Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (leaves 183-189).

It is the purpose of this investigation to determine the amount of rain fall to be expected in various areas of the State of Florida. To date there are no published papers which are concerned with this aspect of rain fall in the state. Although this study is mainly concerned with the amount of rain fall which may be expected at ten per cent intervals throughout the state, it is probable that it has many ramifications which will be of value in other phases of water research. In speaking of the ten per cent intervals of time we are actually dealing with percentages of the total time. Hence, 25 years out of 50 years should not be construed to mean the next 25 years out of the next 50 years. / Typescript. / "August, 1949." / "Submitted to the Graduate Council of Florida State University in partial fulfillment of the requirements for the degree of Master of Science under Plan II." / Advisor: LeRoy Babcock, Professor Directing Paper. / Includes bibliographical references (leaf 58).

published_or_final_version / Geography and Geology / Doctoral / Doctor of Philosophy

Thesis. 1979. M.Arch--Massachusetts Institute of Technology. Dept. of Architecture. / MICROFICHE COPY AVAILABLE IN ARCHIVES AND ROTCH. / Includes bibliographical references. / M.Arch

The subject of this study is rainfall-runoff forecasting and flood warning. Denote by (X(t),Y(t)) a sequence of equally spaced bivariate random variables representing rainfall and runoff, respectively. A flood is said to occur at time period (n + 1) if Y(n + 1) > T where T is a fixed number. The main task of flood warning is that of deciding whether or not to issue a flood alarm for the time period n + 1 on the basis of the past observations of rainfall and runoff up to and including time n. With each decision, warning or no warning, there is a certain probability of an error (false alarm or no alarm). Using notions from classical decision theory, the optimal solution is the decision that minimizes Bayes risk. In Chapter 1 a more precise definition of flood warning will be given. A critical review (Chapter 2) of classical methods for forecasting used in hydrology reveals that these methods are not adequate for flood warning and similar types of decision problems unless certain Gaussian assumptions are satisfied. The purpose of this study is to investigate the application of a nonparametric technique referred to as the k-nearest neighbor (k-NN) methods to flood warning and least squares forecasting. The motivation of this method stems from recent results in statistics which extends nonparametric methods for inferring regression functions in a time series setting. Assuming that the rainfall-runoff process can be cast in the framework of Markov processes then, with some additional assumptions, the k-NN technique will provide estimates that converge with an optimal rate to the correct decision function. With this in mind, and assuming that our assumptions are valid, then we can claim that this method will, as the historical record grows, provide the best possible estimate in the sense that no other method can do better. A detailed description of the k-NN estmator is provided along with a scheme for calibration. In the final chapters, the forecasts of this new method are compared with the forecasts of several other methods commonly used in hydrology, on both real and simulated data.

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Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1979. / Bibliography: leaves 87-93. / Microfiche. / xvi, 218 leaves ill., maps 29 cm

Title page, abstract and table of contents only. The complete thesis in print form is available from the University of Adelaide Library. / This thesis describes the development of a new technique which significantly extends the applicability of stochastic point rainfall models that require historical data for calibration. The technique is demonstrated using a high-resolution point rainfall model based on wet-dry alternating storm events. A model has been produced that is well defined and can be vigorously compared against numerous observed statistics in a quantative manner. The rainfall model presented in this thesis can be used to provide accurate synthetic rainfall data at sites with minimal historical rainfall data providing a powerful tool for application in hydrological risk analysis across Australia. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1282259 / Thesis (Ph.D.) -- University of Adelaide, Dept. of Civil and Environmental Engineering, 2007