Deterministic-statistical model coupling in a DSS for river-basin management

Jean-Luc de Kok, Martijn J. Booij

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8 Citations (Scopus)
46 Downloads (Pure)

Abstract

This paper presents a method for appropriate coupling of deterministic and statistical models. In the decision-support system for the Elbe river, a conceptual rainfall-runoff model is used to obtain the discharge statistics and corresponding average number of flood days, which is a key input variable for a rule-based model for floodplain vegetation. The required quality of the discharge time series cannot be determined by a sensitivity analysis because a deterministic model is linked to a statistical model. To solve the problem, artificial discharge time series are generated that mimic the hypothetical output of rainfall-runoff models of different accuracy. The results indicate that a feasible calibration of the rainfall-runoff model is sufficient to obtain consistency with the vegetation model in view of its sensitivity to changes in the number of flood days in the floodplains.
Original languageEnglish
Pages (from-to)595-606
Number of pages12
JournalEnvironmental modeling and assessment
Volume14
Issue number5
DOIs
Publication statusPublished - 2009

Fingerprint

basin management
river basin
runoff
rainfall
floodplain
time series
vegetation
decision support system
sensitivity analysis
calibration

Keywords

  • Decision-support system - River-basin management - Appropriate modelling - Model accuracy - Elbe - Floodplain vegetation model - Rainfall-runoff model
  • METIS-236459
  • IR-59987

Cite this

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title = "Deterministic-statistical model coupling in a DSS for river-basin management",
abstract = "This paper presents a method for appropriate coupling of deterministic and statistical models. In the decision-support system for the Elbe river, a conceptual rainfall-runoff model is used to obtain the discharge statistics and corresponding average number of flood days, which is a key input variable for a rule-based model for floodplain vegetation. The required quality of the discharge time series cannot be determined by a sensitivity analysis because a deterministic model is linked to a statistical model. To solve the problem, artificial discharge time series are generated that mimic the hypothetical output of rainfall-runoff models of different accuracy. The results indicate that a feasible calibration of the rainfall-runoff model is sufficient to obtain consistency with the vegetation model in view of its sensitivity to changes in the number of flood days in the floodplains.",
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Deterministic-statistical model coupling in a DSS for river-basin management. / de Kok, Jean-Luc; Booij, Martijn J.

In: Environmental modeling and assessment, Vol. 14, No. 5, 2009, p. 595-606.

Research output: Contribution to journalArticleAcademicpeer-review

TY - JOUR

T1 - Deterministic-statistical model coupling in a DSS for river-basin management

AU - de Kok, Jean-Luc

AU - Booij, Martijn J.

N1 - Open Access

PY - 2009

Y1 - 2009

N2 - This paper presents a method for appropriate coupling of deterministic and statistical models. In the decision-support system for the Elbe river, a conceptual rainfall-runoff model is used to obtain the discharge statistics and corresponding average number of flood days, which is a key input variable for a rule-based model for floodplain vegetation. The required quality of the discharge time series cannot be determined by a sensitivity analysis because a deterministic model is linked to a statistical model. To solve the problem, artificial discharge time series are generated that mimic the hypothetical output of rainfall-runoff models of different accuracy. The results indicate that a feasible calibration of the rainfall-runoff model is sufficient to obtain consistency with the vegetation model in view of its sensitivity to changes in the number of flood days in the floodplains.

AB - This paper presents a method for appropriate coupling of deterministic and statistical models. In the decision-support system for the Elbe river, a conceptual rainfall-runoff model is used to obtain the discharge statistics and corresponding average number of flood days, which is a key input variable for a rule-based model for floodplain vegetation. The required quality of the discharge time series cannot be determined by a sensitivity analysis because a deterministic model is linked to a statistical model. To solve the problem, artificial discharge time series are generated that mimic the hypothetical output of rainfall-runoff models of different accuracy. The results indicate that a feasible calibration of the rainfall-runoff model is sufficient to obtain consistency with the vegetation model in view of its sensitivity to changes in the number of flood days in the floodplains.

KW - Decision-support system - River-basin management - Appropriate modelling - Model accuracy - Elbe - Floodplain vegetation model - Rainfall-runoff model

KW - METIS-236459

KW - IR-59987

U2 - 10.1007/s10666-008-9161-7

DO - 10.1007/s10666-008-9161-7

M3 - Article

VL - 14

SP - 595

EP - 606

JO - Environmental modeling and assessment

JF - Environmental modeling and assessment

SN - 1420-2026

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