نشریه آب و خاک
سال بیست و نهم شماره 5 (پیاپی 43، آذر و دی 1394)

Water is one of the most important factors limiting agricultural developments in arid and semiarid regions in the world. To avoid and exit from water crisis, a proper agricultural and water resource management is required. One of the important parameters in this regard, is determination of crops’ evapotranspiration. Evapotranspiration, water evaporation from the soil surface and transpiration of vegetation cover have a major trend and a key element in hydrological cycle for management of water resources, particularly in arid and semi-arid. Evapotranspiration is function of the soil, climate, land use, aerodynamic resistance levels and topography of the area. To provide a suitable irrigation schedule and apply an optimal water use management, determination of water requirement and crop coefficients in various growth stages seems necessary. Crop coefficient can be found through dividing the actual evapotranspiration by the potential evapotranspiration. Since the cuminum is commonly used in Birjand and has cultivated in farm and crop coefficients has not been determined , this study aimed to determine the crop coefficients of cuminum using lysimeter water balance in arid and semi-arid climatic conditions.
In this research, in order to determine cuminum crop coefficients, that is one of the important herbs, a lysimetric experiment was conducted during growth season in faculty of agriculture, Birjand university. This project, was done in lysimeter. For this purpose and due to the size and plant height in three lysimeter (as replications) with a diameter of 20 and a height of 16 cm was used order to the cultivation of Cuminum. In order to drainage at the bottom of each lysimeter was built orifice. For easily of lysimeters drainage, lysimeter floor was poured by small and large sand and lysimeter was filled by soil and animal Fertilizers for better plant growth. Three lysimeters were used; and water requirement of cuminum was calculated using water balance method. To calculate potential evapotranspiration, grass with 12 centimeters height was used as the reference plant. Crop coefficient can be achieved by dividing the actual evapotranspiration to reference evapotranspiration and is not fixed growth period. The cumin plant growth period was divided four stages (initial, development, middle and end). The initial phase of up to 10% on seed germination and plant growth, from 10 percent to flowering development stage, middle stage and final stage of the start of flowering to product reaches to harvest is the end of the middle stage. In each lysimeter average number of 20-15 of seed to increasing germination, were planted on the February 9, 2012. To control weeds, weed was done handing during the growing season. Drainage water is controlled over a period of time measured with weighting method and deep and volume of water was measured. Soil moisture at field capacity using pressure plates was measured. Measuring soil water content and determine irrigation time.
Results and Discussion According to the results obtained for the crop coefficient can be concluded that in the initial stages of plant growth that plant size is small, transpiration is low and therefore Kc have low value. In the middle and development stage increases canopy and increased transpiration rate and increases Kc. At the end stage to reducing activity of the leaves (old leaves) reduced transpiration. The average crop coefficient of cumin in the initial phase of growth during the study to 0.65, then with increasing plant growth, leaf area index were increased and crop coefficient increased to 0.92 in development stage. In the middle of this amount is 1.21 and in the end the 0.85 reached. Average crop coefficients for a four-stage is 0.9. Duration of growth stages for cuminum crops in Birjand region is 24 days for initial stage, 40 days for middle stage and 31 days for development and 19 days for end stage of growth stages.
Conclusions In this study according to important of drug and economic for cuminum plant and that there isn’t report for crop coefficient cuminum and Birjand region, we cultivate cuminum in arid area of Birjand in 2011 year. The results of lysimeters showed that Duration of plant growth stages and value of crop coefficients in the initial , development, middle and end stages, respectively (24, 40, 31 and 19 days) and (0.65, 0.921.21 and 0.85) respectiely.

Surface irrigation is still the most used method. For accessing to high efficiency, irrigation requires careful design and correct implementation. In addition, the design and evaluation of these systems require the identification of the advance, recession, and infiltration curves. Infiltration is the most important and difficult parameter to evaluate surface irrigation systems. The objective of this study was to evaluate five different methods to estimate infiltration parameters (two-point method of Elliott and Walker, recycling furrow infiltrometer, Singh and Yu method, Shepard one-point method and modified Shepard et al. two-point method) and to determine the most compatible method with design and evaluation models of furrow irrigation (hydrodynamic, kinematic wave and zero inertia) by applying SIRMOD software.
For the simulation of the surface irrigation, the continuity and momentum equations (Sant-Venant equations) used. SIRMOD simulation model is one of the models for the management and design of surface irrigation systems. The software package, hydraulic hydrodynamic models, zero inertia and kinetic wave have been placed. These models are resolvent of the Sant-Venant equations based on various assumptions. In this study, two-point method of Elliott and Walker, recycling furrow infiltrometer, Singh and Yu method (to calculate the coefficients of Kostiakov-Louis equation), Shepard one-point method and modified Shepard et al. two-point method (to calculate the coefficients of Philip equation), were used for estimating infiltration parameters. For this purpose, three field data sets were used. The total infiltrated water volume and advance time were predicted in each infiltration method and irrigation simulation model. In order to compare and evaluate the mentioned methods, the relative and standard errors were calculated.
According to the five methods (two-point method of Elliott and Walker, recycling furrow infiltrometer, Singh and Yu method, Shepard one-point method and modified Shepard et al. two-point method) Kostyakof- Louis and Philippe equations coefficients were determined. To evaluate the different methods for estimating infiltration parameters, the volume of water penetration in the furrow length was estimated using five named methods and the findings were compared with the actual volume of infiltrated water in the furrows (was estimated using the input-output hydrograph). Values of relative error in estimating the infiltrated volume in the furrows show the two-point Elliott and Walker method with 9.2 percent relative error is the lowest error than other methods. Then recycling furrow infiltrometer (back water) method is with 21.4 percent relative error. The standard error in the simulation and predict the advance stage in furrows based on different estimated parameters showed that hydrodynamic model by two-point Elliott and Walker method will give the best results (with 12.86 percent standard error). Also in Kinetic Wave model, recycling furrow infiltrometer method has the lowest standard error (10.04 percent) and zero inertia models with two-point Elliott and Walker method have lowest standard error (12.81 percent). In Hydrodynamic and zero inertia models, recycling furrow infiltrometer and two-point method of Elliott and Walker and Singh and Yu method have estimated advance figures in furrow less than its actual value. Shepard et al. one-point method underestimated about 100 meters of furrow length and overestimated from this point to the end of the furrow. Modified Shepard et al. two-point method is generally overestimated. In the kinetic wave model, two-point Elliott and Walker and recycling furrow infiltrometer methods numbers have been estimated to be completed in accordance with the numbers seen in a distance of about 40 meters along the furrow and the low estimate since the end of the furrow. Singh and Yu method overestimated. Shepard et al. one-point and Modified Shepard et al. two-point method were like the other two models.
Elliott and Walker two-point method is generally the least error in the calculation of the total volume of infiltrated water through the grooves, compared to other methods and then using rotating penetrometer (back water) is located. In general it can be said that both recycling furrow infiltrometer and two- point Elliott and Walker, the most appropriate methods to determine the infiltration equation parameters than other methods under study and using them in all three hydrodynamic, kinematic wave and zero inertia models, the results of the simulation irrigation, have created the smallest error. In general, the kinetic wave model than hydrodynamic and zero inertia models, was estimated more accurately the data in water advance stage and this trend can be seen in every five methods for estimating the infiltrated parameters. However, calculated errors in both hydrodynamic and zero inertia models in predicting this stage of irrigation are almost equal.

The study of rivers’ water quality is extremely important. This issue is more important when the rivers are one of the main sources of water supply for drinking, agriculture and industry. Unfortunately, river pollution has become one of the most important problems in the environment. When a source of pollution is transfused into the river, due to molecular motion, turbulence, and non-uniform velocity in cross-section of flow, it quickly spreads and covers all around the cross section and moves along the river with the flow. The governing equation of pollutant transmission in river is Advection Dispersion Equation (ADE). Computer simulation of pollution transmission in rives needs to solve the ADE by analytical or numerical approaches. The ADE has analytical solution under simple boundary and initial conditions but when the flow geometry and hydraulic conditions becomes more complex such as practical engineering problems, the analytical solutions are not applicable. Therefore, to solve this equation several numerical methods have been proposed. In this paper by getting the pollution transmission in the Severn River and Narew River was simulated.
The longitudinal dispersion coefficient is proportional of properties of Fluid, hydraulic condition and the river geometry characteristics. For fluid properties the density and dynamic viscosity and for hydraulic condition, the velocity, flow depth, velocity and energy gradient slope and for river geometry the width of cross section and longitudinal slope can be mentioned. Several other parameters are influencive, but cannot be clearly measured such as sinuosity path and bed form of river. To derive the governed equation of pollution transmission in river, it is enough to consider an element of river and by using the continuity equation and Fick laws to balancing the inputs and outputs the pollution discharge. To calculate the dispersion coefficient several ways as empirical formulas and artificial intelligent techniques have been proposed. In this study LDC is calculated for the Severn River and Narew River and some selected empirical formulas have been assessed to calculate the LDC.
Dispersion Routing As mentioned previously, calculating the LDC is more important, so firstly, the longitudinal dispersion was calculated from the concentration profile by Dispersion Routing Method (DRM). Using the DRM included the four stage.1-considering of initial value for LDC .2-calculating the concentration profile at the downstream station by using the upstream concentration profile and LDC.3- Performing a comparison between the calculated profile and measured profile.4- if the calculating profile is not a suitable cover, the measured profile of the process will be repeated until the calculated profile shows a good covering on the measured profile.
Numerical The ADE includes two different parts advection and dispersion. The pure advection term is related to transmission modeling without any dispersing and the dispersion term is related to the dispersion without any transmission. To discrete the ADE the finite volume method was used. According to physical properties of these two terms and the recommendation of researchers a suitable scheme should be considered for numerical solution of ADE terms. Among the finite volume schemes, the quickest scheme was selected to discrete the advection term, because of this scheme has suitable ability to model the pure advection term. The quickest scheme is an explicit scheme and the stability condition should be considered. To discrete the dispersion term, the central implicit scheme was selected. This scheme is unconditionally stable.
The results of longitudinal dispersion coefficient for the Severn River and Narew River were calculated using the DRM method and empirical formulas. The results of LDC calculation showed that the minimum and maximum values for the Severn River was equal to the 12.5 and 41.5 respectively and for the Narew River were reported as 18.0 and 56.0 respectively. The value of the LDC derived using the DRM was used as one of the input parameters for developing the computer program. For validation of numerical model, a comparison was conducted with results of analytical solution. This comparison showed that the performance of numerical method is quite suitable. For assessing the performance of numerical model the pollution transmission in the both mentioned rivers was simulated. The calculated LDC and time steps and distance steps was considered as 4m and 2s. The results of simulation showed that the performance of developed computer model is suitable for practical purposes.
In this paper the Finite volume method such as numerical model for Discretization the ADE and also estimating the LDS the Dispersion routing method has been used. To primary evaluating of the model the compression between the model result and analytical solution of ADE has been done. To assess the accuracy of the model in engineering work the results of the model compared with two rivers data observations (Severn and Narew). Final result showed that the performance of model is suitable.

