of the country, close to the borders of Turkmenistan and Afghanistan. It is built-up (or metro) area was home to 2,782,976 inhabitants including Mashhad Taman and Torqabeh cities. It was a major oasis along the ancientSilk Road connecting with Merv in the East. The city is located at 36.20º North latitude and 59.35º East longitude, Mashhad features a steppe climate with hot summers and cool winters. The city only receives about 250 mm of precipitation per year, summers are typically hot and dry, with high temperatures sometimes exceeds 35 °C (95 °F). Winters are typically cool to cold and somewhat humid, with overnight lows routinely dropping below freezing.
At first, fractal method was used to produce daily temperature from daily datasets with two attitude and different interval interpolation (5, 10, 15days). Then the same process was applied to produce 3-hours temperature.
1. Downscaling for daily temperature: In this part, we considered that which standardizing approach and which interval interpolation, will carry the best accuracy for the fractal modeling. Although RMSE, R2, AIC, show that standardized approach is not better, but the difference is not substantial.
Results from fractal modeling from 5-day interval interpolation and 10-day interval interpolation with daily measured temperature in Mashhad compared based on 1:1 line of perfect agreement, and showed acceptable (=5%) behavior. In both approaches and two interval interpolation with both 5 and 10 days, predicted temperatures imitate the behavior of the measured temperatures. However, simulation with no standardization approach show better results for both distance interpolation compared to the second approach with standardization.
2. Downscaling daily temperature to 3-hour interval: We compared downscaled 3-hour temperature from two standardizing approaches and two timesinterpolation based on daily temperature with 3-hour measured temperature and compared the results with respect to 1:1 line of perfect agreement. It is clear that the results of the three-hour downscaling show the same results with daily downscaling, because temperature shows the fractal behavior. Although both approaches perform well but un-standardizing is better, yet the difference is not pronounced.
Overall, in both approaches, three-hour and daily downscaling is done precisely and with high quality. The number of interpolation points was reduced by 30% under the second standardizing approach, which followed by considerable computer runtime. However, the result shows that the first approach had better modeling.
The comparison results of the modeling with 5 intervals interpolation and with 10, the 10 intervals interpolation were more acceptable, such that correlation coefficient was between (first approach: 0.98 and 0.7, second approach: 0.98 and 0.65) while RMSE was between (first approach: 1.33 and 3.27 ° C and second approach: 1.44 and 6.02 ° C), and AICc was between (first approach: 0.55-3.27 and second approach: 2.87-3.51).The intercepts and slopes of regression lines between measured and predicted temperatures were not statistically (5% level of significant) different from 0 and 1, respectively.