Optimizing Multiple-Pollutant Waste Load Allocation in Rivers: An Interval Parameter Game Theoretic Model

Nikoo, Mohammad Reza; Beiglou, Pouyan Hatami Bahman; Mahjouri, Najmeh

doi:10.1007/s11269-016-1415-6

Cited by 37 publications

(12 citation statements)

References 29 publications

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“…Although it may be desirable to maximize the benefit or minimize the cost of load reductions, this requires substantial site-specific information about the types of management alternatives and associated costs and benefits. Multiple objective optimization (Allam et al, 2016) and game theoretical models (Nikoo, Beiglou, & Mahjouri, 2016) have often been developed for load allocation in order to take into account stakeholders in the negotiation processes.…”

Section: Integrated Load Allocation and Water Quality Modellingmentioning

confidence: 99%

“…In this approach, output of the water quality model runs are used to derive a linear response matrix (Y. Jia & Culver, 2006), load delivery factors (Shortle et al, 2016), transfer coefficients (Nikoo et al, 2016;Zolfagharipoor & Ahmadi, 2016), or nonlinear stressor-response relationships (F. , which are then read by the optimization model to find the solution. Therefore, an iterative coupled optimization-simulation problem is transformed into a sequentially coupled simulation-optimization model.…”

Section: Integrated Load Allocation and Water Quality Modellingmentioning

confidence: 99%

See 1 more Smart Citation

Integrated Environmental Modelling Framework for Cumulative Effects Assessment

Gupta¹,

Farjad²,

Wang³

et al. 2021

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Section: Integrated Load Allocation and Water Quality Modellingmentioning

confidence: 99%

Section: Integrated Load Allocation and Water Quality Modellingmentioning

confidence: 99%

Integrated Environmental Modelling Framework for Cumulative Effects Assessment

Gupta¹,

Farjad²,

Wang³

et al. 2021

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“…Mahjouri and Abbasi (2015) attempted to minimize the total cost of wastewater treatment by considering the optimal treatment alternatives and the objectives of the stakeholders. Nikoo et al (2016) developed a WLA model for a river and applied the policy of allocating total profits from the permitted trade of wastewater discharge among dischargers. Tavakoli et al (2015) studied the effects of WLA and wastewater load on river water quality management concerning agricultural water return.…”

Section: Introductionmentioning

confidence: 99%

River water quality management using a fuzzy optimization model and the NSFWQI Index

Ghorbani

Afshar

Hamidifar

2021

WSA

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In this study, a novel multiple-pollutant waste load allocation (WLA) model for a river system is presented based on the National Sanitation Foundation Water Quality Index (NSFWQI). This study aims to determine the value of the quality index as the objective function integrated into the fuzzy set theory so that it could decrease the uncertainties associated with water quality goals as well as specify the river's water quality status rapidly. The simulation-optimization (S-O) approach is used for solving the proposed model. The QUAL2K model is used for simulating water quality in different parts of the river system and ant colony optimization (ACO) algorithm is applied as an optimizer of the model. The model performance was examined on a hypothetical river system with a length of 30 km and 17 checkpoints. The results show that for a given number of both the simulator model runs and the artificial ants, the maximum objective function will be obtained when the regulatory parameter of the ACO algorithm (i.e., q0) is considered equal to 0.6 and 0.7 (instead of 0.8 and 0.9). Also, the results do not depend on the exponent of the membership function (i.e., γ). Furthermore, the proposed methodology can find optimum solutions in a shorter time.

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“…Earlier studies on management models for waste load allocation in rivers focused mostly on the maintenance of minimum DO concentration for river health [28][29][30][31][32][33][34][35][36]. Objective functions in these models are based on minimisation of cost, maximisation in the equitable sharing of treatment burden, maximisation of performance, minimisation of a violation index.…”

Section: Introductionmentioning

confidence: 99%

Managing Municipal Wastewater Treatment to Control Nitrous Oxide Emissions from Tidal Rivers

Akella

Bhallamudi

2019

Water

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Waste load allocation management models were developed for controlling nitrous oxide emissions from a tidal river. The decision variables were treatment levels at wastewater discharging stations and the rate of upstream water release. The simulation model for N2O emissions from the river was embedded in the optimization model and the problem was solved using the simulated annealing technique. In two of the models, the total cost was minimized, while in the third model, emissions from the river were minimized for a specified constraint on the available money. Proof-of-concept studies, with hypothetical scenarios for contaminant loading but realistic flow conditions corresponding to the Tyne River, UK, were carried out. It was found that the treatment cost could be reduced by 36% by treating wastewater discharges in the upper reaches more during the high tide as compared to during low tide. For the same level of N2O emissions, approximately 16.7% lesser costs could be achieved by not only treating the wastewater but also inducing dilution by releasing more water from the upstream side. It was also found that beyond a limit, N2O emissions cannot be reduced significantly by spending more money on treatment and water release.

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Optimizing Multiple-Pollutant Waste Load Allocation in Rivers: An Interval Parameter Game Theoretic Model

Cited by 37 publications

References 29 publications

Integrated Environmental Modelling Framework for Cumulative Effects Assessment

Integrated Environmental Modelling Framework for Cumulative Effects Assessment

River water quality management using a fuzzy optimization model and the NSFWQI Index

Managing Municipal Wastewater Treatment to Control Nitrous Oxide Emissions from Tidal Rivers

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