Since flooding causes death and economic damages, then it is important and is one of the most complex and destructive natural disaster that endangers human lives and properties compared to any other natural disasters. This natural disaster almost hit most of countries and each country depending on its policy deals with it differently. Uneven intensity and temporal distribution of rainfall in various parts of Iran (which has arid and semiarid climate) causes flash floods and leads to too much economic damages. Detention basins can be used as one of the measures of flood control and it detains, delays and postpones the flood flow. It controls floods and affects the flood directly and rapidly by temporarily storing of water. If the land topography allows the possibility of making detention basin with an appropriate volume and quarries are near to the projects for construction of detention dam, it can be used, because of its faster effect comparing to the other watershed management measures. The open drains can be used alone or in combination with detention basin instead of detention basin solitarily. Since in the combined system of open and detention basin the dam height is increasing in contrast with increasing the open drainage capacity, optimization of the system is essential. Hence, the investigation of the sensitivity of optimized combined system (open drainage and detention basin) to the effective factors is also useful in appropriately design of the combined system.
This research aims to develop optimization model for a combined system of open drainage and detention basins in a mountainous area and analyze the sensitivity of optimized dimensions to the hydrological factors. To select the dam sites for detention basins, watershed map with scale of 1: 25000 is used. In AutoCAD environment, the location of the dam sites are assessed to find the proper site which contains enough storage volume of the detention basin and the narrower valley. After the initial selection of dam sites, based on the reservoir volume to construction volume ratio of each dam site, best sites were selected to have the higher ratio. The layout of the main drainage scheme that is responsible for collecting and transferring overland flows of farmlands and reservoir outflows was designed. In order to simulate the hydrological processes in upstream watershed and flood analysis, HEC-HMS model which is an extended version of HEC-1 was used as hydrologic model. The optimal combination of open drainages and detention basins was also developed. Watershed in terms of detention basin dams, topography and drainage were divided into 19 smaller sub-basins. The downstream agricultural basin due to the slope and drainage area was divided into 27 sub-basins. Regarding available information of the watershed, SCS method was used to calculate losses and to convert rainfall to runoff hydrograph. In this section Muskingum flood routing method was used considering its accuracy. In the present optimization model, the total cost of the combined system of dams and open drains used as the objective function. It is function bottom outlet diameter which is minimized by using optimization model. Other factors of the simulation model such as dam height and drainage dimensions were defined as function of the diameter of the bottom outlet of dams. After determining the optimal dimensions of the combined system of open drainage and detention basins, a sensitivity analysis was performed on hydrological factors.
After optimization of the dimensions of open drainage and detention basin integrated-system, sensitivity analysis was carried out on the dimensions of system for variation of flood simulation parameters such as rainfall, curve number and lag time. The error of estimated rainfall effected far less than the curve number (CN) on the optimum dimensions and cost. 10% variation of the rainfall depth caused respectively, 7%, 8% and 10% error in optimum dam height, drainage optimal depth and total cost. Lag time was identified less important effect in the determination of optimal dimensions. As its 10% changing produced 10% error in optimal dimensions costs.
The research results showed that curve number is the most important factor in determining the optimal size and cost. As with 10% error in the estimation of curve number caused error rates of 21%, 25% and 24% of the optimal dam height, the optimal depth of the drain and minimized costs, respectively

The hydraulic jump happens when flow transfers from supercritical regime to subcritical regime. The hydraulic jump on smooth bed is called the classic hydraulic jump. One way to increase the energy dissipation in a hydraulic jump is to roughen the bed. Elements including stabilizers and baffle blocks are commonly used as the energy dissipators in stilling basins to stabilize the location and decrease the length and conjugate depths of the hydraulic jumps. If roughness elements are placed uniformly on the bed and orthogonal to the flow direction, the formed jump is addressed as the hydraulic jump on rough bed. Recently, implementing short energy dissipaters and environment friendly rough beds have attracted attention and justify more research in these fields. Recent studies have addressed hydraulic jump on rough beds ([14], [5], and [12]). Relative roughness parameter first defined by Rajaratnam to investigate the jump characteristics and other researchers then used this parameter to investigate the characteristics of jump on rough bed. In this research, similar experiments to Pagliara et al (5) are designed to study continuous and natural rough beds.
All the experiments have been arranged and carried out in the hydraulic laboratory of Ferdowsi University, Mashhad Iran. Hydraulic jump characteristicswere measured in a horizontal rectangular flume, 0.30 m wide, 0.50 m deep, and 11 m long, with smooth glass side walls.The rough bed was simulated by gluing a layer of uniform gravel material with middle diameter 3.5mm and 11mm on a glass plate which was placed on the flume, throughout its length .In the physical model, to simulate a supercritical flow with three constant initial depths including , 1.5 and ,a steel sluice gate is installed. Furthermore, to stabilize the location ofhydraulic jump and create a free-surface jump, a sharp-crested weir with the same width as the channel width is installed at the end of the flume. Water contraction usually occurs after the sluice gate is avoided by a steel plate welded on the sluice gate. So, the initial depth equals the gate opening. According to the experimental procedure, after placing theuniform roughness heights on channel bed, the pump runs and water flows slowly into the flume. Then, discharge increases to reach the desired value and the sluice gate opening is set up to have the hydraulic jump formed at a distance of ahead of the gate. These circumstances maintain enough for data recording. The parameter of gravel particles considered as the most sensible characteristic. The subcritical depth y2 was measured from the profile survey, where the water surface began to be essentially level.
In the smooth and rough beds experiments show that variation in initial depth does not have any effect on decreasing the conjugate depths ratio. The conjugate depths ratio decreases as the roughness increases. The difference between conjugate depths ratio of rough beds with middle diameter 3.5mm (B) and 11mm (C) appears when the Froude number exceeds 7.5 and for Froude numbers greater than 10, a significant drop can be observed in the conjugate depths ratio diagrams from rough bed B to C. The horizontal distance between the beginning and end point of a hydraulic jump is considered as the length of the hydraulic jump. Dimensionless length of the hydraulic jump is presented as which is usually considered as a function of . For Froude number greater than 10, the dimensionless length of the hydraulic jump is nearly constant. Then, the ratio of for Froude numbers greater than 10 seems to be independent of supercritical Froude number and is just a function of roughness. In all experiments the length of the hydraulic jump decreases compared with the smooth bed under conditions that bed roughness is not subjected to water jet.
Experiments demonstrated that in the rough bed by increasing roughness, the conjugated depths ratio decreased compared with the classical hydraulic jump. The variation of initial depth of flow does not have any effect on reducing conjugate depths ratio and dimensionless length of the hydraulic jump. The length of the hydraulic jump in rough beds on average reduced between 28.5% and 47% with respect to the classical hydraulic jump which causes reduction in length of the stilling basin without bed roughness.

A free overfall offers a simple device for flow discharge measuring by a single measurement of depth at the end of the channel yb which is known as the end depth or brink depth. When the bottom of a channel drops suddenly, the flow separates from sharp edge of the brink and the pressure distribution is not hydrostatic because of the curvature of the flow. In channels with subcritical flow regime, control section occurs at the upstream with a critical depth (yc). Although pressure distribution at the critical depth is hydrostatic, the location of the critical depth can vary with respect to the discharge value. So, the end depth at brink is offered to estimate the discharge. A unique relationship between the brink depth (yb) and critical depth (yc), known as end-depth ratio (EDR = yb/yc), exist. Since a relationship between the discharge and critical depth exists, the discharge can ultimately be related to yb. However, when the approaching flow is supercritical, critical section does not exist. Therefore, the discharge will be a function of end depth and channel longitudinal slope.
In current study, an analytical model is presented for a circular free overfall with different flat base height in subcritical and supercritical flow regimes. The flow over a drop in a free overfall is simulated by applying the energy to calculate the EDR and end depth-discharge (EDD) relationship.
End-depth-discharge relationship: The flow of a free overfall in a channel can be assumed that is similar to the flow over a sharp-crested weir by taking weir height equal to zero. It is assumed that pressure at the end section is atmospheric, and also streamlines at the end section are parallel. To account for the curvature of streamlines, the deflection of jet due to gravity, the coefficient of contraction, Cc, is considered. At a short distance upstream the end section, the pressure is hydrostatic. By applying the energy equation between end section and control section which is at upstream the end section, the flow depth at the end of the channel yb in terms of depth at the control section can be determined.
Subcritical flow regime: In this case, the approach flow to the brink is subcritical for negative, zero and mild bed slopes with critical depth at the control section. Using the definition of the Froude number at critical depth, the discharge can be determined. As the explicit relationship between discharge and depth at the brink don’t exist, a relationship should be presented through regression analysis between discharge and yb using the different values of yc over the practical range of 0.01 to 0.84. In this study, below explicit equation is presented for computing Q*(dimensionless discharge) in terms of ( ): Where d is channel diameter, is the ratio of bottom elevation to the channel diameter and . This equation can be used for different values of over the practical range of 0.06–0.6.
Supercritical flow regime: A critical flow occurs upstream of the free overfall under the subcritical approach flow. However, no such critical flow occurs in the vicinity of the overfall under supercritical flow regime. Therefore, the Manning equation for known value of channel bed slope and Manning’s coefficient is exercised to derive the discharge relationship under the supercritical flow regime. Since an explicit equation for discharge in term of yb is impossible, a direct graphical solution for discharge for known end depth, channel bed slope, and ratio of bottom elevation has been provided for supercritical flow regime.
The free overfall in a circular channel with flat base has been simulated by the flow over a sharp-crested weir to calculate the end-depth ratio. This method also eliminates the need of an empirical pressure coefficient. The method estimates the discharge from the known end-depth. In subcritical flows, the EDR has been related to the critical-depth. On the other hand, in supercritical flows, the end-depth has been expressed as a function of the longitudinal slope of the channel using the Manning equation. The mathematical solutions allow estimation of discharge from the known end-depth in subcritical and supercritical flows. The comparisons of the experimental data with this model have been satisfactory for subcritical flows and acceptable for supercritical flows.

Groundwater resources are the main source of fresh water in many parts of Iran. Groundwater resources are limited in quantity and recently due to increase of withdrawal, these resources are facing great stress. Considering groundwater resources scarcity, maintaining the quality of them are vital. Traditional methods to evaluate water quality insist on determining water quality parameter and comparison between them and available standards. The decisions in these methods rely on just specific parameters, in order to overcome this issue, water quality indices (WQIs) are developed. Water quality indexes include a range of water quality parameters and using mathematical operation represent an index to classify water quality. Applying the classic WQI will cause deterministic and inflexible classifications associated with uncertainties and inaccuracies in knowledge and data. To overcome this shortcoming, using the fuzzy logic in water resources problems under uncertainty is highly recommended. In this paper, two approaches are adopted to assess the water quality status of the groundwater resources of a case study. The first approach determined the classification of water samples, whilst the second one focused on uncertainty of classification analysis with the aid of fuzzy logic. In this regard, the paper emphasizes on possibility of water quality assessment by developing a fuzzy-based quality index even if required parameters are inadequate.
The case study is located in the northwest of Markazi province, Saveh Plain covers an area of 3245 km2 and lies between 34º45′-35º03′N latitude and 50º08′-50º50′E longitudes. The average height of the study area is 1108 meter above mean sea level. The average precipitation amount is 213 mm while the mean annual temperature is 18.2oC. To provide a composite influence from individual water quality parameters on total water quality, WQI is employed. In other words, WQI is a weighting average of multiple parameters. The present research used nine water quality parameters (Table 2). In this paper Fuzzy Water Quality Indices (FWQIs) have been developed, involving fuzzy inference system (FIS), based on Mamdani Implication. Firstly, five linguistic scales, namely: Excellent, Good, Poor, Very poor, and Uselessness were taken into account, and then, with respect to ‘If→then’ rules the FWQIs were developed. Later, the seven developed FIS-based indexes were compared with a deterministic water quality index. Indeed seven FWQIs based on different water quality available parameters have been developed. Then developed indices were used to evaluate the water quality of 17 wells of Saveh Plain, Iran.
The present study analysed groundwater quality status of 17 wells of Saveh Plain using FWQI and WQI. Based on the driven results from WQI and its developed fuzzy index, similar performance was observed in most of the cases. Both of them indicated that the water quality in six wells including NO.1, 2, 6, 12, 13, and 17 were suitable for drinking. Due to the fact that the values of both indexes were under 100, the mentioned wells could be considered as drinking water supplies. The indexes illustrated the very poor quality of wells NO.7, 9, 10, 11, 14, and 16. As a result, according to FWQI1 along with WQI, nearly 35% of wells have proper drinking water quality, while approximately 30% and 35% of them suffered from poor and very poor quality, respectively. The overall picture of water quality within the study area was not satisfying, hence, an accurate site selection for discovering water recourses with appropriate quality for drinking purpose must be responsible authorities’ priority. Analysis of FWQI2, FWQI3 and FWQI4 revealed that elimination of the parameters slightly changed the result of FWQI2; however, FWQI3 and FWQI4 did not vary considerably. Thus, Cl influenced the water quality slightly, but Ca and K did not affect the water quality of the plain. The results showed that inexistence of one of the mentioned parameters would not affect the computational process adversely. A glance at FWQI5, FWQI6 and FWQI7 revealed the improper performance of FWQI5 to show wells’ water quality status. Throughout the FWQI5 evaluation process, all the wells’ water quality stood in Excellent category. Due to the considerable values of TDS in the Plain, elimination of this parameter in FWQI5 caused inappropriate evaluation. Hence, whenever a case study deals with a high value of a specific quality parameter, elimination of that parameter would negatively demote validation of the analysis. Figures (3)-(6) represented the results of WQI along with seven FWQIs for 17 utilized wells’ water quality assessment in the study area during the proposed periods.
Throughout the present study, the capability of seven FIS-based indexing procedures in modelling the water quality analysis of 17 wells of Save Plain was discussed. The proposed FWQIs were developed on the basis of Mamdani approach by applying triangular and trapezoidal membership functions to determine the groundwater quality of the case study according to the nine parameters. The results revealed that FWQI1-4 outperformed others. On the other hand, FWQI5-7 which eliminated three out of the nine parameters, did not made a valid contribution to the computational context. This might be related to omitting the effective water quality parameters from the inputs of the model. The results also illustrated that, only six out of 17 wells of the region could be considered as suitable sources for the drinking purpose. The water quality status in five wells was not satisfying, and six wells were plagued by very poor quality of water.

