Abstract
AbstractThe effect of global warming (represented by general circulation model monthly rainfall predictions) on the daily rainfall distribution is investigated using a mixed Gamma distribution to estimate the change of rainfall quantiles. A mixed distribution is used to overcome the limitation of conventional frequency analysis, which uses a continuous distribution, as this is not applicable for the assessment of the effects of global warming. To summarize the results: (1) Even though the variation of daily rainfall distribution is high due to the variation of monthly rainfall amounts, the scale parameter and the wet probability of a mixed Gamma distribution are found to be closely related to the monthly rainfall amounts. On the other hand, the shape factor remains almost the same regardless of the monthly rainfall amount. (2) The rainfall quantiles estimated using the daily rainfall data from June to September were found to be the most similar to those using the annual maximum data. (3) Regardless of the increasing uncertainty as the return period becomes longer, flood risk is found to be increasing as a result of global warming. Copyright © 2005 John Wiley & Sons, Ltd.
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