Direct relationships of discharges to the mean and standard deviation of the intervals between their exceedences |
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| Authors: | Arie Ben-Zvi Benjamin Azmon |
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| Institution: | 1. Sami Shamoon College of Engineering, Basel &2. Byalik Streets , Beer Sheva, 84100, Israel;3. Israel Hydrological Service, PO Box 36118 , Jerusalem, 91360, Israel ariehaya@zahav.net.il;5. Israel Hydrological Service , Haifa, Israel |
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| Abstract: | Abstract This article paves a way for assessing flood risk by the use of two-parameter distributions, for the intervals between threshold exceedences rather than by the traditional exponential distribution. In a case study, the apparent properties of intervals between exceedences of runoff events differ from those anticipated for exponentially distributed series. A procedure is proposed to relate two statistical parameters of the intervals to threshold discharges. It considers partial duration series (PDS) with thresholds equal to all high enough observed discharges. To avoid unnecessary assumptions on the behaviour of those parameters and effects of dependence between parameters for different PDS, a non-parametric trend-free pre-whitened scheme is applied. It leads to power-law relationships between a discharge and the mean and standard deviation of the intervals between its exceedences. Predicted mean inter-exceedence intervals, for the highest observed discharges at the stations, are closer to the observational periods than those predicted by GEV distributions fitted to AMS, and by GP distributions to fitted PDS. In the present case, the latter predictions are longer than the observational periods whereas some of the predicted mean inter-exceedences are shorter than the corresponding observational periods and some others are longer. Citation Ben-Zvi, A. & Azmon, B. (2010) Direct relationships of discharges to the mean and standard deviation of the intervals between their exceedences. Hydrol. Sci J. 55(4), 565–577. |
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| Keywords: | runoff events inter-arrival intervals partial duration series non-parametric analysis power-law relationships exponential distribution Israel |
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