North of the Khouzestan is one of the most important citrus production center. Usually border irrigation is used to irrigate citrus in this area. This system has generally low application efficiency. Several investigations in other arid region have demonstrated in addition to improved irrigation efficiency with low-volume pressurized irrigation systems, citrus trees have adapted with these new irrigation systems. However limited information exists on the performance of mature orchards converted from border surface irrigation to pressurized irrigation systems. Therefore, the current research was conducted to evaluate the feasibility of converting surface irrigation to pressurized irrigation systems on mature citrus trees in climate conditions of North Khouzestan.
This study was conducted during three years at Safiabad Agricultural Research Center to evaluate the yield of citrus trees and the quality of fruits for two Marss and Valencia varieties which grow 7 years previously with surface irrigation and converted to pressurized irrigation systems. The treatments consisted of six irrigation methods including Overhead sprinkle irrigation (OHSI), Under tree sprinkle irrigation(UTSI), Trickle irrigation(TI)(six 8 L/h Netafim emitters), Microjet irrigation (MI)(two 180 microjet were located under canopy near of the trunk at opposite sides of trunk),Bubbler irrigation(BI)(a single located under the canopy of each tree)andSurface irrigation(SI) method.Soil texture was clay loam well drained without salinity(ECe=0.69ds m-1), with 1.25 percent organic carbon. The experimental design was completely randomized design. The trees were irrigated during spring and summer seasons. For calculating irrigation water depth in TI, MI and BI systems, daily evaporation from a class A evaporation pan of the Safiabad weather station (nearby the experimental field) was collected, and evapotranspiration of the citrus trees was calculated applying a pan coefficient of 0.8. During the growth season, soil moisture content was measured before irrigation in root zone depth using weighing method at two points of the beginning and the end of the garden to obtain an average showing changes of the field moisture content. Applied water were measured with flow meter for OHSI, UTSI,TI, MI and BI methods and WSC flume for SI treatment. In middle January after fruit ripening, fruit yield was determined by harvesting all the fruits from six trees located in the center of each plot. Weight of fruits from every tree was recorded. Then, 3kilogram fruits per tree were randomly separated and peel thickness, diameter, weight, juice solid percent, total dissolved solids(TSS) and Citric acid were measured.
Results The annual precipitation was 385,345, and 336 mm for 2004, 2005, and 2006 years, respectively. The mean temperature of June, July and August (the warmest months) for 2004, 2005, and 2006 was 45.6, 45.2 and 45.8°C. Higher temperature in third year caused to increase heat stress, so fruit yield decreased. Irrigation water consumption in OHSI and UTSI were among 15000 to 17000 m3ha-1. Continues contact of irrigation water contacting with leaves in OHSI causes the accumulation of salts on the leaf surface and leaf drop in harvest season. Consumed water in BI, MI and TI compared with SI method reduced by as much as 48.6%, 57.2%, and 58.4%, respectively. Because soil wetted area in BI, MI and TI methods were low and about 30 to 50 percent of soil area.
There were significant differences in citrus yield, water use efficiency (WUE) and quality in 1% and 5%, so that comparison of means in Mars variety showed that the yield of trees in TI and SI methods were significantly higher than UTSI method. On the other hand, fruit yield was similar in OHSI, MI, TI and SI methods. Valencia variety fruit yield was similar for in BI, MI, TI and SI methods in all 3 years, and significantly more than OHSI and UTSI although BI, MI, TI used only 48% to 58% of irrigation water compared with SI method. WUE under BI, MI and TI methods was enhanced by 2 to 3 times more than SI,OHSI and UTSI methods because consumed water decreased in BI, MI and TI about 50%. Fruit size and fruit weight of Marss variety in the OHSI and fruit size and fruit weight of Valencia variety in the OHSI, MI and SI were better than other systems and had a significant difference in 1% probability.
Overall results of this study indicated that it is possible to convert SI to BI, MI and TI methods in northern khouzestan orchards without decreasing in fruit yield and quality of citrus trees. Salt accumulation on leaf surface in OHSI method was caused to drop leaves in harvest season.

Infiltration is the most important physical properties of agricultural soils. Infiltration families are general relationships that attempt to categorize the infiltration behavior of soils. Walker et al. (2006) discussed the assumptions and procedures used to develop the original NRCS families. Those families categorize infiltration behavior according to their steady-intake rate and were developed largely from border irrigation data. As such, those families have been more widely adopted in border/basin irrigation analyses than in furrow studies. In 2004, NRCS decided to revise the families, largely with the goal of enhancing their applicability to furrow irrigation (Walker et al., 2006). In contrast with the original families, Walker et al. (2006) categorized infiltration based on the average rate during the first 6 h of opportunity time. The new families were developed from furrow infiltration measurements, and then adapted to border conditions. Those infiltration measurements were obtained under inflow rate, slope, cross section, and roughness conditions. Recognizing that these flow conditions affect flow depth and that flow depth affects infiltration in furrows, Walker et al. (2006) proposed procedures for adapting the parameters to new hydraulic conditions. Procedures are also provided for adapting the parameters to events late in the irrigation season. Another important aspect of the new families is the use of the Extended Kostiakov equation, which represents steady-state infiltration better than the Kostiakov formula employed by the original NRCS families. The procedures used to adapt the furrow infiltration parameters to different hydraulic conditions are empirical. From the available data, Walker et al. (2006) developed relationships for the reference parameter values (Kref, aref, and f0ref) and reference hydraulic conditions (discharge Qref and wetted perimeter1 WPref) as a function of Fn, the family value.
In this study the currency of revised SCS method to estimate infiltration parameters of furrow irrigation systems in Amirkabir sugar cane fields was evaluated. For this purpose, infiltration parameters and the cumulative 6 hours infiltration (z) for furrow irrigation systems of this region was estimated with revised SCS method and, then compared with field measurement of z. Then, general functions were developed to adjust the parameters to later flow irrigation conditions.
This research was carried out from January 2010 to December 2011. As one of the research fields of Sugarcane Research Center in Amir Kabir Sugarcane Planting and by Products Company of Khuzestan. The field work was conducted on one set of furrow irrigation. This set had three furrows1.8 m wide and 140 m long. The middle furrow of each set was used to take measurements, while the side furrows were used as buffering area. The intake family numbers in revised SCS method (Fn) based on the average infiltration rate during the first 6 h of irrigation. To determine the Fn, double ring experiment were performed before irrigation. Then revised SCS parameters and original SCS parameters were determined. By measuring inflow, outflow, and calculating surface water storage, the volume of infiltrated water was determined. The advance and recession times were recorded at 14 points at 10 m intervals along each furrow. Seven irrigation events were examined. Fiberglass flumes (WSC) type II was used at the beginning and the end of each furrow in the first set where inflow/outflow measurements were to be taken. Experiments were carried out in order to determine the final infiltration rate (f0) with the assumption of uniform soil infiltration characteristics. First, inflow and outflow of the furrow were measured at the beginning and the end of two Fiberglass WSC flumes. Then, when the flow reached a constant level, f0 was measured.
For evaluation of the results, four statistical indices: average prediction error of model (Er), distribution into 45° line (λ), determination coefficient (R2) and average relative error of model (Ea) were used. According to the results, revised SCS method overestimated infiltration value and it had an excessive error. Due to the high error of this technique, empirical formulas for reference parameters to this irrigation conditions was determined. The values of a, K, and F0 parameters were measured in field and correlated with the NRCS Family Number, Fn. Then, general functions were developed to adjust the parameters to later flow irrigation conditions. Review the accuracy of the presented functions showed that these functions with values of λ, R2 and Ea respectively 0.95, 0.91 and %4.5, has the best prediction of infiltration. The coefficient of irrigation condition factor (ICF) for the desired area was determined that the average numeric value equal to 0.82. According to the results of Walker et al. (2006), a typical later continuous intake can be estimated by ICF of 0.80. The average value of the 6 h intake rate (Fn) for the desired area is 0.46 and the average value of basic infiltration rate (f0) is 0.48 which is larger than Fn. This is consistent with the results of Walker et al. (2006).
Results of this study showed that the original SCS method has underestimated cumulative infiltration and revised SCS method with furrow irrigation equations has the overestimated cumulative infiltration. General functions were developed to adjust the parameters to later flow irrigation conditions. Review the accuracy of the presented functions showed that these functions have the best prediction of infiltration. The coefficient of irrigation condition factor (ICF) was also determined, (ICF= 0.82).

The rapid population growth in Iran and the corresponding increases in water demands, including drinking water, industry, agriculture and urban development and existing constraints necessitate optimal scheduling necessity in use of this crucial source. Furthermore, the phenomenon of climate change as a major challenge for humanity can be considered in future periods. Climate change is caused by human activity have also been identified as significant causes of recent climate change, referred to as "global warming". Climate change indicates an unusual change in the Earth's atmosphere and climate consequences of the different parts of planet Earth. Climate change may refer to a change in average weather conditions, or in the time variation of weather around longer-term average conditions. A Warmer climate exacerbates the hydrologic cycle, altering precipitation, magnitude and timing of runoff. The purpose of this study was to evaluate the effect of climate change on water consumption and demand in Bar river basin of Neighbor. Climate change affects precipitation and temperature patterns and hence, may alter on water requirements and demand at three sectors; agriculture, industry and urban water.
At present, Global coupled atmosphere-ocean general circulation models (AOGCMs) are the most frequently used models for projection of different climatic change scenarios. AOGCMs models represent the pinnacle of complexity in climate models and internalize as many processes as possible. These models are based on physical laws that are provided by mathematical relations. AOGCMs models used for climate studies and climate forecast are run at coarse spatial resolution and are unable to resolve important sub-grid scale features such as clouds and topography. As a result AOGCMs output cannot be used for local impact studies. Therefore, downscaling methods were developed to obtain local-scale weather and climate, particularly at the surface level, from regional-scale atmospheric variables that are provided by AOGCMs. Four different downscaling methods exist: regression methods, weather pattern-based approaches, stochastic weather generators, which are all statistical downscaling methods, and limited-area modeling. For this research, HadCM3 and statistical downscaling model (SDSM), precipitation and temperature variations were simulated under A2 scenario. Then the impacts of these variations on Bar River discharge were analyzed, i.e. water resources at three sectors of agriculture, industrial and potable water under climate change during 2011-2040 using WEAP. Results at first part of simulation showed that temperature is increasing and precipitation is decreasing resulted in decreasing of Bar discharge. According to the decreasing on Bar discharge, water allocation was simulated under these conditions of agricultural and industrial development and increasing of population with WEAP. Simulation showed that watershed will face increasing of water demand for all three sectors; agriculture, industry and drinking water, so the highest water shortage would be in agricultural demand and then industry and drinking water respectively. IWRM is the basic managerial need to rest the demands especially for drought periods. Current allocation process is based on steady state conditions while allocation pattern would be done under climate change conditions so we need to be reinvestigat the last allocations for all three sectors. Another challenge for this watershed refers to the gardens and steel factory of Khorasan that they need to use new technologies for reduction of their water needs.
Results In this study, the outputs of General Circulation Models (HadCM3) and statistical downscaling model (SDSM) have been used to investigate the changes of rainfall and temperature under A2 scenario in Bar river basin of Neishaboor and assess the impacts of this changes on the Bar river’s discharge. Finally, using WEAP model under climate change conditions for the period of 2011-2040, the status of basin water resources was evaluated for the three sectors (agricultural, domestic and industrial). The results indicated increased temperature in the Arie station amounting to 16 percent and rainfall reduction in the Arie and Taghan stations amounting to 3.9 and 8.75 percent respectively. Under these conditions, according to the increasing water demands of agricultural and industrial sectors in the future, there will be a shortage of water supply resources in the region. So the agricultural sector with 12 percent will have the highest percentage of water shortage and water scarcity and of the industrial sector will be 2%. However, the drinking water or domestic demand will not face a shortage of supplies.
Therefore given that the most part of agriculture sector’s share of basin is allocated to orchards and on the other hand the most shortages are related to agriculture, then while creating an integrated management of water resources, development and use of modern methods of irrigation during the period of 2011 - 2040 would seem to be necessary.

