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Titlebook: Entropy-Based Parameter Estimation in Hydrology; Vijay P. Singh Book 1998 Springer Science+Business Media Dordrecht 1998 environment.envir

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Generalized Extreme Value Distribution,5) of Great Britain. The GEV distribution is the most widely accepted distribution for describing flood frequency data from the United Kingdom (Sinclair and Ahmad, 1988) and has also become popular elsewhere (Otten and van Montfort, 1980; Prescott and Walden, 1980, 1983; Turkman, 1985; Hosking et al
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Weibull Distribution,nents. Its applications have been reported frequently in hydrology and meteorology. Grace and Eagleson (1966) fitted this distribution to the wet and dry sequences and obtained satisfactory results. Rao and Chenchayya (1974) applied it to short-term increment urban precipitation characteristics in v
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Beta Distribution,fying these parameters are factors of safety or safety indexes, variables representing strength of materials, intensity of loads, etc. Harr (1977) demonstrated the ability of the beta (or Pearson type 1) distribution to approximate most of the geotechnical parameters. Obini and Bourdeau (1985) simpl
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Two-Parameter Pareto Distribution, and biological processes (Saksena and Johnson, 1984), reliability studies and the analysis of environmental extremes. Davison and Smith (1990) pointed out that the Pareto distribution might form the basis of a broad modeling approach to high-level exceedances. DuMouchel (1983) applied it to estimat
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Creating a Multidisciplinary Clinic,um, rivers follow the minimum rate of energy dissipation. Furthermore, a river constantly adjusts its cross-sectional geometry and longitudinal profile to accommodate the influx of water and sediment coming from its drainage basin, and this adjustment is in accordance with the principle of maximum e
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