Showing 26 results for Optimization
K. Asghari, J. Sourinejhad, A. K. Zolanvar,
Volume 9, Issue 3 (10-2005)
Abstract
In this study, the simulation of the BORKHAR plain aquifer located in north-east of Isfahan was done for the estimation of the hydrodynamic coefficients and for the preparation of the prediction and management model with the purpose of the study of the water table surface situation in the next years. The study of the geological situation of the plain and the report of the drilling of its exiting wells indicated that the BORKHAR plain has two kinds of aquifer: confined and unconfined. According to the field data related to the unconfined aquifer, a part of this aquifer was selected for the mathematical simulation. The calibration model for the estimation of the K and Sy. coefficients was done by dividing the plain into four geohydrologic units and by using the PEST, a module of the MODFLOW model. The situation of the water table level during 1380-1390 was studied according to the different management options by the calibration model. If the trend of the exploitation doesn’t change during the next ten years, we will confront with a maximum drop of 48 meters. As a practical way for preventing from this drop, it was suggested that the exploitation management reduce the 30 percent of the demand. One of the most important result of this will be the 26 percent reduction of the drop. By developing an optimization model and by imposing the necessary constraints on the critical regions, and transferring water from other parts, it seems that the trend of the drop will be controllable at a admissible level (less than 10 meters until 1390). Using the optimization model will make a change in the increasing trend of the drop and an improvement in the situation of the aquifer.
Kh. Jalili, S. H. R. Sadeghi, D. Nikkami,
Volume 10, Issue 4 (1-2007)
Abstract
Improper management of watershed land utilization has many ill effects on the available resources. Land use optimization is one of the proper strategies to achieve sustainable development and to reduce resource dissipation. Focusing on Brimvand watershed in Kermanshah province which comprises an area of 9572 ha, the present study was conducted to find out the most suitable land allocation to different land uses viz. garden, irrigated farming, dry farming and rangeland to achieve soil erosion minimization and benefit maximization. The soil erosion, net benefit and standard land capability maps were supposed as the inputs of the objective functions and to defined constraints. The multi-objective linear problem was then solved using simplex method with the help of ADBASE software package and ultimately the optimal solution was gained. Additionally, the results of the study revealed that the amount of soil erosion could reduce by 7.78% whereas the benefit increases at the rate of 118.62%, in case of implementation of optimal solution. The above mentioned optimization led to dry farming decrease and garden increase over that area. The results of sensitivity analysis also showed that objective functions were strongly susceptible to the variation of maximum constraint of irrigated farming and garden areas.
A. Azizian, A. R. Sepaskhah, A.r. Tavakoli, M. Zibaee,
Volume 10, Issue 4 (1-2007)
Abstract
Irrigation water Scarcity is the major limiting factor for crop production in irrigated farming. Therefore, optimal use of water is influenced by seasonal rainfall especially where the water price is high. Nitrogen also plays a key role in plant nutrition. In this study, wheat grain yield production as a function of applied water (irrigation plus seasonal rainfall) and nitrogen fertilizer (applied plus soil residual nitrogen) using existing data of a field experiment, were used. This function was obtained based on the data from the Maraghah Agricultural Experiment station. Based on this production function, maximum attainable yield can be 8.12 t/ha obtained by the consumption of 1.56 m of water (irrigation plus rainfall) and 193 kg/ha of nitrogen. An economic analysis based on the Iso-Quant curve was conducted to optimize the application rates of production inputs (water and nitrogen). When land is limited, the optimum water and nitrogen use will be based on maximizing net returns from land unit area. The optimal levels of these inputs were determined on the basis of farmer ability for paying the costs of water and nitrogen. Furthermore, optimum amounts of water and nitrogen were determined for different levels of wheat yield. The results indicated that despite low price of irrigation water and nitrogen fertilizer, at present market value, optimum values of water were more variable than those of nitrogen, for its high effective role in wheat production. The results also indicated that when there is no limitation of the source and use of water and nitrogen, and farmers are also able to pay their costs, application of 1.47 m of water (irrigation plus rainfall) and 190 kg/ha of nitrogen (applied plus soil residual) will produce maximum profit per hectare, reaching Rls 12,207,506. When water is limited, optimum levels of water and nitrogen will be based on the maximizing profit per unit of water. In this analysis, the use of 0.556 m of water (irrigation plus rainfall) and 190 kg/ha of nitrogen (applied plus soil residual) resulted in maximum net income per unit of applied water (irrigation plus rainfall) amounting to Rls/m3 1203. This amount of water use, which is 64.4 % lower than its amount under maximum yield condition, resulted in 181 % increase of cultivated area. Graphic expansion path on the isolines of yield showed more dependence of wheat production on water than nitrogen. Therefore, the optimum amounts of nitrogen in the three mentioned conditions are close to each other due to its subsidized price and lower effect on wheat production relative to water.
