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Neural Network Modelling of NO3-Time Series from small Headwater Catchments

Title data

Lischeid, Gunnar ; Lange, Holger ; Hauhs, Michael:
Neural Network Modelling of NO3-Time Series from small Headwater Catchments.
In: Kovar, Karel (ed.): Hydrology, water resources and ecology in headwaters : proceedings of the HeadWater'98 Conference held in Meran, Merano, Italy, from 20 to 23 April 1998. - Wallingford : IAHS Press , 1998 . - pp. 467-473 . - (IAHS Publication ; 248 )
ISBN 1901502457

Official URL: Volltext

Abstract in another language

A variety of different processes is known that determine water and solute fluxes in headwater catchments. Water resources management of these systems, however, relies in most cases on empirical experience with respect to its overall response. A promising method to bridge the gap between comprehensive scientific investigations and the need to manage the systems on the basis of limited data sets seems to be the application of artificial neural networks (ANN). Here, time series of N03" concentrations in the runoff of two forested headwater catchments in south Germany are investigated. Furthermore, the application of nonlinear methods presented here reveals a rather intricate behaviour also on the temporal scale, and considerable differences between the two catchments. This demonstrates the validity of ANN as universal descriptive tools.

Further data

Item Type: Article in a book
Refereed: Yes
Additional notes: BAYCEER7214
Institutions of the University: Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling
Faculties > Faculty of Biology, Chemistry and Earth Sciences > Department of Earth Sciences > Chair Ecological Modelling > Chair Ecological Modelling - Univ.-Prof. Dr. Michael Hauhs
Research Institutions > Research Centres > Bayreuth Center of Ecology and Environmental Research- BayCEER
Faculties
Faculties > Faculty of Biology, Chemistry and Earth Sciences
Research Institutions
Research Institutions > Research Centres
Result of work at the UBT: Yes
DDC Subjects: 500 Science
Date Deposited: 30 Sep 2015 05:56
Last Modified: 17 May 2016 08:12
URI: https://eref.uni-bayreuth.de/id/eprint/19968