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dc.contributor.authorTjia, Dewi
dc.contributor.supervisorDr Ritu Guptaen_US
dc.date.accessioned2017-11-03T04:27:18Z
dc.date.available2017-11-03T04:27:18Z
dc.date.issued2016
dc.identifier.urihttp://hdl.handle.net/20.500.11937/57347
dc.description.abstract

Four history matching methods were used to calibrate the parameters of the LUCICAT model for three catchments in Western Australia. The methods used were ant colony optimization (ACOR and DACOR), Robust Parameter Estimation and Gauss Levenberg Marquadt. These methods were applied directly and indirectly, and in the latter case multidimensional Kriging and artificial neural networks were used to build proxy models for LUCICAT. All HM methods performed favourably well.

en_US
dc.publisherCurtin Universityen_US
dc.titleStatistical Methods for History Matching of Hydrological Modelen_US
dc.typeThesisen_US
dcterms.educationLevelPhDen_US
curtin.departmentMathematics and Statisticsen_US
curtin.accessStatusOpen accessen_US
curtin.facultyScience and Engineeringen_US


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