Details zur Publikation |
| Kategorie | Textpublikation |
| Referenztyp | Buchkapitel |
| Titel (primär) | Modelling catchment-scale nitrate transport using a combined process based and data-driven approach |
| Titel (sekundär) | Water quality and sediment behaviour of the future: predictions for the 21st century (Proceedings of the IAHS symposia at the IUGG General Assembly in Perugia, Italy) |
| Autor | Shrestha, R.R.; Rode, M. |
| Quelle | IAHS Publication |
| Erscheinungsjahr | 2007 |
| Department | ASAM; HYMOD |
| Band/Volume | 314 |
| Seite von | 125 |
| Seite bis | 134 |
| Sprache | englisch |
| Keywords | artificial neural network; hybrid model; nitrate transport; water balance |
| Abstract | Diffuse nitrate pollution in catchments is mainly driven by hydrological flow components characterised by complex relationships with streamflow nitrate concentration. This paper demonstrates a combined process-based–artificial neural network (ANN) approach for the simulation of streamflow nitrate concentration based on the relationships between driving and resultant variables. The simulated hydrological flow components from a process based WaSiM-ETH model, together with observations, are used to train two different ANNs. The results show a reasonable match between observed and simulated streamflow and nitrate-N concentration. The ANN with temperature as an input performed better than the ANN without it, indicating the effect of seasonal variability. Nash-Sutcliffe coefficients of 0.746 and 0.856 were obtained for streamflow in calibration and test periods, respectively, while these coefficients were 0.819, 0.629 and 0.627 for nitrate- N concentration in training, cross-validation and test periods, respectively. Hence, the combined approach offers an effective and efficient methodology for modelling catchment scale nitrate dynamics. |
| dauerhafte UFZ-Verlinkung | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=2319 |
| Shrestha, R.R., Rode, M. (2007): Modelling catchment-scale nitrate transport using a combined process based and data-driven approach Water quality and sediment behaviour of the future: predictions for the 21st century (Proceedings of the IAHS symposia at the IUGG General Assembly in Perugia, Italy) IAHS Publ. 314 International Association of Hydrological Sciences (IAHS), Wallingford, Oxfordshire, p. 125 - 134 |
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