Developing a model for multi-objective optimization of open channels and labyrinth weirs: Theory and application in Isfahan Irrigation Networks

Ferdowsi, Ahmad; Anaraki, Mahdi Valikhan; Mousavi, Sayed‐Farhad; Farzin, Saeed; Mirjalili, Seyedali

doi:10.1016/j.flowmeasinst.2021.101971

Cited by 14 publications

(3 citation statements)

References 66 publications

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“…where Xnew is new data, lb is lower bound of experimental inputs, ub is upper bound of experimental inputs, and R ⃗ ⃗ is ran-dom vector. Numerous reliable studies, such as (Ehteram et al, 2018;Farzin and Anaraki, 2021;Ferdowsi et al, 2021;, employed this equation to generate random numbers between specific lower and upper bounds. The pseudo-code of generating new data is shown in Figure 1.…”

Section: Methodsmentioning

confidence: 99%

Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques

Anaraki¹,

Mahmoudian²,

Chianeh³

et al. 2022

J ENVIRON INFORM

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In the present study, a new approach by coupling the interpolation method with computation-based technique (data-mining algorithms and an optimization algorithm) is introduced for modeling and optimization removal of Reactive Orange 7 (RO7) dye removal from synthetic wastewater. To this end, four significant factors like pH, electrolyte concentration, current density, and electrolysis time are considered as input variables. Thus, modeling of RO7 removal is implemented using eight data mining algorithms including multivariate linear regression (MLR), ridge regression (RR), multivariate nonlinear regression (MNLR), artificial neural network (ANN), classification and regression tree (CART), k nearest neighbor (KNN), random forest (RF), and support vector machine (SVM). These algorithms require a large data set for creating reliable results. However, creating a large number of experimental data request consuming high cost and time. Hence, the interpolation methods of kriging (KRG) and inverse distance weight (IDW) are applied for generating more data, whereas KRG has more accuracy than IDW by increasing the 47.080, 36.914, and 1.77% in MAE, RMSE, and R values, respectively. Then, the data mining algorithms are used for modeling the decolorization efficiency (DE) based on the original data and new data from KRG. It is found that using new data leads to significantly increasing accuracy (94.47, 96.43, 1.52, and 2.77% for MAE, RMSE, R and R 2 , respectively) of DE modeling. Also, SVM has demonstrated the highest accuracy out of all data mining algorithms (by increasing the 97.13, 98.30, and 14.42% in MAE, RMSE, and R 2 values, respectively). Another challenge in the removal of RO7 from synthetic wastewater is predicting the maximum removal amount and optimal input variables. For this purpose, the hybrid of SVM and whale optimization algorithm (WOA) is employed. Finally, SVM-WOA has predicted the maximum of DE (91%) by optimal values of 4.2, 1.5 g/L, 4.2 mA/cm 2 , and 18 min for pH, C, I, and Time, respectively. In light of the high performance of the introduced approach for modeling removal process and predicting optimal conditions of removal process, this approach can be suggested for the removal of other pollutants from wastewater when the number of experimental data set is limited.

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Section: Methodsmentioning

confidence: 99%

Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques

Anaraki¹,

Mahmoudian²,

Chianeh³

et al. 2022

J ENVIRON INFORM

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“…The aspects of fluid dynamics and hydrology of flows in networks are another vast area of research. This research includes, for an example, flows in networks of microfluidic channels [ 56 , 57 ], flows in networks of irrigation channels [ 58 ], and, especially, optimal operation and control of multireservoir systems [ 59 , 60 , 61 , 62 , 63 , 64 , 65 ], debris flows in river networks [ 66 ], flows in porous media [ 67 , 68 , 69 ], calibration of water flows in network models [ 70 , 71 , 72 ], etc.…”

Section: Short Overview Of Selected Areas Of Research On Flows In Net...mentioning

confidence: 99%

Flows of Substances in Networks and Network Channels: Selected Results and Applications

