Assessment of uncertainty sources in water quality modeling in the Niagara River

Franceschini, Samuela; Tsai, Christina W.

doi:10.1016/j.advwatres.2010.02.001

Cited by 55 publications

(23 citation statements)

References 20 publications

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“…The advanced eutrophication module is the most complicated module, which incorporates different parameters of eutrophication. This module includes many mass-balance equations to calculate the fate, transport, transformations, phytoplankton, as well as BOD, DO, and nitrification dynamics [46][47][48]. Interactions, components, and structure considered in the WASP model are shown in Figure 2.…”

Section: Overview Of Wasp Modelmentioning

confidence: 99%

Modeling Approach for Water-Quality Management to Control Pollution Concentration: A Case Study of Ravi River, Punjab, Pakistan

Iqbal

Shoaib

Agwanda

et al. 2018

Water

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Abstract:One of the challenging problems of Punjab, the most populous province of Pakistan, is the surface water-quality problem of the Ravi River, which flows through the main cities of the province. At present, the overall status of water quality is very polluted, primarily due to residential and industrial wastewater directly discharged into the Ravi River through a network of drains. Due to the poor quality of the water, the river ecosystem is not favorable for the aquatic and surrounding environment. Hence, management options are proposed to reduce pollution. Therefore, the study was formulated to identify the main sources of pollution along the Ravi River and their potential impact on the course of the river channel. In addition, the study applied a numerical model WASP 8.1 (Water Quality Simulation Program) to discover the best strategy for the improvement of water quality. Through the model simulation it was found that, if the flow at headwater and link canals is increased up to 50%, along with 75% improvement in the pollution concentration of drains through wastewater-treatment facilities, the water quality of the Ravi River can be improved up to an acceptable limit of water-quality standards.

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Section: Overview Of Wasp Modelmentioning

confidence: 99%

Modeling Approach for Water-Quality Management to Control Pollution Concentration: A Case Study of Ravi River, Punjab, Pakistan

Iqbal

Shoaib

Agwanda

et al. 2018

Water

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“…EFDC has been applied to different water bodies including rivers, lakes, reservoirs, wetlands, estuaries, and coastal regions in environmental assessment and management [63][64][65]. Franceschini and Tsai [66] coupled two numerical models, the Environmental Fluid Dynamic Code (EFDC), for the hydrodynamic portion, and WASP, for the fate and transport of contaminants, using the data from May 1995 to March 1997 on Lake Eris, and achieved an improved comparison of model predictions and measured data. For algae growth prediction, Wu and Xu [67] used the EFDC model to describe and simulate the eutrophication process in the Daoxiang Lake, Beijing.…”

Section: Efdcmentioning

confidence: 99%

A review of hydrological/water-quality models

Gao¹,

Li²

2014

Front. Agr. Sci. Eng.

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Water quality models are important in predicting the changes in surface water quality for environmental management. A range of water quality models are wildly used, but every model has its advantages and limitations for specific situations. The aim of this review is to provide a guide to researcher for selecting a suitable water quality model. Eight well known water quality models were selected for this review: SWAT, WASP, QUALs, MIKE 11, HSPF, CE-QUAL-W2, ELCOM-CAEDYM and EFDC. Each model is described according to its intended use, development, simulation elements, basic principles and applicability (e.g., for rivers, lakes, and reservoirs and estuaries). Currently, the most important trends for future model development are: (1) combination models-individual models cannot completely solve the complex situations so combined models are needed to obtain the most appropriate results, (2) application of artificial intelligence and mechanistic models combined with nonmechanistic models will provide more accurate results because of the realistic parameters derived from nonmechanistic models, and (3) integration with remote sensing, geographical information and global position systems (3S) -3S can solve problems requiring large amounts of data.

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“…With the addition of the wetting and drying capability , ROMS is suitable for modeling tidal dynamics and water circulation, temperature, salinity, and sediment transport in a shallow, back-barrier estuary. The Water Quality Analysis Simulation Program (WASP; Ambrose et al, 1988;Di Toro, Fitzpatrick, and Thomann, 1983;Wool, Davie, and Rodriguez, 2003), developed by the U.S. Environmental Protection Agency (EPA), incorporates watershed nutrient loading and internal nutrient cycling to calculate dissolved oxygen (DO), oxygen demand, nutrient concentrations, sediment, and phytoplankton dynamics and has been widely used for water-quality and TMDL assessment in rivers, reservoirs, lakes, and estuaries (Abdelrhman, 2015;Camacho et al, 2014;Franceschini and Tsai, 2010;Hosseini, Chun, and Lindenschmidt, 2016;Kaufman, 2011;Lindenschmidt, 2006 and references therein;Tetra Tech, 2012, 2015. WASP can receive hydrodynamic information from other models (EFDC, DYNHYD, RIVMOD, CE-QUAL-RIV1, SWMM) through a binary hydrodynamic linkage file; however, a coupling between ROMS and WASP was not available prior to this study.…”

Section: Introductionmentioning

confidence: 99%

Toward a Comprehensive Water-Quality Modeling of Barnegat Bay: Development of ROMS to WASP Coupler

Defne

Spitz

dePaul

et al. 2017

Journal of Coastal Research

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The Regional Ocean Modeling System (ROMS) has been coupled with the Water Quality Analysis Simulation Program (WASP) to be used in a comprehensive analysis of water quality in Barnegat Bay, New Jersey. The coupler can spatially aggregate hydrodynamic information in ROMS cells into larger WASP segments. It can also be used to resample ROMS output at a finer temporal scale to meet WASP time-stepping requirements. The coupler aggregates flow components, temperature, and salinity in ROMS output for input to WASP via a hydrodynamic linkage file. The coupler was tested initially with idealized cases designed to verify the water mass balance and conservation of constituent mass using oneto-one and one-to-many connectivity options between segments. A realistic example from the Toms River embayment, a subdomain of Barnegat Bay, was used to demonstrate the functionality of the coupling. A WASP eutrophication model accounting for dissolved oxygen (DO), nitrogen, and constant phytoplankton concentrations was applied to explore the distribution and trends in DO and nitrogen in the embayment for the period of July-August 2012. Results of DO modeling indicate satisfactory agreement with measurements collected at in-bay stations and also indicate that this coupled approach, despite substantial differences in spatiotemporal discretization between the models, provides adequate predictive capabilities. ADDITIONAL INDEX WORDS:ROMS, WASP, hydrodynamic linkage, coupler.

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Assessment of uncertainty sources in water quality modeling in the Niagara River

Cited by 55 publications

References 20 publications

Modeling Approach for Water-Quality Management to Control Pollution Concentration: A Case Study of Ravi River, Punjab, Pakistan

Modeling Approach for Water-Quality Management to Control Pollution Concentration: A Case Study of Ravi River, Punjab, Pakistan

A review of hydrological/water-quality models

Toward a Comprehensive Water-Quality Modeling of Barnegat Bay: Development of ROMS to WASP Coupler

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