Literature DB >> 23202384

Model development for prediction and mitigation of dissolved oxygen sags in the Athabasca River, Canada.

Nancy Martin1, Preston McEachern, Tong Yu, David Z Zhu.   

Abstract

Northern rivers exposed to high biochemical oxygen demand (BOD) loads are prone to dissolved oxygen (DO) sags in winter due to re-aeration occurring within limited open water leads. Additionally, photosynthesis is reduced by decreased daylight hours, inability of solar radiation to pass through ice, and slower algal growth in winter. The low volumetric flow decreases point-source dilution while their travel time increases. The Athabasca River in Alberta, Canada, has experienced these sags which may affect the aquatic ecosystem. A water quality model for an 800 km reach of this river was customized, calibrated, and validated specifically for DO and the factors that determine its concentration. After validation, the model was used to assess the assimilative capacity of the river and mitigation measures that could be deployed. The model reproduced the surface elevation and water temperature for the seven years simulated with mean absolute errors of <15 cm and <0.9 °C respectively. The ice cover was adequately predicted for all seven winters, and the simulation of nutrients and phytoplankton primary productivity were satisfactory. The DO concentration was very sensitive to the sediment oxygen demand (SOD), which represented about 50% of the DO sink in winter. The DO calibration was improved by implementing an annual SOD based on the BOD load. The model was used to estimate the capacity of the river to assimilate BOD loads in order to maintain a DO concentration of 7 mg/L, which represents the chronic provincial guideline plus a buffer of 0.5 mg/L. The results revealed the maximum assimilative BOD load of 8.9 ton/day at average flow conditions, which is lower than the maximum permitted load. In addition, the model predicted a minimum assimilative flow of about 52 m(3)/s at average BOD load. Climate change scenarios could increase the frequency of this low flow. A three-level warning-system is proposed to manage the BOD load proactively at different river discharges. Other mitigation options were explored such as upgrading the wastewater treatment of the major BOD point source and oxygen injection in the effluents. The model can be used as a management tool with updated SOD values to forecast the DO in low flow years and evaluate mitigation measures. As well, the methodology presented here can be applied to manage other ice-covered rivers.
Copyright © 2012 Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23202384     DOI: 10.1016/j.scitotenv.2012.10.030

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  5 in total

1.  Modeling hourly dissolved oxygen concentration (DO) using two different adaptive neuro-fuzzy inference systems (ANFIS): a comparative study.

Authors:  Salim Heddam
Journal:  Environ Monit Assess       Date:  2013-09-21       Impact factor: 2.513

2.  Analyzing sediment dissolved oxygen based on microprofile modeling.

Authors:  Chao Wang; Baoqing Shan; Hong Zhang; Nan Rong
Journal:  Environ Sci Pollut Res Int       Date:  2014-04-26       Impact factor: 4.223

3.  Dynamic water quality modelling and uncertainty analysis of phytoplankton and nutrient cycles for the upper South Saskatchewan River.

Authors:  Eric Akomeah; Kwok Pan Chun; Karl-Erich Lindenschmidt
Journal:  Environ Sci Pollut Res Int       Date:  2015-07-23       Impact factor: 4.223

4.  Determination of Sediment Oxygen Demand in the Ziya River Watershed, China: Based on Laboratory Core Incubation and Microelectrode Measurements.

Authors:  Nan Rong; Baoqing Shan; Chao Wang
Journal:  Int J Environ Res Public Health       Date:  2016-02-19       Impact factor: 3.390

5.  Assessment of Water Quality Profile Using Numerical Modeling Approach in Major Climate Classes of Asia.

Authors:  Muhammad Mazhar Iqbal; Muhammad Shoaib; Hafiz Umar Farid; Jung Lyul Lee
Journal:  Int J Environ Res Public Health       Date:  2018-10-15       Impact factor: 3.390

  5 in total

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