Introduction Subdaily estimates of reference evapotranspiration (ET¬¬o) are needed in many applications such as dynamic agro-hydrological modeling. The ASCE and FAO56 Penman–Monteith models (ASCE-PM and FAO56-PM, respectively) has received favorable acceptance and application over much of the world, including the United States, for establishing a reference evapotranspiration (ETo) index as a function of weather parameters. In the past several years various studies have evaluated ASCE-PM and FAO56-PM models for calculating the commonest hourly or 15-min ETo either by comparing them with lysimetric measurements or by comparison with one another (2, 3, 5, 9, 10, 11, 16, 17, 19). In this study, sub-daily ET¬o estimates made by the ASCE-PM and FAO56-PM models at different timescales (1-360 min) were compared through conduction of a computational experiment, using a daily-to-subdaily disaggregation framework developed by Parchami-Araghi et al. (14).
Materials and Methods Daily and subdaily weather data at different timescales (1-360 min) were generated via a daily-to-subdaily weather data disaggregation framework developed by Parchami-Araghi et al. (14), using long-term (59 years) daily weather data obtained from Abadan synoptic weather station. Daily/subdaily net longwave radiation (Rnl) was estimated through 6 different approaches, including using two different criteria for identifying the daytime/nighttime periods : 1) the standard criteria implemented in both ASCE-PM and FAO56-PM models and 2) criterion of actual time of sunset and sunrise in combination with 1) estimation of clear-sky radiation (Rso) based on the standard approach implemented in both ASCE-PM and FAO56-PM models (1st and 2nd Rnl estimation approaches, respectively), 2) integral of the Rso estimates derived via a physically based solar radiation model developed by Yang et al. (25), YNG model, for one-second time-steps (3rd and 4th Rnl estimation approaches, respectively), and 3) integral of the calculated Rnl based on Rso estimates derived via YNG model for one-second time-steps (5th and 6th Rnl estimation approaches, respectively). The capability of the two models for retrieving the daily ETo was evaluated, using root mean square error RMSE (mm), the mean error ME (mm), the mean absolute error ME (mm), Pearson correlation coefficient r (-), and Nash–Sutcliffe model efficiency coefficient EF (-). Different contributions to the overall error were decomposed using a regression-based method (7).
Results Discussion Results showed that during the summer days, 24h sum of subdaily radiation and aerodynamic components of ETo and the estimated ETo derived from both models were in a better agreement with the respective daily values. The reason for this result can be attributed to the nighttime value of cloudiness function (f) and the longer nighttime during the cold seasons. Because the nighttime values for f are equal the f value at the end of the previous daylight period until the next daylight period. The difference between subdailty ETo derived from the ASCE-PM and FAO56-PM models during the day and night was highly dependent on the wind speed. In case of both models, daily aerodynamic component of ETo (ETod,aero) were reproduced more efficiently, compared to radiation component (ETod,rad). Except in the case of 6th Rnl estimation approach, FAO56-PM model (with a mean model efficiency (MEF) of 0.9934 to 0.9972) had better performance in reproducing the daily values of ETo (ETod), compared to ASCE-PM model (with a MEF of 0.9910 to 0.9970). The agreement between 24h sum and daily values of aerodynamic component had a lower sensitivity to the adopted time-scale, compared to the radiation component. Compared to the FAO56-PM model the performance of the ¬ASCE-PM model in reproducing the ETod,rad, ETod,aero and ETod had higher sensitivity to the approach utilized for calculation of Rnl and hence, to the uncertainty of net radiation. Results showed that a smaller time step does not necessarily leads to an improvement in agreement between 24h sum of subdaily and daily values of ETo. Deficiency of the standard daytime/nighttime identification criteria was resulted in a higher daily averaged daytime (1.3831 to 1.6753 h) used in cloudiness function calculations, compared to the respective value used in calculations of the radiation and aerodynamic components. In order to estimate the subdaily ETo under climatic condition of the studied region, the use of ASCE-PM model based on the 6th Rnl estimation approach, (ASCE-PM)6, with a MEF of 0.9970 is preferred, compared to other studied alternatives. Another advantage of the (ASCE-PM)6 and (FAO56-PM)6 models is their computational efficiency in case of their implementation in hydrological models.

Precise prediction of river flows is the key factor for proper planning and management of water resources. Thus, obtaining the reliable methods for predicting river flows has great importance in water resource engineering. In the recent years, applications of intelligent methods such as artificial neural networks, fuzzy systems and genetic programming in water science and engineering have been grown extensively. These mentioned methods are able to model nonlinear process of river flows without any need to geometric properties. A huge number of studies have been reported in the field of using intelligent methods in water resource engineering. For example, Noorani and Salehi (23) presented a model for predicting runoff in Lighvan basin using adaptive neuro-fuzzy network and compared the performance of it with neural network and fuzzy inference methods in east Azerbaijan, Iran. Nabizadeh et al. (21) used fuzzy inference system and adaptive neuro-fuzzy inference system in order to predict river flow in Lighvan river. Khalili et al. (13) proposed a BL-ARCH method for prediction of flows in Shaharchay River in Urmia. Khu et al. (16) used genetic programming for runoff prediction in Orgeval catchment in France. Firat and Gungor (11) evaluated the fuzzy-neural model for predicting Mendes river flow in Turkey. The goal of present study is comparing the performance of genetic programming and M5 model trees for prediction of Shaharchay river flow in the basin of Lake Urmia and obtaining a comprehensive insight of their abilities.
Shaharchay river as a main source of providing drinking water of Urmia city and agricultural needs of surrounding lands and finally one of the main input sources of Lake Urmia is quite important in the region. For obtaining the predetermined goals of present study, average monthly flows of Shaharchay River in Band hydrometric station has been gathered from 1951 to 2011. Then, two third of mentioned data were used for calibration and the rest were used for validation of study models including genetic programming and M5 model trees. It should be noted that for prediction of Shaharchay river flows, previous data of mentioned river in 1, 2 and 3 months ago (Q, Q, Q) were used.
Genetic programming: was first proposed by Koza (17). It is a generalization of genetic algorithms. The fundamental difference between genetic programming and genetic algorithm is due to the nature of the individuals. In genetic algorithm, the individuals are linear strings of fixed length (chromosomes). In genetic programming, the individuals are nonlinear entities of different sizes and shapes (parse trees). Genetic programming applies genetic algorithms to a “population” of programs, typically encoded as tree-structures. Trial programs are evaluated against a “fitness function”. Then the best solutions are selected for modification and re-evaluation. This modification-evaluation cycle is repeated until a “correct” program is produced.
Model trees generalize the concepts of regression trees, which have constant values at their leaves. So, they are analogous to piece-wise linear functions. M5 model tree is a binary decision tree having linear regression function at the terminal nodes, which can predict continuous numerical attributes. Tree-based models are constructed by a divide-and-conquer method.
In order to investigate the probability of using different mathematical functions in genetic programming method, three combinations of the functions were used in the current study. The results showed that in the case of predicting river flows with Q, M5 model trees with root mean squared error of 4.7907 in comparison with genetic programming by the best mathematical functions and root mean squared error of 4.8233 had better performances. Obtained results indicated that adding more mathematical functions to the genetic programming and producing more complicated analytical formulations did not have positive effect in reducing prediction error. Unlike the previous observed trend, in case of predicting river flows with Q Q, the genetic programming method with root mean squared error of 3.3501 in comparison with M5 model trees with error of 3.8480 had more satisfied performance. Finally, in the case of predicting river flows with Q, Q,Q, the genetic programming method with root mean squared error of 3.3094 in comparison with M5 model trees with error of 3.5514 presented better predictions. As a result, it can be stated that genetic programming by the best mathematical functions and considering the input parameters of Q,Q,Q, by resulting less root mean squared error and high correlation coefficients had the best performances among others. Also, the results showed that adding more trigonometric functions did not improve the precisions of the predictions.
In this research, the intelligent models such as genetic programming and M5 model trees have been used for prediction of monthly flows of Shaharchay River located in East Azerbaijan, Iran. The obtained results showed that the genetic programming by the best mathematical functions and M5 model trees in case of considering the input parameters of Q,Q,Q, by less root mean squared error had the best performances in river flow predictions. As a conclusion, the genetic programming method by specific mathematical functions including four basic operations, logarithm, power and using input parameters of Q,Q,Q, has been proposed as the best and precise model for predicting Shaharchay River flows.

Hydrologic homogeneous group identification is considered both fundamental and applied research in hydrology. Clustering methods are among conventional methods to assess the hydrological homogeneous regions. Recently, Self Organizing feature Map (SOM) method has been applied in some studies. However, the main problem of this method is the interpretation on the output map of this approach. Therefore, SOM is used as input to other clustering algorithms. The aim of this study is to apply a two-level Self-Organizing feature map and Ward hierarchical clustering method to determine the hydrologic homogenous regions in North and Razavi Khorasan provinces.
SOM approximates the probability density function of input data through an unsupervised learning algorithm, and is not only an effective method for clustering, but also for the visualization and abstraction of complex data. The algorithm has properties of neighborhood preservation and local resolution of the input space proportional to the data distribution. A SOM consists of two layers: an input layer formed by a set of nodes and an output layer formed by nodes arranged in a two-dimensional grid. In this study we used SOM for visualization and clustering of watersheds based on physiographical data in North and Razavi Khorasan provinces. In the next step, SOM weight vectors were used to classify the units by Ward’s Agglomerative hierarchical clustering (Ward) methods. Ward’s algorithm is a frequently used technique for regionalization studies in hydrology and climatology. It is based on the assumption that if two clusters are merged, the resulting loss of information, or change in the value of objective function, will depend only on the relationship between the two merged clusters and not on the relationships with any other clusters. After the formation of clusters by SOM and Ward, the most frequently applied tests of regional homogeneity based on the theory of L-moments are used to compare and modify the clusters which are formed by clustering algorithms and find the best clustering method to achieve hydrologically homogeneous regions. Two statistical measures are used to form a homogeneous region, (i) discordancy measure and (ii) heterogeneity measure. The discordancy measure, Di, is used to find out unusual sites from the pooling group (i.e., the sites whose at-site sample L moments are markedly different from the other sites). Generally, any site with Di>3 is considered as discordant. The homogeneity of the region is evaluated using homogeneity measures which are based on sample L-moments (LCv, LCs and LCk), respectively. The homogeneity measures are based on the simulation of 500 homogeneous regions with population parameters equal to the regional average sample l-moment ratios. The value of the H-statistic indicates that the region under consideration is acceptably homogeneous when H

Introduction Development of water resources projects are accompanied by several environmental impacts, among them, the changes in the natural flow regime and the reduction of downstream water flows. With respect to the water shortages and non-uniform distribution of rainfall, sustainable management of water resources would be inevitable. In order to prevent negative effects on long-term river ecosystems, it is necessary to preserve the ecological requirements of the river systems. The assessment of environmental flow requirements in a river ecosystem is a challenging practice all over the world, and in particular, in developing countries such as Iran. Environmental requirements of rivers are often defined as a suite of flow discharges of certain magnitude, timing, frequency and duration. These flows ensure a flow regime capable of sustaining a complex set of aquatic habitats and ecosystem processes and are referred to as "environmental flows". There are several methods for determining environmental flows. The majority of these methods can be grouped into four reasonably distinct categories, namely as: hydrological, hydraulic rating, habitat simulation (or rating), and holistic methodologies. However, the current knowledge of river ecology and existing data on the needs of aquatic habitats for water quantity and quality is very limited. It is considered that there is no unique and universal method to adapt to different rivers and/or different reaches in a river. The main aim of the present study was to provide with a framework to determine environmental flow requirements of a typical perennial river using eco-hydrological methods. The Barandozchi River was selected as an important water body in the Urmia Lake Basin, Iran. The preservation of the river lives, the restoration of the internationally recognized Urmia Lake, and the elimination of negative impact from the construction of the Barandoz dam on this river were the main concerns in this study.
With lack of ecological data, the environmental requirements of the Barandozchi River were investigated using five eco-hydrological methods (1- Tennant, 2- Tessman, 3- Flow Duration Indices, 4- FDC shifting, 5- DRM). Some of these methods are too simplistic and do not take into account the direct hydro-ecological interactions (e.g. Tennant method), and some have been developed for a specific country/region (e.g., DRM), and need to be adapted to a different physiographic environment before they can be reliably applied. Two ecological friendly models GEFC, and DRM were tested to estimate the environmental flow of this river. The results were compared with corresponding flows allocated for the release from the Barandoz Dam (currently under construction).
The prediction of the mean annual environmental flows from five eco-hydrological methods are presented and compared with the corresponding value reported in the downstream dam’s documents. The ultimate decision making based on the potential flows in the river, the environmental class of the river management, and engineering judgment is also recommended for the flows in the river towards the Urmia Lake. The results indicated that the flow allocation for the river environment (4% of mean annual flows) is not sufficient to meet the minimum flow requirements for any of the targeting species in the river ecosystem. In order to maintain the Barandozchi River at minimum acceptable environmental status (i.e. Class C of environmental management), an average annual flow of 1.9 m3/s (26% MAR) are to be provided. The distribution of monthly flow rates in the river is also recommended for sustaining the Barandozchi River life.
The provision for the minimum ecological flows was investigated in the Barandozchi River ecosystem. The results indicated that, in order to maintain the Barandozchi River at minimum acceptable environmental status (i.e. Class C), an average annual flow of 1.9 m3/s (26% MAR) are to be provided along the river towards the internationally recognized Urmia Lake, in Iran. Considering the construction of the Barandoz dam on this river, the pre-determined environmental flow releases from the dam are to be revised in order to increase the order of flows from 4% to 26% or more. Further investigation is necessary to take into account for the targeting riverine species and for the saving of the Urmia lake ecosystem. It is noted that minimum flow requirements are to be allocated in critical months of the year or during drought period of the river basin. Water leasing from agricultural users is an option or a necessary action whenever long-term environmental damages to the river ecosystem must be avoided.

