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Uniqueness and observability of conceptual rainfall‐runoff model parameters: The percolation process examined

Uniqueness and observability of conceptual rainfall‐runoff model parameters: The percolation... Many researchers have expressed concerns regarding the uniqueness of parameter estimates for conceptual rainfall‐runoff (R‐R) models obtained through calibration. Recent studies (Sorooshian et al., this issue; Sorooshian and Gupta, this issue) have revealed that even though stochastic parameter estimation techniques can help, the problems are not all due to inefficiencies in the calibration techniques used but are caused by the manner in which the model is structurally formulated. Thus even when calibrated under ideal conditions (simulation studies), it is often impossible to obtain unique estimates for the parameters. It is possible to resolve this problem, at least in part, by appropriate reparameterizations of the pertinent model equations. In this paper the percolation equation of the soil moisture accounting model of the National Weather Service River Forecast System (SMA‐NWSRFS) will be discussed. It is shown that a logical reparameterization of this equation can result in conditions that improve the chances of obtaining unique parameter estimates. It is believed that these results have implications for other conceptual R‐R models in which similar approaches are used in the representation of the percolation/infiltration process. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Water Resources Research Wiley

Uniqueness and observability of conceptual rainfall‐runoff model parameters: The percolation process examined

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References (9)

Publisher
Wiley
Copyright
Copyright © 1983 by the American Geophysical Union.
ISSN
0043-1397
eISSN
1944-7973
DOI
10.1029/WR019i001p00269
Publisher site
See Article on Publisher Site

Abstract

Many researchers have expressed concerns regarding the uniqueness of parameter estimates for conceptual rainfall‐runoff (R‐R) models obtained through calibration. Recent studies (Sorooshian et al., this issue; Sorooshian and Gupta, this issue) have revealed that even though stochastic parameter estimation techniques can help, the problems are not all due to inefficiencies in the calibration techniques used but are caused by the manner in which the model is structurally formulated. Thus even when calibrated under ideal conditions (simulation studies), it is often impossible to obtain unique estimates for the parameters. It is possible to resolve this problem, at least in part, by appropriate reparameterizations of the pertinent model equations. In this paper the percolation equation of the soil moisture accounting model of the National Weather Service River Forecast System (SMA‐NWSRFS) will be discussed. It is shown that a logical reparameterization of this equation can result in conditions that improve the chances of obtaining unique parameter estimates. It is believed that these results have implications for other conceptual R‐R models in which similar approaches are used in the representation of the percolation/infiltration process.

Journal

Water Resources Research – Wiley

Published: Feb 1, 1983

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