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

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

Research output: Contribution to journalArticle

698 Citations (Scopus)

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

Fingerprint

sensitivity analysis
water quality
catchment
rivers
hydrologic models
water flow
sampling
ammonia
methodology
nitrates
river
basins
suspended sediment
phosphorus
parameterization
prediction
nitrogen
nitrate
parameter
basin

Keywords

  • Model parameters
  • River
  • Sensitivity analysis
  • Water quality

ASJC Scopus subject areas

  • Soil Science
  • Earth-Surface Processes

Cite this

A global sensitivity analysis tool for the parameters of multi-variable catchment models. / van Griensven, A.; Meixner, Thomas; Grunwald, S.; Bishop, T.; Diluzio, M.; Srinivasan, R.

In: Journal of Hydrology, Vol. 324, No. 1-4, 15.06.2006, p. 10-23.

Research output: Contribution to journalArticle

van Griensven, A, Meixner, T, Grunwald, S, Bishop, T, Diluzio, M & Srinivasan, R 2006, 'A global sensitivity analysis tool for the parameters of multi-variable catchment models', Journal of Hydrology, vol. 324, no. 1-4, pp. 10-23. https://doi.org/10.1016/j.jhydrol.2005.09.008
van Griensven, A. ; Meixner, Thomas ; Grunwald, S. ; Bishop, T. ; Diluzio, M. ; Srinivasan, R. / A global sensitivity analysis tool for the parameters of multi-variable catchment models. In: Journal of Hydrology. 2006 ; Vol. 324, No. 1-4. pp. 10-23.
@article{e940545924744d51b23a4e598c978cc7,
title = "A global sensitivity analysis tool for the parameters of multi-variable catchment models",
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.",
keywords = "Model parameters, River, Sensitivity analysis, Water quality",
author = "{van Griensven}, A. and Thomas Meixner and S. Grunwald and T. Bishop and M. Diluzio and R. Srinivasan",
year = "2006",
month = "6",
day = "15",
doi = "10.1016/j.jhydrol.2005.09.008",
language = "English (US)",
volume = "324",
pages = "10--23",
journal = "Journal of Hydrology",
issn = "0022-1694",
publisher = "Elsevier",
number = "1-4",

}

TY - JOUR

T1 - A global sensitivity analysis tool for the parameters of multi-variable catchment models

AU - van Griensven, A.

AU - Meixner, Thomas

AU - Grunwald, S.

AU - Bishop, T.

AU - Diluzio, M.

AU - Srinivasan, R.

PY - 2006/6/15

Y1 - 2006/6/15

N2 - 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.

AB - 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.

KW - Model parameters

KW - River

KW - Sensitivity analysis

KW - Water quality

UR - http://www.scopus.com/inward/record.url?scp=33646725682&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33646725682&partnerID=8YFLogxK

U2 - 10.1016/j.jhydrol.2005.09.008

DO - 10.1016/j.jhydrol.2005.09.008

M3 - Article

AN - SCOPUS:33646725682

VL - 324

SP - 10

EP - 23

JO - Journal of Hydrology

JF - Journal of Hydrology

SN - 0022-1694

IS - 1-4

ER -