Sorooshian / Singh / Hsu Hydrological Modelling and the Water Cycle

Coupling the Atmospheric and Hydrological Models
1. Auflage 2008
ISBN: 978-3-540-77843-1
Verlag: Springer Berlin Heidelberg
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 63, 291 Seiten

Reihe: Water Science and Technology Library

This volume is a collection of a selected number of articles based on presentations at the 2005 L'Aquila (Italy) Summer School on the topic of 'Hydrologic Modeling and Water Cycle: Coupling of the Atmosphere and Hydrological Models'. The p- mary focus of this volume is on hydrologic modeling and their data requirements, especially precipitation. As the eld of hydrologic modeling is experiencing rapid development and transition to application of distributed models, many challenges including overcoming the requirements of compatible observations of inputs and outputs must be addressed. A number of papers address the recent advances in the State-of-the-art distributed precipitation estimation from satellites. A number of articles address the issues related to the data merging and use of geo-statistical techniques for addressing data limitations at spatial resolutions to capture the h- erogeneity of physical processes. The participants at the School came from diverse backgrounds and the level of - terest and active involvement in the discussions clearly demonstrated the importance the scienti c community places on challenges related to the coupling of atmospheric and hydrologic models. Along with my colleagues Dr. Erika Coppola and Dr. Kuolin Hsu, co-directors of the School, we greatly appreciate the invited lectures and all the participants. The members of the local organizing committee, Drs Barbara Tomassetti; Marco Verdecchia and Guido Visconti were instrumental in the success of the school and their contributions, both scienti cally and organizationally are much appreciated.

Autoren/Hrsg.

Singh, VP

Anderson, M.

Bengtsson, L.

Stephenson, D.

