Nonlinear regression approach to evaluate nutrient delivery coefficient
Implementation of the Korean Total Maximum Daily Load Act calls for new tools to quantify nutrient losses from diffuse sources at a river basin district scale. In this study, it was elucidated that the nonlinear regression model (NRM) reduces the uncertainty of the boundary conditions of the water q...
| Veröffentlicht in: | Water science and technology : a journal of the International Association on Water Pollution Research. - 1986. - 53(2006), 2 vom: 15., Seite 271-9 |
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| Format: | Aufsatz |
| Sprache: | English |
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2006
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| Zugriff auf das übergeordnete Werk: | Water science and technology : a journal of the International Association on Water Pollution Research |
| Schlagworte: | Journal Article Water Pollutants Water Pollutants, Chemical Phosphorus 27YLU75U4W Nitrogen N762921K75 |
| Zusammenfassung: | Implementation of the Korean Total Maximum Daily Load Act calls for new tools to quantify nutrient losses from diffuse sources at a river basin district scale. In this study, it was elucidated that the nonlinear regression model (NRM) reduces the uncertainty of the boundary conditions of the water quality model. The NRM was proposed to analyse the delivery coefficients of surface waters and retention coefficients of pollutants. Delivery coefficient of pollution load was considered as a function of two variables: the watershed form ratio, S(f), which is a measurable geomorphologic variable and the retention coefficient, phi, which is an empirical constant representing the basin-wide retarding capacity of pollutant wash-off. This model was applied on the Geum River, one of the major basins in South Korea. The QUAL2E was used to simulate stream water quality using NRM. In this paper, we elucidate the possibility to use a nonlinear regression model for delivery and retention of nutrients in a drainage basin characterized as both data-rich and data-poor, and the magnitude of the nutrient loads and sources has been uncertain for a long time |
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| Beschreibung: | Date Completed 18.08.2006 Date Revised 17.09.2019 published: Print Citation Status MEDLINE |
| ISSN: | 0273-1223 |