Flood modelling in a high country mountain catchment, New Zealand: comparing statistical and deterministic model estimates for ecological flows
Statistical and deterministic modelling estimates of flood magnitudes and frequencies that can affect flood-plain ecology in the upper Ahuriri River catchment, a mountainous high country catchment in the New Zealand Southern Alps, were evaluated. Statistical analysis of 46 years of historical data s...
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Veröffentlicht in: | Hydrological sciences journal 2013-02, Vol.58 (2), p.328-341 |
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Sprache: | eng |
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Zusammenfassung: | Statistical and deterministic modelling estimates of flood magnitudes and frequencies that can affect flood-plain ecology in the upper Ahuriri River catchment, a mountainous high country catchment in the New Zealand Southern Alps, were evaluated. Statistical analysis of 46 years of historical data showed that floods are best modelled by the generalized extreme value and lognormal distributions. We evaluated application of the HEC-HMS model to this environment by modelling flood events of various frequencies. Model results were validated and compared with the statistical estimates. The SCS curve number method was used for losses and runoff generation, and the model was very sensitive to curve number. The HEC-HMS flood estimates matched the statistical estimates reasonably well, and, over all return periods, were on average approximately 1% greater. However, the model generally underestimated flood peaks up to the 25-year event and overestimated magnitudes above this. The results compared well with other regional estimates, including studies based on L-moments, and showed that this catchment has smaller floods than other similarly-sized catchments in the Southern Alps.Editor D. Koutsoyiannis; Associate editor H. AksoyCitation Caruso, B.S., Rademaker, M., Balme, A., and Cochrane, T.A., 2013. Flood modelling in a high country mountain catchment, New Zealand: comparing statistical and deterministic model estimates for ecological flows. Hydrological Sciences Journal, 58 (2), 328–341. |
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ISSN: | 2150-3435 0262-6667 2150-3435 |
DOI: | 10.1080/02626667.2012.752577 |