مجله پژوهش آب ایران
پیاپی 30 (پاییز 1397)

Seepage from the earth canals is considered as the main portion of water losses in the irrigation projects. Several empirical equations have been proposed by researchers to estimate the seepage losses in canals. Some of these equations estimate accurately but the others should be used with more cautious. Unfortunately, few previous practical formulas for estimating the seepage losses along the earthen canals are applicable and new design equations are needed. Because of complexity, more practical tools are required to model seepage processes. The geometric factors involved in the estimation of seepage are the shape and dimensions of the canal. Regression relations are most commonly used to predict the seepage rate from the earth canals; however the regression analysis can have large uncertainties. Thus, the computed seepage values can be far from the actual ones. Also, the regression analysis has some limitations by predefined equations for modeling. So, gene expression programming (GEP) has been used to model these processes, recently. Through the present paper, some experimental data measurements have been carried out, on trapezoidal earthen canals with different geometry for seepage analysis, and the equations were developed for relating the seepage losses, qs, to the flow and geometry canal parameters. The dimensional analysis of the seepage rate in the canals has shown that the parameters z, k and y are effective in the seepage discharge, qs. As is evident, the dimensionless parameter q/ kh, is a function of the channel side slope, (z), the water depth (y) and the hydraulic conductivity of soil (k) considered as variable parameters. For each of the three samples the hydraulic conductivity of soil was calculated from Darcy relationship, So that in each instance the measurement and estimation of seepage (by the volume method) and the water level measurement in the parameters were done, then the average hydraulic conductivity of soil was calculated and the seepage line was defined for each soils. In artificial intelligence, gene expression programming (GEP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. The effect of the side slope, the water depth and the hydraulic conductivity on seepage rate, qs, in the trapezoidal earthen canals was studied. This study presents gene expression programming (GEP), as an alternative tool in the prediction of the seepage losses in the earth canals. In GEP model they were used arithmetic operations like (*+ , − ,/ ,) and functions such as ( sqrt and power). The performance of GEP in training and testing sets is validated in terms of the common statistical measures R, the correlation coefficient, the root-mean-square error (RMSE). The R shows the degree which two variables are linearly related to. The experimental results showed that the seepage rate increased by increasing of the water depth in canal and hydraulic conductivity of soil, but the seepage rate was not directly related to the canal side slope. In small and narrow earthen canals, the seepage rate initially decreases and then increases with increasing the side slope, z. Considering that, the local features of seepage is a unique, the trapezoidal section with slope Z = 2 in the range of 1.5< Z< 2.5 had the minimum seepage rate. Also, the results of the sensitivity analysis indicated that the parameter k had the greatest impact on the rate of seepage. In general, the performance of GEP models was superior to the statistical regression schemes. These models could be successfully used in computation of the seepage in the canals. Based on the results, model performance can be evaluated as satisfactory, if R> 0.9 and less values of RMSE. The results of GEP were compared with measured values of experimental model. The comparison showed that this software had a good performance in modeling the seepage of earthen canals. The seepage rate calculated by GEP had little difference with the measured seepage. The GEP model performed well in simulating the seepage rate based on all parameters and for each of canal side slopes. The simplified analytic form of the proposed GEP model for qs can be expressed as a function of y, z and k parameters. The equation obtained by GEP is clear and precise function that can be used to calculate the seepage losses from earthen canals in similar situations.

The goal of innovation of modern irrigation networks was to increase efficiency. Negligence in operating and maintaining of irrigation network infrastructure is the main source of inefficiency. In order to achieve the optimum efficiency, effective factors should be classified and ranked, and all criteria be considered for making decision. Analytical hierarchy process (AHP) is one of the generalist systems in cases of decision making. The method was developed by Saaty in 1994. In this study, AHP was used to evaluate operating situation of command units of Fumanat irrigation network as a part of the Sefidrud river irrigation and drainage network, Guilan, Iran. The network is located on left side of the Sefid-rud River, between Pasikhan and Shafarud rivers, and limited to Anzali wetland and the Caspian Sea from the north and Fumanat main channel from the south. In the current study, hierarchy structure was made in three levels by criteria and alternatives (command units) of the network and was developed based on the axis of irrigation network operation program include of "control and water resource allocation" and "control and water distribution". Collecting the requirement data, an application has designed based on hierarchy structure and pairwise comprise. Pairwise comparison and number of elements (number of criteria and alternatives) and their required judgments are the factors that the test questions designed based on them. Four effective criteria involved in operation of irrigation network included: type of water regulation and distribution structure, water allocation, method of water distribution and adherence to cultivation pattern. Weighing the criteria, the opinion of experts of Guilan irrigation network operation company (GINOC) via questionnaire and farmers via interview, with difference policies were considered. By the application of criteria and based on Saaty's numeric weight table (1994), the pairwise comparison tables were created with individual involved components. Then, according to Aczel and Saaty (1983), individual pairwise comparison matrix converted to grouping judgment matrix, by computing geometric mean of components. Collected data points which computed and analyzed were introduced to Expert Choice (EC) software to compute the weight of criteria and commend area. Hierarchy structure was made in EC software and the elements were compared in pairwise. The hierarchy model was solved from the lowest level to the highest. Results of pairwise comparison were displayed on the diagram of weights that showed the inconsistency ratio, as well. Considering the pluses in AHP, for example existence of the consistency between decision maker’s opinion and existence of the pairwise comparison in the giving criteria, the suitable method would be obtained. This model evaluated scale of the effect of criteria in the irrigation network operation problems with simplifying the unintelligibility and complexity in the hierarchy analysis, by high accuracy. This research validated the command unit's priority and showed conformity between results and reality. Based on the results, F1 command unit with the most weight of 0.422 had the best situation in term of operation. This command unit was the first one that was operated by modern irrigation network and being on the upstream could lead it to have the better situation. Also, F1 achieved the first ranking in term of evaluating opinions, while F2, F3 and F4 were in the next ranking. According to final weight results, "type of water regulation and distribution structure" with the weight equal to 0.512 was the most effective criteria in term of operation. So, finding the most effective method for improving the operation of these units would need especial consideration and focus on the case of water regulation and distribution structure. Regulation and fixing are two factors involved in ranking in order to prevent illegal withdrawal by farmers. Final weight of alternatives ratio for difference criteria in F1, F2 and F3 command units showed that the most effective factors in ranking were water allocation, type of water regulation and distribution structure and adherence to cultivation pattern, respectively. Also in term of water allocation, F1 command unit had the first rank ratio and the other criteria (F2, F3 and F4) set in the next ranking. The same ranking of the command units was also observed in term of "type of water regulation and distribution structure". Also, the inconsistency ratio of the model was 0.07 that confirmed grouping judgment.

