Showing 1096 results for Ro
N. Azadi, F. Raiesi,
Volume 26, Issue 1 (5-2022)
Abstract
Biochar as an efficient strategy for the improvement of soil properties and organic waste management may reduce the potential effects of abiotic stresses and increase soil fertility. However, the effects of this organic amendment on soil microbial indicators under combined salinity and pollution have not been studied yet. Therefore, the objective of this study was to evaluate the influence of sugarcane bagasse biochar on some soil bioindicators in a Cd-polluted soil under saline and non-saline conditions. A factorial experiment was carried out with two factors, including NaCl salinity (control, 20 and 40 mM NaCl) and sugarcane bagasse biochar (soils unamended with biochar, amended with uncharred bagasse, 400 oC biochar, and 600 oC) at 1% (w/w) using a completely randomized design. Results showed that salinity increased the mobility of Cd (12-17%), and subsequently augmented its toxicity to soil microorganisms as indicated by significant decreases in the abundance and activities of the soil microbial community. Conversely, sugarcane bagasse biochar application reduced the concentration of soil available Cd (14-18%), increased the contents of soil organic carbon (89-127%), and dissolved organic carbon (4-70%), and consequently alleviated the effect of both abiotic stresses on soil microbial community and enzyme activity. In conclusion, this experiment demonstrated that the application of sugarcane bagasse biochar could reduce the salinity-induced increases in available Cd and mitigate the interaction between salinity and Cd pollution on the measured soil bioindicators.
S. Azadi, H. Nozari, S. Marofi, Dr. B. Ghanbarian,
Volume 26, Issue 1 (5-2022)
Abstract
In the present study, a model was developed using a system dynamics approach to simulate and optimize the profitability of crops of the Jofeyr (Isargaran) Irrigation and Drainage Network located in Khuzestan Province. To validate the results, the statistical indicators of root mean square error (RMSE), standard error (SE), mean biased error (MBE), and determination coefficient (R2) were used. To validate the simulation results of the benefit-cost ratio, the values of these indicators were obtained 0.25, 0.19, 0.005, and 0.96, respectively. Then, to determine the optimal cultivated area of the network and increase the profitability, the cropping pattern was determined both non-stepwise and stepwise in 2013 to 2017 cropping years. In the non-stepwise, the cultivated area of each crop changed from zero to 2 times of current situation. In stepwise, due to social and cultural conditions of inhabitants, this change was slow and 10% of the current situation every year. The analysis of the results showed the success of the model in optimizing and achieving the desired goals and the total benefit-cost ratio increased in all years both non-stepwise and stepwise. For example, in 2017 compared to 2016, production costs decreased by 7.1 percent and sales prices increased by 5.8 percent, and increased the benefit-cost in 2017 compared to the previous year. The results showed that the present model has good accuracy in simulating and optimizing the irrigation network, its cropping pattern, and defining other scenarios.
A. Ghobadi, M. Cheraghi, S. Sobhan Ardakani, B. Lorestani, H. Merrikhpour,
Volume 26, Issue 1 (5-2022)
Abstract
The qualitative assessment of groundwater resources as the most important sources of drinking and agricultural water is very important. Therefore, the present study was conducted to evaluate the quality of heavy metals in groundwater resources of the Hamadan-Bahar plain in 2018 using water quality indices. In so doing, a total of 120 groundwater samples were collected from 20 stations during the spring and summer seasons and the values of physico-chemical parameters were determined based on the standard methods and also the content of heavy metals was determined using inductively coupled plasma spectroscopy (ICP). The results showed that the mean concentrations of As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, and Zn (µg /L) in the samples in the spring season were 5.08, 0.260, 1.05, 2.70, 1.50, 0.490, 1.50, 7.48, and 1.75, respectively, and in the summer season were 20.7, 0.220, 0.950, 7.12, 1.34, 0.490, 1.29, 8.23, and 2.08, respectively and except for As in the summer season, the mean content of other elements was lower than maximum permissible limits established by WHO for drinking water. Meanwhile, the mean values of Cd, HPI, HEI, MI, and PoS indices in the spring season with -7.51, 9.91, 1.42, 1.42, and 328, respectively, indicate the water quality was categorized as low, low, low, low and moderately affected and in the summer season with -5.90, 10.0, 3.04, 3.04, and 673, respectively, were categorized as low, low, low, moderately affected, and high pollution. Due to the extensive use of agricultural inputs, especially chemical and organic fertilizers and chemical pesticides containing heavy metals by farmers in the study area, the possibility of increasing the concentration of heavy metals in the soil and their penetration into groundwater aquifers will not be unexpected in the medium term. Therefore, periodic monitoring in groundwater resources of the study area is recommended.
