Document Detail


Uncertainty analysis at large scales: limitations and subjectivity of current practices--a water quality case study.
MedLine Citation:
PMID:  17898438     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Uncertainty analysis for large-scale model studies is a challenging activity that requires a different approach to uncertainty analysis at a smaller scale. However, in river basin studies, the practice of uncertainty analysis at a large scale is mostly derived from practice at a small scale. The limitations and inherent subjectivity of some current practices and assumptions are identified, based on the results of a quantitative uncertainty analysis exploring the effects of input data and parameter uncertainty on surface water nutrient concentration. We show that: (i) although the results from small- scale sensitivity analysis are often applied at larger scales, this is not always valid; (ii) the current restriction of the uncertainty assessment to uncertainty types with a strong evidence base gives structurally conservative estimates; (iii) uncertainty due to bias is usually not assessed, but it may easily outweigh the effects of variability; (iv) the uncertainty bandwidth may increase for higher aggregation levels, although the opposite is the standard assumption.
Authors:
R M Bijlsma; P Groenendijk; M W Blind; A Y Hoekstra
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Water science and technology : a journal of the International Association on Water Pollution Research     Volume:  56     ISSN:  0273-1223     ISO Abbreviation:  Water Sci. Technol.     Publication Date:  2007  
Date Detail:
Created Date:  2007-09-27     Completed Date:  2008-02-05     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9879497     Medline TA:  Water Sci Technol     Country:  England    
Other Details:
Languages:  eng     Pagination:  1-9     Citation Subset:  IM    
Affiliation:
Department of Water Engineering & Management, University of Twente, PO Box 217, 7500, AE, Enschede, The Netherlands. r.m.bijlsma@utwente.nl
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MeSH Terms
Descriptor/Qualifier:
Fresh Water / analysis*
Models, Theoretical*
Risk Assessment / methods,  statistics & numerical data
Rivers
Uncertainty
Water Pollution / analysis

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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