Before the formation of significant runoff production, floods could be controlled with less cost and problems. For this reason, watershed measures are implemented to control the flood in a place where precipitation occurred. Watershed management measures are taken to protect water and soil by creating vegetation or constructing check-dams. Given the importance of watershed management projects in managing natural resources and due to the high cost involved in implementing these projects, ensuring of their efficiency is an important part of water and soil conservation measures. In spite of the increasing development of watershed management measures, inadequate study has been done to evaluate their efficiency. The evaluation is generally quantitative or qualitative or combination of them. In this research, a quantitative evaluation is done and the status of the watershed is compared in two periods of after and before constructing watershed management measures. Ramian watershed is a sub-catchment of Voshmgir dam basin in Golestan province, Iran. In this watershed, because of flood dangers, local Watershed Management Directorate has carried out by biological (including forestry, planting pile, forage extension, seedling) and mechanical measures (including gabion), since 1993. Considering the necessity of achieving proper results from implementation of these projects, in this research the performance of watershed management measures has been evaluated. The efficiency of watershed management measures can be quantifying by selecting proper indicator which is appropriate to the type of project, type of assessment, required accuracy and available data. Watershed management measures have been implemented in different parts of the Ramian watershed; therefore they should be evaluated with a determined method to achieve acceptable results. In this research, the effect of watershed management measures is evaluated using flood indices (peak flow and flow volume). The research data were collected by: field survey, literature review, locating and checking the specifications of the check-dams in the main stream of each sub-basin, and mapping the cross-section of the routing reaches. Then, flow simulation was performed using HEC-HMS. To evaluate the effect of biological and mechanical measures, curve number and time delay parameters were used. In order to estimate the curve number, land use map was prepared in pre and post period of biological measures. By comparing land use maps in these two periods using kappa index, it is shown that the amount of land use changes in the Ramian watershed is high. This is due to the fact that in addition to biological measures, other watershed measures (including protection and exclusion and the displacement of villagers by the Department of Natural Resources and the abandonment of agricultural lands, and as a result of changing their vegetation), also affected the land use status of the catchment area. Therefore, the impact of biological measures on flood reduction has been significant. Changes in the time delay is studied by considering the changes in the length and gradient of each main stream, with and without check dams. As most check dams were not constructed in the main stream, the number of structures in the main streams was not high. The changes in the length and gradient of the river in different sub-basins of the Ramian watershed were 1.2% and 3.4% respectively, which was not so tangible. According to small changes in the slope and the length of the main stream, the amount of increase in the delay time was also small and about one percent. Before simulating rainfall-runoff, the daily discharge was investigated to gain favorable changes. A daily statistical analysis of discharge showed that the maximum of daily discharge and the flow coefficient decreased by 45% and 9%, respectively. Similar to the results of the statistical survey, the results of flow simulation through the HEC-HMS hydrologic model confirmed the effectiveness of watershed measures. So, according to the results, the flood has decreased in different return periods after the watershed management measures. The highest decrease of peak and volume of discharge occurred for 10 and 20 year return period. However, for greater return periods the impact of project on the peak discharge decreased. In addition, the major reduction in flood was influenced by biological measures, and mechanical measures played a minor role in the watershed management. Generally, the impact of the watershed management measures in Ramian watershed on flood discharge is evaluated as positive.

