Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
WAVELET-ANN MODEL FOR DIFFUSE POLLUTION PREDICTION IN STREAMS
The use of herbicides, pesticides, and other chemicals in agricultural fields increases the concentration of chemicals in streams which severely affects the health of human and environment. The transport of chemical pollutants into river or streams is not straight forward but complex function of applied chemicals and land use patterns in a given river or stream basin which are difficult to quantify accurately. Development of models based on temporal observations may improve understanding the underlying the hydrological processes in such complex transports. Recently, artificial neural network (ANN) as a non-linear inter-extrapolator is extensively used by hydrologists. Present work utilized temporal patterns extracted from temporal observations using wavelet theory. These patterns are then utilized by an artificial neural network (ANN). The wavelet-ANN conjunction model is then utilized to predict the monthly concentration of diffuse pollution in a stream. The application of the proposed methodology is illustrated with real data to estimate the diffuse pollution concentration in a stream system due to application of a typical herbicide, atrazine, in corn fields.
WAVELET-ANN MODEL FOR DIFFUSE POLLUTION PREDICTION IN STREAMS
The use of herbicides, pesticides, and other chemicals in agricultural fields increases the concentration of chemicals in streams which severely affects the health of human and environment. The transport of chemical pollutants into river or streams is not straight forward but complex function of applied chemicals and land use patterns in a given river or stream basin which are difficult to quantify accurately. Development of models based on temporal observations may improve understanding the underlying the hydrological processes in such complex transports. Recently, artificial neural network (ANN) as a non-linear inter-extrapolator is extensively used by hydrologists. Present work utilized temporal patterns extracted from temporal observations using wavelet theory. These patterns are then utilized by an artificial neural network (ANN). The wavelet-ANN conjunction model is then utilized to predict the monthly concentration of diffuse pollution in a stream. The application of the proposed methodology is illustrated with real data to estimate the diffuse pollution concentration in a stream system due to application of a typical herbicide, atrazine, in corn fields.
WAVELET-ANN MODEL FOR DIFFUSE POLLUTION PREDICTION IN STREAMS
Singh, Raj Mohan (Autor:in)
ISH Journal of Hydraulic Engineering ; 17 ; 1-11
01.01.2011
11 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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