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Rainfall-runoff modelling : the primer / Keith Beven
Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Publisher: Chichester, West Sussex ; Hoboken, NJ : Wiley-Blackwell, 2012Edition: 2nd ed (Online-Ausg.)Description: Online-Ressource (1 online resource (xxix, 457 p.)) : ill., mapsISBN:- 9781280586132
- 1280586133
- 9781119951018
- 9780470714591
- 551.488
- 551.48/8 23
- GB980
- GB980 .B48
Contents:
Summary: 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.Summary: Rainfall-Runoff Modelling: The Primer -- Contents -- Preface to the Second Edition -- About the Author -- List of Figures -- 1 Down to Basics: Runoff Processes and the Modelling Process -- 1.1 Why Model? -- 1.2 How to Use This Book -- 1.3 The Modelling Process -- 1.4 Perceptual Models of Catchment Hydrology -- 1.5 Flow Processes and Geochemical Characteristics -- 1.6 Runoff Generation and Runoff Routing -- 1.7 The Problem of Choosing a Conceptual Model -- 1.8 Model Calibration and Validation Issues -- 1.9 Key Points from Chapter 1 -- Box 1.1 The Legacy of Robert Elmer Horton (1875-1945) -- 2 Evolution of Rainfall-Runoff Models: Survival of the Fittest? -- 2.1 The Starting Point: The Rational Method -- 2.2 Practical Prediction: Runoff Coefficients and Time Transformations -- 2.3 Variations on the Unit Hydrograph -- 2.4 Early Digital Computer Models: The Stanford Watershed Model and Its Descendants -- 2.5 Distributed Process Description Based Models -- 2.6 Simplified Distributed Models Based on Distribution Functions -- 2.7 Recent Developments: What is the Current State of the Art? -- 2.8 Where to Find More on the History and Variety of Rainfall-Runoff Models -- 2.9 Key Points from Chapter 2 -- Box 2.1 Linearity, Nonlinearity and Nonstationarity -- Box 2.2 The Xinanjiang, ARNO or VIC Model -- Box 2.3 Control Volumes and Differential Equations -- 3 Data for Rainfall-Runoff Modelling -- 3.1 Rainfall Data -- 3.2 Discharge Data -- 3.3 Meteorological Data and the Estimation of Interception and Evapotranspiration -- 3.4 Meteorological Data and The Estimation of Snowmelt -- 3.5 Distributing Meteorological Data within a Catchment -- 3.6 Other Hydrological Variables -- 3.7 Digital Elevation Data -- 3.8 Geographical Information and Data Management Systems -- 3.9 Remote-sensing Data -- 3.10 Tracer Data for Understanding Catchment Responses.PPN: PPN: 807355577Package identifier: Produktsigel: ZDB-26-MYL | ZDB-30-PAD | ZDB-30-PQE
Rainfall-Runoff Modelling: The Primer; Contents; Preface to the Second Edition; About the Author; List of Figures; 1 Down to Basics: Runoff Processes and the Modelling Process; 1.1 Why Model?; 1.2 How to Use This Book; 1.3 The Modelling Process; 1.4 Perceptual Models of Catchment Hydrology; 1.5 Flow Processes and Geochemical Characteristics; 1.6 Runoff Generation and Runoff Routing; 1.7 The Problem of Choosing a Conceptual Model; 1.8 Model Calibration and Validation Issues; 1.9 Key Points from Chapter 1; Box 1.1 The Legacy of Robert Elmer Horton (1875-1945)
2 Evolution of Rainfall-Runoff Models: Survival of the Fittest?2.1 The Starting Point: The Rational Method; 2.2 Practical Prediction: Runoff Coefficients and Time Transformations; 2.3 Variations on the Unit Hydrograph; 2.4 Early Digital Computer Models: The Stanford Watershed Model and Its Descendants; 2.5 Distributed Process Description Based Models; 2.6 Simplified Distributed Models Based on Distribution Functions; 2.7 Recent Developments: What is the Current State of the Art?; 2.8 Where to Find More on the History and Variety of Rainfall-Runoff Models; 2.9 Key Points from Chapter 2
Box 2.1 Linearity, Nonlinearity and NonstationarityBox 2.2 The Xinanjiang, ARNO or VIC Model; Box 2.3 Control Volumes and Differential Equations; 3 Data for Rainfall-Runoff Modelling; 3.1 Rainfall Data; 3.2 Discharge Data; 3.3 Meteorological Data and the Estimation of Interception and Evapotranspiration; 3.4 Meteorological Data and The Estimation of Snowmelt; 3.5 Distributing Meteorological Data within a Catchment; 3.6 Other Hydrological Variables; 3.7 Digital Elevation Data; 3.8 Geographical Information and Data Management Systems; 3.9 Remote-sensing Data
3.10 Tracer Data for Understanding Catchment Responses3.11 Linking Model Components and Data Series; 3.12 Key Points from Chapter 3; Box 3.1 The Penman-Monteith Combination Equation for Estimating Evapotranspiration Rates; Box 3.2 Estimating Interception Losses; Box 3.3 Estimating Snowmelt by the Degree-Day Method; 4 Predicting Hydrographs Using Models Based on Data; 4.1 Data Availability and Empirical Modelling; 4.2 Doing Hydrology Backwards; 4.3 Transfer Function Models; 4.4 Case Study: DBM Modelling of the CI6 Catchment at Llyn Briane, Wales; 4.5 Physical Derivation of Transfer Functions
4.6 Other Methods of Developing Inductive Rainfall-Runoff Models from Observations4.7 Key Points from Chapter 4; Box 4.1 Linear Transfer Function Models; Box 4.2 Use of Transfer Functions to Infer Effective Rainfalls; Box 4.3 Time Variable Estimation of Transfer Function Parameters and Derivation of Catchment Nonlinearity; 5 Predicting Hydrographs Using Distributed Models Based on Process Descriptions; 5.1 The Physical Basis of Distributed Models; 5.2 Physically Based Rainfall-Runoff Models at the Catchment Scale; 5.3 Case Study: Modelling Flow Processes at Reynolds Creek, Idaho
5.4 Case Study: Blind Validation Test of the SHE Model on the Slapton Wood Catchment
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