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After five decades, the field of Statistical Hydrology continues to evolve and remains a very active area of investigation. Researchers continue to examine various distributions, methods of estimation of parameters, and problems related to regionalization. However, much of this research appears in journals and reports and usually in a form not easily accessible to practitioners and students. Flood Frequency Analysis answers this need by presenting the most popular and promising distributions and estimation procedures in a unified format. It offers the details that provide the basis for the computations, and illustrates each procedure with real data.
Reliable estimates of streamflow characteristics are needed for planning, design, and operation of works for providing water supplies and for protection from flooding. This book brings together some of the most useful estimation methods - those that are simple, practical, and require only commonly available or readily obtainable data, and which give results comparable in accuracy with those derived from more sophisticated methods. The author describes how streamflow data are collected, how the characteristics are computed, how they are changed by man's activities, and how they are used in planning and design. Chapters describing statistical principles and techniques, and the effects of various climatic and physiographic factors on streamflow are included. The analytical methods are described in sufficient detail that the reader can apply them to his data. Further applications and other techniques are referred to in bibliographies.
This book is the first complete account of the L-moment approach to regional frequency analysis of environmental extremes.
The objective of frequency analysis in a hydrologic context is to infer the probability that various size events will be exceeded or not exceeded from a given sample of recorded events. Two basic problems exist for most hydrologic applications. First the sample is usually small, by statistical standards, resulting in uncertainty as to the true probability. And secondly, a single theoretical frequency distribution does not always fit a particular data-type equally well in all applications. This manual provides guidance in fitting frequency distributions and construction of confidence limits. Techniques are presented which can possibly reduce the errors caused by small sample sizes. Also, some types of data are noted which usually do not fit any theoretical distributions.