Comparison Between the Kinematic Wave Model and the Storage Function Runoff Model

Tanaka, Gaku; Fujita, Mutsuhiro; Kudo, Mutsunobu; Uchijima, Kunihide

doi:10.2208/jscej.1999.614_21

Cited by 4 publications

(6 citation statements)

References 8 publications

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“…An approach to distributed hydrological model development combining a GIS (Geographic Information System) with the kinematic wave model has been used widely in rainfall−runoff modeling for basins of different scales (Chua, Wong, & Sriramula, ; Yomoto & Islam, ). The kinematic wave model is based on the resistance law of river channels; it is a physically based model, as it uses physical parameters to characterize a basin (Tanaka, ; Tanaka, Fujita, & Kudo, ). The energy budget approach has been mostly used in snowmelt calculation (Herrero, Polo, Moñino, & Losada, ; Ohara & Kavvas, ).…”

Section: Methodsmentioning

confidence: 99%

Parameter sensitivity analysis for a physically based distributed hydrological model based on Morris' screening method

Huang

Wen

Wang

et al. 2020

J Flood Risk Management

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Achieving accurate parameter calibration is a relatively difficult problem in development and application of physically based distributed hydrological models. In the current research, Morris' screening method (one factor at a time [OAT]) and an error evaluation calibration were jointly adopted for parameter sensitivity analysis (PSA) for a distributed hydrological model developed for a single mountainous terrain. The results indicated that (1) the order of sensitivity of the parameters for rainfall−runoff calculation is thickness of the first soil layer, coefficient of permeability, infiltration velocity, porosity, and coefficient of roughness; (2) the order of the parameters for snowmelt calculation is bulk transfer coefficient, temperature correction factor, and albedo of snow cover layer surface; and (3) the value change of each parameter of the first layer in the soil vertical profile mainly impacts the numerical value of discharge of the surface flow, while the value change of each parameter of the second layer impacts the numerical value of discharge of the surface flow less, but results in the peak misplacement to some extent. The results are expected to provide methodology references for PSA and calibration for the physically based distributed hydrological model which developed for mountainous or otherwise single terrain. K E Y W O R D Sbasin, hydrological modelling, Morris' screening method (OAT), physical parameter, sensitivity analysis, surface water

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Section: Methodsmentioning

confidence: 99%

Parameter sensitivity analysis for a physically based distributed hydrological model based on Morris' screening method

Huang

Wen

Wang

et al. 2020

J Flood Risk Management

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“…However, observed rainfall that causes¯oods is a non-stationary and mutually dependant random variable. Therefore, the results obtained by Fujita et al [1] and Tanaka et al [2] donot provide sucient solutions. In this paper, we assume that observed rainfall belongs to the ®rst-order auto-regressive process, AR (1).…”

Section: Introductionmentioning

confidence: 95%

“…Fujita et al [1] used the simplest storage function runo model and proposed a method for estimating the PDF by calculating the ®rst four moments of discharge on the condition that rainfall inputs were mutually independent. By applying the new method proposed by * Fujita et al [1], Tanaka et al [2] estimated the ®rst four moments of discharge from several runo models, such as the Kinematic wave model and two types of storage function runo model obtained from lumping the Kinematic wave model. However, observed rainfall that causes¯oods is a non-stationary and mutually dependant random variable.…”

Section: Introductionmentioning

confidence: 99%

Non-Stationary and Mutually Dependent Rainfall Input and Its Stochastic Response

Tanaka

Fujita

Kaido

et al. 2002

Systems Analysis Modelling Simulation

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Observed rainfall is a non-stationary and mutually dependant random variable. Based on the condition that the stochastic characteristics of rainfall are known, we derived dierential equations whose solutions provide the ®rst four moments of discharge output from a storage function runo model. The validity of the derived dierential equations was cross-checked by a simulation method. The results showed that it is possible to obtain the probability density function of discharge from the calculated ®rst four moments of discharge.

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“…F : average rainfall intensity By substituting egs. (4), (5) and (6) into egs. (1) and(2), the following equations can be obtained.…”

Section: St Venant Equations and Related Modelsmentioning

confidence: 99%

“…Originally, the EFRM was first used in control engineering for analyzing nonlinear elements such as threshold and saturation. The notion of EFRM had already been used by Fujita and Kudo (1995) 4, and Fujita (1998, 1999) 5,6) to describe the characteristics of runoff models. These studies focused only on the gain characteristics of storage function model and kinematic wave model.…”

Section: Introductionmentioning

confidence: 99%

Application of the Equivalent Frequency Response Method to Nonlinear Runoff System

Hamouda

Fujita

2001

Doboku Gakkai Ronbunshu

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This paper proposes a new approach using the Equivalent Frequency Response Method (EFRM) for analyzing St. Venant model for unsteady one-dimensional flow along with its related models such as kinematic wave, diffusion wave and gravity wave models with two different lower stream boundary conditions. It is possible to calculate the gain, time lag, and impulse response function by the proposed method. Moreover, a new criterion is presented for evaluating the validity of each model for a range of Froude and kinematic wave number based on the obtained impulse response function. Finally, this paper suggests the possibility of applications of EFRM to real runoff analysis.

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Comparison Between the Kinematic Wave Model and the Storage Function Runoff Model

Cited by 4 publications

References 8 publications

Parameter sensitivity analysis for a physically based distributed hydrological model based on Morris' screening method

Parameter sensitivity analysis for a physically based distributed hydrological model based on Morris' screening method

Non-Stationary and Mutually Dependent Rainfall Input and Its Stochastic Response

Application of the Equivalent Frequency Response Method to Nonlinear Runoff System

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