J. Torkamani, M. Sabohi,
Volume 11, Issue 1 (4-2007)
Abstract
The endogenous selection and determination of return reference level is important in specifying risk efficient set. Thus, using multi-objective programming, Target–MOTAD in the framework of Mean-PAD and maximin parametric analysis models was established to obtained reference level of return endogenously. To determine non–inferior set for the farmers understudy, at first, the pay-off matrix was obtained through maximizing objectives under consideration. Then, upper and lower bounds of non-inferior set were determined using non- inferior set estimation (NISE) technique. The results obtained from maximin model indicated that Min and Max of maximin model were 270252 and 217753 thousands Rials, respectively. Furthermore, a subset of non-inferior set was obtained using different return reference levels. Comparing the results of model and the current farmers' plan showed that the current acreage of crops, except for sugar beet was approximately placed in the range determined by the model. In addition, the results also indicated that farmers' plan could be a non- inferior set. Considering the importance and also scarcity of water in the study area, average water return in the farmers' plan was compared to non-inferior set which included all the upper and lower non-inferior set. The results showed that farmers obtained 18150 Rials per hours of used water. However, average water return changed the range of 19100 to 30200 Rials for non-inferior set, indicating that farmers are able to use water more efficiently. The results also showed that changing farmers' cropping pattern is a complicated task and that it is necessary to have a systematic view in ordere to achieve desirable change.
S.a. Mohseni Movahed, M.j. Monem,
Volume 11, Issue 40 (7-2007)
Abstract
Poor performance of irrigation canals and its effect on decreasing of Agricultural water productivity require attention for their improvement. In this paper a new mathematical model is introduced which could present optimal operation considering downstream requirements of turnouts, canal inlet flow, actual constraints and real conditions of canal system. Four performance indicators of delivery including efficiency, adequacy, equity and stability are considered as an objective function in the process of optimization. Since this objective function is an implicit function of decision variables (regulation of turnouts and control structures) and hydraulic parameters, it is necessary to implement hydrodynamic model, using numerical optimization methods. SA (Simulated Annealing) technique is a numerical
meta – heuristic intelligent search method which is used in combination with a hydrodynamic model (ICSS) (Irrigation Conveyance System Simulation.) for performance optimization of canal system. Theoretically it is proven that SA technique is capable of tending towards global optimum solution asymtotically. Taking short random steps in SA algorithm guarantees avoiding instability in hydrodynamic model. The developed model has been applied on E1R1 Distributary canal of Dez irrigation network for ten days. The results indicated that optimal performance improved very well in comparison with the present situation.In this model the weighting coefficients of indicators are determined using sensitivity analysis in optimization process. Consistency test on the derived coefficients shows that proposed method is appropriate. Applying weighting coefficients for performance indicators in the processes of optimization has resulted in 7 to 21 percent improvement compared to the case of equall weighting coefficients. Also, the results indicate that the developed model (ICSS-DOM) (ICSS-Delivery Optimization Model) is an efficient tool for the evaluation and optimization of irrigation canal performance, producing good and valid results in a relatively short and suitable time.
