By Vujica Yevjevich, Nilgun Bayraktar Harmancioglu (auth.), Vijay P. Singh (eds.)
Floods represent a continual and major problem during the usa and plenty of different components of the realm. they're chargeable for losses amounting to billions of greenbacks and rankings of deaths every year. nearly all elements of the nation--coastal, moun tainous and rural--are laid low with them. features of the matter of flooding that experience lengthy been themes of clinical inquiry are flood frequency and probability analyses. Many new, even superior, tech niques have lately been constructed for acting those analyses. however, genuine adventure issues out that the frequency of say a IOO-year flood, in lieu of being encountered at the commonplace as soon as in a single hundred years, might be as low as as soon as in 25 years. it truly is as a result acceptable to pause and ask the place we're, the place we're going and the place we needs to be going with reference to the expertise of flood frequency and danger analyses. a method to deal with those ques tions is to supply a discussion board the place humans from all quarters of the realm can gather, talk about and percentage their event and services bearing on flood frequency and threat analyses. this can be what con stituted the incentive for organizing the overseas Symposium on Flood Frequency and threat Analyses held may perhaps 14-17, 1986, at Louisiana nation Universj. ty, Baton Rouge, Louisiana.
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Additional info for Application of Frequency and Risk in Water Resources: Proceedings of the International Symposium on Flood Frequency and Risk Analyses, 14–17 May 1986, Louisiana State University, Baton Rouge, U.S.A
If we assume that the m candidste flood distributions have flood-like properties, then it is reasonable to assume a diffuse prior model probability, namely 1 m P (Mi is true) i 1, .... , m Unless one finds a flood model with a dominant posterior probability of being true, it, makes Sense to incorporate explicitly model uncertainty into a flood frequency analysis. , 1977; Tung and Mays, 1981a). data) is the marginal or Bayesian pdf for the ith model given by Although this approach handles model uncertainty, judgements, nevertheless, have to be made as to which models to include in the composite set.
The continuous retention rate represents the infiltration capacity when the soil becomes saturated. It is controlled by the capability of lower soil horizons to transmit water downward, and may be determined by a trial and error process if rainfall and corresponding runoff data are available. S. Bureau of Reclamation, 1973). The runoff curve method uses soil and ground cover data for estimation of retention losses. S. S. Bureau of Reclamation, 1973). 2. Unit hydrographs. A unit hydrograph is the hydrograph resulting from one unit of rainfall excess over a specified duration.
Such extrapolations are very much affected by model and parameter uncertainty. This review reflects on the contributions that Bayesian theory has made, and can possibly make, in managing this uncertainty. Some of the issues examined from a Bayesian perspective include the choice of a flood distribution, the exploitation of gauged and historic site information possibly affected by measurement error, development of regional models and the pooling of site and regional information. 1. INTRODUCTION The late sixties and early seventies saw the first applications of Bayesian ideas to flood frequency analysis.
Application of Frequency and Risk in Water Resources: Proceedings of the International Symposium on Flood Frequency and Risk Analyses, 14–17 May 1986, Louisiana State University, Baton Rouge, U.S.A by Vujica Yevjevich, Nilgun Bayraktar Harmancioglu (auth.), Vijay P. Singh (eds.)