Drought and water deficit is a challenge in arid and semi-arid regions which have recently intensified because of climate change. In recent years, the combined effect of climate change and socioeconomic factors exacerbate desertification processes, especially due to lack of water resources in land, wetlands and lakes, which appears in most parts of the country. Climate change is one of the challenges which lead to many environmental consequences. Trend analysis of river flows is an important issue in water resources planning and management and can provide valuable information. Heretofore, a numerous studies used parametric and non-parametric methods to examine the existence of significant trends in hydro-climatic time series. Most of the studies used non-parametric methods for trend analysis and a few studies used linear regression test. The non-parametric methods were used in this study because the non-parametric methods are distribution-free, robust against outliers, and have a higher power for non-normally distributed data. The Mann-Kendall (MK) method (Mann, 1945; Kendall, 1975) is the most commonly used non-parametric method that has recommended for identification of monotonic trends in different hydrologic and climatologic time series by World Meteorological Organization (WMO). The serial dependence between observations should not exist when the original classic MK test used for trend detection. However, in most of the hydro-meteorological time series, significant autocorrelation with different time lags, in addition to lag-1, may exist among observations. In such a situation, application of the classic version of the MK test for trend analysis could yield unreliable results. As some of previous studies showed that the presence of positive auto-correlation overestimates the significance of both positive and negative trends, whereas negative auto-correlation underestimates the significance of both positive and negative trends. The existence of more than one significant auto-correlation among data called as long-term persistence (LTP). To incorporate the LTP behavior in MK test, Hamed (2008) suggested to remove the effect of all significant serial correlation before applying the classic MK test. The surface water is one of the main resource for providing irrigation demand in Hamadan province. However, in recent decays, because of increasing the farm land area, the available surface water resources cannot provide the agricultural demand for water completely, so the farmers have drilled a lot of wells to extract groundwater for irrigation uses. The overexploitation of groundwater led to severe decline of the water table in most parts of the Hamadan province. In this study, the trend of river flows of the Hamadan province was investigated in monthly, seasonal and annual time scales by using Mann-Kendall non-parametric test, after removing the effect of all significant serial correlation. For this purpose, monthly stream flow data of 17 hydrometric stations during 1985 to 2013 were used. The Sen’s slope estimator was used to estimate trend line slope. Also, the abrupt change points in the stream flow time series were detected using the Pettitt test. The results showed that in annual time scale all stations had negative trends, as about half of them were significant at the 10 % level or less. The most severe significant negative trend in 1% level belonged to Bujin station with a Z value of -3.28. At seasonal time scale, the discharges of most rivers were experienced decreasing trend which the summer ranked first. In monthly time scale, among 204 considered series (12*17), only 15 stream flow series showed a significant positive trend (at 10% significance level) and 102 stream flow series have experienced a significant decreasing trend (at 10% significance level) and 87 series had no significant trend. The most significant negative trend of monthly stream flow series belonged to Kooshkabad stations in June with Z value of -4.45. The maximum number of stations with significant negative trend at monthly time scale at the level of 10% or less belonged to April. The highest slope of the trend line for annual time scale belonged to the Aran station, which was equal to 0.36 m3/s/yr. In general, trends of river flows in Hamadan province were statistically negative at 10% level. The results of applying the Pettitt test showed that in most stations, the significant change point in annual stream flow time series were occurred between 1995 and 1999. The results of investigating the trend of precipitation across the Hamadan province reveal that there is no negative trend in precipitation, and it seems the main reason of decreasing stream flow in this province is due to water extraction at the upstream of rivers in recent years. The results of the present study may be used by water resources planners to alter surface water allocations based on the trend of river flows.

Sloping coastal structures such breakwaters, are the most common structures that used near shore. Breakwaters are generally constructed to protect vessels, facilities, and coastal buildings against wave erosion and attack. Different materials such as concrete or large rock are used to construct these structures. Design of breakwater includes both hydraulic and structural aspects. During physical process, wave run-up is one of the important parameters in the hydraulic design that control the crest level of these structures. However, prediction of wave run-up has not yet fully understood and therefore, research study on different types and scale of breakwater is going on. A large number of experimental and field studies have been performed in this regard. However, scale effect in experimental measurement and cost in field study are the main disadvantages of these methods. By computational improvement, numerical methods have gradually been applied to model waves around breakwaters in one, two and three dimensions. These techniques can generally be classified into mesh-based and mesh-free categories which can be implemented in an Eulerian and/or a Lagrangian frame. Although traditional mesh-based methods (such as finite differencing (FDM), finite element (FEM) and finite volume (FVM)) have been applied in this area, they face many difficulties such as mesh dependency, large deformation or fragmentation, accurate tracking of the free-surface, modeling movable boundaries, and uniform mesh generation for complicated geometries. In order to overcome difficulties and limitations that associated with traditionally Mesh-based methods, next generation of numerical methods namely mesh-free methods have been gradually applied in fluid mechanics. Among these techniques, smooth particle hydrodynamics (SPH), with a Lagrangian frame, has been claimed to be one of the most powerful methods for modeling broad range of complex hydrodynamic phenomena. SPH was originally developed in the late 1970s for astrophysical applications and was later applied to solid mechanics. The capability of SPH in capturing large deformations led to its subsequent application to simulate some free-surface flows such as modeling of wave reflection and transmission at permeable or impermeable breakwaters. This research aims to apply 2D weakly compressible SPH to Rigid breakwater in multi slope bed, and evaluate the hydraulic performance resulting from the interaction of water waves on impermeable and non-overtoppable type of breakwater and insight into this powerful method for coastal structures using SPHysics. Effect of different parameters such as variation in still water depth, wave period, wave steepness, side slope of breakwater on the wave run-up is investigated. Additionally, in order to compare the wave run-up on rubble mound breakwater, simulation results using SPH have been compared with experimental work. The continuity and momentum equations in a 2-D Lagrangian frame and linearized version of the state equation were used to model viscous, weakly compressible and baratropic fluid around breakwater. To solve these nonlinear equations using SPH, the B-Spline kernel function is used during modeling. Moreover, the radius of the support domain was taken as 1.2 times the initial particle distance and Linked-list method is used for search algorithm in the numerical method. Solid boundaries such as walls are represented by dummy particles using two set of virtual particles. To model wave run-up problem, piston type wave maker is located at the end of a long rectangular tank which is oscillated with prescribed frequency. A tank with initial height and length equal to 0.2 and 4 m, respectively, was considered. A wave with different period (Ti=1.273s, 1.626s, 1.979s) and depth (di= 0.48m, 0.51m, 0.54m) was generated using piston type wave maker. Additionally, various slope of breakwater (cot α=1.25, 2, 2.5) and slope of sea bed (0.382, 1.1460) was considered. As a consequence, run up which has a crucial role in design of breakwaters was grown by increasing of period, depth and slope of breakwater. The satisfactory agreement between SPH results and the USBR experimental data showed that this numerical technique is capable of handling wave run-up on rigid breakwater. Further, due to investigate wave run-up rate on impermeable and rubble mound breakwaters, numerical results of this study is compared with experimental measurements by shirian, Shankar and Jayaratne. Similar tendency of wave run-up with variation of side slope of breakwater and wave period is observed. However, wave run-up on impermeable breakwaters is higher (approximately 40%) than rubble mound types.