E. Valizadegan, M. Shafai Bejestan, H. Mohammad Vali Samani,
Volume 15, Issue 55 (4-2011)
Abstract
Reservoir sedimentation is an unavoidable problem which has unsuitable effects on reservoirs such as decreasing of reservoir useful volume, decreasing of dam stability, unsuitable operation of operational gates and penstocks and decreasing of flood control volume. The minimization of reservoir sedimentation is a nonlinear and constrained optimization problem. Constrains imposed include reservoir storage level and releases in each time, and reservoir storage level in the end of operational period. In this study, after calibration of GSTARS3 software, one of the newest mathematical model for simulation of river and reservoir sedimentation developed by USBR, for region of Voshmgir dam, results of running of software were converted as a part of data file to an optimization model by a mediator computer program. After running the optimization model, results were converted to GSTARS3 by another mediator computer program. Then, GSTARS3 was run again with new data file, obtained from running the optimization model. Results of running of GSTARS3 were converted to the optimization model again. The continuation of this process (loop) finished when the desired accuracy was obtained. In other words, the optimum condition was obtained when the running of this loop finished. The constrained optimization problem changed to unconstrained problem using penalty function method. The Powell method, a method of direct search methods, was used to solve this unconstrained optimization problem. Capabilities of the model were demonstrated through its application to the Voshmgir dam in Gorgan for a 12 month period to obtain the optimal operation policy for minimization of reservoir sedimentation.
S. Azizpour, P. Fathi, K. Nobakht-Vakili,
Volume 16, Issue 60 (7-2012)
Abstract
Soil saturated hydraulic conductivity (k) and effective porosity (f) are the most important parameters to simulate the processes associated with irrigation, drainage, hydrology, leaching and other agricultural and hydrological processes. Present methods to measure these parameters are often difficult, time consuming and costly. Therefore, a method which provides more accurate estimates of these parameters is essential and is considered inevitable. The purpose of this study was simultaneous estimation of k and f using approach inverse problem. In this study, analytical drainage model of Glover-Dam was used to simulate the inverse problem method. Also, genetic algorithm was used as an optimization technique for determination of optimal values of k and f. In order to measure the data required for calibration and evaluation of the proposed inverse problem model, a physical model was designed and constructed in the laboratory. The results showed that the proposed method is good for simultaneosly estimating simultaneous soil k and f. Also with variable f assumption, the prediction error of water table around the drainage was reduced significantly.
M. Navabian, M. Aghajani,
Volume 16, Issue 60 (7-2012)
Abstract
In Guilan province, Sefidrud River, as the main source of irrigating rice in Guilan province, has been subjected to increasing salinity and a decreasing discharge because of decreasing in the volume of sefidrud dam, diverting water upstream and entering different sewages into the river. This research tries to determine optimum irrigation depth and intermittent periods in proportion to salinity resistance at different growth stages using optimization- simulation model. After calibration, Agro-hydrological SWAP model was used to simulate different growth stages of rice. Optimization results were obtained for managing fresh and saline intermittent water, 8-day intermittent period, for salinity of 0.747 dS/m in sensitive maturity stage and salinity of 3.36 dS/m in resistant vegetative, tiller and harvest growth stages. It is suggested that the depth of irrigation water be 1, 3, 3 and 5 cm for vegetative, tiller, maturity and harvest stages, respectively. Comparing managements of irrigation and saline based on the resistance of different growth stages to salinity and exploitation of irrigating water with a constant salinity during growth periods of the plant showed that irrigation management based on resistance of different growth periods of the plant to salinity causes rice yield to be improved by 23percent.
