مجله مهندسی آبیاری و آب ایران
پیاپی 35 (بهار 1398)

Predicting rivers flow, as one of the main resources of water for human beings, has always been one of the important issues discussed in hydrology and water resources. So, different models have been used for modeling and predicting rivers flow.
 In this study, two genetic models, Gene Expression Programming (GEP) and genetic programming (GP) were evaluated. Flow, temperature, precipitation, and evaporation data were used to model the daily flow in Tale Zang station. The results showed that GEP model, with R2=0.86 and RMSE=0.0030 m3/s, had the better performance than GP model, with R2=0.85 and RMSE=0.0037 m3/s. Moreover, the speed of GEP was more than GP and had ability to present results in a short time. By increasing the number of data, the speed of GP decreased and sometimes it couldn’t present results, while GEP had the ability to work with more data and model the river flow.

The mechanism of flow and sediment transport in channel bend is much more complex when the outer bank of the bend is employed for lateral diversion. Due to the secondary current, sediment moves away from outer bank and therefore outer bank of the bend is one of the best locations for lateral diversion. In this experimental investigation, three structures including Sill, Dike and skimming wall were used to control the amount of bed sediment at lateral intake with three ratio of diverted flow discharge of 0.17, 0.21 and 0.26. Results showed that to have a fix percentage of flow diversion in all experiments, these structures have been effective on water level compared to the control conditions and they had an effect on input Froude number. The combination of skimming wall of 14 ̊, dike and sill had the most controlled bed sediment in different percentages and 92 percent of sediment movement to the lateral intake decreased compared to the control experiment. In the sill experiment, by increasing the percentage of flow diversion, the effect of this structure reduced, the least percentage of reduction of sediment diversion at discharge ratio of 26 percent has been 65 percent. Changes in the strength of secondary flow were investigated quantitatively at the intake mouth and it was revealed that the process of changes in sill and control experiments is different from other experiments. Investigating shear stress of the bed channel, it was shown that, firstly, the amount of shear stress in outer bend is more than inner bend and secondly, by increasing the percentage of flow diversion, shear stress increases along the intake. Using skimming wall of 14̊, the local pattern of shear stress in front of the intake changes such that the amount of shear stress near the intake decreases, the maximum shear stress is moved towards the center of the channel and back of the structure, which leads to decreased amount of erosion and diversion of sediment to the intake

Spur dikes are structures which are constructed at an angle or perpendicular to flow to reduce flow velocity and bank erosion. As constricting structures, spur dikes narrow the flow channel and alter the flow structure in their vicinity, and develop vortices around the constricted region. In this paper the flow pattern alteration and bed morphological variation due to the various orientations of a group of parallel impermeable, non-submerged spur dikes having unequal lengths are numerically investigated. Numerical model validation is carried out utilizing experimental data. The results show that changing the orientation of spur dikes from 90° to 45° (reduction of channel width constriction by 12%), the maximum depth of scouring beneath the first spur dike is reduced by 50%.

One of these types of weir is the sharp edges overflow, which is widely used due to the current flow pattern and ease of flow pass. In the present study, the flow characteristics of the proposed horizontal sharp edge triangular overflow with different angles of 30, 60, 90, 120, 150 and 180 degrees at downstream are simulated for 10 different discharges using the FLOW-3D numerical model. In this regard, after validation of the amount of the flow depth over the weir with valid experimental results, parameters of the discharge coefficient, pressure profile, velocity in transverse section and flow pattern have been calculated and analyzed. The results indicated the high accuracy of RNG turbulence model compared with other turbulence models with correlation coefficient R2 = 0.9996. Other results showed that discharge coefficient of proposed weir increases with 6% in compared with experimental weir model (with vertex at upstream). Weir with 150-degree angle has the highest increment of discharge coefficient with about 8.5%. As the angle rises from 30 to 150 degrees, the minimum pressure range progresses from the tip of the weir and goes downwards. The maximum amount of pressure in the downstream of overflow was observed for weir with 120-degree angle with a value of 1100 Pascal. The minimum pressure of 10 pascal was obtained in a small range of 150-degree weir. As the flow approach to tip of the overflow, the flow passing from the side and tip of the overflow and has high velocity values. The maximum longitudinal velocity was observed with a value of 1.53 meter on second in a 90-degree overflow.