Nitrate is a common ion in nitrogen cycle. Nitrate can reduced to nitrite, nitrogen and other forms through microbial activities. In recent decades, high nitrate concentrations in drinking water have been became a serious concern in the world. Nitrate distribution in the groundwater is controlled through hydraulic parameters, concentration of dissolved oxygen and availability of carbon source as electron donors. There are some methods for nitrogen removal such as biological processes, chemical processes, and Biological denitrification. Biological denitrification is the process by which nitrate is reduced to nitrogen gas, through a sequence of enzymatic reactions. Changing methods of use or increase the absorption of nitrate nitrogen in agricultural systems has been known as the best way to reduce pollution of groundwater nitrate to prevent the transmission of groundwater in the first place. Denitrification beds have been known as the most common method for nitrate removal with high efficiency. In this study, salinity effect on performance of denitrification beds, constructed of mix of soil and sugarcane bagasse, was surveyed. This study was done in the research laboratory of Shahid Chamran University, Ahvaz, Iran. A physical model consists of 9 polyethylene columns with 350 mm length and 76.2 mm diameter was constructed. A 5-cm layer of fine sand was placed at the top and bottom of the soil columns to ensure that the inlets and outlets of the columns did not clog. Three replications were made for each treatment. The columns were fed via an upward flow by falling head. An upward flow was used to ensure the entire pore volumes of the columns were filled. Three treatments with different salinity levels, 2, 5 and 8 ds m-1, were considered. Water samples were collected from the effluent of the columns in clean plastic containers during the 14-week experiment, and were then subjected to nitrate, ammonium, and pH measurements. Sampling of influent and effluent was done in the beginning of experiments, daily for one week. After one week, sampling was limited to once in a week and finally once in every two weeks. The nitrate and ammonium concentrations were analyzed immediately in the samples by using spectrophotometer (DR5000, Hach, USA) at wave lengths of 275 and 425 nm, respectively. For all samples, the outflow discharge rates were conducted through collecting of a given volume of water in a specific time. Duration of experiments was 98 days. Entrance constant head of 102 cm were used. Fourier transform infrared spectroscopy (FTIR) (Bruker model, Germany) was employed according to the potassium bromide (KBr). The changes in functional groups of sugarcane bagasse, before and after use in biofilters, were examined by FTIR spectra. Also, the external morphology of the biomass was studied by scanning electron microscopy (SEM, 1455VP, LEO, Germany). All statistical analyses were performed using SPSS 21 software. Correlation analysis was done for determining correlation kind (positive or negative) and the values of significant. All significant testing was at the 95 % confidence level. Reported error values were ±1 standard deviation. The results of this research were shown that nitrate removal efficiency reduced with increasing of salinity. The removal efficiency was 83.87, 78.72 and 63 %, respectively in the salinity levels of 2, 5 and 8 ds m-1. But, there was a threshold for salinity level. Moreover, in the constant hydraulic loading rate, the lowest nitrate removal rate was belonged to the highest salinity level. Also, it was be observed that the values of C:N reduced with increasing of salinity. The results of correlation analyzes between the effective parameters on performance of beds indicated which hydraulic loading rate, hydraulic retention time and salinity has significant effect on removal efficiency. Also the results showed that, hydraulic factors such as hydraulic retention time and hydraulic loading rate have positive and negative impacts on performance of bioreactor beds, respectively. The SEM images showed considerable differences between sugarcane bagasse images before and after experiment. The results of FTIR and SEM analyze approved degradation of sugarcane bagasse during the experiments through activities of bacteria available in beds. In the higher salinity level, carbon source was consumed faster and more than other lower salinity levels. The FTIR and SEM results confirmed reduction of C:N ratio in the highest salinity level than other levels.

