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Predicting water runoff in ungauged water catchment areas is vital to practical applications such as the design of drainage infrastructure and flooding defences, runoff forecasting, and for catchment management tasks such as water allocation and climate impact analysis. This full colour book offers an impressive synthesis of decades of international research, forming a holistic approach to catchment hydrology and providing a one-stop resource for hydrologists in both developed and developing countries. Topics include data for runoff regionalisation, the prediction of runoff hydrographs, flow duration curves, flow paths and residence times, annual and seasonal runoff, and floods. Illustrated with many case studies and including a final chapter on recommendations for researchers and practitioners, this book is written by expert authors involved in the prestigious IAHS PUB initiative. It is a key resource for academic researchers and professionals in the fields of hydrology, hydrogeology, ecology, geography, soil science, and environmental and civil engineering.
This important monograph is based on the results of a study on the identification of conceptual lumped rainfall-runoff models for gauged and ungauged catchments. The task of model identification remains difficult despite decades of research. A detailed problem analysis and an extensive review form the basis for the development of a Matlab® modelling toolkit consisting of two components: a Rainfall-Runoff Modelling Toolbox (RRMT) and a Monte Carlo Analysis Toolbox (MCAT). These are subsequently applied to study the tasks of model identification and evaluation. A novel dynamic identifiability approach has been developed for the gauged catchment case. The theory underlying the application of rainfall-runoff models for predictions in ungauged catchments is studied, problems are highlighted and promising ways to move forward are investigated. Modelling frameworks for both gauged and ungauged cases are developed. This book presents the first extensive treatment of rainfall-runoff model identification in gauged and ungauged catchments.
Overview Historically, the concept of "ondelettes" or "wavelets" originated from the study of time-frequency signal analysis, wave propagation, and sampling theory. One of the main reasons for the discovery of wavelets and wavelet transforms is that the Fourier transform analysis does not contain the local information of signals. So the Fourier transform cannot be used for analyzing signals in a joint time and frequency domain. In 1982, Jean MorIet, in collaboration with a group of French engineers, first introduced the idea of wavelets as a family of functions constructed by using translation and dilation of a single function, called the mother wavelet, for the analysis of nonstationary signals. However, this new concept can be viewed as the synthesis of various ideas originating from different disciplines including mathematics (Calder6n-Zygmund operators and Littlewood-Paley theory), physics (coherent states in quantum mechanics and the renormalization group), and engineering (quadratic mirror filters, sideband coding in signal processing, and pyramidal algorithms in image processing). Wavelet analysis is an exciting new method for solving difficult problems in mathematics, physics, and engineering, with modern applications as diverse as wave propagation, data compression, image processing, pattern recognition, computer graphics, the detection of aircraft and submarines, and improvement in CAT scans and other medical image technology. Wavelets allow complex information such as music, speech, images, and patterns to be decomposed into elementary forms, called the fundamental building blocks, at different positions and scales and subsequently reconstructed with high precision.
A synthesis of international catchment hydrology research, for researchers and professionals in hydrology, soil science, and environmental and civil engineering.
Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and authoritative text, first published in 2001. The book provides both a primer for the novice and detailed descriptions of techniques for more advanced practitioners, covering rainfall-runoff models and their practical applications. This new edition extends these aims to include additional chapters dealing with prediction in ungauged basins, predicting residence time distributions, predicting the impacts of change and the next generation of hydrological models. Giving a comprehensive summary of available techniques based on established practices and recent research the book offers a thorough and accessible overview of the area. Rainfall-Runoff Modelling: The Primer Second Edition focuses on predicting hydrographs using models based on data and on representations of hydrological process. Dealing with the history of the development of rainfall-runoff models, uncertainty in mode predictions, good and bad practice and ending with a look at how to predict future catchment hydrological responses this book provides an essential underpinning of rainfall-runoff modelling topics. Fully revised and updated version of this highly popular text Suitable for both novices in the area and for more advanced users and developers Written by a leading expert in the field Guide to internet sources for rainfall-runoff modelling software
This important monograph is based on the results of a study on the identification of conceptual lumped rainfall-runoff models for gauged and ungauged catchments. The task of model identification remains difficult despite decades of research. A detailed problem analysis and an extensive review form the basis for the development of a Matlab- modelling toolkit consisting of two components: a Rainfall-Runoff Modelling Toolbox (RRMT) and a Monte Carlo Analysis Toolbox (MCAT). These are subsequently applied to study the tasks of model identification and evaluation. A novel dynamic identifiability approach has been developed for the gauged catchment case. The theory underlying the application of rainfall-runoff models for predictions in ungauged catchments is studied, problems are highlighted and promising ways to move forward are investigated. Modelling frameworks for both gauged and ungauged cases are developed. This book presents the first extensive treatment of rainfall-runoff model identification in gauged and ungauged catchments."
River stage or flow rates are required for the design and evaluation of hydraulic structures. Most river reaches are ungauged and a methodology is needed to estimate the stages, or rates of flow, at specific locations in streams where no measurements are available. Flood routing techniques are utilised to estimate the stages, or rates of flow, in order to predict flood wave propagation along river reaches. Models can be developed for gauged catchments and their parameters related to physical characteristics such as slope, reach width, reach length so that the approach can be applied to ungauged catchments in the region. The objective of this study is to assess Muskingum-based methods for flow routing in ungauged river reaches, both with and without lateral inflows. Using observed data, the model parameters were calibrated to assess performance of the Muskingum flood routing procedures and the Muskingum-Cunge method was then assessed using catchment derived parameters for use in ungauged river reaches. The Muskingum parameters were derived from empirically estimated variables and variables estimated from assumed river cross-sections within the selected river reaches used. Three sub-catchments in the Thukela catchment in KwaZulu-Natal, South Africa were selected for analyses, with river lengths of 4, 21 and 54 km. The slopes of the river reaches and reach lengths were derived from a digital elevation model. Manning roughness coefficients were estimated from field observations. Flow variables such as velocity, hydraulic radius, wetted perimeters, flow depth and top flow width were determined from empirical equations and cross-sections of the selected rivers. Lateral inflows to long river reaches were estimated from the Saint-Venant equation. Observed events were extracted for each sub-catchment to assess the Muskingum-Cunge parameter estimation method and Three-parameter Muskingum method. The extracted events were further analysed using empirically estimated flow variables. The performances of the methods were evaluated by comparing both graphically and statistically the simulated and observed hydrographs. Sensitivity analyses were undertaken using three selected events and a 50% variation in selected input variables was used to identify sensitive variables. The performance of the calibrated Muskingum-Cunge flood routing method using observed hydrographs displayed acceptable results. Therefore, the Muskingum-Cunge flood routing method was applied in ungauged catchments, with variables estimated empirically. The results obtained shows that the computed outflow hydrographs generated using the Muskingum-Cunge method, with the empirically estimated variables and variables estimated from cross-sections of the selected rivers resulted in reasonably accurate computed outflow hydrographs with respect to peak discharge, timing of peak flow and volume. From this study, it is concluded that the Muskingum-Cunge method can be applied to route floods in ungauged catchments in the Thukela catchment and it is postulated that the method can be used to route floods in other ungauged rivers in South Africa.