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CRC PUBLICATIONS |
Stochastic Modelling of Daily Rainfall
Senlin Zhou, Ratnasingham Srikanthan and Tom McMahon
Publication Type:
Working Document
This is a publication of the current CRC for Catchment Hydrology
CRC Program:
Climate Variability
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Publication Keywords:
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Abstract / Summary:
Stochastic generation of rainfall data offers an alternative to the use of observed records. This paper presents an evaluation of daily rainfall generation models at 21 stations across Australia. The models are the Transition Probability Matrix (TPM) method, the Daily and Monthly Mixed (DMM) algorithm, and a variation of each model.
A goal of stochastic modelling is to generate synthetic data representative of the statistical characteristics of the historical data. One hundred replicates of length equal to the historical data were generated using the above models. Preliminary assessment of the models suggests that overall both the TPM and DMM models preserved key statistical characteristics of the historical rainfall at the annual, monthly and daily levels. The DMM model was unable to preserve the amounts of rainfall on solitary wet days and the TPM model needed to be modified by the empirical adjustment factor to preserve the annual variability.
CRC Working Document 02/5 is now available for purchase ($22.00 per copy) from the Centre Office and can be downloaded below.
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Centre Office:
CRC for Catchment Hydrology
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