D. Rajabi, H. Karami, Kh. Hosseini, S. F. Mousavi , S. A. Hashemi,
Volume 19, Issue 73 (11-2015)
Abstract
Non-linear Muskingum model is an efficient method for flood routing. However, the efficiency of this method is influenced by three applied parameters. Therefore, efficiency assessment of Imperialist Competition Algorithm (ICA) to evaluate optimum parameters of non-linear Muskingum model was addressed in this study. In addition to ICA, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) were also used to find an available criterion to verify ICA. In this regard, ICA was applied for Wilson flood routing then, routing of two flood events of DoAab Samsami River was investigated. In case of Wilson flood, the target function was considered as the sum of squared deviation (SSQ) of observed and calculated dischargem. Routing two other floods, in addition to SSQ, another target function was also considered as the sum of absolute deviations of observed and calculated discharge. For the first floodwater based on SSQ, GA indicated the best performance however, ICA was in the first place, based on SAD. For the second floodwater, based on both target functions, ICA indicated a better operation. According to the obtained results, it can be said that ICA could be recommended as an appropriate method to evaluate the parameters of Muskingum non-linear model.
S.a. Mohseni Movahed, M. Koochakzadeh, P. Salehimoghadam,
Volume 21, Issue 3 (11-2017)
Abstract
Basin irrigation is one of the conventional surface irrigation methods used to irrigate many crops all over the world. EDOBASIN, a new mathematical model for evaluation, design and optimal operation of basin irrigation has been introduced in this paper. In this model the linear combination of desired efficiencies are considered in an objective function, and based on decision variables that include discharge, length and width of basin and also restrictions of parameters, the optimal design is performed. This model is a simulation-optimization model in which the volume balance equations are used for hydrodynamic simulation and SA method are used for optimization steps. Optimization capabilities with various decision options and allowing weights to the indicators are good characteristics of this model. Comparison of advance time in this model with the well-known model SIRMOD for a real condition showed a good accuracy in the evaluation phase. In addition, the significant improvement of efficiencies after optimizing them simultaneously indicate that the model is an efficient tool for optimal design and use of this model for a data plot of an experimental field could enhance the efficiency of deep percolation ratio and application efficiency to 20% and keep constant the level of 100% for the efficiencies of water requirement and distribution uniformity.
M. A. Geranmehr, M. R. Chamani, K. Asghari,
Volume 22, Issue 3 (11-2018)
Abstract
A water distribution network (WDN) may not be able to satisfy all required demands when it’s in the pressure deficit mode or under over-loaded demand conditions. Analysis of the network in this mode requires pressure dependent analysis (PDA). Unlike demand driven analysis (DDA), PDA needs an extra equation for every node to relate the nodal demand and the nodal pressure; so it should be solved with the other network’s equations simultaneously. In this paper, based on the Particle Swarm Optimization (PSO) algorithm, a decision support system has been developed by using MATLAB and EPANET for PDA simulation in WDNs. A four-loop network selected from the literature was analyzed using different scenarios and different pressure dependent functions presented by the previous investigations. The results showed that the proposed model (PSO-PDA) was as accurate as the previous ones and provided better convergence. The results of the nodes’ pressure and discharge also indicated minor differences obtained by different PDA functions. However, the differences between the results of PDA and DDA were considerable.
S. Chavoshi,
Volume 22, Issue 4 (3-2019)
Abstract
Regional flood frequency studies are initialized by the delineation of the homogeneous catchments. This study was based on "Region of Influence" concept, aiming to find the similar catchments in the south of Caspian Sea. The methodology utilized the Particle Swarm Optimization Algorithm, PSO, to optimize the fuzzy system over a dataset of catchment properties. The main catchment variables in relation to flood were determined by the principle component analysis method and employed as the inputs in the fuzzy system. Catchments grouping was performed over these fuzzy input variables by the iterative process. The optimum similar groups were obtained by PSO, and the heterogeneous L-moment index was used as the termination criterion for the optimization process. A total of 61 hydrometric stations located in the study area were selected and their relevant catchments' physical, climatic and hydrologic properties in relation to flood were studied. Principle Component Analysis by Variomax Rotation Factor over the catchments datasets tended to four out of 16 physical variables, including area, mean elevation, Gravelious Factor and Form Factor, as the main parameters in terms of homogeneity with 84 percent of accumulative variance. These variables, as well as mean annual rainfall, were used as the input data to define the fuzzy system. PSO algorithm was then employed to optimize the developed fuzzy system. The developed algorithm tended to yield the best result in the 9th iteration with 26 and 22 for the minimum average and the optimum values of cost function, respectively. The topology of the resulting algorithm included inertia weight, local and acceleration rates, the number of generations and population size, with the values of 0.7298, 1.4962, 1.4962, 10 and 5, respectively. This study tended to a total of 61 regions of influence, proportional to the relevant 61 sites. According to the geographical location of the catchments in the region, it could be concluded that the geographical proximity doesn't necessarily involve homogeneity. The obtained results indicated the efficient potential of PSO-FES in the delineation of the homogenous catchments in the study area.
