Abstract not available

In recent years, there have been significant researches on holistic approaches to design flood estimation in Australia. The Monte Carlo Simulation technique, an approximate form of Joint Probability Approach, has been developed and tested to small gauged catchments. This thesis presents the extension of the Monte Carlo Simulation Technique to large catchments using runoff routing model URBS. The URBS-Monte Carlo Technique(UMCT),has been applied to the Johnstone River and Upper Mary River catchments in Queensland. The thesis shows that the UMCT can be applied to large catchments and be readily used by hydrologists and floodplain managers. Further the proposed technique provides deeper insight into the hydrologic behaviour of large catchments and allows assessment of the effects of errors in inputs variables on design flood estimates. The research also highlights the problems and potentials of the UMCT for application in practical situations. / Masters of Engineering (Hons.)

Design flood estimation is often required in hydrologic practice. For catchments with sufficient streamflow data, design floods can be obtained using flood frequency analysis. For catchments with no or little streamflow data (ungauged catchments), design flood estimation is a difficult task. The currently recommended method in Australia for design flood estimation in ungauged catchments is known as the Probabilistic Rational Method. There are alternatives to this method such as Quantile Regression Technique or Index Flood Method. All these methods give the flood peak estimate but the full streamflow hydrograph is required for many applications. The currently recommended rainfall based flood estimation method in Australia that can estimate full streamflow hydrograph is known as the Design Event Approach. This considers the probabilistic nature of rainfall depth but ignores the probabilistic behavior of other flood producing variables such as rainfall temporal pattern and initial loss, and thus this is likely to produce probability bias in final flood estimates. Joint Probability Approach is a superior method of design flood estimation which considers the probabilistic nature of the input variables (such as rainfall temporal pattern and initial loss) in the rainfall-runoff modelling. Rahman et al. (2002) developed a simple Monte Carlo Simulation technique based on the principles of joint probability, which is applicable to gauged catchments. This thesis extends the Monte Carlo Simulation technique to ungauged catchments. The Joint Probability Approach/ Monte Carlo Simulation Technique requires identification of the distributions of the input variables to the rainfall-runoff model e.g. rainfall duration, rainfall intensity, rainfall temporal pattern, and initial loss. For gauged catchments, these probability distributions are identified from observed rainfall and/or streamflow data. For application of the Joint Probability Approach to ungauged catchments, the distributions of the input variables need to be regionalised. This thesis, in particular, investigates the regionalisation of the distribution of rainfall duration and intensity. In this thesis, it is hypothesised that the distribution of storm duration can be described by Exponential distribution. The developed new technique of design flood estimation can provide the full hydrograph rather than only peak value as with the Probabilistic Rational Method and Quantile Regression Technique. The developed new technique can further be improved by addition of new and improved regional estimation equations for the initial loss, continuing loss and storage delay parameter (k) as and when these are available. / (M. Eng.) (Hons)

Thesis (M.S.)--University of Nevada, Reno, 2005. / "December 2005." Includes bibliographical references (leaves 77-78). Online version available on the World Wide Web.

River ice breakup and associated flooding are realities for many northern communities. This is certainly the case in Hay River, NWT, which is located at the junction of the Hay River and Great Slave Lake. Hay River experiences a wide range of spring river ice scenarios; from docile thermal melt outs, to severe ice jams resulting in life-threatening, disastrous flooding. This study involved the analysis of five seasons of aerial and time-lapse photographs, water level measurements and hydrometeorologic data. This work also compiled an extended historical record of breakup in the Hay River delta, which was compared against the field data gathered for this study; combining local, experiential knowledge with scientific observation into a cohesive description of breakup. This will be used to advise the non-technical flood watch community on the patterns of timing and sequencing of breakup, which is critical for evacuation planning. / Water Resources Engineering

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No description available.

Thesis (M.Eng. (Hons.)) -- University of Western Sydney, 2004. / "Masters of Engineering (Hons) thesis, University of Western Sydney, December 2004. Supervisors: Ataur Rahman and Don Carroll" Includes bibliography.

Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 2002. / "May 2002" Includes list of papers published during this study. Errata slip inserted inside back cover of v. 1. Includes bibliographical references (leaves 331-357).

Thesis (M.S.)--Florida State University, 2004. / Advisor: Dr. T.N. Krishnamurti, Florida State University, College of Arts and Sciences, Dept. of Meteorology. Title and description from dissertation home page (viewed June 18, 2004). Title and description from dissertation home page (viewed <date>). Includes bibliographical references.