Investigation of the flow pattern in meandering rivers is much more complicated than straight ones. Also, most rivers in the path of bends are not uniform due to channel width variations. Therefore, the use of a robust numerical model for simulating flow pattern in rivers is necessary. In this research, SSIIM three-dimensional numerical model was used to simulate the flow pattern in a meandering reach of ​​the Doab river in Chaharmahal and Bakhtiari province. For this purpose, after doing field measurements and model calibration the velocity values ​​calculated by the model were compared with the measured values in a relatively uniform section of bend by using RMSE and MAPE error criteria. Results obtained showed that the values of these two criteria are 0.081 and 0.075, respectively. This indicates that the model performance is good. Moreover, various flow characteristics including vertical and horizontal velocity profiles, the velocity lines in longitudinal and transverse directions and also the distribution of bed shear stress in location of two converged and diverged the bends are compared. The results of this study indicate that velocity values in longitudinal direction in converged bend is higher than diverged one. the high accuracy of the model in the study of flow pattern in the river bend. Furthermore, the density of the stream lines and the values of bed shear stress at the interval reach of two bends are maximum. As result, it can be said that flow pattern simulated well with the model

The proper estimation of sediment yield of rivers is important for planning and managing water resources. Various methods have been developed to determine the relationship between discharge and sediment concentration. Sediment rating curve is one of the most common methods for estimating the suspended sediment yield in rivers, which is always associated with a large error. In order to improve estimation of sediment yield using sediment rating curve, the equation coefficients can be optimized using artificial intelligence methods. The purpose of this research is to use a genetic algorithm to optimize the Sediment rating equation coefficients for Gorganroud river (Ghazaghli station) and Fariman river (Bagh Abbasi station). With this aim in mind, discharge and suspended sediment concentration data have been acquired for the stations. Sediment rating curve equation was calculated for each station with training data. Then an optimal coefficient of equation was achieved using genetic algorithm model defined in MATLAB 2017 software. The study results showed that the genetic algorithm model for Ghazaghli and Bagh Abbasi stations had a better performance than the sediment rating curve with the Nash-Sutcliff coefficient of 0.5 and 0.72 and coefficient of determination of 0.5 and 0.89, respectively. Also, the genetic algorithm for Bagh Abbasi Station with the limited samples has better accuracy than the sediment rating curve method. The study results indicate a high performance of the genetic algorithm in optimizing the coefficients of Sediment rating curve equation, especially in low data stations.

Precipitation is one of the important climatic parameters in hydrological models. Therefore, the accurate estimation of its amount and spatial distribution in a watershed is of great importance. In recent years, due to the limited number of raingage stations especially in mountainous areas, the use of satellite precipitation data as an effective tool for predicting regional distribution of rainfall has gained lots of attention by the researchers. In the present study, the accuracy of TRMM 3B43 data, which is one of the TRMM products, was evaluated in 40 raingage stations and 9 synoptic stations in Hormozgan province in a monthly scale. Comparison of satellite data with the observation data was performed for the time period 1998-2012. To assess the agreement between TRMM rainfall data with observation data, the statistical criteria including Spearman correlation coefficients (Rs), Pearson correlation coefficient (Rp), mean absolute error (MAE), root mean square error (RMSE) and mean square error (MSE), as well as probability of detection (POD), false alarm ratio (FAR), true skill statistics (TSS) and critical success index (CSI) were used. Based on the results, the highest value of POD (1) was observed in August and the lowest POD (0.92) was obtained in May. Moreover, the highest FAR (0.91) and the lowest CSI (0.08) were observed in May, and the lowest FAR (0.16) and the highest CSI (0.83) was obtained in January. In addition, the highest Rp (0.64) and Rs (0.76) were seen in December while the lowest Rp and Rs were occurred in April, May and July. These results indicate that the TRMM satellite has the highest accuracy of predicting rainfall in winter and spring while it has the lowest performance in summer. In other words, the TRMM satellite is able to predict rainfall in cold months better than in warm months of the year. The results also showed that TRMM overestimates rainfall in most months of the year, however the results were significantly improved after calibration especially in August and December as seen in spatial distribution maps.