B. Raheli Namain, S. Mortazavi, A. Salman Mahini,
Volume 23, Issue 2 (9-2019)
Abstract
Agriculture production with high quality and adequate income for farmers and the least harmful effects in environment are the main objectives of agriculture optimization. The main objective of this study was ranking, optimization and land allocation of Gonbadkavoos’s Drylands for strategic products such as wheat, barley, oilseed rape and soybean under environment and socio-economic scenarios. Because the available information on fertilizer and pesticide consumption was not sufficient and reliable, this data was collected through face-to-face interviews with farmers. The results showed that some slightly and moderately hazardous pesticides were consumed in study area. In this study, the optimized combination of agriculture products was applied by using the modeling approach and considering environmental and socio-economic aspects in Gonbadkavoos County. This approach uses MCAT software, which is based on multi-criteria techniques and metaheuristic algorithms. The results of the environmental scenario show ed that barley, oilseed rape and soybean, with little difference, had the highest benefit-to-cost ratio and profitability, respectively. The slight difference could be related to the use of fertilizers and pesticides. In the socio-economic scenario, oilseed rape, wheat and barley had the highest benefit-to-cost ratio and land allocation, respectively. The represented approach using the decision support system (MCAT) can help planners to design optimal cropping systems and aid good management of fertilizers and water consumption.
N. Ganji Khorramdel, M. Abdoos, S. M. Hoseini Mooghaari,
Volume 23, Issue 3 (12-2019)
Abstract
Due to water use increasing, attention to optimal water resources allocation is needed. In recent decades, the use of intelligent evolutionary methods for optimization of water allocation was focused more by researchers. The aim of this study is to development on water resources planning model that determined the proper cultivation, optimal exploitation of groundwater and surface water resources although water allocation among crops is a way to minimize the adverse effects of dehydration and increase its revenue. In this study, for maximizing profits, estimating crop water requirements at different periods to optimize the management of cropping patterns and irrigation management in cultivation in Varamin irrigation network using a new evolutionary algorithm was called the water cycle. Then for validation of this method is that a new approach and ensure the integrity of its performance Its results are compared with a genetic algorithm model and linear programming as our base (R2=0.9963). The results showed that the area cropping pattern was not optimal and the area under cultivation of crops such as wheat, barley, tomatoes, Bamjan, melon, alfalfa reaches zero and the new paradigm of the largest area under cultivation to industrial goods and then was assigned cucumbers. While our revenues have increased about 11 percent. In addition to amount of water in different months remain in the network that can be used for many that such as injection into underground aquifers or other crops based on the amount of water available.
