WEAP and QUAL2K Model Integration for Water Quality Evaluations as a Result of Urban Expansion Scenarios in the Federal District of Brazil

Silva, Tatiana Dumke da; Alves, Conceição de Maria Albuquerque

doi:10.1061/9780784479889.035

Cited by 5 publications

(2 citation statements)

References 8 publications

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“…Also, the low MAE means a good simulation when using the current models. The calibration error results are along with Da Silva & Alves (2016).…”

Section: Models Calibration and Validationmentioning

confidence: 99%

“…The results reveal that the proposed methodology could effectively develop sustainable inter-basin water allocation management. Da Silva et al (2016) integrated the WEAP and QUAL2 K models to evaluate the effect of population growth on BOD concentration changes in the Descoberto river basin under different management scenarios. The results showed that treatment efficiency at WWTP of the river should be enhanced under the population growth scenario.…”

Section: Graphical Abstract Introductionmentioning

confidence: 99%

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An integrated fuzzy optimization and simulation method for optimal quality-quantity operation of a reservoir-river system

2022

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In this study, a novel optimization-simulation dynamic approach is developed for optimal water operation of reservoir-river systems to improve the water quality and supply the water demands along the river. To this purpose, the WEAP-QUAL2 K linked model is developed to simulate water quality and quantity, which is coupled to a fuzzy multi-objective imperialist competition algorithm (FMOICA) dynamically. The approach's applicability is demonstrated through the case study of the Dez reservoir river in Iran. The simulation and optimization period is six years (October 2019-September 2025). The stochastic models (SARIMA(1,0,1)(1,1,1)) are used to forecast inflow into the Dez dam reservoir for the simulation period. Given that in the verification stage of the QUAL2 K and WEAP models, it can be concluded that the model has high accuracy in simulating the parameters of water quality and quantity. Two scenarios are considered, the first scenario is used for dynamical coupling of the quantity-quality model (reference scenario), and the second is the fuzzy optimization of a linked model (optimal scenario). The results showed that average water supply reliability increased from 86.13% in the reference scenario to 95.76% in the optimal scenario. Also, under the optimal scenario, the river water quality improves. As well as, it is found that environmental flow rate demands of the river are fully supplied in different months.

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“…Also, the low MAE means a good simulation when using the current models. The calibration error results are along with Da Silva & Alves (2016).…”

Section: Models Calibration and Validationmentioning

confidence: 99%

Section: Graphical Abstract Introductionmentioning

confidence: 99%

An integrated fuzzy optimization and simulation method for optimal quality-quantity operation of a reservoir-river system

2022

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Uncertainty Analysis of River Water Quality Based on Stochastic Optimization of Waste Load Allocation Using the Generalized Likelihood Uncertainty Estimation Method

Babamiri,

Dinpashoh

2023

Water Resour Manage

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River water quality management using an integrated multi-objective optimization-simulation approach based on bankruptcy rules

Babamiri,

Dinpashoh

2023

Environ Sci Pollut Res

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WEAP and QUAL2K Model Integration for Water Quality Evaluations as a Result of Urban Expansion Scenarios in the Federal District of Brazil

Cited by 5 publications

References 8 publications

An integrated fuzzy optimization and simulation method for optimal quality-quantity operation of a reservoir-river system

An integrated fuzzy optimization and simulation method for optimal quality-quantity operation of a reservoir-river system

Uncertainty Analysis of River Water Quality Based on Stochastic Optimization of Waste Load Allocation Using the Generalized Likelihood Uncertainty Estimation Method

River water quality management using an integrated multi-objective optimization-simulation approach based on bankruptcy rules

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