Water allocation management should be performed in a way that the various practical irrigation parts and drainage networks remain stable. Thus, irrigation management transfer and participatory irrigation management have been proposed in more than 57 countries. Such issue along with institutional mechanisms for participation severely emphasizes a new adjustable organization to transfer the investment from public resources to non-governmental sources and thus granting and handling the burden on public WUAs. In this study, the reliability of irrigation indicator was used to evaluate general irrigation planning performance of 20 WUAs along areas at Alborz Integrated Water and Land Management Project in Mazandaran province.
The overall project area encompassed the watersheds of the BabolRiver, Talar and Saih River of the Mazandaran Province, Iran. The Alborz Irrigation and Drainage network is located in the lower catchment between the Babol and Siah Rivers (western and eastern boundaries respectively) and with the Caspian Sea to the north in. The site located between 36ú 15ó N and 36ú 46ó N latitude and 52ú 35ó E and 53ú E longitude and covers 90520 ha. In downstream of Alborz reservoir, two diversion dam, Raiskola and Ganjafroz is located and two irrigation channels depends on these dam are constructed.
Organizing the WUAs is also important in other respects, so that the sources and utilization areas will be limited to 2,000 hectares to 6,000 hectares from 10000 hectares to 30000 hectares, respectively, which increases the simulation accuracy in a small-scale model. WUAs are classified based on the following principles:• Adaptation of hydrological and water boundaries,
• Land use and cropping pattern
• Main and secondary irrigation and drainage channels location,
• Ensuring the financial stability and independence,
• Considering the cultural needs, local farmers’ roles and social studies in the region.
In order to evaluate the water allocation, the reliability index must also be defined which stands as the oldest and most practical criterion for water resource systems analysis serving as the indicator which identifies and analyzes the system status for failure or non-failure condition. In some studies, to determine the reliability index, the entire month in which the system was successful in providing the required water divided by the entire system operation duration. Accordingly, the system can be considered as reliable if the deficiency in not more than 20% in simulation, that is, the probability of 80% can be used to provide the water supply level over four years out of five years. The application of the given method will be used in evaluating the demand balance simulation.
The results of estimating the reliability index showed that the water users association with the highest priority in terms of location priority have approximately a reliability index of 70%, representing considerable shortages and deficiency making inevitable use of other resources (BMC1, HATKI1, B3-1-1, TMC1 and RaiskolaWUAs) among which Raiskola had the highest priority relative to other WUAs, with about 91 percent, and was successful in providing the required water. WUAs with lower location priority adjacent to Siahrood River have been successful in approximately 75 percent of their water supply. The WUAs with the lowest priority (HATKI3, TMC3 and BMC3) had the lowest reliability index of about 50% meaning they were successful in meeting the water supply for only 50%. The C24-1 WUAs was 100 percent successful in its water supply which could be also noticeable among other WUAs. In order to assess the success of the system to meet the demand of WUAs, the Alborz network functionality was investigated. The major water utilization from river channels and the release of Alborz Dam were analyzed based on the statistical normal distribution function governing the However, the volume can be varied between160 to 480 million cubic meters. The possibility of 80% supply level (supplying four out of five years) for standing as an example of a guaranteed supply of an irrigation project is about 198 million cubic meters. The probability of 20% of the water supply (a complete supply of a year out of five years) is about 347 million cubic meters. This means that the system is only able to provide an estimate of one year out of five years. The overview of which reveals a considerable value (347 million cubic meters), while from the total surface water flowing in the Alborz network (585 million cubic meters), requirements of Alborz dam supply, environmental needs and output to the sea must be considered. Regarding the 50% probability, the supply value is equal to 277 million cubic meters. Based on the given points and also the conducted analyses, the Alborz network water resources balance results can be estimated. Considering the water resources allocation management among WUAs in Alborz Dam irrigation systems, it was found that among 20 selected WUAss in the area, 5 WUAs of BMC2, B3-2, HATKI3, C25-3 and C25-4 were not able to supply all their needs despite using all resources available in the project.
With aim of minimizing the deficiencies and spatial priorities each one of WUAs were evaluated. Result showed that demand of 460 MCM of WUAs, 277.02 MCM is supplied from surface water. It could be concluded that average reliability is 70 percent and probability of 20 and 80 percent of reliability are 347 and 198 MCM that should be taken into account as total level allocation and first level allocation, respectively. It also could be used to estimate water balance in drought and wet periods, as the application of different management scenarios in withdrawals of AB- bandans and aquifer of Alborz scheme. The results of estimating the reliability index showed that the WUAs with the highest priority in terms of location priority have approximately a reliability index of 60%, representing considerable shortages and deficiency.

In two last decades, greenhouse cultivation of different plants has developed among Iranian farmers, approximately 45 percent of national greenhouse cultures consisting of cucumber, tomato and pepper. As huge amounts of agricultural water in Iran are extracted from groundwater resources and a large number of Iranian plains are in critical conditions, and because irrigation is the major consumer of water (95 percent), it must be performed in a scientific manner. One approach to this is to obtain the knowledge of the consumptive use of major crops which is named evapotranspiration (ETc).
This research was carried out in a north-south greenhouse belonging to Plant Protection Research Institute, located on northern Tehran, Iran, for estimating greenhouse cucumber evapotranspiration. Trickle irrigation method was used, and meteorological data such as temperature, humidity and solar radiation were measured daily. Physical and chemical measurements were conducted and electric conductivity (EC) and pH values of 3.42 dsm-1 and 7.19, respectively, were recorded. Soil texture and bulk density were measured as to be sandy loam and 1.4 gr cm-3, respectively. In order to measure the actual evapotranspiration, cucumber seeds were also cultured in six similar microlysimeters and irrigation of each microlysimeter was based on FC moisture. If any drained water was available, it was measured. Finally, with measured meteorological characteristics in greenhouse which are suggested to have an effect on ET and were measurable, the best multiple linear regression and artificial neural network were established. The average data from three microlysimeters were used for calibration and that from three other microlysimeters were used for validation set.
In the former case, when we used one multiple linear regression with measurable meteorological variables inside the greenhouse to predict cucumber ET for the entire growth period, high and considerable amounts of error occurred, as the difference between measured and predicted values of ET is approximately 2.86 mm day-1 which is noticeable. Overestimation of the cucumber ET in the first and last stages which will result in decreasing water use efficiency and underestimation in blooming and yielding fruit stages, when cucumber is more susceptible to water stress, are the other disadvantages of using one equation for the entire growth period to describe and predict cucumber ET. In contrast, when we divided growth period into four steps, the MLR method’s performance in prediction of ET was improved and the difference mentioned above between measured and predicted values of ET (2.86 mm day-1) decreased to about 1.32 mm day-1. The results showed that measured and predicted values of ET ranged from (0.08 to 4.75) and (0.13 to 4.25) when the whole growth period is considered as one step, respectively. These mentioned values were obtained (0.08 to 1.5) and (0.13 to 1.75); (0.71 to 2.64) and (1.31 to 4.25); (2.18 to 4.75) and (1.69 to 4.13); (1.32 to 2.61) and (2.66 to 3.74) for each of growth period stages, respectively. Also the value of total ET for the entire growth period is measured 273.45 mm and predicted 275.7 and 275.59 mm, when the whole growth period is considered as one step or divided into four stages, respectively. Although dividing the growth period improved ET prediction, the results in the first and especially the third stage are still discussable. Therefore, as with MLR method, the capability of ANN technique was investigated in prediction of cucumber ET. Comparison of measured and predicted values of ET confirms that ANN has better performance than MLR, even when growth period is divided.
Determining cucumber evapotranspiration in the greenhouse was the main objective of this study. For this purpose we used Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) techniques. In MLR, first we used one equation for the entire growth period. The results showed that this single equation is not able to simulate actual ET of cucumber. To overcome this problem, we divided the growth period into four stages and derived a separate equation for each stage. The results showed that this procedure improves prediction of cucumber ET, especially in the second and last stages of growth period. Statistical indices such as RMSE, Ens, PBIAS and PSR, t-statistical results, measured versus predicted ET values, and predicted values of ET in the growth period indicate that ANN technique is not only reliable, but also easier than the MLR technique.

A total dissolved solid (TDS) is an important indicator for water quality assessment. Since the composition of mineral salts and discharge affects the TDS of water, it is important to understand the relationship of mineral salts composition with TDS.
In this study, methods of artificial neural networks with Levenberg-Marquardt training algorithm, adaptive neuro fuzzy inference system based on Subtractive Clustering and Gene expression programming were used to model water quality properties of Zarrineh River Basin at upstream of Boukan dam, to be developed in total dissolved solids prediction. ANN and ANFIS programs code were written using MATLAB programming language. Here, the ANN with one hidden layer was used and the hidden nodes’ number was determined using trial and error. Different activation functions (logarithm sigmoid, tangent sigmoid and linear) were tried for the hidden and output nodes and the GeneXpro Tools 4.0 were used to obtain the equation of the best models. Therefore, water quality data from two hydrometer stations, namely Anyan and Safakhaneh hydrometer stations were used during the statistical period of 18 years (1389-1372). In this research, for selecting input variables to the data driven models the stepwise regression method was used. In the application, 75% of data set were used for training and the remaining, 25% of data set were used for testing, randomly. In this paper, three statistical evaluation criteria, correlation coefficient (R), the root mean square error (RMSE) and mean absolute error (MAE), were used to assess model’s performances.
By applying stepwise method, the first significant (at 95% level) variable entered to the model was the HCO3. The second variable that entered to the model was Ca. The third and fourth ones were Na and Q respectively. Mg was finally entered to the model. The optimal ANN architecture used in this study consists of an input layer with five inputs, one hidden and output layer with three and two neurons for Anyan and Safakhaneh hydrometer stations, respectively. Similar ANN, ANFIS-SC5 model had the best performance. It is clear that the ANFIS with 0/4 and 0/7 radii value has the highest R and the lowest RMSE for Anyan and Safakhaneh hydrometer stations, respectively. Various GEP models have been developed using the input combinations similar ANN and ANFIS models. Comparing the GEP5 estimations with the measured data for the test stage demonstrates a high generalization capacity of the model, with relatively low error and high correlation. From the scatter plots it is obviously seen that the GEP5 predictions are closer to the corresponding measured TDS than other models. As seen from the best straight line equations (assume the equation as y=ax) in the scatter plots that the a coefficient for GEP5 is closer to 1 than other models. In addition to previous operation, Gene expression programming offered mathematical relationships in the stations of Anyan and Safakhane with the correlation coefficients, respectively 0.962 , 0.971 and with Root-mean-square errors, respectively 12.82 , 29.08 in order to predict dissolved solids (TDS) in the rivers located at upstream of the dam. The obtained results showed the efficiency of the applied models in simulating the nonlinear behavior of TDS variations in terms of performance indices. Overall, the GEP model outperformed the other models. For all of applied models, the best result was obtained by application of input combination (5) including HCO3, Ca, Na, Q and Mg. The results are also tested by using t test for verifying the robustness of the models at 95% significance level. Comparison results indicated that the poorest model in TDS simulation was ANN especially in test period. The observed relationship between residuals and model computed TDS values shows complete independence and random distribution. It is further supported by the respective correlations for GEP5 models (R2 = 0.0011 for Anyan station and R2 = 0.0123 for safakhaneh station) which are negligible small. Plots of the residuals versus model computed values can be more informative regarding model fitting to a data set. If the residuals appear to behave randomly it suggests that the model fits the data well. On the other hand, if non- random distribution is evident in the residuals, the model does not fit the data adequately. On the base of these results, we propose GEP, ANFIS-SC and ANN methods as effective tools for the computation of total dissolved solids in river water, respectively.
It can be concluded that the ANN, ANFIS-GP, ANFIS-SC and GEP models can be considered as promising tools for forecasting TDS values, based on water quality parameters. It is notable from the results that the prediction accuracy of all applied models increases by increasing the number of input combinations. With attention to the aim of current research that is presenting the feasibility of artificial intelligence techniques for modeling TDS values, it is notable that the results presented in this paper are for research purpose and applying the abstained results for real-world needs some complicated steps and building artificial intelligences methods, based on complete data and parameters maybe affected the TDS values.