A. Safadoust, S. Ghanizadeh, M. Nael,
Volume 26, Issue 1 (5-2022)
Abstract
This study was conducted to investigate the effects of vegetation type (Alfalfa and Wheat) and slope (5% and 20%) on runoff and drainage pollution in clay loam soil. Sampled soils were repacked in the box with one soil drainage outlet and one surface flow outlet and were cultivated by wheat or alfalfa. A solution containing 0.05 M KCl was poured quickly and uniformly, over the surface of each box, after plant growth. Simulated rainfall was applied to the soil box with the intensity of a constant rate of 64 mm h-1 for 2 hours immediately. Then the concentration of Cl- and K+ were measured in the collected samples of runoff and the drainage outlet. Results showed that the measured concentration of K+ was lower than the Cl- concentration as a result of its absorbable property. The breakthrough curves (BTCs) of Cl- and K+ showed that slope and vegetation type affected the transport of Cl- and K+. The peak of the BTCs for Cl- and K+ in runoff ranked in the order of wheat and 20% slope> alfalfa and 20% slope> wheat and 5% slope> alfalfa and 5% slope, and in the drainage changed to alfalfa and 5% slope> wheat and 5% slope> alfalfa and 20% slope> wheat and 20% slope. For each slope, the intensive vegetation cover of alfalfa than wheat considerably reduces Cl- or K+ pollution in runoff; whereas drainage development of larger and deeper root systems was the cause of higher leached concentrations for both tracers. Based on our research changes in soil surface vegetation cover from wheat to alfalfa are suggested in slope land to prevent surface water pollution; although other factors such as the climate, soil texture, and structure should also be considered.
M. Masoomi, M. Pourgholam-Amiji, M. Parsinejad,
Volume 26, Issue 1 (5-2022)
Abstract
In this study, the Drainmod-S model was used to vary soil salt concentration and the effect of underground drainage on the amount of leaching in a physical model (large lysimeter). A soil extractor was installed at depths of 40, 50, and 70 cm at a distance of 35 cm from the drainage to measure the salinity of the soil solution. In this study, three scenarios were applied including salinity profiles under conventional conditions (mid-season and end-season drainage), soil salinity profiles under different drainage conditions, and prior scenarios with saline irrigation. The second and third scenarios were applied in four drainage stages, respectively. These stages include transplanting and mid-season drainage (days 15 to 20), mid-season drainage (days 35 to 40), mid-season and end-season drainage (days 55 to 60), and end-season drainage (days 75 to 80). The results showed that after simulating the total solute concentration overtime at a depth of 40 cm and comparing it with the measured values, the coefficient of determination (R2) was 0.77 indicating an acceptable Drainmod-S model simulation. This parameter for simulating solute concentration at 50 and 70 cm depth was 0.76 and 0.75, respectively. The mean absolute error parameter (MAE) value was also negligible.
B. Moravejalahkami, M.h. Rahimian,
Volume 26, Issue 1 (5-2022)
Abstract
The current research was performed to present a quick and proper method for basin irrigation infiltration equation estimation by optimization of the Manning roughness coefficient. A two-level optimization of the Manning roughness coefficient method was presented by developing a zimod simulation model and initial intake families method, USDA-NRCS, (infiltration equation based on soil characteristics), and modified intake families (infiltration equation based on soil characteristics and inflow discharge). The investigation of the results of the model based on observed advance, recession, and surface storage showed the relative error of surface storage volume estimation was decreased by 38 to 50 % by adjusting the initial intake families method. The normalized root mean square error (NRMSE) of the advance estimation was between 0.22 to 0.85 for initial intake families and this parameter was between 0.09 to 0.5 for modified intake families. NRMSE of the recession estimation was between 0.13 to 0.75 for initial intake families and this parameter was between 0.09 to 0.19 for modified intake families. The presented method based on modified intake families increases the accuracy of infiltration estimation as compared to the initial intake families method and can evaluate basin irrigation acceptably. In addition, this method needs less time for basin irrigation evaluation as compared to the complete methods of optimization of infiltration parameters and roughness coefficient.
