YE Hanfeng, GUO Shuhai, LI Fengmei, LI Gang. Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model[J]. Chinese Geographical Science, 2013, 23(3): 301-311. doi: 10.1007/s11769-013-0586-9
Citation: YE Hanfeng, GUO Shuhai, LI Fengmei, LI Gang. Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model[J]. Chinese Geographical Science, 2013, 23(3): 301-311. doi: 10.1007/s11769-013-0586-9

Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model

doi: 10.1007/s11769-013-0586-9
Funds:  Under the auspices of Water Pollution Control and Management Key Project of Science and Technology of China (No. 2013ZX07202-007), Liaoning Hundred-Thousand-Ten Thousand Talents Program
More Information
  • Corresponding author: GUO Shuhai. E-mail: shuhaiguo@iae.ac.cn
  • Received Date: 2012-04-25
  • Rev Recd Date: 2012-08-20
  • Publish Date: 2013-05-29
  • Rivers in the Liaohe River Estuary area have been seriously polluted by discharges of wastewater containing petroleum pollutants and nutrients. In this paper, The Enhanced Stream Water Quality Model (QUAL2K) and its revised model as well as One-dimensional Tide Mean Model (1D model) were applied to predict and assess the water quality of the tidal river reach of the Liaohe River Estuary. Dissolved oxygen (DO), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N) and total phosphorus (TP) were chosen as water quality indices in the two model simulations. The modelled results show that the major reasons for degraded rivers remain petroleum and non-point source pollution. Tidal water also has a critical effect on the variation of water quality. The sensitivity analysis identifies that flow rate, point load and diffuse load are the most sensitive parameters for the four water quality indices in the revised QUAL2K simulation. Uncertainty analysis based on a Monte Carlo simulation gives the probability distribution of the four water quality indices at two locations (6.50 km and 44.84 km from the river mouth). The statistical outcomes indicate that the observed data fall within the 90% confidence intervals at all sites measured, and show that the revised QUAL2K gives better results in simulating the water quality of a tidal river.
  • [1] Brown L C, Barnwell T O, 1987. The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Document and User Manual (EPA/600/3-87-007). Athens, GA: US Envi-ronmental Protection Agency, Environmental Research Labor-atory.
    [2] Carroll J, O'Neal S, Golding S, 2006. Wenatchee River Basin dissolved oxygen, pH, and phosphorus total maximum daily load study. Washington State Department of Ecology. Available at: http://www.ecy.wa.gov/biblio/0603018.html
    [3] Caviness K S, Garey A F, Patrick N D, 2006. Modeling the Big Black River: A comparison of water quality models. Journal of the American Water Resources Association, 42(3): 617-627.
    [4] Chapra S C, Pelletier G J, 2003. QUAL2K: A Modeling Frame-work for Simulating River and Stream Water Quality: Documen-tation and Users Manual. Medford, MA: Civil and Environmental Engineering Department, Tufts University.
    [5] Chapra S C, Pelletier G J, Tao H, 2007. QUAL2K: A Modeling Framework for Simulating River and Stream Water Quality: Documentation and Users Manual. Medford, MA: Civil and Environmental Engineering Department, Tufts University.
    [6] Cho J H, Ha S R, 2010. Parameter optimization of the QUAL2K model for a multiple-reach river using an influence coefficient algorithm. Science of the Total Environment, 408: 1985-1991. doi:  10.1016/j.scitotenv.2010.01.025
    [7] Cox B A, 2003. A review of currently available in-stream water-quality models and their applicability for simulating dissolved oxygen in lowland rivers. The Science of the Total Environment, 314-316: 335-377. doi: 10.1016/S0048-9697(03) 00063-9
    [8] Fan C, Ko C H, Wang W S, 2009. An innovative modeling ap-proach using QUAL2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation. Journal of Environmental Management, 90(5): 1824-1832. doi:  10.1016/j.jenvman.2008.11.011
    [9] Ghosh N C, Mcbean E A, 1998. Water quality modeling of the Kali River, India. Water, Air, and Soil Pollution, 102(1-2): 91-103.
    [10] Kannel P R, Lee S, Kanel S R et al., 2007b. Application of QUAL2Kw for water quality modeling and dissolved oxygen control in the river Bagmati. Environmental Monitoring and Assessment, 125(1-3): 201-217. doi:  10.1007/s10661-006-9255-0
    [11] Kannel P R, Lee S, Lee Y S et al., 2007a. Application of automated QUAL2Kw for water quality modeling and management in the Bagmati River, Nepal. Ecological Modeling, 202(3-4): 503-517. doi:  10.1016/j.ecolmodel.2006.12.033
    [12] Kim K S, Je C H, 2006. Development of a framework of auto-mated water quality parameter optimization and its application.
    [13] Environmental Geology, 49(3): 405-412. doi:  10.1007/s00254-005-0085-0
