title: Uncertainty analysis at large scales: limitations and subjectivity of current practices--a water quality case study.
abstract: 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: Department of Water Engineering & Management, University of Twente, PO Box 217, 7500, AE, Enschede, The Netherlands. r.m.bijlsma@utwente.nl
authors: R M
authors: RM
authors: Bijlsma
authors: P
authors: P
authors: Groenendijk
authors: M W
authors: MW
authors: Blind
authors: A Y
authors: AY
authors: Hoekstra
mesh_terms: D005618:Fresh Water / Q000032:analysis*; D008962:Models, Theoretical; D018570:Risk Assessment / Q000379:methods / Q000706:statistics & numerical data; D045483:Rivers; D035501:Uncertainty; D014876:Water Pollution / Q000032:analysis