This thesis defines a methodology for the evaluation of the worth of streamflow data using a Bayes risk approach. Using regional streamflow data in a regression analysis, the Bayes risk can be computed by considering the probability of the error in using the regionalized estimates of bridge or culvert design parameters. Cost curves for over- and underestimation of the design parameter can be generated based on the error of the estimate. The Bayes risk can then be computed by integrating the probability of estimation error over the cost curves. The methodology may then be used to analyze the regional data collection effort by considering the worth of data for a record site relative to the other sites contributing to the regression equations. The methodology is illustrated by using a set of actual streamflow data from Missouri. The cost curves for over- and underestimation of the streamflow design parameter for bridges and culverts are hypothesized so that the Bayes risk might be computed and the results of the analysis discussed. The results are discussed by demonstrating small sample bias that is introduced into the estimate of the design parameter for the construction of bridges and culverts. The conclusions are that the small sample bias in the estimation of large floods can be substantial and that the Bayes risk methodology can evaluate the relative worth of data when the data are used in regionalization.

No description available.

Thesis (M.S.)--University of Nevada, Reno, 2006. / "Fall, 2006." Includes bibliographical references (leaves 66-67). Online version available on the World Wide Web. Library also has microfilm. Ann Arbor, Mich. : ProQuest Information and Learning Company, [2006]. 1 microfilm reel ; 35 mm.

Thesis (Ph. D.)., Memorial University of Newfoundland, 1998. / Bibliography: leaves 193-201.

Thesis (Ph. D.)--Florida State University, 2006. / Advisor: James B. Elsner, Florida State University, College of Social Sciences, Dept. of Geography. Title and description from dissertation home page (Sept. 19, 2006). Document formatted into pages; contains x, 90 pages. Includes bibliographical references.

Most of the research was sponsored by the U.S. Geological Survey.

Reservoir spillways are designed to pass extreme flood events without significant damage. For Category A dams in the UK (whereby a breach will endanger lives in a community), designs are based on the Probable Maximum Flood (PMF) arising from the critical duration Probable Maximum Precipitation (PMP). This may occur in the winter, coupled with snowmelt, or in the summer when more heat for convection is available. This thesis details an analysis of 20 extreme rainfall events which occurred in the UK in the past 15 years and were observed by radar. Storm efficiencies have been determined in a Lagrangian frame of reference for these events and used as input into a storm model to determine the corresponding PMP. Results show that while the peak rainfall rates are somewhat less with the storm model than suggested by the NERC FSR (current UK guidelines), the overall volume of rainfall is slightly greater resulting in differences in the maximum storage requirement of the reservoir.

There is a frequent need for estimates of design floods by hydrologists and engineers for the design of hydraulic structures. There are various techniques for estimating these design floods which are dependent largely on the availability of data. The two main approaches to design flood estimation are categorised as methods based on the analysis of floods and those based on rainfall-runoff relationships. Amongst the methods based on the analysis of floods, regional flood frequency analysis is seen as a reliable and robust method and is the recommended approach. Design event models are commonly used for design flood estimation in rainfall-runoff based analyses. However, these have several simplifying assumptions which are important in design flood estimation. A continuous simulation approach to design flood estimation has many advantages and overcomes many of the limitations of the design event approach. A major concern with continuous simulation using a hydrological model is the scale at which should take place. According to Martina (2004) the “level” of representation that will preserve the “physical chain” of the hydrological processes, both in terms of scale of representation and level of description of the physical parameters for the modelling process, is a critical question to be addressed. The objectives of this study were to review the literature on different approaches commonly used in South Africa and internationally for design flood estimation and, based on the literature, assess the potential for the use of a continuous simulation approach to design flood estimation. Objectives of both case studies undertaken in this research were to determine the optimum levels of catchment discretisation, optimum levels of soil and land cover information required and, to assess the optimum use of daily rainfall stations for the configuration of the ACRU agrohydrological model when used as a continuous simulation model for design flood estimation. The last objective was to compare design flood estimates from flows simulated by the ACRU model with design flood estimates obtained from observed data. Results obtained for selected quaternary catchments in the Thukela Catchment and Lions River catchment indicated that modelling at the level of hydrological response units (HRU’s), using area weighted soils information and more than one driver rainfall station where possible, produced the most realistic results when comparing observed and simulated streamflows. Design flood estimates from simulated flows compared reasonably well with design flood estimates obtained from observed data only for QC59 and QCU20B. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2010.

Floods cannot be prevented, but their devastating effects can be minimized if advance warning of the event is available. The South African Disaster Management Act (Act 57 of 2002) advocates a paradigm shift from the current "bucket and blanket brigade" response-based mind set to one where disaster prevention or mitigation are the preferred options. It is in the context of mitigating the effects of floods that the development and implementation of a reli able flood forecasting system has major significance. In the case of flash floods, a few hours lead time can afford disaster managers the opportunity to take steps which may significantly reduce loss of life and damage to property. The engineering challenges in developing and implementing such a system are numerous. In this thesis, the design and implement at ion of a flash flood forecasting system in South Africa is critically examined. The technical aspect s relating to spatio-temporal rainfall estimation and now casting are a key area in which new contributions are made. In particular, field and optical flow advection algorithms are adapted and refined to help pred ict future path s of storms; fast and pragmatic algorithms for combining rain gauge and remote sensing (rada r and satellite) estimates are re fi ned and validated; a two-dimensional adaptation of Empirical Mode Decomposition is devised to extract the temporally persistent structure embedded in rainfall fields. A second area of significant contribution relates to real-time fore cast updates, made in response to the most recent observed information. A number of techniques embedded in the rich Kalm an and adaptive filtering literature are adopted for this purpose. The work captures the current "state of play" in the South African context and hopes to provide a blueprint for future development of an essential tool for disaster management. There are a number of natural spin-offs from this work for related field s in water resources management. / Thesis (Ph.D.Eng.)-University of KwaZulu-Natal, Durban, 2007.

A linear reservoir cell model is presented which is proposed as a good candidate for real time flood forecasting applications. The model is designed to be computationally efficient since it should be able to run on a P.C and must operate online in real time. The model parameters and forecasts can be easily updated in order to allow for a more accurate forecast based on real time observations of streamflow and rainfall. The final model, once calibrated, should be able to operate effectively without requiring highly skilled and knowledgeable operators. Thus it is hoped to provide a tool which can be incorporated into an early warning system for mitigation of flood damage, giving water resources managers the extra lead-time to implement any contingency plans which may be neccssary to ensure the safety of people and prevent damage to property. The use of linear models for describing hydrological systems is not new, however the model presented in this thesis departs from previous implementations. A particular departure is the novel method used in the conversion of observed to effective rainlfall. The physical processes that result in the rainfall to runoff conversion are non-linear in nature. Most of the significant non-linearity results from rainfall losses, which occur largely due to evaporation and human extraction. The remaining rainfall is converted to runoff. These losses are particularly significant in the South African climate and in some regions may be as much as 70-90 % of the total observed rainfall. Loss parameters are an integral part of the model formulation and allow for losses to be dealt with directly. Thus, input to the model is observed rainfall and not the "effective" rainfall normally associated with conceptual catchment models. The model is formulated in Finite Difference form similar to an Auto Regressive Moving Average (ARMA) model; it is this formulation which provides the required computational efficiency. The ARMA equation is a discretely coincident form of the State-Space equations that govern the response of an arrangement of linear reservoirs. This results in a functional relationship between the reservoir response constants and the ARMA coefficients, which guarantees stationarity of the ARMA model. / Thesis (M.Sc.Eng.)-University of Natal, Durban, 2001.