A global sensitivity analysis tool for the parameters of multi-variable catchment models

A. van Griensven, T. Meixner, S. Grunwald, T. Bishop, M. Diluzio, R. Srinivasan

Research output: Contribution to journalArticle

747 Scopus citations

Abstract

Over-parameterisation is a well-known and often described problem in hydrological models, especially for distributed models. Therefore, methods to reduce the number of parameters via sensitivity analysis are important for the efficient use of these models. This paper describes a novel sampling strategy that is a combination of latin-hypercube and one-factor-at-a-time sampling that allows a global sensitivity analysis for a long list of parameters with only a limited number of model runs. The method is illustrated with an application of the water flow and water quality parameters of the distributed water quality program SWAT, considering flow, suspended sediment, total nitrogen, total phosphorus, nitrate and ammonia outputs at several locations in the Upper North Bosque River catchment in Texas and the Sandusky River catchment in Ohio. The application indicates that the methodology works successfully. The results also show that hydrologic parameters are dominant in controlling water quality predictions. Finally, the sensitivity results are not transferable between basins and thus the analysis needs to be conducted separately for each study catchment.

Original languageEnglish (US)
Pages (from-to)10-23
Number of pages14
JournalJournal of Hydrology
Volume324
Issue number1-4
DOIs
StatePublished - Jun 15 2006
Externally publishedYes

Keywords

  • Model parameters
  • River
  • Sensitivity analysis
  • Water quality

ASJC Scopus subject areas

  • Water Science and Technology

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