F. Khafi, A.r. Hossienpour, H. Motaghian,
Volume 26, Issue 2 (9-2022)
Abstract
One of the significant factors affecting biochar properties is the pyrolysis temperature. This study aimed to investigate the effect of pyrolysis temperature on the properties and fractionation of Zn and Pb in biochars produced by sewage sludge. Biochars were prepared at temperatures of 300 to 700 °C and the physicochemical properties, availability, and fractionation of Zn and Pb were investigated. The results showed that pH, pHzpc, percentage of calcium carbonate, cation exchange capacity, specific surface area, and porosity in biochars were higher than in the feedstock. By increasing biochar production temperature, the mentioned properties increased. FT-IR revealed that the OH functional group is present in free form, either in the structure of C-OH and -COOH and aliphatic-CH2 groups in the sewage sludge. By converting sewage sludge to biochar, the intensity of these peaks decreased. In contrast, peaks representing complex aromatic structures appeared. The availability of Zn and Pb in biochar was reduced as compared to sewage sludge. The results of fractionation indicated that sewage sludge has bio-availability and toxicity of Pb and Zn. the amount of oxide and residual fractions of these two metals increased by converting sewage sludge to biochar at different temperatures. Therefore, it seems that biochar production from sewage sludge reduces the toxicity and bio-availability of Zn and Pb. Also, by incrementing the temperature of production, the bio-availability potential (bonding with organic matter), and non-toxicity (residual) of these metals increased.
N. Salamati, H. Dehghanisanij, L. Behbahani,
Volume 26, Issue 2 (9-2022)
Abstract
Increasing crop production per unit volume of water consumption requires recognizing the most dependent variable in drip irrigation to the volume of water consumption and also identifying the most important variables independent of water productivity in surface and subsurface drip irrigation for optimal use of available water resources. The present research was carried out in Behbahan Agricultural Research Station during four cropping seasons (2013-2017) on a Kabkab date variety. Experimental treatments include the amount of water in the subsurface drip irrigation method based on two levels of 75% and 100% water requirement and in surface drip irrigation based on 100% water demand. Data were analyzed using a randomized complete block design with three replications. The results of the analysis of variance of the mean of different irrigation treatments in quantitative traits showed that the effect of irrigation was significant at the level of 1% in terms of cluster weight index, fruit weight, and fruit flesh to kernel weight ratio. The results of regression analysis of variance showed that in the dependent variable of cluster weight, the consumption water volume explained 19.1% (R2 = 0.191) of the fluctuations of the dependent variable (cluster weight). Among all the studied variables, the volume of water consumption explained the most significant changes in date cluster drying. Fruit moisture with t (2.096) and equivalent beta coefficient (0.046) had a significant positive effect on water productivity at the level of 5%. The results of the Pearson correlation coefficient showed that the effect of yield on changes in water productivity was much greater than the volume of water consumed so the yield caused significant changes in water productivity. While the effect of water consumption on water productivity was not significant.
F. Zarif, A. Asareh, M. Asadiloor, H. Fathian, D. Khodadadi Dehkordi,
Volume 26, Issue 2 (9-2022)
Abstract
An accurate and reliable prediction of groundwater level in a region is very important for sustainable use and management of water resources. In this study, the generalized feedforward (GFF) and radial basis function (RBF) of artificial neural networks (ANNs) have been evaluated for monthly predicting groundwater levels in the Dezful-Andimeshk plain in southwestern Iran. The partial mutual information (PMI) algorithm was used to determine efficient input variables in ANNs. The results of using the PMI algorithm showed that efficient input variables for monthly predicting groundwater level for piezometers affected by water discharge and recharge include only water level in the current month. Also, efficient input variables for predicting the water level for piezometers affected only by water discharge include the water level in the current month, the water level in the previous month, the water level in the previous two months, transverse coordinates of piezometers to UTM, the water level in the previous three months, the water level in the previous four months, the water level in the previous five months and longitudinal coordinates of piezometers to UTM. In addition, efficient input variables of monthly predicting groundwater level for piezometers neither affected by water discharge nor water recharge, respectively, include the water level in the current month, the water level in the previous month, the water level in the previous two months, the water level in the previous three months, the water level in the previous four months, the water level in the previous five months, the water level in the previous six months, transverse coordinates of piezometer to UTM and longitudinal coordinates of piezometer to UTM. The results indicated that the GFF network is more accurate than the RBF network for monthly predicting groundwater level for piezometers including water discharge and recharge and piezometers including only water discharge. Also, the RBF network is more accurate for monthly predicting groundwater levels for piezometers that include neither water discharge nor recharge than the GFF network.