    [14] Lindenschmidt K E, 2006. The effect of complexity on parameter sensitivity and model uncertainty in river water quality modeling. Ecological Modelling, 190(1-2): 72-86. doi:  10.1016/j.ecolmodel.2005.04.016
    [15] Liu Juan, Sun Qian, Mo Chunbo et al., 2008. The pollution status and characteristics of Daliaohe estuary and its adjacent sea area. Fisheries Science, 27(6): 286-289. (in Chinese)
    [16] Liu Yaping, Huang Baoguo, Xiong Jingdong, 2003. Scouring and silting influence on Panshan Sluice to river course in upstream and downstream and prevention measures. Water Resources & Hydropower of Northeast China, 21(227): 30-31. (in Chinese)
    [17] Mahamah D S, 1998. Simplifying assumptions in water quality modeling. Ecological Modelling, 109(3): 295-300.
    [18] Mei Changlin, Zhou Jialiang, 2002. Practical Statistic Method. Beijing: Science Press. (in Chinese)
    [19] MEP (Ministry of Environmental Protection of China), 2009a. State Standards on Environmental Protection (HJ 495-2009): Water Quality-Technical Regulation on the Design of Sampling Programmes. Beijing: China Environmental Science Press, 1-12. (in Chinese)
    [20] MEP (Ministry of Environmental Protection of China), 2009b. State Standards on Environmental Protection (HJ 493-2009): Water Quality-Technical Regulation of the Preservation and Handling of Samples. Beijing: China Environmental Science Press, 1-6. (in Chinese)
    [21] Ning S K, Chang N B, Yang L et al., 2001. Assessing pollution prevention program by QUAL2E simulation analysis for the Kao-Ping River Basin, Taiwan. Journal of Environmental Management, 61(1): 61-76. doi:  10.1006/jema.2000.0397
    [22] Ostfeld A, Salomons S, 2005. A hybrid genetic-instance based learning algorithm for CE-QUAL-W2 calibration. Journal of Hydrology, 310(1-4): 122-142. doi: 10.1016/j.jhydrol.2004.12. 004
    [23] Paliwal R, Sharma P, Kansal A, 2007. Water quality modelling of the river Yamuna (India) using QUAL2E-UNCAS. Journal of Environmental Management, 83(2): 131-144. doi:  10.1016/j.jenvman.2006.02.003
    [24] Palmieri V, de Carvalho R J, 2006. Qual2e model for the Corum-bataí River. Ecological Modelling, 198(1-2): 269-275. doi:  10.1016/j.ecolmodel.2006.04.018
    [25] Pan Gui'e, 2005. Preliminary study on evolution and management of the Liaohe estuary. Journal of Sediment Research, (1): 57-62. (in Chinese)
    [26] Park S S, Lee Y S, 2002. A water quality modeling study of the Nakdong River, Korea. Ecological Modelling, 152(1): 65-75.
    [27] Park S S, Uchrin C G, 1997. A stoichiometric model for water quality interactions in macrophyte dominated water bodies. Ecological Modelling, 96(1-3): 165-174.
    [28] Parvathinathan G, 2002. An evaluation of uncertainty in water quality modeling for the Lower Rio Grande River using QUAL2E-UNCAS and Neural Networks (Master Thesis). Texas: Texas A&M University.
    [29] Pelletier G J, Chapra S C, Tao H, 2006. QUAL2Kw―A frame-work for modeling water quality in streams and rivers using a genetic algorithm for calibration. Environmental Modelling & Software, 21(3): 419-425. doi:  10.1016/j.envsoft.2005.07.002
    [30] SEPA (State Environmental Protection Administration of China), 2002. Methods for Monitor and Analysis of Water and Waste-water, 4th ed. Beijing: China Environmental Science Press, 40-47, 201-202, 227-231, 243-245, 279-282. (in Chinese)
    [31] Shen Zhenyao, Hong Qian, Yu Hong et al., 2008. Parameter un-certainty analysis of the non-point source pollution in the Daning River watershed of the Three Gorges Reservoir Region, China. Science of the Total Environment, 405(1-3): 195-205. doi:  10.1016/j.scitotenv.2008.06.009
    [32] Streeter H W, Phelps E B, 1925. A Study of the pollution and natural purification of the Ohio river. Public Health Bulletin, (146): 175.
    [33] Tao H, 2008. Calibration, sensitivity and uncertainty analysis in surface water quality modeling (Doctoral Dissertation). Medford: Tufts University.
    [34] USEPA (United States Environmental Protection Agency), 2009. River and stream water quality model (QUAL2K). Available at: http://www.epa.gov/athens/wwqtsc/html/qual2k.html.
    [35] Wang Xiaoguang, Yu Weijun, Shi Junyan et al., 2009. Evaluation of fishery water quality of Shuangtaizi River in downstream Liao River. Journal of Hydroecology, 2(6): 127-131. (in Chi-nese)
    [36] Wu Chengcheng, Zheng Xilai, Lin Guoqing, 2010. Study on tidal influx in Shuangtaizi estuary. Journal of Water Resources & Water Engineering, 21(4): 105-110. (in Chinese)
    [37] Xie Yongming, 1996. Outline of Environmental Water Quality Model. Beijing: China Science & Technology Press, 219-223. (in Chinese)
    [38] Zhang Yunpu, 2006. Pollution of Shuangtaizi River Panjin section and its control measures. Heilongjiang Environmental Journal, 30(3): 81-82. (in Chinese)
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Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model