One of the most important issues in water resources management, is the optimal operation of dam reservoirs. In this research metaheuristic invasive weed optimization algorithm was used to find optimal water allocation strategies for a period of 10 years in Tazeran dam that located in the west of Iran. The developed model in this research is provided for optimal operation in the present state of cropping pattern. The downstream field of Tazeran dam are divided into two zones consist of Tazeran and Evandeh. The defined objective function is to minimize total deficiencies during the simulation period. In order to investigate the reservoir performance indicators of time reliability, percentage to provide volume and vulnerability is used. The results of IWO algorithm also compared with the results of the Genetic algorithm method. Due to the inadequate and inappropriate distribution of Tazeran river flow, simulations have been done in two states, use of surface water flows alone and the combination of surface and underground water flow. Result shows that using IWO and GA method and use of surface and ground water simultaneously, Tazeran dam is able to provide 77.2% and 76.24% of the total downstream of water requirement. Also, reliability and vulnerability indicators in Tazeran region are 55.45% and 33%, respectively, in the IWO method and 52.72% and 41% in the GA method.

This study was carried out using AquaCrop plant growth model to simulate potato crop yield in irrigation levels of 100, 80 and 65 percent of plant water requirement under climate change conditions in Shahrekord region. The data of two years of 2013 and 2014 were used to calibrate and validate the AquaCrop plant growth model. In order to investigate the effect of climate change on product yield, the output data of the HadCM3 general circulation model under two scenarios A2 and B1 for the periods 2011- 2030 and 2046-2065 are downscaled using LARS-WG model and used as inputs of the growth model. Based on the results, the simulation of potato yields with the AquaCrop plant growth model was carried out with high precision so that the average difference between observed and simulated values in calibration and validation stage was 0.56 and 0.68 ton/ha, respectively. Also, the mean absolute error (MAE) for simulating minimum temperature, maximum temperature, sunshine hours and precipitation with LARS-WG model was 0.05, 0.03, 0.01 and 0.16, respectively which reflects the good performance of the model in producing climate data for the future periods. Simulation results showed that the potato yield for the periods 2011-2030 and 2046-2065 under the A2 scenarios was 15.8 and 24.5 percent, respectively, and under B1 scenario, 11.8 and 22.4 percent increase compared to the base period. Also, for I80 and I65 treatments, the yield value decreases in both the future periods and the two scenarios campared to the base period.

This study was carried out using AquaCrop plant growth model to simulate potato crop yield in irrigation levels of 100, 80 and 65 percent of plant water requirement under climate change conditions in Shahrekord region. The data of two years of 2013 and 2014 were used to calibrate and validate the AquaCrop plant growth model. In order to investigate the effect of climate change on product yield, the output data of the HadCM3 general circulation model under two scenarios A2 and B1 for the periods 2011- 2030 and 2046-2065 are downscaled using LARS-WG model and used as inputs of the growth model. Based on the results, the simulation of potato yields with the AquaCrop plant growth model was carried out with high precision so that the average difference between observed and simulated values in calibration and validation stage was 0.56 and 0.68 ton/ha, respectively. Also, the mean absolute error (MAE) for simulating minimum temperature, maximum temperature, sunshine hours and precipitation with LARS-WG model was 0.05, 0.03, 0.01 and 0.16, respectively which reflects the good performance of the model in producing climate data for the future periods. Simulation results showed that the potato yield for the periods 2011-2030 and 2046-2065 under the A2 scenarios was 15.8 and 24.5 percent, respectively, and under B1 scenario, 11.8 and 22.4 percent increase compared to the base period. Also, for I80 and I65 treatments, the yield value decreases in both the future periods and the two scenarios campared to the base period.

More than 75% of the rice cultivated land is located in the northern provinces of Mazandaran, Gilan and Golestan. In recent years, the second cultivation of rice has been developed. This research was carried out in Mazandaran province, Khazarabad region of Sari, for the Premature varieties of local Tarom during two seasons for second cultivation in (2016 and 2017). In this study, triplicate overflow was used to measure inlet and outflow discharges. Three lysimeter were used to determine the water requirement of the fields. The water requirement was calculated from the input difference, which included the amount of water input that was calculated by overflow, as well as rainfall and output, including (evapotranspiration, permeability of the lateral submerged area and drainage water) Also, the irrigation of three stages of crop, reproductive and rearing for the first crop of (2015) was estimated to be 1.10, 1/5, 1/2 The coefficient for the second cultivation of (2016) was ./98, 1.4, 1.03, and the second planting factor of 2017 was ./95, 1.34, 1/01 respectively. The results show that the amount of water requirement in the second cultivation of 2016 and 2017 is 33%, 27% less than the first crop of 2015 respectively. Also, the average of crop factor in three stages of growth in the second cultivation of 2016 and 2017 was 10% and 12%, respectively, compared to the first one of 2015. Therefore, in regions where there is a good level of rainfall during the second crop, it is possible to recommend the second crop of rice.