Channel geometry has been considered by numerous researchers over the years. Regime theory and hydraulic geometry are among the most important models, regarding the river engineering and river morphology, developed over the past centuries. There is an important condition for river engineers in which river shape, geometry section size and longitudinal slope of the river is in equilibrium with the hydraulic and sediment characteristics applied to the river. Each of the existing regime equations that are developed by different researchers would be reliable and applicable in certain conditions which are similar to the derivation conditions. Therefore, determination of regime equations to be used in a wider range of conditions is necessary for future researches. In fact, hydraulic geometry relationships describe the alluvial channel shape and determine changes of width, channel average depth, velocity and longitudinal slope of the river with discharge. This condition is considered for a cross-section and is called at-a-station hydraulic geometry. However, if changes the width, channel average depth, velocity and longitudinal slope of the river bed are considered over a river reach for a particular flow discharge, it is called downstream hydraulic geometry. This discharge could be bankfull discharge or mean annual discharge. In this study, the term “hydraulic geometry relations” refers to downstream hydraulic geometry relations and particular flow discharge is bankfull discharge. The main focus of this study is to analytically derive the hydraulic geometry equations the concept of secondary flow in meandering channels; Therefor, first, the principles and concepts of the hydraulic geometry are presented. Because of the importance of independent and dependent variables, they should be selected carefully. There are several parameters that control the rivers. Three parameters of flow discharge, bed particle size, and bed sediments load are more important than others so that changes of each parameter will influence the equilibrium and stability of the river. A new hydraulic geometry is developed to achieve the equilibrium state with four degrees of freedom of depth, width, bed longitudinal slope and velocity. Therefore, four equations are required to find the four unknowns (depth, width, bed longitudinal slope and velocity). Then, the hydraulic geometry equations are theoretically developed by using four governing equations: continuity, resistance to flow, bed load equations and secondary flow. The third equation which estimates sediment transport is a function of Shields function and Shields function equation can be used instead of this equation. The fourth equation considers the effect of secondary flow and is as the ratio of the radial shear stress to the longitudinal shear stress. Because of the numerous bends in such rivers, cylindrical coordinates should be used. A particle starts to move when its shear stress is higher than this value in threshold condition. Two stresses influence sediment particles in a meander: radial shear stress and longitudinal shear stress. Therefore, the angle between the resultant shear stress and the longitudinal shear stress is very important. By increasing the angle, the radial shear stress will increase and a stronger secondary flow would form. Therefore, the sediment particle will move from the outer bend to the inner and makes a sharper bend. By decreasing the angle, the longitudinal shear stress will increase and a weaker secondary flow will form, so that there is a milder bend. Therefore, to consider the effect of the secondary flow in the equations, the radial shear stress to the longitudinal shear stress ratio can be used. Thus, the independent variables of equations are: flow discharge, mean sediment size and slope. While, the dependent variables of equation are: the mean depth; surface width; mean flow velocity; and Shields parameter. Eatone and Milarer (2004) considered the longitudinal slope of the bed as the independent variable for two reasons: Measurement of the bed longitudinal slope is usually easier and cheaper than that of the sediment load in most rivers; and bed load functions are not necessarily capable of calculating accurate values. Therefore, parameters of the bed slope and sediment load were selected as the independent and dependent variables, respectively, in this case. Hey and Thorne (1986) field data for the UK rivers were applied to calibration the developed the model. A reasonable agreement between observed and calculated values was obtained partially. However, some discrepancies were also observed in the results which may be due to the assumptions made in the model. Finally, sensitivity analysis was conducted to figure out the parameter to which the model is most sensitive.

In econometrics, the autoregressive conditional heteroscedasticity (ARCH) model is a statistical model for time series data that describes the variance of the current error term or innovation as a function of the actual sizes of the previous time periods' error terms; often the variance is related to the squares of the previous innovations. The ARCH model is appropriate when the error variance in a time series follows an autoregressive (AR) model; if an autoregressive moving average model (ARMA) model is assumed for the error variance, the model is a generalized autoregressive conditional heteroscedasticity (GARCH) model. For forecasting, combining ARIMA and ARCH models could be considered. For instance, a hybrid ARIMA-ARCH model was examined for shipping freight rate forecast. ARCH models are commonly employed in modeling financial time series that exhibit time varying volatility and volatility clustering, i.e. periods of swings interspersed with periods of relative calm. ARCH-type models are sometimes considered to be in the family of stochastic volatility models, although this is strictly incorrect since at time t the volatility is completely pre-determined (deterministic) given previous values. After the introduction of ARCH models there were enormous theoretical and practical developments in financial econometrics in the eighties. It became clear that ARCH models could efficiently and quite easily represent the typical empirical findings in financial time series, e.g. the conditional heteroscedasticity. In particular after the collapse of the Bretton Woods system and the implementation of flexible exchange rates in the seventies ARCH models are increasingly used by researchers and practitioners. However the ARCH model is only the starting point of the empirical study and relies on a wide range of specification tests. Some practically relevant disadvantages of the ARCH model have been discovered recently, for example, the definition and modelling of the persistence of shocks and the problem of modelling asymmetries. Thus a large number of extensions of the standard ARCH model have been suggested. We will discuss them in detail later. Time series models