doi: 10.1007/s11769-013-0586-9
Funds:  Under the auspices of Water Pollution Control and Management Key Project of Science and Technology of China (No. 2013ZX07202-007), Liaoning Hundred-Thousand-Ten Thousand Talents Program
    Corresponding author: GUO Shuhai. E-mail: shuhaiguo@iae.ac.cn

Abstract: Rivers in the Liaohe River Estuary area have been seriously polluted by discharges of wastewater containing petroleum pollutants and nutrients. In this paper, The Enhanced Stream Water Quality Model (QUAL2K) and its revised model as well as One-dimensional Tide Mean Model (1D model) were applied to predict and assess the water quality of the tidal river reach of the Liaohe River Estuary. Dissolved oxygen (DO), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N) and total phosphorus (TP) were chosen as water quality indices in the two model simulations. The modelled results show that the major reasons for degraded rivers remain petroleum and non-point source pollution. Tidal water also has a critical effect on the variation of water quality. The sensitivity analysis identifies that flow rate, point load and diffuse load are the most sensitive parameters for the four water quality indices in the revised QUAL2K simulation. Uncertainty analysis based on a Monte Carlo simulation gives the probability distribution of the four water quality indices at two locations (6.50 km and 44.84 km from the river mouth). The statistical outcomes indicate that the observed data fall within the 90% confidence intervals at all sites measured, and show that the revised QUAL2K gives better results in simulating the water quality of a tidal river.

YE Hanfeng, GUO Shuhai, LI Fengmei, LI Gang. Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model[J]. Chinese Geographical Science, 2013, 23(3): 301-311. doi: 10.1007/s11769-013-0586-9
Citation: YE Hanfeng, GUO Shuhai, LI Fengmei, LI Gang. Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model[J]. Chinese Geographical Science, 2013, 23(3): 301-311. doi: 10.1007/s11769-013-0586-9
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