Wind erosion is one of the most serious problems in southwest Iran. Fine-grained structure of sand dunes with not enough strong composition and their low moisture retention property make them susceptible to wind erosion. They lack organic matter and are considered inherently of low fertility (Ahmadi, 2002). Studies have shown that non-erodible materials which include bentonite clay (Diouf et al., 1990), ureamelamine formaldehyde and urea–formaldehyde with 0.25% sodium chloride (Lahalih and Ahmed, 1998), acids, enzymes, lignosulfonates, polymers, tree resins (Santoni et al., 2001), waterborne polymer emulsion (Al-Khanbashi and Abdalla, 2006), polyvinyl alcohol and a polyvinyl acetate emulsion (Newman et al., 2005; Han et al., 2007), ash and polyacrylamide (Yang and Zejun, 2012).have significant potential in reducing wind erosion The area under farming of sugarcane in Khuzestan, Iran, is more than 130,000, ha. Vinasse and Filter Kike are two organic ingredients of sugarcane residues which are generated as byproduct materials insugarcane processing. In recent years these residues have been released into the environment and cause it regarded as water pollutant. Over 800,000 m3 of Vinasse is annually stored in each agro-industry. Vinasse also is rich in K, Ca, and Mg with moderate amounts of P and N,and non toxic complexes or heavy metals. Filter Kike is another residue produced in huge amounts by the agro-industry that is composed of cellulosic substances, CaCO3, N, P, K, organic matter, and clay. Therefore, the objective of this research is to investigate the effect of sugarcane mulch on water holding capacity in soil. This study is performed to evaluate the feasibility of using sugarcane residues inproduce of ecofriendly mulches for environmental use. In order of achieving these goals, Vinase, Filter Cake, and clay soil from near the sand dunes were used as sugarcane mulches. Further comparison between traditional oil mulches and sugarcane mulches was also carried out.
The experiments were conducted in the soil laboratory of Khuzestan-Ramin University of Agricultural and Natural Resources. For this purpose, Vinasse and clay soil samples were used to make sugarcane mulches. Different quantities of Vinase, Filter Kike, and clay samples were mixed in water to select the best batch mix (by trial and error). A mulch sprayer was then used to spray the batch mixes on sand dune beds packed in trays 1054510cm. In addition, the same procedures were employed to choose an oil mulch treatment as control for comparison with sugarcane mulch treatments. Water holding capacity was measured in 100, 333, 1000, 5000, 10000, 15000 hPa suction by pressure plate and Macro elements ( N, P, K ) and microelements (Fe, Cu, Zn) were determined by conventional methods and atomic absorption in each treatment. Experiments were carried out using a factorial experiment with a completely random design in threereplicants.
The wide range of pH values obtained were dependent on the different batch mixes of Vinase, clay soil, and Filter Kike. Reaction (pH) of Vinase was lower (5.00) than those of Filter Kike (7.5) and soil (8.07). EC and SAR values of treatments were both affected by Vinase, soil, and Filter Kike. This could be due to the higher EC and the low level of SAR in Vinase in contrast to soil and Filter Kike. EC and SAR are two major chemical factors known to affect sand dune stabilization (Bresler, 1982). Based on Table 3, N, P, K, Fe, Zn, and Cu in sugarcane mulches varied from 0.15-0.66 (%), 10.82-28.46 (mg.Kg-1), 133.01-633.33 (meq.Li-1), 15.22-36.76 (mg.Kg-1), 2.19-2.93 (mg.Kg-1), and 0.92-4.1 (mg.Kg-1), respectively. The results revealed that sugarcane mulches are rich in N, P, and K that are essential in soil fertility.
The results determined that there was significant effect (p

Phosphorus (P) is the second limiting nutrient in soils for crop production after nitrogen. Phosphorus is an essential nutrient in crop production. Determination of forms of soil phosphorus is important in the evaluation of soil phosphorus status. Various sequential P fractionation procedures have been used to identify the forms of P and to determine the distribution of P fractions in soils (Chang and Jackson, 1957, Williams et al., 1967; Hedley et al., 1982), but are not particularly sensitive to the various P compounds that may exist in calcareous soils. A Sequential fractionation scheme has been suggested for calcareous soils by which three types of Ca-phosphates i.e. dicalcium phosphate, octacalcium phosphate, and apatite could be identified (Jiang and Gu, 1989). These types of Ca-phosphates were described as Ca2-P (NaHCO3-extractable P), Ca8-P (NH4AC-extractable P) and Ca10-P (apatite type), respectively. In this study, the amount and distribution of soil inorganic phosphorus fractions were examined in 49 soil samples of Fars province according to the method described by Jiang and Gu (1989).
Based on the previous soil survey maps of Fars province and According to Soil Moisture and Temperature Regime Map of Iran (Banaei, 1998), three regions (abadeh, eghlid and noorabad) with different Soil Moisture and Temperature Regimes were selected. The soils were comprised Aridic, xeric, and ustic moisture regimes along with mesic, and hyperthemic temperature regimes. 49 representative samples were selected. The soil samples were air-dried and were passed through a 2-mm sieve before analysis. Particle size distribution was determined by hydrometer method (Gee and Bauder 1996). Also, Cation exchange capacity (CEC; Sumner and Miller 1996), calcium carbonate equivalent (Loeppert and Suarez 1996), organic matter content (Nelson and Sommers 1996), and pH by saturated paste method (Thomas 1996) were determined . Inorganic phosphorus sequential fractionation scheme was preformed according to the method described by Jiang and Gu (1989). Olsen-P fraction that was extracted by NaHCO3 (Olsen and Sommers 1982) was regarded as P-availability index. Also, Total-P by perchloric acid (HClO4) digestion (Sparks; 1996) and organic P were determined.. All of the extraction procedures were performed in duplicate and the amounts of P were colorimetrically measured in the supernatants by the ascorbic acid method of Murphy and Riley (1962).The relationships between forms of P and some of the soil properties were established using correlation method.
The chemical data of the soils showed that soils were calcareous with CCE range between 9.94 to 74.27 % ( average 51.10%) and pH range between 7.02 to 8.36 (average 7.85). Also, the amounts of CEC were between 5.35 to 29.39 cmol () kg-1(average 16.68 cmol () kg-1). The results showed a wide range in content of Phosphorus fractions. The amount of total Phosphate ranged from 301.87 to 1458.68 mg kg-1 with an average of 626.63 mg kg-1 . Calcium Phosphate ranged from 147.83 to 666.90 mg kg-1 with an average of 324.79 mg kg-1, that comprised 85 and 52 percent of inorganic and total Phosphorus, respectively. The amount of Fe-P ranged from 0.38 to 59.18 mg kg-1 with an average of 7.56 mg kg-1 that comprised 13.64 and 8.34 percent of inorganic and total Phosphorus, respectively. Also, the amount of Al-P ranged from 20.49 to 123.09 mg kg-1 with an average of 52.28 mg kg-1that comprised 1.97 and 1.21 percent of inorganic and total Phosphorus, respectively. The results of correlation study showed that available Phosphorus was significantly correlated with Ca2-P, Ca8-P, Al-P, Ca10-P, and Pt (total phosphorus). So, in calcareous soils, awareness of soil properties and phosphorus fractions and their relationships are important for evaluation of phosphorous status in soil and understanding of soil chemistry that influence soil fertility.
The relative abundance of inorganic P forms were in order of Ca10 – P > Ca8- P > Al –P> Ca2-P> Fe-P. Among the inorganic P fractions, Ca-P had the highest value and varied from 147.83 to 666.90 mg kg-1, which accounted for 53 percent of the sum of P fractions, occurred in H2SO4 extractable P fraction, which is attributed to primary Ca–P minerals, indicating their weak weathering nature. Also, correlation study showed that available Phosphorus was significantly correlated with Ca2-P, Ca8-P, Al-P, Ca10-P, and Pt. This result indicate that these fractions probably can be used by plant.

Soil is a hardly renewable natural resource. Although soil degradation, caused by either human activities and natural processes is a relatively slow procedure, but its effects are long lasting and most often, irreversible in the time scale of man's life. Among the most significant soil contaminants resulting from both natural and human sources, heavy metals are more important due to their long- term toxicity effects. For evaluating soil's enrichment rate by heavy metals, a wide and full study of soils background values, including total and available fractions of heavy metal contents should be done. Zanjan province has some great mines and concentrating industries of lead and zinc especially in Angoran, Mahneshan. Unfortunately produced waste materials of these industries spread over the adjacent areas. Investigations showed that accumulation of some heavy metals in vegetables and crops planted in this region had occurred. Therefore, performing some investigations in these polluted areas and assessing pollution rate and heavy metals distribution in arable lands had prime importance. Our goals were: 1) determining the total and available amounts of Cu, Pb, Zn and Cd in the soils of arable lands in polluted areas of Zanjan city, 2) producing the distribution map for the metals mentioned above and 3) calculating pollution indices in the soils.
The study area was in south west of Zanjan city. For soil sampling, a 1 Km by 1 Km grid defined in ArcGIS software on landuse layer and totally 144 points that placed on agricultural lands, due to our goals, were sampled. For sampling, in a 5m radius around the point we collected some subsamples from depth of 0 - 15 cm, and after mixing the subsamples, finally a 1Kg soil sample prepared and sent to the laboratory. Sampled soils were air dried and were passed through a 2mm sieve. Soils organic matter (OM) content and texture were determined by Walkely-Black and Bouyoucos hydrometer methods, respectively. Soils pH were determined by glass/calomel electrode in saturation paste, EC by EC-meter in saturation paste extract, and calcium carbonate equivalent (lime) by reverse titration method. Total and available amounts of Zn, Cu, Cd and Pb were extracted by Aqua- Regia method (wet oxidation by chloridric acid and nitric acid with the 3:1 ratio) and by DTPA extracting solution, respectively. After extracting and filtering liquid samples, metal concentrations were measured by atomic adsorption method using GBC avanta P. Statistical analysis by SPSS and indices calculation by Excel were performed, and distribution maps were prepared by Inverse Distance Weighting method in ArcGIS software. For evaluating pollution rate, Geoaccumulation index, Enrichment factor and Availability Ratio indices were calculated and interpreted.
The textures of soil samples were loam, clay loam and sandy loam. The OM contents of almost soils were less than 2 percent. Lime was less than 25 percent and acidity of soils were neutral to slightly alkaline. Soils salinity were less than 2 dS/m except a few samples. Accordingly, these soils were suitable for agriculture and there were no limitation due to evaluated properties. Median values for the total concentrations of Cd, Cu, Pb and Zn (extracted by Aqua Regia) were 0.5, 22.5, 14 and 82.3 mg/Kg of soils, respectively, and for available fraction (extracted by DTPA) were 0.1, 0.9, 1.6 and 3.2 mg/Kg of soils that were much lower than measured total values. According to 90th percentile of geoaccumulation index, at least 10 percent of samples had been polluted with Zn, Pb and Cd. Enrichment factor revealed no long term pollution. Availability ratios of Pb and Zn were relatively high, showing there exists unique and recent pollution source for them. All pollution indices showed positive correlations with OM content of soils (except for availability ratios of Cd, which had negative correlation). Therefore, OM content of soils were respect to control these indices. Geoaccumulation index of Zn, Cd and Pb, and availability ratios of Zn and Pb showed negative correlations with soil pH. Therefore, in some seasons of the year, their availabilities will increase in soil.
The results showed that Cu content in soils were not in the critical limit but Cd, Pb and Zn content in soils were greater than standard levels and reclamation procedures for remedy of these soils must be done. The high values of the heavy metals in available fraction inthe soils increased the risk of bioaccumulation in microbial and biotic tissues. In areas where there are high content of available form of heavy metals in soils, it could be an index of new contamination in soils by heavy metals. According to geoaccumulation index of Cd, Zn and Pb, there are some contaminated points around waste depositition areas near Zanjan city. These points are in the direction that wind could effectively transport the particles of wastes to urban area. Enrichment factor (EF) showed that at least there were a few points polluted by Cd, Zn and Cu, although EF values were generally low. The leaked wastes of Zinc and lead industries had been spread in deposited areas caused difficulties in determining background values for the selected metals.

