Estimating Catchment Nutrient Flow with the HBV-NP Model: Sensitivity To Input Data

The dynamic catchment model HBV-N has been further developed by adding routines for phosphorus transport and is now called the HBV-NP model. The model was shown to satisfactorily simulate nutrient dynamics in the Roenneaa catchment (1 900 km super(2)). Its sensitivity to input data was tested, and r...

Full description

Saved in:
Bibliographic Details
Published inAmbio Vol. 34; no. 7; pp. 521 - 532
Main Authors Andersson, L, Rosberg, J, Pers, B C, Olsson, J, Arheimer, B
Format Journal Article
LanguageEnglish
Published 01.11.2005
Online AccessGet full text

Cover

Loading…
More Information
Summary:The dynamic catchment model HBV-N has been further developed by adding routines for phosphorus transport and is now called the HBV-NP model. The model was shown to satisfactorily simulate nutrient dynamics in the Roenneaa catchment (1 900 km super(2)). Its sensitivity to input data was tested, and results demonstrated the increased sensitivity to the selection of input data on a subcatchment scale when compared with the catchment scale. Selection of soil and land use databases was found to be critical in some subcatchments but did not have a significant impact on a catchment scale. Although acceptable on a catchment scale, using templates and generalization, with regards to emissions from point sources and rural households, significantly decreased model performance in certain subcatchments when compared with using more detailed local information. A division into 64 subcatchments resulted in similar model performance at the catchment outlet when compared with a lumped approach. Adjusting the imported matrixes of the regional leaching of nitrogen, from agricultural land, against mean subcatchment water percolation did not have a significant impact on the model performance.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
content type line 23
ObjectType-Feature-2
ISSN:0044-7447
1654-7209
DOI:10.1043/0044-7447(2005)034[0521:ECNFWT]2.0.CO;2