Journal of Irrigation and Water Engineering
Year:2017 | Volume:7 | Issue:27|Papers Count:11

Local scour involves removal of material from around piers and abutments as the flow accelerates around the obstructed flow area. This phenomenon is sometimes the main reason for the bridge failure. Different structures such as submerged vanes can be used to change the flow pattern and prevent scouring around the piers and abutments. In this study, the effect of submerged vanes on the reduction of the local scour around the bridge abutment was studied. Experiments were conducted in a compound cross section flume with non-cohesive sediments having diameter (d50) of 1 mm. Experiments were performed for two cases of with and without the presence of submerged vanes. Vanes with a length of 10 cm and height of 3.33 cm (L/H=3) were installed in front of the bridge abutment with an angle of 20 ° to the flow direction. They were used in three layouts of one row, two parallel rows, and two zigzag rows. The results showed that the geometric property of the scour hole developed in the nose of abutment was similar to those previous related studies. For all flow conditions, the results showed that the submerged vanes reduced the scour hole around the bridge abutment and moved the scouring away from the abutment to the center of channel. Furthermore, the performance of the layout of two parallel rows was better than the layouts of one row and two zigzag rows, and it reduced the maximum scour depth up to 87.81 %.

In the present research, three-dimensional flow in a rectangular channel, containing a bridge abutment, was simulated by using flow-3D software. For validation of the numerical results, three-dimensional components of flow velocity in the vicinity of the abutment were obtained from an experimental test. After comparison of the measured and numerical results, it was shown that RNG performed better (R2=0.963, RMSE=0.02 and MAE=0.03) than the other two turbulence models (LES and k-e). The optimum mesh size was chosen based on the above results. Results revealed that it is necessary to consider return vortices and fluctuations in flow velocity in the vicinity of the abutment, especially in the downstream, for proper design and location of abutment geometry. Viscosity and energy of flow turbulence in the downstream of the rectangular abutment reached their maximum value and existence of the obstacle was more pronounced. It was shown that in the section after the abutment, simultaneous reduction of velocity and becoming negative, the viscosity had an increasing trend and reached up to 0.67 Pa sec. The section located in the middle of the abutment had minimum turbulence energy (0.00245 J/kg) and the next section had maximum turbulence energy (3.59 J/kg). Pressure variations around the abutment showed that maximum pressure (933 Pa) occurred in the previous section and minimum pressure (860 Pa) was seen after the abutment.

This research was conducted to compare the efficiency of some simulation models including sediment rating curves and artificial neural networks for simulating the suspended sediment load amount. Optimized model basis of flow discharge in Shahrood watershed upon the hydrometric stations including Glinak, Baghkalaye, Loshan and Rajayi dasht was represented. In order to simulate the suspended sediment load we compared one linear rating curve and artificial neural network with multi-layer perceptron and radial base function models. Then performance evaluation these models was carried out by NASH and RMSE criteria. The results showed that artificial neural network with multi-layer perceptron method in comparison on sediment rating curve model in all of these stations simulated better models. So that artificial neural network with sigmoid triggering function in Glinak and Rajayi dasht stations with RMSE as 1.033 and 0.825 ton/day and NASH as 0.84 and 0.839 and this model with tansigmoid triggering function in Baghkalaye and Loshan stations with RMSE as 0.799 and 0.883 ton/day and NASH as 0.772 and 0.895, respectively, have the better efficiency for simulating of suspended sediment load amount. Also comparison of two neural network models showed that MLP model is better than RBF model for simulating of suspended sediment load amount. The only benefit of RBF networks is less time needed for training.

Fans are places with high permeability and have the highest share in recharge of aquifers. But with the development of urbanization and loss of permeable surfaces, occurs a lot of floods. In this study, quantitative and qualitative management of urban runoff on the part of district 22 in Tehran is investigated. The research-based best management practices BMP, which is one of the most modern and effective methods of quantitative and qualitative urban runoff is high. In these studies, EPA-SWMM software uses two strategies swale and Bio retention. System (green roofs) to control the flow and pollution, the concentration of total suspended solids (TSS) of the basin located in District 22 of Tehran Municipality was evaluated. The results showed an average decrease of 18.2% compared to the management solution of green roof garden with an average reduction of climate 9.7 percent better performance in reducing the height of the peak runoff is discharged from the basin. The results showed an average decrease of 18.2% compared with the green roof management solution with an average reduction of 9.7 percent to swale, the better the height of the peak runoff is discharged from the basin. The green roof management solution on average 18.7% of the total pleasure of suspended solids (TSS) and swale decreased 12 percent. The green roof more efficient management solution enjoys TSS removal. The green roof is the best and most efficient management solution BMP was chosen for the study area.

