Regularized calibration of a distributed hydrological model using available information about watershed properties and signature measures

Prafulla Pokhrel, Hoshin Vijai Gupta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

Physically-based distributed models are increasingly being used to predict the behaviour of hydrological processes in data-sparse regions. However, a model is a simplified representation of the real system and some form of calibration cannot be avoided. Because distributed models have large numbers of parameters to be specified, the resulting parameter estimation problem becomes ill conditioned. In this study we investigate a calibration approach teat uses: (a) a simple form of spatial regularization (using scalar multipliers) to reduce the dimension of the calibration problem, and (b) signature measures targeting specific behavioural response of a watershed system to guide the parameter search towards a more "hydrologically consistent" set of parameters. Signature measures are applied as "regularization constraints", in an approach that is functionally similar to "Tikhonov regularization", and which results in a better-conditioned optimization problem compared to the benchmark case. The approach is demonstrated for the Blue River Basin in Oklahoma, USA.

Original languageEnglish (US)
Title of host publicationIAHS-AISH Publication
Pages20-25
Number of pages6
Volume333
StatePublished - 2009
EventSymposium HS.2 at the Joint Convention of the International Association of Hydrological Sciences, IAHS and the International Association of Hydrogeologists, IAH - Hyderabad, India
Duration: Sep 6 2009Sep 12 2009

Other

OtherSymposium HS.2 at the Joint Convention of the International Association of Hydrological Sciences, IAHS and the International Association of Hydrogeologists, IAH
CountryIndia
CityHyderabad
Period9/6/099/12/09

Fingerprint

watershed
calibration
behavioral response
targeting
river basin
parameter
parameter estimation

Keywords

  • Distributed hydrological model
  • Multicriteria optimization
  • Parameter estimation
  • Regularization

ASJC Scopus subject areas

  • Earth and Planetary Sciences(all)

Cite this

Regularized calibration of a distributed hydrological model using available information about watershed properties and signature measures. / Pokhrel, Prafulla; Gupta, Hoshin Vijai.

IAHS-AISH Publication. Vol. 333 2009. p. 20-25.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Pokhrel, P & Gupta, HV 2009, Regularized calibration of a distributed hydrological model using available information about watershed properties and signature measures. in IAHS-AISH Publication. vol. 333, pp. 20-25, Symposium HS.2 at the Joint Convention of the International Association of Hydrological Sciences, IAHS and the International Association of Hydrogeologists, IAH, Hyderabad, India, 9/6/09.
@inproceedings{dd3dd3762c1e47c3b6bc55a1eae88e48,
title = "Regularized calibration of a distributed hydrological model using available information about watershed properties and signature measures",
abstract = "Physically-based distributed models are increasingly being used to predict the behaviour of hydrological processes in data-sparse regions. However, a model is a simplified representation of the real system and some form of calibration cannot be avoided. Because distributed models have large numbers of parameters to be specified, the resulting parameter estimation problem becomes ill conditioned. In this study we investigate a calibration approach teat uses: (a) a simple form of spatial regularization (using scalar multipliers) to reduce the dimension of the calibration problem, and (b) signature measures targeting specific behavioural response of a watershed system to guide the parameter search towards a more {"}hydrologically consistent{"} set of parameters. Signature measures are applied as {"}regularization constraints{"}, in an approach that is functionally similar to {"}Tikhonov regularization{"}, and which results in a better-conditioned optimization problem compared to the benchmark case. The approach is demonstrated for the Blue River Basin in Oklahoma, USA.",
keywords = "Distributed hydrological model, Multicriteria optimization, Parameter estimation, Regularization",
author = "Prafulla Pokhrel and Gupta, {Hoshin Vijai}",
year = "2009",
language = "English (US)",
isbn = "9781907161049",
volume = "333",
pages = "20--25",
booktitle = "IAHS-AISH Publication",

}

TY - GEN

T1 - Regularized calibration of a distributed hydrological model using available information about watershed properties and signature measures

AU - Pokhrel, Prafulla

AU - Gupta, Hoshin Vijai

PY - 2009

Y1 - 2009

N2 - Physically-based distributed models are increasingly being used to predict the behaviour of hydrological processes in data-sparse regions. However, a model is a simplified representation of the real system and some form of calibration cannot be avoided. Because distributed models have large numbers of parameters to be specified, the resulting parameter estimation problem becomes ill conditioned. In this study we investigate a calibration approach teat uses: (a) a simple form of spatial regularization (using scalar multipliers) to reduce the dimension of the calibration problem, and (b) signature measures targeting specific behavioural response of a watershed system to guide the parameter search towards a more "hydrologically consistent" set of parameters. Signature measures are applied as "regularization constraints", in an approach that is functionally similar to "Tikhonov regularization", and which results in a better-conditioned optimization problem compared to the benchmark case. The approach is demonstrated for the Blue River Basin in Oklahoma, USA.

AB - Physically-based distributed models are increasingly being used to predict the behaviour of hydrological processes in data-sparse regions. However, a model is a simplified representation of the real system and some form of calibration cannot be avoided. Because distributed models have large numbers of parameters to be specified, the resulting parameter estimation problem becomes ill conditioned. In this study we investigate a calibration approach teat uses: (a) a simple form of spatial regularization (using scalar multipliers) to reduce the dimension of the calibration problem, and (b) signature measures targeting specific behavioural response of a watershed system to guide the parameter search towards a more "hydrologically consistent" set of parameters. Signature measures are applied as "regularization constraints", in an approach that is functionally similar to "Tikhonov regularization", and which results in a better-conditioned optimization problem compared to the benchmark case. The approach is demonstrated for the Blue River Basin in Oklahoma, USA.

KW - Distributed hydrological model

KW - Multicriteria optimization

KW - Parameter estimation

KW - Regularization

UR - http://www.scopus.com/inward/record.url?scp=78751676415&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78751676415&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781907161049

VL - 333

SP - 20

EP - 25

BT - IAHS-AISH Publication

ER -