There are a separate and combined effects of nitrogen and water, as most important factors, on plant growth. This experiment was conducted to optimize the use of these inputs in drip-irrigated tomatoes to gain optimum quantitative and qualitative yield. The experimental design was RCBD as split manner with three replications in three years. Three irrigation treatments: 75, 100 and 125 percent of calculated irrigation water (IW), and four rates of nitrogen: 0, 75, 150 and 225 kgha-1 N were as main and subplot, respectively. The results showed that effects of each factor on yield, irrigation water use efficiency (IWUE) and nitrogen use efficiency (NUE) was induced by the other one. In treatments of 75%, 100% and 125% of IW, maximum yield, IWUE and NUE obtained from 75, 150 and 225 kgha-1 nitrogens, respectively. Increasing in water rates decreased IWUE in the absence or low rate of N, but increased it in presence of high rates of this nutrient. Although nitrogen application was associated with reduction in NUE, but high water rates improved it. Increasing in mean weight, vitamin C and nitrate concentration of the fruit were obvious by increasing in water and nitrogen rates. Fruit TSS was increased by N application and decreased by increasing water. It was concluded that nitrogen use management should be considered for efficient use of irrigation water in different irrigation regimes

The presence of heavy metals in the environment due to their harmful effects on human health, regarded as a problem. Today, high-performance biosorbents for wastewater treatment containing heavy metals such as cadmium were developed and are preferable than other absorbents. The aim of this study was investigation of effect of influent concentration on cadmium removal in a fixed- bed column using adsorbent Conocarpus. Conocarpus was prepared from waste vegetable of DEHLORAN city gardens and surface structure of absorbent was investigated. In this study, the effect of influent concentration on cadmium removal wasinvestigatedand Adams- Bohart  and Thomas models were used to the column adsorption modeling. Physical characteristics results showed that the adsorbent has deep pores and complex, intricate, uneven and irregular surface of filamentary structure. The results of breakthrough curves review showed that in higher concentrations, breakthrough time of bed was decreased. breakthrough curves slope increased and breakthrough volume decreased with increasing initial cadmium concentration. Also Adams- Bohart  model has a better fit of the column data

One of the methods to determine the water quality is applying water quality index. This comprises several parameters with different effects on water quality. Therefore, one important problem is to calculate the exact value for each of the parameters. The purpose of the present study is to compare the effects of equal weights and weighted parameters on the results of water quality index in Fasa plain employing Entropy theory. To this end 9 Chemical parameters from 55 groundwater samples were investigated and ranked using the water quality index. Then, the weight of the parameters was calculated with the weights that obtained by the Shannon Entropy method. Thereafter, the significant difference was investigated between two groups. In order to determine the efficiency of each of these two methods, the Spearman's correlation was employed between the rating of wells quality in two methods and the rating of wells quality which was calculated by Sholer diagram. At the end, the clustering and qualitative zoning of wells were plotted. The results showed that there was a significant difference between the results of the water quality index whose weights obtained from the equal weights method and Shannon Entropy method in 0.01 level. Also, the high correlation (0.926) between ratings of wells quality by Sholer diagram method and ratings of wells quality was obtained by Shannon Entropy method indicates the high significance of this method in calculating water quality index.

Using computer models in order to investigation of pollution changes in the rivers is essential. The first step in protecting water resources is the comprehensive awareness of their quality. So, in this research using system dynamics approach to developed computer model in the VENSIM programming environment, which can simulate the process of changing water quality in 468.8 m from the detector source. In order to calibrate and validate the model results, data collected from one of the irrigation channels of Nahavand (Nahr Shaaban) in Hamedan were used. After statistical analysis and calculation of RMSE, SE, MAE and R2, the fit between measured and simulated was calculated. In the irrigation channel, sodium chloride with electrical conductivity of 0.746 mmohs/cm was injected for 20 minutes and there were three sampling stations. The best fit of the model results with measured data was at the distance of 12.5 m (the first sampling station), and the lowest adaptation was in the second sampling station at the distance of 228 m from the injection source. The values of statistical indexes in the first sampling station were 0.35 mmohs/cm, 0.18, 0.13 mmohs/cm and 0.90, and at the second sampling station were 0.47 mmohs/cm, 0.24, 0.22 mmohs/cm and 0.81, respectively. The results showed that the model has good accuracy in simulation of water quality process.