Rain water harvesting is one of the most significant water utilization management techniques to cope with water scarcity. Recognizing the potential of rain water is the first step in rain water management. The multi criteria decision analysis (MCDA) is known as an important tool in natural resources management decision particularly in water management. In this research, multi-criteria decision-making approach and geographic information system (GIS) were used to identify the areas with rainwater harvesting potential. The criteria including suitability for purpose, accuracy and ease of access, acceptance in the local communities, the cost and time were selected, and the weight of each criterion was calculated by using the Shannon entropy method. Totally, 31 indicators were selected for decision making and the weight each index was calculated and prioritized using TOPSIS. The results show that among the ranked indices, soil permeability has the highest weight (0.820) and the soil texture show the second order with the weight of 0.810, while the average annual rainfall and groundwater levels with the weights of 0.615 and 0.517 indicate the lower priority for rain water harvesting.

This study investigated the adsorption capacity of rice husk and seashell compounds. Particles were classified in five different sizes of 841, 400, 177, 125 and 74 μm which based on ASTM sieves. Sodium chloride solution was prepared in different concentration of 25, 50, 100, 200, 300, 500, 750, 1000, 3000, 5000, 7000 and 10000 ppm. The effects of the sizes, dosage, contact time, rate of mixing with duration of 10, 15, 25, 35, 45, 60 and 120 minutes for the salt removal done with batch experiments in 25oC. in this method the sodium chloride solution with certain amounts of adsorbent put on a shaker device with constant speed of 200 rpm and were mixed at intervals of 10, 15, 25, 35, 45, 60 and 120 minutes. Then the samples in centrifuged with 10000 rpm in 10 minute and the upper solution used for chloride titration. The effects of different amount of absorbent on salt absorbance showed that for all samples the highest absorbance is related to the range of 2 gram. Due to increasing of absorbents quantity from 0.5 to 2 gr, the absorbance percentage of rice husk and sea shell from 51 to 58 and 27 to 42 respectively. Among the used sizes of particles the most efficiency was related to the size of 74 mm in salt absorption. The optimum time of used samples was identified as 25 and 10 min for rice husk and sea shell respectively. Based on isotherm model, rice husk followed langmouir model, while seashell followed Freundlich.

In this research, the effect of alternate irrigation and drainage on yield and the change trend of plant height and tiller number of Hashemi rice cultivar was investigated in subsurface- drained paddy fields. The experiments were done under a randomized complete block design with four subsurface drainage treatments and a conventional surface drainage treatment (control). During rice growing season, the treatments were subjected to two drainage periods of 10 and 5 days (26 and 43 days after transplanting) as midseason drainage and one drainage period as end season drainage (63 days after transplanting until harvest). Alternate irrigation and drainage increased tiller number and decreased plant height in subsurface drainage treatments compared with control, 2-3 tiller and 1-6 cm, respectively. Subsurface drainage resulted in 10- 38 % and 21- 40 % more grain yield and harvest index, respectively, than control. Based on the results, alternate irrigation and drainage will increase the productivity of subsurface- drained paddy fields.

In horticultural plants, determining of evapotranspiration because of The existing problems in the direct measurement such as installing large lysimeter or the exact equipment and length during tree growth, often estimated indirectly and on the basis of meteorological data. With regard to the spatial variability of meteorological parameters and sometimes inappropriate distribution of meteorological stations estimating evapotranspiration is not possible with sufficient accuracy. Therefore use of procedures such as the remote sensing methods that consider these changes is best. In this study, evapotranspiration of olive trees were measured and determined with direct and indirect methods in two growing seasons 1393 and 1394 in Tarom district of Zanjan at different development stages. The actual evapotranspiration were determined by direct method, By measuring the moisture balance components and in the indirect method with help from the satellite imagery of land sat 8. Then by determining of the reference crop evapotranspiration, olive crop coefficient were calculated and were compared and evaluated. The results showed that calculated evapotranspiration and plant coeffiecient of remote sensing mehod in various olive growth stages matched with moisture balance data. So that, evapotranspiration correlation coefficient was 0.73, 0.87 and 0.82 for first, second and cumultative year, respectively. Moreover, correlation coefficients of plant coefficient was 0.95, 0.62 and 0.86, respectively. It is concluded that remote sensing method can be useful to estimate evapotranspiration of olive tree.