as the mathematical-physical models are able to model linear and nonlinear processes. These models contain two sectors included stochastic and deterministic components that deterministic part of model has been estimated by the observed data and stochastic part of model has been calculated by stochastic methods. So, the structure of time series models is in accordance with the structure of hydrological series if the appropriate model selected (Salas, 1993). The most applied time series models in the hydrology and water resources studies, is linear models. Nonlinear models is used and developed in the sciences related with the statistics, economics and mathematics. The application of linear time series models in hydrology has been started from the current four decades and developed by the Box-Jenkins models. Thomas and Fiering (1962) were as the first researches that had been used linear autoregressive models for the river flow analysis. The purpose of this paper is to introduce combined ARMA-PARCH model in order to modeling river discharge and increasing accuracy of hydrological modeling and comparing current ARMA models with the combined model. Time series modeling has been applied by Thomas and Fiering (1962) for the first time and has been developed by Box and Jenkins in the 1970. Among time series models AR model is the most simple model on the basis of Markov chain method. ARCH model is the first model for modeling variance series proposed by Engle (1982). Since then, it has been widely used to model volatility of financial and economic time series. The main idea of the ARCH models is in two forms: (A) The corrected average of return period is independent (B) Model is dependent and can be explained by a simple quadratic function. Using time series models is one of the applicable ways to simulate and predict hydrological series. One of the most problems in the predicting time series models is method of generating random series. In this process, with the changing generated data, predicted series will be changed. In this study, after initial investigations on the Zarineh-rud River flow series, ARMA models fitted and ARMA(1,0) model selected as the best model. Residual series of ARMA model extracted and fitted with the PARCH model. Finally two models combined and ARMA-PARCH model obtained. Results showed that by the combining ARMA and PARCH models, error (root mean square error) and accuracy of model (regression coefficient) improved about 40 and 10 percent. Also from the results it is concluded that maximum and minimum points of the average river discharge series is modeled properly with the combined model in the studied station.

The process of scouring is removal of sediments from river bed, caused due to moving water or waves. Scour can be classified into two broad categories: General scour and local scour. Contraction scour, as a type of general scour, occurs due to a reduction in channel cross-sectional area. Local scour on the other hand occurs due to the direct effect of an obstruction on the flow field. Contraction scour is observed where the flow is constricted due to the placement of structures like bridges etc. The flow accelerates in constrictions which increase the bed shear stress and the turbulence associated with it. The development of contraction scour is noted when the critical shear stress of the bed materials is overcome by the bed shear stress. This paper provides a comprehensive discussion on scour within channel contractions. Scour within a channel contraction occurs where the waterway is restricted by the foundations or road approach embankments of a bridge. Alternately, contraction scour takes place when a bridge is located at a natural contraction in the river width. Contraction scour is an important phenomenon in rivers. To reach the aims of this work, both experimental and numerical modeling has been done. In this study, the experiments curried out in a flume with length of 20 m and width of 0.6 m, located in hydraulic laboratory of Shahrekord University. The average size of the sediments in the flume was d50 = 0.78 mm. The bed sediment layer was 16 cm thick. The experiments were run with three different discharges: 20, 30 and 40 l/s and flow depth was regulated at 30 cm. Also, the experiments were conducted with four different contractions of 20 cm, 30 cm 40 and 50 cm wide, which was resulted in three different the contraction ratio of 0.33, 0.5 and 0.67. SSIIM computer model has been used for contraction scour prediction in stream for two different conditions, including sudden (with angle of 90o) and gradual (with angle of 50o) contractions. Calibration of SSIIM model was conducted based on the results from the experimental study. SSIIM numerical model is capable of solving the Navier-Stokes equations on three-dimensional network with k-ε turbulence model. Likewise, it utilizes volume control with power upstream or second-order law for discretizing equations. This software also addresses to solve the passive pressure field using iteration technique and simple method (semi-implicit method for solving equations with pressure). After calibration of experiments to analyze the output results, Tecplot software was employed because the display of the obtained results from scouring through SSIIM was not clear. In current study, parameters such as flow pattern, scouring pattern, and water depth were simulated. Calibration of results was carried out by the experimental data. With monitoring model results, the start of scour for all models in the beginning of the narrowing part and the side walls was simulated. The greatest value of the scouring achieved at the same place as in experimental model. According to the results of the model regarding flow pattern simulation, it can be stated that flowing lines are constricted by reaching to narrowing part beginning and along the narrowing section changed to parallel lines. At the end of constriction, flow lines are being expanded and at the gradual opening, rotational currents are formed. Maximum amount of scour was calculated 12 cm in flow rate of 40 L/s and 20 cm constriction with 9.09% error that this amount was measured 11 cm in the laboratory. In addition, the least amount of scour was measured 1.8 cm in flow rate of 20 L/s and 40 cm constriction with 20% error in numerical model and 1.5 cm in the laboratory. Obtained results showed that the model was adequate for modeling of contraction scour, in parameters of scouring maximum depth, erosion pattern and circular flows. Accuracy of the model was acceptable according to the average of Nash – Sutcliffe coefficient of 0.923, average error of 10.18 and the maximum error of 20%. Based on the calibrated model, contraction scour was simulated for sudden transition and results showed that scour maximum depth was increased at a rate of 29.5%, comparing with gradual transition. This indicated that gradual transition plays a positive role to reducing contraction scour.

