Estimating runoff in ungauged catchments from rainfall, PET and the AWBM model

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Author(s)
Boughton, Walter
Chiew, Francis
Griffith University Author(s)
Year published
2007
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Multiple linear regressions are used to relate average annual runoff to average annual rainfall and areal potential evapotranspiration (PET) using data from 213 catchments grouped according to location in six of the major Drainage Divisions of Australia. A method is presented for estimating daily runoff from daily rainfall data using the AWBM model, which self-calibrates its surface storage parameters to the estimate of average annual runoff from the regressions, and using default values for its baseflow parameters. Two-thirds of the estimates of average annual runoff were within Ჵ% of the actual value. The approach can also ...
View more >Multiple linear regressions are used to relate average annual runoff to average annual rainfall and areal potential evapotranspiration (PET) using data from 213 catchments grouped according to location in six of the major Drainage Divisions of Australia. A method is presented for estimating daily runoff from daily rainfall data using the AWBM model, which self-calibrates its surface storage parameters to the estimate of average annual runoff from the regressions, and using default values for its baseflow parameters. Two-thirds of the estimates of average annual runoff were within Ჵ% of the actual value. The approach can also estimate satisfactorily the monthly and annual runoff series in many catchments, with the simulations being only slightly poorer than those obtained by directly calibrating the AWBM against recorded runoff.
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View more >Multiple linear regressions are used to relate average annual runoff to average annual rainfall and areal potential evapotranspiration (PET) using data from 213 catchments grouped according to location in six of the major Drainage Divisions of Australia. A method is presented for estimating daily runoff from daily rainfall data using the AWBM model, which self-calibrates its surface storage parameters to the estimate of average annual runoff from the regressions, and using default values for its baseflow parameters. Two-thirds of the estimates of average annual runoff were within Ჵ% of the actual value. The approach can also estimate satisfactorily the monthly and annual runoff series in many catchments, with the simulations being only slightly poorer than those obtained by directly calibrating the AWBM against recorded runoff.
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Journal Title
Environmental Modelling & Software
Volume
22
Copyright Statement
© 2007 Elsevier. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal's website for access to the definitive, published version.