M. J. Asadi, S. Shabanlou, M. Najarchi, M. M. Najafizadeh,
Volume 23, Issue 3 (12-2019)
Abstract
In this study, the discharge coefficient of the circular side orifices was predicted using a new hybrid method. Combinations made in this study were divided into two sections: 1) the combination of two algorithms including Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) and providing the PSOGA algorithm 2) using the PSOGA algorithm in order to optimize the Adaptive Neuro Fuzzy Inference Systems (ANFIS) network and providing the ANFIS-PSOGA method. Next, by identifying the parameters affecting on the discharge coefficient of the circular side orifices, 11 different combinations were provided. Then, the sensitivity analysis conducted by ANFIS showed that the Froude number and the ratio of the flow depth to the orifice diameter (Ym/D) were identified as the most effective parameters in modeling the discharge coefficient. Also, the best combination including the Froude number (Fr), the ratio of the main channel width to the side orifice diameter (B/D), the ratio of the orifice crest height to its diameter (W/D) and the ratio of the flow depth to the orifice diameter (Ym/D) for estimating the discharge coefficient was introduced. For this model, the values of Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE) and correlation coefficient (R) were obtained 0.021, 0.020 and 0.871, respectively. Additionally, the performance of the ANFIS-PSOGA method was compared with the ANFIS-PSO and ANFIS methods. The results showed that the ANFIS-PSOGA method for predicting the discharge coefficient was the superior model
A. Kheyrandish, S. F. Mousavi, H. R. Ghafouri, S. Farzin,
Volume 23, Issue 4 (12-2019)
Abstract
In this research, conjunctive and integrated operation of surface and ground water resources of Behbahan plain (Maroon dam's reservoir and existing wells, respectively) was investigated. Simulation of allocation of water demands in this basin was performed by four scenarios, using WEAP software: 1) current conditions (M1), 2) reference scenario for the next 16 years (M2), 3) land development scenario (M3), and 4) optimal scenario (M4). The optimal scenario was performed with multi-purpose linear programming. Based on the results, drinking water demands was satisfied completely in all scenarios. Under the scenario of current conditions, all agricultural demands, except the traditional rights, supplied more than 50% in the low-flow months. In the reference scenario, water supply for agricultural demands in some months was less than 100% and even in June and July, the water supply for North and South Irrigation networks of Behbehan plain was less than 10%. In the land development scenario, agricultural demands of all irrigation networks, except Ramhormoz network, satisfied more than 90% in all months. The optimal scenario performed better than other scenarios for minimum Maroon River flow and volume of storage in the reservoir. Comparison of the four scenarios in satisfying the environmental needs also revealed that the optimal scenario performed better than the other three scenarios in the spring months. However, it provided less than 100% of water needs in the whole year. Comparison of the four scenarios also showed that the first two scenarios had the highest reliability percent in the Jayzan-Fajr, South Behbahan and North Behbahan Irrigation Networks and traditional water rights. Frequency of storage-time-probability from the storage volume in the optimal scenario also showed that maximum storage lifetime of the lasting storage volume was 558 million m3 (which was equal to half of the volume of Maroon dam’s reservoir) with the highest probability (60%).
A. Atarodi, H. Karami, A. Ardeshir, Kh. Hosseini,
Volume 24, Issue 1 (5-2020)
Abstract
In general, engineering designs need to optimize the factors affecting the under-study phenomenon; however, this is often a costly and time-consuming process. In this regard, new methods have been developed to optimize with fewer tests; thus, they can make the whole process more affordable. In this study, Taguchi and Taguchi-GRA methods were used to design the geometric parameters of the protective spur dike in order to optimize their efficiency in reducing the scouring in a series of spur dikes. The results of both methods showed the optimal ratio of the length of the protective spur dike to the length of the first spur dike was 2.5 and the angle of the protective spur dike was 90 °. However, the ratio of the length of the protective spur dike to the length of the main spur dike in the Taguchi method was 0.8 and in the Taguchi-GRA method, it was 0.6. In addition, using variance analysis showed that the distance between the protective spur dike from the first spur dike, the protective spur dike angle, and the length of the protective spur dike were, respectively, the most effective on the performance of the protective spur dike. The results of this study, therefore, indicate that both methods are highly effective in optimization and, therefore, can be useful in the hydraulic engineer studies.
