Thesis (Ph. D.)--Texas State University-San Marcos, 2007. / Vita. Appendices: leaves 194-207. Includes bibliographical references (leaves 208-209).

Thesis (Ph. D.)--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 Jan. 14, 2005). Includes bibliographical references.

Thesis (M.S.)--Virginia Polytechnic Institute and State University, 1993. / Vita. Abstract. Includes bibliographical references (leaves 123-126). Also available via the Internet.

Thesis (Ph. D.)--Texas State University-San Marcos, 2007. / Vita. Appendices: leaves 194-207. Includes bibliographical references (leaves 208-209).

A thesis submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, for the degree of Master of Science. Johannesburg, 1980 / Monthly mean s e a - l e v e l p r e s s u r e ove r th e o c ea nic areas a d j a c e n t t o t h e Kepublic o f South A f r i c a i s an aly s e d . R ela t i o n s h i p s between t h e oceanic p r e s s u r e and r a i n f a l l over t h i s p a r t o f t h e c o n t i n e n t a re d i s c u s s e d . P r i n c i p a l compon e n ts a n a l y s i s is used t o d e r i v e u n c o r r e l a t e d f u n c t i o n s of th e o r i g i n a l p r e s s u r e v a r i a b l e s . Three major p r e s s u r e f i e l d s were i d e n t i f i e d , termed a g e n e r a l , a l o n g i t u d i n a l and a l a t i t u d i n a l p r e s s u r e f i e l d . The r e l a t i o n s h i p s between p r e s s u r e and r a i n f a l l a re a s s e s s e d by r e g r e s s i n g monthly r a i n f a l l on t h e p r i n c i p a l comnonent s c o r e s . R a i n f a l l in w in te r maxima a r e a s appears t o be d i r e c t l y r e l a t e d t o oceanic s e a - l e v e l p r e s s u r e s i t u a t i o n s , whereas the r e s t o f th e country shows an o u t - o f - s e a s o n r e l a t i o n s h i p between r a i n f a l l and p r e s s u r e over n o n - c o n t i n e n t a l a r e a s .

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)

Extreme rainfall events may have catastrophic impacts on the population and infrastructures, therefore it is essential to have accurate knowledge of extreme rainfall characteristics. Moreover, both the scientific community and policymakers have recently shown a growing interest in the potential impacts of climate change on water resources management. Indeed, changes in the intensity and frequency of occurrence of extreme rainfall events may have serious impacts. As such, it is important to understand not only the current patterns of extreme rainfalls but also how they are likely to change in the future. / The objective of the present research is therefore to find the best method for estimating accurately extreme rainfalls for the current time period and future periods in the context of climate change. The analysis of extreme rainfall data from the province of Quebec (Canada) revealed that, according to L-moment ratio diagrams, the data may be well described by the Generalized-Extreme-Value (GEV) distribution. Results also showed that a simple scaling relationship between non-central moments (NCM) and duration can be established and that a scaling method based on NCMs and scaling exponents can be used to generate accurate estimates of extreme rainfalls at Dorval station (Quebec, Canada). Other results demonstrated that the method of NCMs can accurately estimate distribution parameters and can be used to construct accurate Intensity-Duration-Frequency (IDF) curves. / Furthermore, a regional analysis was performed and homogenous regions of weather stations within Quebec were identified. A method for the estimation of missing data at ungauged sites based on regional NCMs was found to yield good estimates. / In addition, the potential impacts of climate change on extreme rainfalls were assessed. Changes in the distribution of annual maximum (AM) precipitations were evaluated using simulations from two Global Climate Models (GCMs) under the A2 greenhouse gas emission scenario: the Coupled Global Climate Model version 2 (CGCM2A2) of the Canadian Centre for Climate Modelling and Analysis, and the Hadley Centre's Model version 3 (HadCM3A2). Simulations from these two models were downscaled spatially using the Statistical DownScaling Model (SDSM). A bias-correction method to adjust the downscaled AM daily precipitations for Dorval station was tested and results showed that after adjustments, the values fit the observed AM daily precipitations well. The analysis of future AM precipitations revealed that, after adjustments, AM precipitations downscaled from CGCM2A2 increase from current to future periods, while AM precipitations downscaled from HadCM3A2 show a mild decrease from current to future periods, for daily and sub-daily scales.

Thesis (M.Sc. Earth Sciences)--University of Waikato, 2008. / Title from PDF cover (viewed February 23, 2009) Includes bibliographical references (p. 72-75)

No description available.

A research report submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, in fulfilment of the requirements for the degree of Master of Science in Engineering, 2017 / The main problem to be investigated is how short duration data records can be augmented using existing data from nearby catchments with data with long periods of record. The purpose of the investigation is to establish a method of improving hydrological data using data from a gauged catchment to improve data from an ungauged catchment. The investigation is undertaken using rainfall data for catchments in Lesotho. Marginal distributions describing the annual maximum rainfall for the catchments, and a joint distribution of pairs of catchments were established. The parameters of these distributions were estimated using the Bayesian – Markov Chain Monte Carlo approach, and using both the single-site (univariate) estimation and the two-site (bivariate) estimations. The results of the analyses show that for catchments with data with short periods of record, the precision of the estimated location and scale parameters improved when the estimates were carried out using the two-site (bivariate) method. Rainfall events predicted using bivariate analyses parameters were generally higher than the univariate analyses parameters. From the results, it can be concluded that the two-site approach can be used to improve the precision of the rainfall predictions for catchments with data with short periods of record. This method can be used in practice by hydrologists and design engineers to enhance available data for use in designs and assessments. / CK2018