Locating Optimal Position of Pumping Wells in Aquifer Using Meta-Heuristic Algorithms and Finite Element Method

Akbarpour, Abolfazl; Zeynali, Mohammad; Tahroudi, Mohammad Nazeri

doi:10.1007/s11269-019-02386-6

Cited by 14 publications

(8 citation statements)

References 23 publications

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“…Also, the result of this study revealed that the FE slightly outperformed the FD, although there is an underestimation in both methods, especially at the end of the simulation period. This result is well compatible with the findings of some related studies (Simpson & Clement 2003;Akbarpour et al 2020). Simpson & Clement (2003) reported that the FE model is more robust for groundwater modeling than FD, especially for coarsely discretized problems.…”

Section: Modeling Performancesupporting

confidence: 92%

Application of multi-model ensemble averaging techniques for groundwater simulation: synthetic and real-world case studies

Jafarzadeh

Pourreza‐Bilondi

Akbarpour

et al. 2021

Journal of Hydroinformatics

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Growing demands in arid regions have increased groundwater vulnerabilities necessitating appropriate modeling and management strategies to understand and sustain aquifer system behaviors. Sustainable management of aquifer systems, however, requires a proper understanding of groundwater dynamics and accurate estimates of recharge rates which often cause error and uncertainty in simulation. This study aims to quantify the uncertainty and error associated with groundwater simulation using various multi-model ensemble averaging (MEA) techniques such as simple model averaging, weighted averaging model, multi-model super ensemble, and modified MMSE. Two numerical solutions, i.e., finite difference and finite element (FE), were first coupled under three schemes such as explicit scheme (ES), implicit scheme, and Crank-Nicolson Scheme to numerically solve groundwater simulation problems across two case studies, synthetic and real-world (the Birjand aquifer in Iran) case studies. The MEA approach was considerably successful in calibrating a complex arid aquifer in a way that honors complex geological heterogeneity and stress configurations. Specifically, the MEA techniques skillfully reduced the error and uncertainties in simulation, particularly those errors associated with water table variability and fluctuation. Furthermore, a coupled FE-ES method outperformed other approaches and generated the best groundwater-level simulation for the synthetic case study, while stand-alone FE was particularly successful for the Birjand aquifer simulation as a real-world case study.

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Section: Modeling Performancesupporting

confidence: 92%

Application of multi-model ensemble averaging techniques for groundwater simulation: synthetic and real-world case studies

Jafarzadeh

Pourreza‐Bilondi

Akbarpour

et al. 2021

Journal of Hydroinformatics

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“…In the genetic algorithm (GA) and its multi-objective version (Non-Dominated Sorting Genetic Algorithm, NSGA-II), there are crossover and mutation phases. In the singleobjective version, the population is sorted by the value of the objective function, and the selection of the best individual is based on the objective function value (Akbarpour et al, 2020). In the NSGA-II algorithm, the rank of each solution in the population is based on the non-dominated sorting and crowding distance.…”

Section: Ga and Nsga-ii Algorithmsmentioning

confidence: 99%

Optimizing pump-and-treat method by considering important remediation objectives

et al. 2022

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The efficiency of groundwater remediation by pump-and-treat (PAT) method is affected by several components. The most important of these components include the pumping wells location, pumping rate, and remediation period. In this research, hybrid optimization-simulation models were developed to find the appropriate groundwater remediation strategy by PAT method. The GA-FEM and NSGA-II-FEM models were used to solve four optimization problems for a hypothetical and real aquifer. These optimization problems were investigated from one objective problem to a four-objectives problem. In the multi-objective problems, in each step, one objective function is added to the previous set of objective functions. In the one-objective case, the objective function was defined as minimizing the contaminant concentration by pumping at a constant rate, while in the two-objectives problem, minimizing the drawdown of groundwater head by pumping at a constant rate was added. In the three-objectives problem, the pumping rate was variable and the mean pumping rate from all the wells is minimized. Finally, minimizing the remediation period is added in the four-objective case. The results indicated that locating the pumping wells in the path of the contaminant flow and close to the source improves the efficiency of the PAT system. The wells with higher pumping rates would be in the path of contamination flow and the wells with lower pumping rates should be located in nodes near the Dirichlet boundary. It is concluded that the remediation period in the hypothetical and real aquifer cannot be less than almost 3000 and 760 days, respectively. Finally, it can be said, the most important component in choosing the proper PAT strategy is the proper location of pumping wells.

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“…Lower RMSE and SSE, and higher NSE indicate higher accuracy of the model. In the above relations, Q i , b Q i and Q i are the measured, simulated and mean discharges of the outflow hydrograph, respectively, and n is the number of data (Tahroudi et al 2019;Akbarpour et al 2020;Shahidi et al 2020).…”

Section: Model Performancementioning

confidence: 99%

Flood routing via a copula-based approach

et al. 2021

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Floods are among the most common natural disasters that if not controlled may cause severe damage and high costs. Flood control and management can be done using structural measures that should be designed based on the flood design studies. The simulation of outflow hydrograph using inflow hydrograph can provide useful information. In this study, a copula-based approach was applied to simulate the outflow hydrograph of various floods, including the Wilson River flood, the River Wye flood and the Karun River flood. In this regard, two-dimensional copula functions and their conditional density were used. The results of evaluating the dependence structure of the studied variables (inflow and outflow hydrographs) using Kendall's tau confirmed the applicability of copula functions for bivariate modeling of inflow and outflow hydrographs. The simulation results were evaluated using the root-mean-square error, the sum of squared errors and the Nash–Sutcliffe efficiency coefficient (NSE). The results showed that the copula-based approach has high performance. In general, the copula-based approach has been able to simulate the peak flow and the rising and falling limbs of the outflow hydrographs well. Also, all simulated data are at the 95% confidence interval. The NSE values for the copula-based approach are 0.99 for all three case studies. According to NSE values and violin plots, it can be seen that the performance of the copula-based approach in simulating the outflow hydrograph in all three case studies is acceptable and shows a good performance.

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Locating Optimal Position of Pumping Wells in Aquifer Using Meta-Heuristic Algorithms and Finite Element Method

Cited by 14 publications

References 23 publications

Application of multi-model ensemble averaging techniques for groundwater simulation: synthetic and real-world case studies

Application of multi-model ensemble averaging techniques for groundwater simulation: synthetic and real-world case studies

Optimizing pump-and-treat method by considering important remediation objectives

Flood routing via a copula-based approach

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