[PDF] Inverse Modelling Of The Rainfall Runoff Relation eBook

Author : Thomas Henricus Maria Rientjes
Publisher : IOS Press
Page : 371 pages
File Size : 17,6 MB
Release : 2004-01-01
Category : Technology & Engineering
ISBN : 9789040724916

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"This is a Ph.D. dissertation. It is commonly known that the relation between rainfall and runoff plays an important role in many water related societal issues. Generally speaking, one can say these issues relate to a) the operational aspects of (real-time) water management practices such as high and low water forecasting b) the simulation of hydrologic processes and systems for defining design criteria for infra structural works and c) defining effects of land use and climate change on runoff processes. An example of the role of rainfall-runoff processes in operational water management is the optimal use of limited available water volumes for domestic and/or agricultural use. By quantifying the runoff volumes in a channel network system, a strategy can be developed to manage, redistribute and allocate the water spatially and temporally over the various water users. Contents include: Introduction, Rainfall-runoff modeling, Review of Distributed Physically Based Rainfall-runoff Modeling, Model Concept ""Flowsim,"" Model Calibration, Case Study Troy Catchment."

Author : Dieter Theiner
Publisher : VDM Publishing
Page : 216 pages
File Size : 45,71 MB
Release : 2008-05-01
Category : Science
ISBN : 9783836494304

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The aim of the presented doctoral thesis is the development of components for an operational flood forecasting system. Two methods to determine the rainfall-runoff relationship were applied in a case study in a small Alpine catchment: (i) Application of the raster-based hydrological model WaSiM-ETH. This model is based on the conceptual TOPMODEL- approach. Model parameters were determined by an inverse modelling algorithm; (ii) Application of artificial neural networks for a short-term runoff prediction. The study area was the catchment of the Zieplbach torrent in the Community of Westendorf, Tyrol, Austria. Discharge and precipitation measurements of this 1 km catchment were available for the period from July 2000 until July 2003. This book is suited for hydrologists and hydraulic engineers using hydrological models or with an interest in data-driven approaches.

Author : Keith J. Beven
Publisher : John Wiley & Sons
Page : 384 pages
File Size : 23,47 MB
Release : 2003
Category : Mathematics
ISBN : 9780470866719

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Amid climatic changes linked to global warming, ongoing changes in land-use patterns, and growing international concern with the environment it is increasingly important to understand the potential impact of these changes on the environment. Rainfall-runoff modeling is an important predictor of that impact. This book introduces rainfall-runoff models that have been developed over the past 24-30 years, giving examples of their practical applications. It provides a summary of available techniques for rainfall modeling based upon the most recent research, but in a way that serves as a primer for the subject. Provides an overview of how catchment rainfall-runoff systems work A history of rainfall-runoff models Examples of models can be downloaded over the Internet Looks at uncertainty in model prediction

Author : Jagadeesh Anmala
Publisher : LAP Lambert Academic Publishing
Page : 200 pages
File Size : 30,76 MB
Release : 2010-07
Category :
ISBN : 9783838383392

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The book addresses a two-pronged approach for the determination of a watershed's response by developing a physically-based model and a neural network-based model. For the physically-based model, the watershed is partitioned into a series of one-dimensional overland flow planes and channel elements, and water is routed over these elements in a cascading fashion. A system of partial differential equations under the kinematic wave approximation was used to describe surface water movement. The applicability of ANNs was investigated by developing a neural network-based runoff predictive model. The performance of ANNs, with different architectures, was evaluated using monthly precipitation and temperature data (input) and watershed runoff (output) for 3 medium-sized watersheds - El Dorado, Marion, and Council Grove in Kansas, USA. The prediction of watershed response was also studied using several existing empirical rainfall-runoff models. The advantage of ANNs over the physically-based models is that they require only input and output data for mapping of an unknown function such as rainfall-runoff relationship. In the case of physically-based models a lot more data is required.

Author : Keith J. Beven
Publisher : John Wiley & Sons
Page : 489 pages
File Size : 20,3 MB
Release : 2012-01-30
Category : Technology & Engineering
ISBN : 047071459X

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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

Author : Dilip Kumar
Publisher : LAP Lambert Academic Publishing
Page : 64 pages
File Size : 36,61 MB
Release : 2011-05
Category :
ISBN : 9783838341729

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The rainfall runoff model is one of the most frequently used events in hydrology. It determines the runoff signal which leaves the watershed from the rainfall signal received by the basin. The present study develops an distributed approach to simulate the rainfall runoff process of a catchment. The catchment area has been divided in to the numbers of divisions equal to the numbers of rain gauge station. An lump model is also developed using average rainfall of the catchment. In case of lump model, average rainfall is calculated using thessian polygon method. In order to estimate runoff from rainfall events, loss rate or infiltration parameters for the basin have to be calculated, which is a basic input for further rainfall runoff modelling. The infiltration capacity of the basin depends on the land use and soil property. Therefore the estimation of infiltration parameters or curve number of the basin is made initially. An inverse model is formulated and solved for estimating the curve numbers for the lump and distributed models.

Author : Thorsten Wagener
Publisher : World Scientific
Page : 320 pages
File Size : 19,57 MB
Release : 2004
Category : Technology & Engineering
ISBN : 9781860945397

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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."