M. M. Fallahi, B. Yaghoubi, F. Yosevfand, S. Shabanlou,
Volume 24, Issue 3 (11-2020)
Abstract
Rainfall may be considered as the most important source of drinking water and watering land in different areas all over the world. Therefore, simulation and estimation of the hydrological phenomenon is of paramount importance. In this study, for the first time, the long-term rainfall in Rasht city was simulated using an optimum hybrid artificial intelligence (AI) model over a 62 year period from 1956 to 2017. The gene expression programming (GEP) and wavelet transform (WT) were combined to develop the hybrid AI model (WGEP). Firstly, the most effective lags of time series data were identified by means of the autocorrelation function (ACF); then eight various GEP and WGEP models were defined. Next, the GEP models were analyzed and the superior GEP model as well as the most influenced lags was detected. For instance, the variance accounting for (VAF), correlation coefficient (R) and scatter index (SI) for the superior GEP model was calculated to be 0.765, 0.508 and 0.709, respectively. Additionally, lags (t-1), (t-2), (t-3) and (t-12) were the most influenced. Then, the different mother wavelets were examined, indicating that the demy mother wavelet was the most optimal one. Moreover, analyzing the numerical simulations showed that the mother wavelet enhanced the performance of the GEP model significantly. For example, the VAF index for the superior WGEP model was increased almost three times after using the mother wavelet. Furthermore, the R and MARE statistical indices for the WGEP model were computed to be 0.935 and 0.862, respectively.
H. Alizadeh, A. Hoseini, M. Soltani,
Volume 24, Issue 3 (11-2020)
Abstract
The construction of irrigation network and the water transfer from Karkheh Dam to Dashte-Abbas, due to neglecting the groundwater resources has increased groundwater level and waterlogging of the agricultural land in the recent years. The aim of this study was, therefore, to optimize the conjunctive use of surface and groundwater resources in Dashte-Abbas to minimize waterlogging problems and achieve the maximum net income. For this purpose, the behavior of groundwater was simulated using the system dynamics (SD) approach. The conjunctive use of surface and groundwater resources was then optimized using the Vensim multi-criteria optimization method with the objective function of maximizing the net income of the plain. The SD model calibration was done using climatic, hydrological, agricultural, and environmental data from the 2001-2009 time period; then it was validated based on the information from the 2009-2016 period. Evaluation of the developed SD model showed that the model had high accuracy in simulating key variables such as groundwater levels (ME=60cm, R2=97%, RMSE=47cm) and groundwater salinity (RMSE=100μS/cm, R2=74%, and ME=123μS/cm). Furthermore, the results of the optimization model showed that the optimum use of surface and groundwater resources for the agricultural demand was 65% and 35%, respectively. To sum up, it could be concluded that with the optimization of the conjunctive use of surface and groundwater resource, s about 10 MCM of water consumption could be annually saved to irrigate almost 800 ha of the new lands.
M. Fuladipanah, M. Majediasl,
Volume 24, Issue 4 (2-2021)
Abstract
The prediction of local scouring as a dynamic and nonlinear phenomenon using methods of acceptable predictive capability has always been of interest to researchers. The shape of the bridge pier is one of the important factors in the formation and magnitude of the scour hole. In this paper, the scour depth of three bridge piers with cylindrical, sharp nose and rectangular shapes was predicted in two scenarios using the support vector machine algorithm with 395 field data obtained from the US Geological Survey and Froehlich (1988), based on different combinations of dimensionless parameters as the water attack angle (α), Froud number (Fr), the ration of pier length to width (l/b), and the ratio of mean sediment size to pier width (D50/b). The results of the study, while confirming the acceptable performance of the SVM algorithm for all piers in both scenarios, showed that in the first and second scenarios, the most optimal performance was related to the rectangular pier shape with correlation coefficient of 0.8702 and 0.8838, with and maximum Ds (DDR) values of 0.854 and 1.229 respectively, during the testing phase. The positive effect of increasing the number of data on the performance of the SVM algorithm was also confirmed by further probing the evaluation indicators. The results of the comparison pointed out the overestimation of the predicted scour depth values of absolute error between 11% to 35%.
