流域污染负荷水质响应的时空数值源解析方法研究

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Abstract

A new method, Numerical Source Apportionment (NSA) approach,was proposed based on the widely applied water quality model, The Environmental Fluid Dynamics Code (EFDC), to get the source component of pollutants, theoretically for any location of the lake at any time. The main idea behind was to take partial derivative of water quality equation with respect to each polluting source. After that, a set of partial differential equations were derived from one water quality partial differential equation. These equations were then solved together with hydrodynamic model in EFDC. As a result, by running model only one time, the contribution of each polluting source at each spatial and temporal point could be achieved. Generalized Lake Fuxian model was taken to validate NSA. Source apportionment results of NSA are coordinate with traditional perturbation method, which validated NSA method. On the other hand, for there were 34independent polluting source in numerical case study, to get source apportionment results traditional perturbation method had to run model for 35 times while NSA only required one time which indicated NSA has obvious advantage on computation efficiency. Further analysis showed NSA could provide more precise description on the dynamic of source apportionment.

Key words： numerical source apportionment environmental fluid dynamics code (EFDC) water quality response load reduction spatial and temporal resolution

Received: 25 April 2016

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X52

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	Articles by authors
	ZOU Rui
	SU Han
	CHEN Yan
	YE Rui
	ZHAO Lei
	LIU Yong

Cite this article:

ZOU Rui,SU Han,CHEN Yan等. A numerical source apportionment approach for quantifying the spatial-temporal water quality responses to watershed loadings[J]. CHINA ENVIRONMENTAL SCIENCECE, 2016, 36(12): 3639-3649.

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http://manu36.magtech.com.cn/Jweb_zghjkx/EN/ OR http://manu36.magtech.com.cn/Jweb_zghjkx/EN/Y2016/V36/I12/3639

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[1]	Mcrae C,Love G D,Murray I P,et al.Potential of gas chromatography isotope ratio mass spectrometry to source polycyclic aromatic hydrocarbon emissions[J].Analytical Communications,1996,33(9):331-333.
[2]	张怀成,董捷,王在峰.水污染源源解析研究最新进展[J].中国环境监测,2013,29(1):18-22.
[3]	Watson J G,Chow J C.Source characterization of major emission sources in the Imperial and Mexicali Valleys along the US/Mexico border[J].Science of the Total Environment,2001,276(1-3):33-47.
[4]	Kumru M N,Bakaç M.R-mode factor analysis applied to the distribution of elements in soils from the Aydın basin,Turkey[J].Journal of Geochemical Exploration,2003,77(2):81-91.
[5]	赵洁,徐宗学,刘星才,等.辽河河流水体污染源解析[J].中国环境科学,2013,33(5):838-842.
[6]	李发荣,李玉照,刘永,等.牛栏江污染物源解析与空间差异性分析[J].环境科学研究,2013,26(12):1356-1363.
[7]	Chen P,Li L,Zhang H.Spatio-temporal variations and source apportionment of water pollution in Danjiangkou Reservoir Basin,Central China[J].Water,2015,7(6):2591-2611.
[8]	Wang Q,Wu X,Zhao B,et al.Combined multivariate statistical techniques,Water Pollution Index (WPI) and Daniel Trend Test methods to evaluate temporal and spatial variations and trends of water quality at Shanchong River in the Northwest Basin of Lake Fuxian,China[J].Plos One,2015,10(4):e0118590.
[9]	Gu Q,Wang K,Li J,et al.Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs[J].International Journal of Environmental Research&Public Health,2015,12(10):13179-13194.
[10]	Yuan Z,Guo F,Wei M,et al.Water quality assessment and source identification of Daliao River Basin using multivariate statistical methods.[J].Environmental Monitoring&Assessment,2009,152(1-4):105-121.
[11]	瞿明凯,李卫东,张传荣,等.基于受体模型和地统计学相结合的土壤镉污染源解析[J].中国环境科学,2013,33(5):854-860.
[12]	Bzdusek P A,Christensen E R,Li A,et al.Source apportionment of sediment PAHs in Lake Calumet,Chicago:application of factor analysis with nonnegative constraints[J].Environmental Science&Technology,2004,38(1):97-103.
[13]	王在峰,张水燕,张怀成,等.水质模型与CMB相耦合的河流污染源源解析技术[J].环境工程,2015(2):135-139.
[14]	肖传宁,卢文喜,安永凯,等.基于两种耦合方法的模拟-优化模型在地下水污染源识别中的对比[J].中国环境科学,2015,35(8):2393-2399.
[15]	Ahmadi M,Arabi M,Ii J C A,et al.Toward improved calibration of watershed models:Multisite multiobjective measures of information[J].Environmental Modelling&Software,2014,59:135-145.
[16]	Henry R C.Duality in multivariate receptor models[J].Chemometrics&Intelligent Laboratory Systems,2005,77(1):59-63.
[17]	Hamrick,J.M.A three-dimensional environmental fluid dynamics computer code:theoretical and computational aspects[R].Virginia:Special Report in Applied Marine Science and Ocean Engineering No.317,Virginia Institute of Marine Science,1992.
[18]	Hamrick,J.M.User's manual for the environmental fluid dynamics computer code[R].Virginia:Special Report in Applied Marine Science and Ocean Engineering No.331,Virginia Institute of Marine Science/School of Marine Science,The College of William and Mary,1996.
[19]	邹锐,张晓玲,刘永,等.抚仙湖流域负荷削减的水质风险分析[J].中国环境科学,2013,33(9):1721-1727.
[20]	Dennis R L,Arnold J R,Tonnesen G S,et al.A new response surface approach for interpreting Eulerian air quality model sensitivities[J].Computer Physics Communications,1999,117(1/2):99-112.
[21]	Seigneur C,Tesche T W,Roth P M,et al.Sensitivity of a Complex Urban Air Quality Model to Input Data.[J].Journal of Applied Meteorology,1981,20(1981):1020-1040.