Snow is one of the most important forms of precipitation in the mountainous regions. This parameter has an important role in supply of drinking and agriculture water resources, and energy production. Monitoring of the snow cover area creates the possibility of estimating the snowmelt runoff that is used in control and management of the watershed water. Required water of more than one sixth of the world's population is supplied through melting seasonal snow and glaciers. If the warming phenomenon happens, a huge number of populations will encounter the risk of the lack of water. So, monitoring the snow cover area is considered very important in order to understand regional hydrological cycles. The snowy areas of Iran are mainly located in mountainous heights where the monitoring and measurement stations for snow have not developed. Therefore, it is not possible to measure the accumulation and melting of the snow exactly. Obtaining enough information about snow reserves during a period can be useful for proper use of the water from snow melting, saving water and prevention of its waste, controlling the flood, and providing water for downstream lands. Snow survey stations and satellite images are used for estimating spatial and temporal distribution of the snow in watersheds. When the number of stations is enough and their data are complete, the statistics obtained from snow survey stations will be acceptable, while there is lack of such facilities in most mountainous regions of country. In this study, Normalized difference snow index (NDSI) was used for determining snow-covered areas. The index is applied as an automated algorithm to recognize the snow and calculated pixel by pixel. The final snow cover map is provided in the binary form. It means that study area is classified into two classes: snow and no snow. ArcGIS10.2.2 software was used for calculating snow cover area. According to the produced maps, the northwest of the study area is always covered by snow in winter. Because this region includes the maximum elevation (more than 3000 meters) and Sabalan mountain is located there. So, in comparison with other regions, temperature is lower in this area which leads to snowfall and snow durability. Also, the southwest of the catchment is covered by snow in most of the maps, due to the existence of the Bozgush Mountain with approximate elevation of 2000 to 2700 meters. The minimum density of the snow was showed in the northeast of the catchment, due to being on the catchment outlet and having the lowest elevation. Also, the central parts of the catchment often include low snow cover. In this region, low elevation and high temperature cause low snowfall and high velocity of snowmelt. Existence of Ardabil city in the northeast of the catchment leads to high temperature in this zone in comparison with other zones. The percentage changes of the snow cover area per month were calculated during years 2011- 2014 in comparison with the same month in 2010 in order to survey the monthly changes of the snow cover area in winter in the study area. It was concluded that the snow cover area in the first month of the winter, during all 4 years, has been decreased in comparison with the same month in 2010 and maximum reduction was associated with the first month of the winter in 2011. Provided maps and calculated snow cover areas showed that northwest and southwest of Balighlu Chay watershed is often covered with snow in winter, due to existence of Sabalan and Bozgush mountains in these regions. Low-elevation regions, including the end (northeast of the study area) and center of watershed had the lower snow cover. Maximum snow cover area was 1205.7KM2 (96.7%) in the period studied, and was related to 7/1/2010. However, during 5 years, maximum snow cover area has often occurred in February. Investigating snow cover area monthly in winter, during 5 years, showed that the amount of snow covers in the study area had intensive changes. The average winter snow cover area for each year indicated that this parameter has decreased and increased alternatively during 5 years. The maximum and minimum average winter snow cover area were related to 2012 (857.4KM2 ), and 2011 (414.6KM2). To sum up, intensive fluctuation in snow cover area reflects the vulnerability of the water resources in the study area, which are dependent on snowmelt.

Analyzing water distribution networks is very important under deficiency of fresh drinking water. Careful analysis of urban water supply systems has been much highlighted than before due to water scarcity and water crisis. Analysis of a water distribution network means that the hydraulic characteristic of a water suppling network should be evaluated to test the efficiency of the water supplying network in delivering water to the determined locations. Indeed, the main goal of construction of a water distribution system is to effectively deliver fresh drinking water to consumers with appropriate quality, quantity, and pressure over time. A high quality water distribution system should consist of some main features including: provide acceptable water quality that should not get deteriorated in the distribution pipes network; supply water at all the intended places with sufficient pressure head and sufficient amount of water during firefighting; be designed in a way that no consumer experiences water supply shut-off during maintenance of any part of the system; and also contain fairly watertight to reduce losses due to leakage. In this paper, the Bezein water distribution network, located in west of Shiraz, Iran, with a total area of 77 hectares and the occupied area of 34 hectares, with 1907 connection and population of about 7,600 was selected as the case study. The network was simulated with WaterGEMS software. The WaterGEMS is multi-platform software which can model hydraulic and water quality of water distribution systems with the options of advanced interoperability, geospatial model-building, optimization, and management tools. The Bezein town is provided with a 150-millimeter diameter main pipe diverted from a 300-millimeter diameter pipeline that supplies drinking water for Shiraz city. The Bezein water distribution network includes pipelines with diameters of 150, 110, 100, 80 and 63 millimeters, which are made of asbestos, polyethylene, and PVC. An electromagnetic flow meter has recorded the discharge and pressure head of the entering flow to the Bezein town every 15 minutes. Based on the measurements, 471261 cubic meters of water with a pressure head of 60 meters entered the water supply network during 2012, indicating the per capita flow of 170 liters per day. Modeling water distribution system was performed by assigning required amount of water demand to each joint (water delivery location), based on appropriate monthly and hourly demand factors after introducing pipeline network plan of the Bezein water distribution network to the WaterGEMS software. The model has been calibrated according to 8 measured joints in the network with the root mean square error of 6.8 meters of water head. The results of model, including the hydraulic parameters of the water distribution network such as water discharge, velocity of flow in pipes, pressure of flow at joints, energy line, and hydraulic grade line, have been simulated during 2012 in every hour after calibration process. Analysis indicates that the flow velocity was lower than 0.3 meter per second in more than 95 percent of pipes in the water distribution network, in August as the maximum consumption time of year. The flow velocity of 0.3 m/s is the minimum recommended velocity to prevent sedimentation in pipes of water distribution network based on standards. However, velocity of flow in all of the pipes of the network was lower than the recommended amount in the minimum consumption time of the year according to model analysis. Simulation have shown that pressure head in more than 50 percent of the joints was more than 50 meters which is the recommended pressure value in water distribution network. Low velocity in pipes increases the probability of sedimentation and, on the other hand, the high value of pressure head in pipes leads to leakage and will increase the risk of stress fracture in peak pressure hours of the water distribution network. According to analyses of hydraulic parameters, lack of optimized hydraulic condition in this network is possibly due to the use of high-diameter pipes as large as 150, 110, 100 and 80 mm. Results of this study express the necessity of determining hourly and monthly demand factors in terms of exact consumer needs for designing an optimal water distribution network and also emphasize analysis of water distribution systems with the Extended Period Simulation method, in order to evaluate and modify current problems.