Dimitrova

2022

Entropy

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This review paper is devoted to a brief overview of results and models concerning flows in networks and channels of networks. First of all, we conduct a survey of the literature in several areas of research connected to these flows. Then, we mention certain basic mathematical models of flows in networks that are based on differential equations. We give special attention to several models for flows of substances in channels of networks. For stationary cases of these flows, we present probability distributions connected to the substance in the nodes of the channel for two basic models: the model of a channel with many arms modeled by differential equations and the model of a simple channel with flows of substances modeled by difference equations. The probability distributions obtained contain as specific cases any probability distribution of a discrete random variable that takes values of 0,1,…. We also mention applications of the considered models, such as applications for modeling migration flows. Special attention is given to the connection of the theory of stationary flows in channels of networks and the theory of the growth of random networks.

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“…Several optimization methods can help in determining the most economical open channel design, which is a channel design that minimizes construction expenses per unit length, given a set design discharge, roughness factor, and bed incline. The best design for a channel section can be determined through mathematical approaches [8]. Within the scope of this project, a significant action taken was the addition of concrete linings to irrigation canals.…”

Section: Introductionmentioning

confidence: 99%

Using GIS Techniques to Determine Appropriate Locations for Constructing Concrete Water Canals in the Baranti Plain of Erbil Governorate, Iraq

Hamad,

Çullu,

Bilgili

et al. 2024

Water

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Water, being the basic resource for life on earth, is of great importance in arid and semi-arid regions, which face the direct impacts of climate change. This study aims to solve water scarcity for Baranti Plain farmers by constructing concrete canals using modern technology. The Baranti Plain is located approximately 25 km north of Erbil in Iraq and spans an area of 445 km2. The Great Zap River flows through its northern region, with an average discharge of about 400 m3 per second. In response to the challenges faced in this area, the Ministry of Agriculture and Water Resources collaborated with the Food and Agriculture Organization (FAO) to gather essential data. This extensive dataset, covering the period from 2000 to 2021, particularly focuses on ground-level monitoring in September. Notably, the region experienced a significant decline in groundwater levels, totaling 23 m on average. Additionally, there was a 7.8% increase of urban expansion, and the number of wells increased from 257 in 2006 to 600 in 2021. To counter the diminishing groundwater levels and facilitate agricultural irrigation, a proposal was introduced to harness the waters of the Great Zap River. This plan involves channeling the river waters to the plain through a network of concrete canals known as the Baranati Project Plain. For precise planning, a digital elevation model (DEM) with a 12.5 m resolution was procured to analyze the area using GIS. This investigation revealed a height difference of 130 m between the Great Zap River and the Baranti Plain. Subsequently, the area was segmented into four zones based on its suitability for the project: highest, medium, low, and unsuitable. Notably, the combined areas of high, medium, and low suitability encompass 68% of the entire study region. The project’s next phase used a flow calculator to determine the channel’s shape, area, slope, and water requirements. The final phase involved analyzing annual rainfall data from three meteorological stations (Bastora, Ankawa, and Khabat), showing an average annual rainfall of 396 mm. The project has the capacity to irrigate more than 30,000 hectares of land, benefiting more than 1200 farmers. It is expected to stop the use of over 600 wells for irrigation and potentially raise groundwater levels by about 2.5 m annually. Our work revealed that addressing groundwater depletion requires implementing canals, rainwater harvesting, farmer education, modern irrigation, drilling restrictions, and supporting water.

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Developing a model for multi-objective optimization of open channels and labyrinth weirs: Theory and application in Isfahan Irrigation Networks

Cited by 14 publications

References 66 publications

Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques

Dye Pollutant Removal from Synthetic Wastewater: A New Modeling and Predicting Approach Based on Experimental Data Analysis, Kriging Interpolation Method, and Computational Intelligence Techniques

Flows of Substances in Networks and Network Channels: Selected Results and Applications

Using GIS Techniques to Determine Appropriate Locations for Constructing Concrete Water Canals in the Baranti Plain of Erbil Governorate, Iraq

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