WANG Qinggai, ZHAO Xiaohong, YANG Mushui, et al.. Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River, China[J]. Chinese Geographical Science, 2011, 21(6): 646-655.
Citation: WANG Qinggai, ZHAO Xiaohong, YANG Mushui, et al.. Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River, China[J]. Chinese Geographical Science, 2011, 21(6): 646-655.

Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River, China

  • Publish Date: 2011-11-04
  • With the development of industry and agriculture, nitrogen, phosphorus and other nutrients in the Hanshui River greatly
    increase and eutrophication has become an important threat to the water quality of the Hanshui River, especially in the middle and lower
    reaches. The primary objective of this study was to establish the water quality model for the middle and lower reaches of the Hanshui
    River based on the model of MIKE 11. The main pollutants migration and transformation process could be simulated using the water
    quality model. The rainfall-runoff model, hydrodynamic model and water quality model were established using MIKE 11. The pollutants,
    such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), ammonia nitrogen, nitrate nitrogen, phosphorus, dissolved
    oxygen (DO), were simulated and predicted using the above three models. A set of methods computing non-point source pollution load of
    the Hanshui River Basin was proposed in this study. The simulated and observed values of COD, BOD5, ammonia, nitrate, DO, and total
    phosphorus were compared after the parameter calibration of the water quality model. The simulated and observed results match better,
    thus the model can be used to predict water quality in the future for the Hanshui River. The pollution trend could be predicted using the
    water quality model according pollution load generation. It is helpful for government to take effective measures to prevent the water
    bloom and protect water quality in the river.
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通讯作者: 陈斌, bchen63@163.com
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River, China

Abstract: With the development of industry and agriculture, nitrogen, phosphorus and other nutrients in the Hanshui River greatly
increase and eutrophication has become an important threat to the water quality of the Hanshui River, especially in the middle and lower
reaches. The primary objective of this study was to establish the water quality model for the middle and lower reaches of the Hanshui
River based on the model of MIKE 11. The main pollutants migration and transformation process could be simulated using the water
quality model. The rainfall-runoff model, hydrodynamic model and water quality model were established using MIKE 11. The pollutants,
such as chemical oxygen demand (COD), biochemical oxygen demand (BOD), ammonia nitrogen, nitrate nitrogen, phosphorus, dissolved
oxygen (DO), were simulated and predicted using the above three models. A set of methods computing non-point source pollution load of
the Hanshui River Basin was proposed in this study. The simulated and observed values of COD, BOD5, ammonia, nitrate, DO, and total
phosphorus were compared after the parameter calibration of the water quality model. The simulated and observed results match better,
thus the model can be used to predict water quality in the future for the Hanshui River. The pollution trend could be predicted using the
water quality model according pollution load generation. It is helpful for government to take effective measures to prevent the water
bloom and protect water quality in the river.

WANG Qinggai, ZHAO Xiaohong, YANG Mushui, et al.. Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River, China[J]. Chinese Geographical Science, 2011, 21(6): 646-655.
Citation: WANG Qinggai, ZHAO Xiaohong, YANG Mushui, et al.. Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River, China[J]. Chinese Geographical Science, 2011, 21(6): 646-655.

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