M.h. Sadeghi Ravesh,
Volume 26, Issue 2 (9-2022)
Abstract
The optimal strategy selection is an influential factor to enhance the efficiency of land reclamation projects. On the other hand, the process of desertification of the land during environmental degradation is the consequence of the interaction between various factors that make it challenging to select appropriate solutions. Therefore, this study aimed to provide systematic optimization strategies in the form of a group decision-making model in the Yazd-Khezrabad plain. The important strategies were identified using the Delphi model. Then, the alternative initial ranking was formed by Cook and Seiford method framework using the vote taken from the decision makers on strategies. Finally, by estimating the linear distance of each option and including the matrix of the intervals, the last priority of the strategies was obtained from solving the assignment problem. The results indicated that the strategies of "prevent land use inappropriate change" (A18) and "the regeneration of vegetation cover" (A23) with Value=1 and Reduced Cost=0, were identified as the most important combating-desertification strategies in the region, respectively. The results of this study help desert managers to utilize limited facilities and capital dedicated to controlling the desertification process efficiently and effectively.
Z. Kolivand, A.r. Pardakhti,
Volume 26, Issue 2 (9-2022)
Abstract
In the past years, by increasing population and water consumption, as well as the high cost of developing surface water resources, the exploitation of groundwater resources has increased significantly. In the current situation, a significant part of the country's water consumption in all sectors of consumption is provided by groundwater sources. On the other hand, the development of industry and the entry of pollutants, including heavy metals, into the groundwater endanger the health of humans. The present research has investigated the non-cancerous risk caused by heavy metals in the groundwater of Urmia plain for both children and adults. This research is based on a descriptive-analytical method based on the available data, in which the concentration of polluting metals obtained from the studies conducted in the fall and winter of 2016 from the number of 12 wells supplying rural drinking water in the Urmia plain has been analyzed. Also, human health risk assessment was measured using the United States Environmental Protection Agency index. The results showed that there are six heavy metals including cadmium, copper, iron, manganese, nickel, and lead in the region's groundwater, among which two of the wells have cadmium and lead values higher than national and international standards. Also, the total non-cancer risk index through ingestion and skin absorption for both children and adults groups was found to be 0.23 and 0.096, respectively, which is less than one, and this indicates that the water quality of the region is suitable for drinking.
M. Seifollahi, S. Abbasi, M.a. Lotfollahi-Yaghin, R. Daneshfaraz, F. Kalateh, M. Fahimi-Farzam,
Volume 26, Issue 2 (9-2022)
Abstract
Unpredictable settlement of earth dams has led researchers to develop new methods such as artificial neural networks, wavelet theory, fuzzy logic, and a combination of them. These methods do not require time-consuming analyses for estimation. In this research, the amount of settlement in rockfill dams with a central core has been estimated using artificial intelligence methods. The data of 35 rockfill dams with a central core were used to train and validate the models. The artificial neural network, wavelet transform model, and fuzzy-neural adaptive inference system are the proposed models which were used in the present study. According to the results, the best model for an artificial neural network had two hidden layers, the first layer of 18 neurons and the second layer of 7 neurons, with the Tansig-Tansig activation function, with a coefficient of determination R2=0.4969. The best model for the fuzzy-neural inference system had the ring function (Dsigmoid) as a membership function, with three membership functions and 142 repetitions with a coefficient of determination R2=0.2860. Also, combining wavelet-neural network conversion with the coif2 wavelet function due to the more adaptation this function has to the input variables, the better the performance, and this function, with a coefficient of determination R2=0.9447, had the highest accuracy compared to other models.
M. Zareian,
Volume 26, Issue 2 (9-2022)
Abstract
This study was conducted to investigate the effects of climate change on temperature and precipitation changes in important synoptic weather stations in Yazd province (including Yazd, Bafgh, Marvast, and Robat-e-Poshtebadam). Accordingly, a combination of the outputs of the latest AOGCM models presented in the IPCC sixth assessment report (CMIP6) were used to increase the accuracy of temperature and precipitation forecasts. A weighting method was used based on the Kling-Gupta combined index (KGE) to combine these models. After weighting the models, the monthly temperature and precipitation changes were calculated based on SSP126, SSP245, and SSP585 emission scenarios. Then, daily temperature and precipitation time series were extracted for different weather stations using the LARS-WG downscaling model. The results showed that in all the weather stations, CanESM5 and BCC-CSM2-MR models have the best ability to simulate the temperature and precipitation of the historical period, respectively. Results also showed that in all emission scenarios, the annual temperature will increase and the annual precipitation will decrease. The annual temperature of this region will increase between 0.2 to 0.6 °C, and the annual precipitation will decrease between 2.9 and 13.7% in different weather stations. Also, the maximum temperature increase and precipitation decrease in this region, will occur in spring and autumn, respectively.