Rapid transition from a supercritical to subcritical flow is characterized by large-scale turbulence and energy dissipation. This transition is called hydraulic jump. The hydraulic jump is a type of rapid varied flows that used for water chlorination in treatment plants and energy dissipation of the flow and other hydraulic purposes. Due to the importance and complex structure of this phenomenon, many experimental, analytical and numerical studies have been carried out in this field. In general, hydraulic jumps occur after ogee spillways. Also, stilling basins are usually situated at downstream of ogee spillways. Therefore, for proper design of the length of stilling basins, accurate determination of the hydraulic jump length has a significant importance. In this study, a hybrid model (ANFIS-PSO) is introduced which uses Adaptive Neuro Fuzzy Inference Systems (ANFIS) and Particle Swarm Optimization (PSO) for predicting the hydraulic jump length on sloping rough beds. The Adaptive neuro fuzzy inference system is a kind of artificial neural network which is based on the Takagi-Sugeno fuzzy inference system. The inference system is a set of fuzzy IF–THEN rules that have learning capability to approximate nonlinear functions. In this model, PSO is applied to enhance the performance of ANFIS by adjusting the membership functions and subsequently minimizing the error. In fact, PSO is considered as an evolutionary computational method, optimizing continues and discontinues making decision functions. Additionally, PSO is considered as a population-based search method in which each potential solution, known as a swarm, represents a particle of a population. In this approach, the particle position changes continuously in a multi-dimensional search space, until reaching the optimal response and/or computational limitations. Also, in the current study, to evaluate the performance of ANFIS-PSO models, the Monte Carlo simulation (MCs) is applied. Monte Carlo simulation is a broad class of computational algorithms that rely on repeated random sampling to obtain numerical results. Their main idea is using randomness to solve problems that might be deterministic in principle. They are often used in physical and mathematical problems and are most useful when it is difficult or impossible to use other approaches. The Monte Carlo simulation is mainly used in different problems such as optimization and numerical integration from a probability distribution. Also, in this paper, the k-fold Cross Validation (k=4) is used for examination of the models ability. In k-fold Cross Validation, the original sample is randomly separated into k equal size sub-samples. In k sub-samples, a single sub-sample is retained as the validation data for testing the model, and the remaining k-1 sub-samples are used as training data. The cross-validation process is then repeated k times (the folds), with each of the k sub-samples used exactly once as the validation data. The k results from the folds can then be averaged to produce a single estimation. The advantage of this method over repeated random sub-sampling is that all observations are used for both training and validation, and each observation is used for validation exactly once. At first, five ANFIS-PSO models are defined using effective parameters on length of hydraulic jump. To validate the ANFIS-PSO models, the Kumar and Lodhi’s (2016) experimental measurements were used. The experimental model was conducted in a rectangular channel with a length of 8.0 m, 0.60 m width and 0.60 m depth. Three slopes of a flume, viz. 0.005, 0.010 and 0.016, were observed. Next, by analyzing the ANFIS-PSO models results, the superior model is presented. The superior model predicts the length of hydraulic jump in terms of Froude Number (F1), ratio of roughness bed (Ks/h1), ratio of sequent depth (h2/h1) and slope bed (S0). This model simulates the experimental measurement with suitable accuracy. For superior model, the Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and the correlation coefficient (R) were respectively computed equal to 3.750, 0.688 and 0.984. In addition, the scatter index (SI) for superior model was estimated equal to 0.055. Also, in order to more examine the ANFIS-PSO models results, the ratio of the predicted jump length to the observed jump length (λ=(Lr/h1)(Predicted)-(Lr/h1)(Observed)) was introduced. For the superior model, the average of this ratio was calculated equal to 1.003. According to numerical models results, the Froude number is identified as the most effective parameter for modeling the length of the hydraulic jump.