W.,

Sorooshian, Soroosh

Hsu, Kuo-Lin

Coppola, Erika

Tomassetti, Barbara

Verdecchia, Marco

Visconti, Guido

Inhaltsverzeichnis

1;Contents;6
2;Preface;8
3;Contributors;10
4;General Review of Rainfall-Runoff Modeling: Model Calibration, Data Assimilation, and Uncertainty Analysis;13
4.1;1 Introduction;13
4.2;2 Various Modeling Approaches: Lumped, Distributed andMore;14
4.3;3 The Problem of Model Calibration (Parameter Estimation);16
4.4;4 Ensemble Inference vs. Optimization;21
4.5;5 Hydrologic Uncertainties;22
4.6;6 Bayesian Inference and Sequential Data Assimilation;25
4.7;7 Summary;31
4.8;References;31
5;Part 1 Measurement of Hydrologic Variables;37
5.1;Satellite-Based Precipitation Measurement Using PERSIANN System;39
5.1.1;1 Introduction;39
5.1.2;2 Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks ( PERSIANN);41
5.1.3;3 PERSIANN Cloud Classification System (CCS);44
5.1.4;4 Merging Precipitation Observations from Multiple Sources;46
5.1.5;5 Evaluation and Hydrologic Application of PERSIANN Rainfall;51
5.1.6;6 Summary;55
5.1.7;References;57
5.2;Satellite Clouds and Precipitation Observations for Meteorology and Climate;61
5.2.1;1 Introduction;61
5.2.2;2 Passive Microwave Methods;62
5.2.3;3 Blended Global Products;64
5.2.4;4 Combining Spaceborne Radar and PMW;66
5.2.5;5 Exploiting Cloud Microphysics;67
5.2.6;6 Climate and Global Model Applications;69
5.2.7;7 A Glimpse on International Efforts;73
5.2.8;Appendix: RelevantWeb Sites;76
5.2.9;References;76
5.3;Advanced Techniques for Polarimetric Radar Estimation of Rainfall;81
5.3.1;1 Introduction;81
5.3.2;2 Polarimetric Radar Observables;82
5.3.3;3 Path Attenuation Correction at C Band;84
5.3.4;4 Hydrometeor Classification at C Band;89
5.3.5;5 Estimation of Raindrop Size Distribution and Rainrate;93
5.3.6;6 Concluding Remarks;98
5.3.7;References;102
5.4;Measurements of Hydrological Variables from Satellite: Application to Mediterranean Regions;105
5.4.1;1 Introduction;106
5.4.2;2 Data Assimilation Techniques;107
5.4.3;3 Land Surface Temperature Estimation;109
5.4.4;4 Cloud Mask Algorithms;113
5.4.5;5 Satellite Data Assimilation: Application to Mediterranean Regions;114
5.4.6;6 Concluding Remarks and Open Questions;121
5.4.7;References;121
6;Part 2 Data Merging and Dowscaling;127
6.1;Geostatistical Tools for Validation of Satellite and NWP Model Rainfall Estimates;129
6.1.1;1 The Rainfall Validation Problem;129
6.1.2;2 The Geostatistical Solution;130
6.1.3;3 The Kriging Algorithm;134
6.1.4;4 Validation;144
6.1.5;5 Conclusions;148
6.1.6;6 Answers to Questions;148
6.1.7;Appendix: Rainfall Interpolation Using Kriging;150
6.1.8;The Assumptions;151
6.1.9;The Method;151
6.1.10;The Error on the Estimate;155
6.1.11;Health Warning;155
6.1.12;References;155
6.2;An Ensemble Approach to Uncertainty Estimation for Satellite- Based Rainfall Estimates;157
6.2.1;1 Introduction;157
6.2.2;2 The Problem of Uncertainty Estimation for Satellite-Derived Rainfall;158
6.2.3;3 Case Study;159
6.2.4;4 An Ensemble Approach to Uncertainty Estimation;161
6.2.5;5 Validation;166
6.2.6;6 Areal Average Rainfall Ensemble;169
6.2.7;7 Conclusions;174
6.2.8;References;174
7;Part 3 Hydrologic Modelling: Short and Long- Time Scale;175
7.1;Cetemps Hydrological Model (CHyM), a Distributed Grid- Based Model Assimilating Different Rainfall Data Sources;177
7.1.1;1 Introduction;177
7.1.2;2 Cellular Automata Based Algorithm for Pit and Flat Area DEM Correction and Flowstream Network Extraction;179
7.1.3;3 Assimilation of Different Rainfall Data Sets;194
7.1.4;4 Parametrization of Physical Processes Contributing to Hydrological Cycle;201
7.1.5;5 Some Applications of Chym Drainage Network of CHyM Model;203
7.1.6;6 Concluding Remarks;211
7.1.7;References;212
7.2;Rainfall Thresholds for Flood Warning Systems: A Bayesian Decision Approach;215
7.2.1;1 Introduction;215
7.2.2;2 Description of the Proposed Methodology;219
7.2.3;3 Operational Use of the Rainfall Threshold Approach;227
7.2.4;4 A Framework for Testing the Procedure;229
7.2.5;5 The Case Study;230
7.2.6;6 Conclusions;234
7.2.7;Appendix: The Rainfall-Runoff Model Used: the Lumped Version of the TOPKAPI Model;235
7.2.8;References;238
7.3;Watershed Hydrological Modeling: Toward Physically Meaningful Processes Representation;241
7.3.1;1 Introduction;242
7.3.2;2 Numerical Integration Schemes for the Governing Equations;242
7.3.3;3 Influence of the Parameters Averaging on the Physical Representativeness;246
7.3.4;4 Conclusions;251
7.3.5;References;252
7.4;Simulating Climate Impacts on Water Resources: Experience from the Okavango River, Southern Africa;255
7.4.1;1 Introduction;256
7.4.2;2 The "Water and Ecosystem Resources in Regional Development" ( WERRD) Project;257
7.4.3;3 Dataset Development Within the WERRD Project;257
7.4.4;4 Description of the Hydrological Modeling Tools used in WERRD;259
7.4.5;5 Simulating Climate Impacts;265
7.4.6;6 Results;269
7.4.7;7 Discussion and Conclusions;274
7.4.8;References;275
8;Colour Plate Section;279
9;Index;303