F. Daechini, M. Vafakhah, V. Moosavi, M. Zabihi Silabi,
Volume 26, Issue 2 (9-2022)
Abstract
Surface runoff is one of the most significant components of the water cycle, which increases soil erosion and sediment transportation in rivers and decreases the water quality of rivers. Therefore, accurate prediction of hydrological response of watersheds is one of the important steps in regional planning and management plans. In this regard, the rainfall-runoff modeling helps hydrological researchers, especially in water engineering sciences. The present study was conducted to analyze the rainfall-runoff simulation in the Gorganrood watershed located in northeastern Iran using AWBM, Sacramento, SimHyd, SMAR, and Tank models. Daily rainfall, daily evapotranspiration, and daily runoff of seven hydrometric stations in the period of 1970-2010 and 2011-2015 were used for calibration and validation, respectively. The automated calibration process was performed using genetic evolutionary search algorithms and SCE-UA methods, using Nash Sutcliffe Efficiency (NSE) and root mean of square error (RMSE) evaluation criteria. The results indicated that the SimHyd model with NSE of 0.66, TANK model using Genetic Algorithm and SCE-UA methods with NSE of 0.67 and 0.66, and Sacramento model using genetic algorithm and SCE-UA methods with NSE of 0.52 and 0.55 have the best performance in the validation period.
S. Dehghan Farsi, R. Jafari, A.r. Mousavi,
Volume 26, Issue 2 (9-2022)
Abstract
The objective of the present study was to investigate the performance of some of the extracted information for mapping land degradation using remote sensing and field data in Fras province. Maps of vegetation cover, net primary production, land use, surface slope, water erosion, and surface runoff indicators were extracted from MOD13A3, MOD17A3, Landsat TM, SRTM, ICONA model, and SCS model, respectively. The rain use efficiency index was obtained from the net primary production and rainfall map, which was calculated from meteorological stations. The final land degradation map was prepared by integrating all the mentioned indicators using the weighted overlay method. According to the ICONA model, 5.1, 9, 47.21, 27.91, and 10.73 percent of the study area were classified as very low, low, moderate, severe, and very severe water erosion; respectively. Overlaying the ICONA map with other indicators showed that very high and high classes, moderate, and low and very low classes of land degradation covered 1.3, 18.7, 70, 0.9, and 9.1 percent of the study area, respectively. According to the results, integrating remote sensing with ICONA and SCS models increases the ability to identify land degradation.
J. Abedi Koupaei, M.m. Dorafshan, A.r. Gohari,
Volume 26, Issue 3 (12-2022)
Abstract
One of the most significant techniques for saline wastewater treatment is bioremediation. Halophytes are known as the plants that can tolerate the high concentration of salts, in such salinity common plants cannot be often able to survive. In this research, the feasibility of desalination by using halophyte (Chenopodium quinoa Willd.) was studied. Quinoa plants were grown in the hydroponic system in 12 containers including 9 containers with plants and 3 containers without plants as control. Fifteen plants were planted in each container and three salinity levels including 2, 8, and 14 ds/m for two different periods (15 and 30 days) were studied in a multi-factors completely randomized design. Three replications of each salinity level were conducted and the Electrical Conductivity (EC) parameters, including Calcium, Magnesium, Sodium, and Chloride ions were determined before and after treatment by Quinoa plants. The results showed that the Quinoa plants reduced 5.33%, 8.12%, and 9.35% of the EC at EC~2 dS/m (Marginal Water), EC~8 dS/m (Brackish Water), and EC~14 dS/m (Saline Water), respectively. Moreover, Calcium, Magnesium, Sodium, and Chloride ions decreased up to 10%, 7.62%, 5.60%, and 7.01%, respectively depending on the salinity levels. Therefore, the Quinoa plant has a relatively low potential in unconventional water treatment especially saline wastewater.