Soil organic carbon (SOC) has great impacts on soil properties, soil productivity, food security, land degradation and global warming. Similar to other soil properties, SOC has a strong spatial heterogeneity as a result of dynamic interactions between parent material, climate and geological history, at both regional and continental scales. However, landscape attributes including slope, aspect, altitude, and land use types are dominant factors influencing on SOC in areas with the same parent materials and climate regime. Understanding and identifying the spatial and temporal distribution of SOC is essential to evaluate soil quality, agricultural management, watershed modeling and soil carbon sequestration budgets. Therefore, the objectives of this study was to estimate soil organic carbon content in the Aligodarz watershed, and to investigate the effects of altitude, slope, and land use type on SOC.
The research was carried out in the Aligodraz watershed in Lorestan province of Iran. The study area is located between latitudes N 33° 10' 51.72"to N 33° 34' 28.22" and longitudes E 49° 27' 17.99"to E 49° 58' 40.84" 14 that covers an area of 1078.9 km2. It has an altitude between 1866.3 and 3200 m above sea-level. The primary land uses within the watershed include pasture, dryland and irrigated farming. In this study, soil samples were randomly collected from 206 sites at depth of 0– 15 cm during June and August 2003. The mean distance between samples was about 5 km. Soil samples were air-dried in the shade for about 7 days and then passed through a 0.25 mm prior to determination of SOC. Soil organic carbon content was determined in triplicate for each sample using the Walkey-Black method. Basic statistical analyses for frequency distribution, normality tests, Pearson's correlation and analysis of variance were conducted using SPSS (version 18.0). Calculation of experimental variograms and modeling of spatial distribution of SOC were carried out with the geostatistical software GS (version 5. 1). Maps were generated by using ILWIS (version 3.3) GIS software.
The results revealed that the raw SOC data have a long tail towards higher concentrations, whereas that squareroot transformed data can be satisfactorily modelled by a normal distribution. The probability distribution of SOC appeared to be positively skewed and have a positive kurtosis. The square root transformed data showed small skewness and kurtosis, and passed the K–S normality test at a significance level of higher than 0.05. Therefore, the square root transformed data of SOC was used for analyses. The SOC concentration varied from 0.08 to 2.39%, with an arithmetic mean of 0.81% and geometric mean of 0.73%. The coefficient of variation (CV), as an index of overall variability of SOC, was 44.49%. According to the classification system presented by Nielson and Bouma (1985), a variable is moderately varying if the CV is between 10% and 100%. Therefore, the content of SOC in the Aligodarz watershed can be considered to be in moderate variability. The experimental variogram of SOC was fitted by an exponential model. The values of the range, nugget, sill, and nugget/sill ratio of the best-fitted model were 6.80 km, 0.058, 0.133, and 43.6%, respectively. The positive nugget value can be explained by sampling error, short range variability, and unexplained and inherent variability. The nugget/sill ratio of 43.6% showed a moderate spatial dependence of SOC in the study area. The parameters of the exponential smivariogram model were used for kriging method to produce a spatial distribution map of SOC in the study area. The interpolated values ranged between 0.30 and 1.40%. Southern and central parts of this study area have the highest SOC concentrations, while the northern parts have the lowest concentrations of SOC. Kriging results also showed that the major parts of the Aligodarz watershed (about 87%) have statistically SOC content less than 1%. Lower SOC concentrations were associated with high altitude (r = −0.265**). The results of Pearson correlation analysis showed that soil organic carbon content has a significantly negative correlatiton with slope gradient (r = −0.217**). The results also indicated that the SOC content was variable for the different land use types. The irrigated lands had the highest SOC concentrations, while the pasture lands had the lowest SOC values.
The square-root transformed data of SOC in Aligodarz watershed of Lorestan province, Iran, followed a normal distribution, with an arithmetic mean of 0.81%, and geometric mean of 0.73%. The coefficient of variation and nugget/sill ratio revealed a moderate spatial dependence of SOC in the study area. The results indicated that the major parts of the Aligodarz watershed have SOC content less than 1%. The land use type had a significant effect on the spatial variability of SOC and that lower SOC concentrations were associated with higher altitude and slope gradients. The irrigated and pasture lands had the highest and lowest SOC concentrations, respectively.

Soil forms a thin layer over the surface of the earth that performs many essential life processes . Soil has always been important to humans and their health, providing a resource that can be used for shelter and food production. Higher heavy metals concentration within soils has beenshown to be toxic for human bodies, since they might be broken out easily via dust or direct contact through trophic levels. In addition long term heavy metals recalcitrance in soil results in low potential of soil productivity . Heavy metals interact complicatedly in soil. The present study was conducted in large scale by analyzing elements Mn, Co, Ni, Zn, Pb, Cd and Cu in soils in central lands of Zanjan province. The main objectives of present research were to investigate heavy metals diffusion and total contamination status in soil and determination of their possible origin using multivariate analysis.
This research was conducted in central lands located in Zanjan province (northwest of Iran). In terms of the main land uses, study area may involve farmlands, rangelands, urbanized and industrial lands. Study sites are totally covered 2000 km2 in coordinates of 36.20 to 36.41 N latitude and 48.19 to 48.53 E longitude. Sampling was conducted based on gridding method in randomized manner in August 2011. Urban lands affected by much anthropogenic activities and farm and rangelands together were placed in grids of 1.5×x 1.5 and 3×3 km2 respectively. Totally number of 241 soil samples (0-10 cm depth) was taken. Soil specimen's digestions were conducted using nitric acid 5 normal. Total elements concentration of Pb, Zn, Ni, Mn, Cu, Cr, Fe and Co were measured using Atomic adsorption device Perkin-Elmer: AA 200 and Cd concentration was determined by Atomic adsorption device equipped with graphic furnace model Rayleigh: WF-1E. Mean separation analysis of parameters (Pearson and spearman) was conducted using Duncan test in probability level of 5%. Principle component analysis (PCA) and hierarchical cluster analysis (HCA) were used to classify metals group. Achieving a simple structure and better results interpretation, data rotation in varimax type was conducted in PCA algorithm. Before cluster analysis, data were standardized and subsequently exposed to cluster analysis and plotting dendrogram, Euclidean approach was applied.
Results and Discussion Multivariate analysis (PCA, CA and CM) have been shown as an efficient tool to identify heavy metals origins, helping us in better data comprehension and interpretation. Results obtained on multivariate analysis approaches might are promising to distinguish polluted area and heavy metals potential origin, in turns indicating soil environmental quality.
PCA is known as an efficient method to determine anthropogenic impacts on a spatial scale and it may be essential to specify heavy metals contamination degree in respect to anthropogenic and litogenic contribution. As it illustrated, heavy metals are categorized in three-component model framework, accounting for 67% of total data variations. In rotated component matrix the first PC (PC1, 30% of variance) involves Ni, Cr, Co, Mn and Fe, while the second PC (PC2, 19% of variance) involves Zn and Pb and eventually the third one (PC3, 18% of variance) covers Cu and Cd among others. PC1 can be introduced as geological component because of its less coefficient of variations than others, skewedness less than 1 and normalized data status. It denotes lithogenic distribution of these metals in area. Furthermore,as above mentioned, the average heavy metalconcentrations werefound to be less than calculated background threshold. Because of their increased concentration in soil, high coefficient of variations and very high concentration than background threshold level as well as positive skewedness in heavy metals, PC2 and PC3 can be defined to antropogenical components. Atmospheric precipitation (deposition) serves as one of the main anthropogenic source of heavy metals pollution in the soil samples near theintense transportation traffic roads, accumulation site of factories solidwaters, energy generation process, metal melting, construction and traffic breaking out in whole area. Our results are in line with enormous findings on farming operations as the main factor that cause changes in Cd concentration in soils. although Pb, Cu, Zn and Cd have been shown to have anthropogenic origin inputs, however in respect to PCA analysis, the main origins for Lead and Zn may be municipal and industrial operations specially Pb processing factory as well as industrial complexes. At the same time, Cu and Cd stems from farming operations as well as municipal activities. The main municipal input origins for elements Pb, Cu and Cd include all components used in automobile industry, batteries, engines oils, fossil fuels and construction materials (like cement).
Cluster analysis is used to classifying those samples having common and similar characteristics as well as evaluating information obtained from PCA analysis. Cluster analysis gave the same groups. So two majororigins can be identified. First (CI) involves prior interpreted lithogenic elements (Cr, Co, Mn and Fe), while two later clusters (C2, C3) contain anthropogenic elements (Pb, Cu, Zn and Cd). Many researchers believed that Mn, Cr, Ni and Fe are controlled by parent material. In contrast, they attributed any increases of Pb, Cu, Cd and Zn accumulation to anthropogenical operations. Cluster analysis gives the same results as derived from PCA, enabling us to identify two major origins on which heavy metals break out hence, multivariate analysis results confirms the presence of two different heavy metals origins within soils.
The aim of this research was to provide some preliminary information on heavy metals (Pb,Zn,Cd,Cu,Ni,Co,Cr,FeandMn) contamination status in soils in Zanjan province. Metal contamination cannot be assessed by common metal concentration test, hence useful and promising tools were applied to evaluate heavy metals pollution. The highest level of heavy metals pollution and accumulation was related to Cd, Pb and followed by then Cu. Multivariate analysis showed that Fe, Mn, Cr, Co and Ni are controlled by parent materials, while Pb, Cu and Zn originate from anthropogenic sources. In the second class, anthropogenic activity did not seem to significantly affect their accumulation which is strongly supported the lithogenicaly origin of these heavy metals in this study.

Soil erosion by water is one of the most widespread forms of land degradation and it has caused many undesirable consequences in last decades. On steep slopes, rill erosion is the most important type of erosion, which produces sediment and rill flow. It can be also considered as a vehicle for transporting soil particles detached from upland areas. Recent studies indicate that soil detachment rates are significantly influenced by land use. It is also known that there is a major difference between detachment rates of disturbed and natural soils (Zhang et al., 2003). Plowing rills especially in steep slopes increases sediment production. Sun et al. (2013) reported that the contribution of rill erosion in hill slope lands in china was more than 70%, which was approximately 50% of total soil erosion. In addition, measured soil loss is statistically related to hydraulic indicators such as slope, water depth, flow velocity, flow shear stress and stream power (Knapen et al., 2007). This study aims to evaluate the effects of hydraulic variables (shear stress and stream power) on spatial-temporal soil detachment rate. The focus is on the plowing rills in hillslope areas under wheat dry farming cultivation.
The study area is located in hilly slopes with the slope of 22.56% under dry farming wheat cultivation at 60 km of west of Shiraz, Iran. Top-down conventional plowing was carried out in order to create 10 meters furrows. Slope and cross sections of rills were measured throughout the experiment at 1 m intervals by rill-meter. Water was added to the top of the rills for 10 minutes and inflow rates were 10, 15 and 20 L min-1. Hydraulic parameters such as shear stress and stream power were calculated measuring rill morphology and water depth. Flow velocity and hydraulic radius along the different rill experiments were also calculated. Sediment concentrations were measured in three equal regular time and distance intervals (measurement points (MPs)), they were considered to calculate sediment detachment rate in different times and sections of each rill experiment for spatial and temporal soil detachment rate evaluation. One-way analysis of variance (ANOVA) was employed to test the significance of differences of sediment detachment rate among different treatments.
The results showed that the maximum values of shear stress and stream power were 14.07 Pa and 10.29 Wm-2 and the minimum values were 7.41 and 2.77 respectively. This research also indicated that changes in longitudinal profile of these hydraulic parameters along the rills affected the soil detachment rate values. Obtained average, minimum and maximum of the soil detachment rate were determined as 0.09, 0.02 and 0.22 kgm-2s-1, respectively. Due to Detachment-Transport Coupling mechanism, there was a significant difference between the initial and following MPs (P

the use of municipal solid waste (MSW) compost in agriculture as a soil conditioner is increasing day by day because of its positive effects on biological, physical, and chemical soil properties. However, some of the composts because of contamination with heavy metals and other impurities can have deleterious effects on groundwater quality, agricultural environment, food chain, plant growth and activity of soil microorganisms. Therefore, this study was conducted to investigate the physical and chemical properties, fertilizing potential and heavy metal polluting potential of two types of municipal solid waste composts with processing time between 4 to 8 years (type A) and between1 to 4 years (type B) produced in Sanandaj city with the aim of using it as an organic fertilizer.
Sanadaj city, the center of Kurdistan province, with a population of about 335,000 is located in the west of Iran. The current solid waste generation from the city is about 320 t/day, which are not separated at source of generation. About 200 t of the total produced wastes are composted using an open windrows system at the Sanandaj MSW Composting Plant, which is located in 10 km of Sanadaj-Kamiaran road and the rest are disposed at the landfill site. The compost manufactured by the composting plant has been collected around it in two different locations. The first belonges to the product of 2004-2008 (type A) and the second belonges to the product of 2009-2013 (type B). Till now, due to lack of quality information associated with these products, they have remained unused. Therefore, in this study, we sampled 3 samples composed of six subsamples (each containing 2 kg) from the products in March 2013. The samples were analyzed to determine the physical properties (including undesirable impurities, initial moisture content, particle size distribution, particle density, bulk density (ρb), porosity, and maximum water holding capacity), and the chemical properties (including organic carbon, ash content, pH and salinity) and total amounts of N, P, Ca, Mg, K, Na, Mn, Fe, Cr, Zn, Pb, Ni and Cd using standard methods.
The results showed that bulk density, ash content, and the amounts of elements based on the dry weight of compost increased with composting time, however particle size decreased. It is well known that dry bulk density increased with composting time as ash content increased and particle size decreased by decomposition, turning and screening. The decreases of particle size with composting time cause an enrichment of metals based on the dry weight of compost. It is likely due to solubilization of metals in waste by organic acid produced during the microbial decomposition of organic matter and their subsequent adsorption on finer particles due to the higher surface area and the higher ion exchangeable capacity. The evaluation of the fertilizing potential of the surveyed composts by comparing their properties with different standard sets showed that the both composts under test in this study were failed to meet the standard permissible limits with regard to glass content (on average, 21.7 times over the permissible limit), gravel content (on average, 1.4 times over the permissible limit), lead content (on average, 1.6 times over the permissible limit), and salinity content (on average, 1.4 times over the permissible limit). Furthermore, compost type B also failed to meet the standard permissible limits with regard to initial moisture content (on average, 1.4 times over the permissible limit) and ρb (0.2 gcm-3, less than permissible limit) for agricultural purposes. The results showed that excessive amount of glass impurity bigger than 2 mm, salinity and lead contents are the major problems in the use of the composts for agricultural purposes. It should be noted that according to the maximum permissible limit of lead (150-300 mg kg-1) for compost C1 quality class described by Australian standard; both the composts can be used as fertilizers or soil amendments. In order to eliminate glass impurity, remediation approaches such as fine milling and pelleting is needed to disguise the residual glasses and render it as relatively harmless. A feasible approach to eliminate these problems is probably physical fractionation of the studied composts. It allows us to assess the distribution of nutrients and contaminants values in the different physical fractions of the composts, which is useful to detect and to eliminate of the particle sizes which are the responsible for these impurities.
The assessment of MSW-based compost for use in agricultural soil as fertilizer or conditioner is a sustainable recycling practice owing to its nutrient content and its positive effects on soil physico-chemical properties. Thus, we evaluated the fertilizing potential of two MSW composts produced in Sanandaj city for agricultural purposes. Altogether, the results of the study showed that excessive amount of glass impurity bigger than 2 mm and salinity were the major problems in the use of the composts for agricultural purpose. As a result, the quality of the surveyed composts was not suitable for agricultural purposes without appropriate remediation of these restrictions.

