Preprints
https://doi.org/10.5194/hessd-4-2307-2007
https://doi.org/10.5194/hessd-4-2307-2007
23 Jul 2007
 | 23 Jul 2007
Status: this preprint was under review for the journal HESS but the revision was not accepted.

Computationally efficient calibration of WATCLASS Hydrologic models using surrogate optimization

M. Kamali, K. Ponnambalam, and E. D. Soulis

Abstract. In this approach, exploration of the cost function space was performed with an inexpensive surrogate function, not the expensive original function. The Design and Analysis of Computer Experiments(DACE) surrogate function, which is one type of approximate models, which takes correlation function for error was employed. The results for Monte Carlo Sampling, Latin Hypercube Sampling and Design and Analysis of Computer Experiments(DACE) approximate model have been compared. The results show that DACE model has a good potential for predicting the trend of simulation results. The case study of this document was WATCLASS hydrologic model calibration on Smokey-River watershed.

M. Kamali, K. Ponnambalam, and E. D. Soulis
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
M. Kamali, K. Ponnambalam, and E. D. Soulis
M. Kamali, K. Ponnambalam, and E. D. Soulis

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