P. Fattah, Kh. Hosseini, A.a. Hashemi,
Volume 26, Issue 3 (12-2022)
Abstract
Splash (raindrop) erosion plays an significant role in soil loss, especially in arid and semi-arid regions with poor vegetation. In this paper, by analyzing the pattern of rainfalls that occurred during 26 years in four basins located in Semnan County, their effect on the pattern of eroded sediments from the basin was investigated. Sedimentary layers from the sampling of retarding reservoir sediments in 2017 were related to the corresponding precipitations. Due to the occurrence of the highest amount of rainfall in each quarter of rainfall, rainfall hyetographs were divided into four categories. Cumulative precipitation curves with similar quartiles were drawn in one shape and compared with sediment curves and vice versa taking into account the physical characteristics of the basin. The results showed that the Aliabad basin (with less slope and more elongation) with an effective quarter of type 3 had the highest similarity in precipitation and sediment patterns. Also, the Western Soldereh basin (with the highest slope and the least elongation) with an effective quarter of type 2 had the least similarity in precipitation and sediment patterns. The results indicate the vital role of rainfall patterns on the resulting sediment patterns, which show up to 85% similarity.
M.r. Bahadori, F. Razzaghi, A.r. Sepaskhah,
Volume 26, Issue 3 (12-2022)
Abstract
Inefficient use of limited water resources, along with increasing population and increasing water demand for food production has severely threatened agricultural water resources. One way to overcome this problem is to improve water productivity by introducing new crops that tolerate water stresses such as quinoa. In this study, the effect of water stress at different stages of plant growth (vegetative, flowering, and grain filling) was studied on plant parameters, yield, and water productivity of quinoa (cv. Titicaca). This study was conducted under field conditions and the treatments were performed as a block experiment in a completely randomized design with four replications. Experimental factors were: treatment without water stress or full irrigation (F) and water stress treatment (D) at 50% of the need for full irrigation at different stages of quinoa growth. The application of deficit irrigation during different stages of plant growth decreased stomatal conductance, leaf area index, leaf water potential, seed yield, and water productivity, while deficit irrigation increased the green canopy temperature. According to the results of the present study, the flowering stage of quinoa was very sensitive to water stress leading to produce lower yield compared with the amount of yield obtained when vegetative and or grain filling stages are under water stress conditions.
F. Naeimi Hoshmand, F. Ahmadzadeh Kaleybar,
Volume 26, Issue 3 (12-2022)
Abstract
Hydrological models for evaluating and predicting the amount of available water in basins, flood frequency analysis, and developing strategies to deal with destructive floods are expanding daily. In this study, HEC-GeoHMS and Arc Hydro extensions in ArcGIS software and the HEC-HMS model were used to simulate design flood hydrographs in the Aydooghmush basin in the northwest of Iran. SCS-CN, SCS-UH, Maskingham, and monthly fixed methods were used to calculate rainfall losses, rainfall-runoff transformation, flood routing, and base flow, respectively. In model calibration with two real flood events, the average of absolute values of the residuals, the sum of the remaining squares, and the weight of the peak mean the error squares for the flood volume were 2.75, 5.91, and 5.32, respectively and for peak discharge were 8.9, 8.0, and 8.0, respectively. Model validation was evaluated as acceptable with a one percent error rate in the peak of discharge and a 19 percent in the flood volume. For maximum 24-hour precipitation, the log-Pearson type 3 was determined as the most suitable distribution in the SMADA model and design precipitation was extracted in different return periods. Thus, for the return period of 2 to 1000 years, the peak discharge and volume of the design flood were simulated equally to 18.8 to 415.6 m3 s-1 and 5.7 to 87.9 MCM, respectively.
M. Sadeghi, T.o. Naeeni, F. Kilanehei, M. Galoie,
Volume 26, Issue 3 (12-2022)
Abstract
One of the most important hydraulic structures in a dam is the spillway. The design of the ogee spillway crest is based on the lower profile of the free-flow jet passing through the sharp-crested weir. When the downstream ogee spillway profile for the design discharge conforms to the lower profile of the free-jet passing through the sharp-crested weir, the pressure on that surface of the spillway becomes zero. In this study, the design of the ogee spillway was performed initially based on both two- and three-dimensional numerical modeling and then compared to the USBR standard method. The comparison of the final numerical and analytical results showed that although the vertical two-dimensional outputs were completely in agreement with the USBR standard profile, the three-dimensional profiles were different because in this model, guide walls were not considered. According to the analysis, if the flow entering the spillway is parallel to its axis, the lower profile of the sharp-edge spillway will be in complete agreement with the standard profile. Since, the design of guide wall geometry for ogee spillways is carried out using physical modeling which iteratively revises during a high-cost trial and error procedure, this research based on the case study of the spillway of Karun-3 dam has been tried using numerical modeling. The closest geometry to the geometry of the overflow guide wall was obtained which creates the least difference in transverse velocities. In this way, the design of guide walls can be done with more accuracy and low cost in comparison to physical modeling.