Accumulation of heavy metals in agronomic soils continuously by contaminated waste waters not only causes to contamination of soils but also it affects food quality and security. Cadmium and lead are one of the most important heavy metals due to long permanence and persistence in soil can cause problems to human and animal health. Some medicinal plants are able to accumulate of heavy metals from contaminated soils. Heavy metals are not able to enter in the essential oil of some aromatic plants. Study of these plants helps human to select them for cultivating the resistant medicinal plants in contaminated soils.
This experiment was carried out in the research greenhouse of agriculture faculty of Ferdowsi university of Mashhad in 2011. Seeds were cultivated in planting aprons into peat moss medium. Then the uniform plantlets were transferred into soil in the plastic boxes (30×50×35 cm) at two leaf stage. In each box 6 plantlets were sown with distance of 15 cm on the planting rows and 20 cm between rows. Experiment was set up as factorial on the basis of randomized complete block design with three replications. The first factor was cadmium concentrations consisted of 0,10,20,40 mg per kilogram and the second factor was lead concentrations consisted of 0,100,300 and 600 mg/kg. Plants were irrigated during of15 weeks with cadmium and lead nitrogen nitrate solutions and then irrigated with distilled water. The differences of nitrogen amounts in treatments were compensated with ammonium nitrate on the basis of differences between level of the highest treatment and the treatment which obtained lower amount of nitrogen. Plants were harvested after 180 days at the beginning of flowering. All shoots and roots were weighted separately as fresh weight and then were dried under shading and then were weighted. The essential oil sage was determined by using of 30 grams of dried sage leaves with distillation method with Clevenger. Cadmium and lead contents in shoot and root were measured by wet digestion method (digestion by Perchloric and Nitric acid). Cadmium and lead contents were detected by atomic absorption apparartus. Data were analyzed by MSTATC software and all means were compared by DMRT at 5% of probability.
Result and Results argued that fresh weight of sage at 40 mg/kg of cadmium were decreased 4.61% as compare as control. Dry weight of sage decreased at 600 mg/kg of lead 11.08 % as compare of control. Mean comparisons indicated that at the highest concentrations of cadmium and lead fresh and dry weight of sage were dropped. Growth decrement due to toxicity of cadmium causes to photosynthesis and respiration decline, carbohydrate metabolism decreasing and leaf chlorosis. Researchers observed lead ions by interfering with water balance lead to water stress. High concentrations of lead may cause to decrease the availability of water for plant and high concentrations of cadmium causes to disturb the protein synthesis and lead to protein decline in plant cells. Plant height of sage was declined at 40 mg/kg and 600 mg/kg as compared as control 14.17 and 10.83, respectively. Essential oil in sage was dropped in high levels of cadmium and lead as compare of control 12 and 14.51, respectively. Researchers stated that cadmium concentrations of 2,6 and 10 mg/lit and 50,100 and 500 mg/kg of lead had no significant effect on peppermint, but caused to drop the essential oil percentage of dill and basil.
Disturbance of carbon nutrition in plant cells during the photosynthesis process by heavy metals lead to a decrease in the essential content. The most cadmium absorption by sage shoots belonged to 40 mg/kg and 600 mg/kg of cadmium and lead, respectively and then 40 mg/kg cadmium and 300 mg/kg lead were ranked as second treatment. Increase of cadmium and lead concentrations in irrigation water led to increase of these heavy metals into sage shoots. Increase of lead and cadmium concentrations caused to antagonistic effects of cadmium and lead absorption into shoots of sage. In this experiment cadmium and lead concentrations of all treatments were too below to detect by atomic absorption apparatus. In this study cadmium and lead could not enter to essential oil. Researchers stated that high doses of cadmium, lead, zinc and copper concentrations could not enter into essential oil in sage. Some researchers showed that cadmium, lead and copper were not transferred to essential oil of peppermint, dill and basil during the essential oil distillation process. This finding confirmed that selection of medicinal plants as alternative plants with crops in cadmium and lead contaminated soils.
Fresh and dry weight of Sage in the condition of contaminated soil by 100 mg/kg cadmium and 600 mg/kg lead were declined 4.61 and 5.16 % as compare as control, respectively. At the highest doses of cadmium and lead the essential oil of sage were dropped but, these heavy metals were not detected in essential oil. So, it is seems that this medicinal plant may be applied in the contaminated soil or in the condition of using of contaminated irrigated water by cadmium and lead.

According to the fifth International Panel on Climate Change (IPCC) report, increasing concentrations of CO2 and other greenhouse gases resulting from anthropogenic activities have led to fundamental changes on global climate over the course of the last century. The future global climate will be characterized by uncertainty and change, and this will affect water resources and agricultural activities worldwide. To estimate future climate change resulting from the continuous increase of greenhouse gas concentration in the atmosphere, general circulation models (GCMs) are used. Resolution of the output of the GCM models is one of the problems of these models. Using downscaling tools to convert global large-scale data to climate data for the study area is essential. These techniques are used to convert the coarse spatial resolution of the GCMs output into a fine resolution, which may involve the generation of station data of a specific area using GCMs climatic output variables. The objectives of this study are, therefore, to investigate and evaluate the statistical downscaling approaches.
Different models and methods have been developed which the uncertainty and validation of results in each of them in the study area should be investigated to achieve the more real results in the future. In the present study, the performance of SDSM, IDW and LARS-WG models for downscaling of the temperature and precipitation data of Pars Abad synoptic station were compared and investigated. IDW technique is based on the functions of the inverse distances in which the weights are characterized by the inverse of the distance and normalized, so their aggregate equivalents one. SDSM is categorized as a hybrid model, which utilized a linear regression method and a stochastic weather generator. The GCM’s outputs (named as predictors) are used to a linearly condition local-scale weather generator parameters at single stations. LARS-WG is a stochastic weather generator and it is widely used for the climate change assessment. This model uses the observed daily weather data, to compute a set of parameters for probability distributions of weather variables, which are used to generate synthetic weather time series of arbitrary length by randomly selecting values from the appropriate distributions. In this study, data from the Pars Abad meteorological station, which was used as the data for the baseline period, was also used to predict climate variables. The record of data is 30 years (1971-2000), and the mean temperature and precipitation are 13.7 and 283 mm per year, respectively. The driest month is August, which receives less than 5 mm of rain. Most of the rainfall occurs in April, averaging at 47 mm. July is the warmest month of the year, with an average temperature of 28.9 oC, and January is the coldest, with an average temperature of -2.3 °C. Precipitation differs by 42.8 mm between the driest and wettest months of the year and the average temperature varies by 31.2 °C.
The calibration and validation results of the SDSM and LARS-WG models in the case of temperature showed that two models have better abilities for temperature simulation in comparison with precipitation data and, in all models, the increasing temperature was observed for most of the warm months. In the case of precipitation, the results of three models have considerable different towards each other and changes intensity of decreasing and increasing precipitation compared to the baseline in IDW model is higher and in LARS-WG model is lower than two other models. But, in case of calculated evapotranspiration, the results of SDSM and IDW models indicate the increasing evapotranspiration in the all months even modest and its maximum value is in last spring and summer. While, calculated evapotranspiration by using LARS-WG model has showed the lower estimation than the baseline period which implies the low ability of model to calculate this model. In general, scenario A2 resulted in more increases in temperature than B2 in each time period. Whereas, in the case of rainfall, the results for each time period were different. For ETo, in comparison to the baseline, both A2 and B2 scenarios showed an increase during both time periods.
In general, the results showed that all three models have similar and good performance for simulating and downscaling of temperature and precipitation data. Therefore, these three models can be adopted to study climate change impacts on natural phenomenon.

Rainfall has the highest variability at time and place scale. Rainfall fluctuation in different geographical areas reveals the necessity of investigating this climate element and suitable models to forecast the rate of precipitation for regional planning. Ardabil province has always faced rainfall fluctuations and shortage of water supply. Precipitation is one of the most important features of the environment. The amount of precipitation over time and in different places is subject to large fluctuations which may be periodical. Studies show that, due to the certain complexities of rainfall, the models which used to predict future values will also need greater accuracy and less error. Among the forecasting models, Arima has more applications and it has replaced with other models.
In this research, through order 2 Autoregrressive, Winters, and Arima models, monthly rainfalls of Ardabil synoptic station (representing Ardabil province) for a 31-year period (1977-2007) were investigated. To assess the presence or absence of significant changes in mean precipitation of Ardabil synoptic station, rainfall of this station was divided into two periods: 1977-1993 and 1994-2010. T-test was used to statistically examine the difference between the two periods. After adjusting the data, descriptive statistics were applied. In order to model the total monthly precipitation of Ardabil synoptic station, Winters, Autoregressive, and Arima models were used. Among different models, the best options were chosen to predict the time series including the mean absolute deviation (MAD), the mean squared errors (MSE), root mean square errors (RMSE) and mean absolute percentage errors (MAPE). In order to select the best model among the available options under investigation, the predicted value of the deviation of the actual value was utilized for the months of 2006-2010.
Statistical characteristics of the total monthly precipitation in Ardabil synoptic station indicates that in May, the highest and in August, the lowest monthly total rainfall accounted in this station. Standard deviation of rainfall reached to the lowest level in August and its peak in November. Coefficients of skewness and kurtosis of total rainfall in all seasons, indicates a lack of compliance with normal distribution. From the view of the range of total monthly rainfall, October and August have highest and the lowest tolerance in these parameters, respectively. The results showed that the percentage of the mean absolute error for Arima, Winters and Autoregressive models was 61.82, 148.39 and 81.54 respectively and its R square came to be 88.28, 61.07 and 85.12 respectively. The comparison of the parameters is an indication of the fact that Arima has the highest R square and the lowest mean absolute error of 88.28 and 61.82 respectively than Winters and Autoregressive models. The presence or absence of significant changes in mean precipitation during 1977-1993 and 2010-1994 in Ardabil synoptic station shows that the difference of rainfall is not significant at the 5% error level from statistical point of view. The comparison between the monthly mean rainfall of Ardabil synoptic station in 1994-2010 and 1977-1993 indicates that rainfall has somewhat decreased in the former in recent years. Considering the low average monthly rainfall of Ardabil synoptic station in 1994-2010 compared to 1977-1993 (21.98 versus 26.11 mm), although no statistically significant difference was found in the average rainfall, low rainfall in this station would not be unexpected in the coming years. The comparison of predicted and actual values from 2011 to 2013 in Ardabil synoptic station showed that fitting real data with expected data was relatively acceptable. The observed differences between the actual and predicted values can be related to the influence of rainfalls and many local and dynamical factors of this area. Therefore, it is necessary for climatologists to better explain and predict phenomena besides statistical models and pay more attention to general circulation models (GCM) under different climate conditions.
Results of rainfall investigation by order 2 Autoregrressive, Winters, and Arima models showed a descending trend in monthly rainfalls in the coming years across the study location. The results of modeling and analysis of monthly rainfalls in Ardabil synoptic station showed that among these models, Arima was better than the other two because it enjoyed the lowest MAPE and the highest R2. AIC, RMSE and MAD scales of different patterns were calculated and finally, SARIMA(1,1,1)(2,0,1)12 pattern having the lowest AIC, RMSE and MAD was selected as the most appropriate pattern for monthly rainfall forecasting in Ardabil synoptic station.