Despite the importance of evapotranspiration in the planning and management of water resources, its dependence on climatic factors on the one hand and influence of each of these components on the other hand has made it difficult to estimate evapotranspiration. Therefore, in this study, attempts to explore the possibility of predicting these important component in Sistan and Baluchestan using meta-heuristic models such as neuro-fuzzy inference system, GEP and SVM. In this regard, according to the FAO Penman-Monteith equation, the monthly potential evapotranspiration in four synoptic stations- Zahedan, Zabol, Iranshahr, and Chabahar- was calculated using the monthly weather data. These values as a reference to compare the results of the Neuro-fuzzy inference models, genetic programming, and SVM methods were studied. The five models applied in this study were: Model 1 includes input of average air temperature, shiny hours and relative humidity in the same month. Model 2 includes average air temperature, relative humidity, and wind speed in the same month. Model 3 includes average air temperature, relative humidity, and wind speed in the same month. Model 4 includes average air temperature, relative humidity, wind speed, and average shiny hours in the same month, and model 5 includes average air temperature, relative humidity, wind speed, and shiny hours in the same month and the earlier month. The results of different models were compared based on the statistical coefficient of determination and root mean square error. These findings show that in the neuro-fuzzy model, the models 2 (r2=0.945), 3 (r2=0.982 (, 4 (r2=0.26), and 5 (r2=0.423), respectively in Zahedan, Zabul and Chabahar, and Iranshahr Chabahar stations own greater accuracy. Analysis of results in the gene- expression planning model also indicates that in the test section, the model no.4, with the coefficients of 0.974, 0.9811, 0.982, and 0.815, respectively for the stations of Zahedan, Zabol, Iranshahr, and Chabahar, has higher accuracy. Likewise, in the SVM model, due to the coefficients of determination, 0.997, 0.998, 0.998, and 0.979, respectively in the stations of Zahedan, Zabol, Iranshahr, and Chabahar, the model 5 had the highest accuracy. Comparison of 3 models in this study also showed that in all stations, the Support Vector Machine, the programming model of gene expression, and the neuro-fuzzy model were paced in the first, the second, and the third levels of importance for estimating the monthly potential evapotranspiration.

Drought as a complex event that caused by the occurrence of one or more of the dry period, hasthe adverse effects of economic, social and environmental in a short period of time. Investigation of the drought spatial variability using appropriate indicators can help to the correct management of drought. In this study, using data obtained from the drought indicators of short-term (3-months) SPI, ZSI and PNI, drought severity zoning map was obtained using the geostatistical methods in GIS software for West Azerbaijan Province. The results showed that among the geostatistical interpolation and definitive methods, the method of inverse distance weighting (IDW) with 2 power for ZSI and SPI index has the lowest error of RMSE, MAPE and MBE compared to other interpolation methods. The least estimated amount of RMSE for each indicator was calculated respectively 0.22, 0.3 and 0.36. The zoning maps showed that the south and southwest of West Azerbaijan Province have less drought due to the focus of forests and the good rainfall in these areas whereas was observed more drought in the north and northeast of province than other regions in West Azerbaijan Province. According to SPI index, 48.12 % of the province consist of the severe drought and 32.25 % has normal drought conditions.

Optimum utilization of water resources in the country requires improving the accuracy of forecasting and estimation time of drought. One of the most important issues in monitoring and predicting drought is choosing an appropriate index for the area. In the present study, besides determining two indices of SPI and CZI in two scales of short-term and medium-term using the precipitation of two rain gauge stations in a period of 43 years (1972-2015) located in Abiyek City, the drought forecasting was performed using the Direct Multi-Step Neural Network in six time ahead. The Kappa- Cohen statistic used in order to review the consistency of quality classes between the predicted and observed values. The results of using this network in this study indicated an acceptable performance and capability of this network to estimate the drought using the two scales of SPI and CZI and predict some earlier steps of weather drought. Based on results of the weighted Kappa statistic showed that with increasing the prediction step, the similarity between the prediction amounts and the observed amounts in quality classes of drought decrease in two indices of SPI and CZI. So, by increasing the time scales (from 3 to 9 month), the similarity increases. The results of the prediction with the two mentioned indices and in different scales showed that Ziaran station seems more appropriate because it is located in the center of the area. Therefore, choosing an appropriate station in prediction issues helps improve the models significantly. Finally, this research can be useful in predicting the time of drought at least for the next six months, and help water planning and water resources managers in macro level in the country.