Distributed conceptual hydrological modelling [Elektronische Ressource] : simulation of climate, land use change impact and uncertainty analysis / von Jens Götzinger

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• Publié par: universitat_stuttgart
• Publié le: 01 janvier 2007
• Nombre de lectures: 37
• Langue: English
• Poids de l'ouvrage: 8 Mo

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Heft 164 Jens Götzinger

Distributed Conceptual Hydrological
Modelling - Simulation of Climate, Land
Use Change Impact and Uncertainty
Analysis



Distributed Conceptual Hydrological Modelling -
Simulation of Climate, Land Use Change Impact and
Uncertainty Analysis






Von der Fakultät Bau- und Umweltingenieurwissenschaften der
Universität Stuttgart zur Erlangung der Würde eines
Doktor-Ingenieurs (Dr.-Ing.) genehmigte Abhandlung



Vorgelegt von
Jens Götzinger
aus Landstuhl




Hauptberichter: Prof. Dr. rer. nat. Dr.-Ing. András Bárdossy
Mitberichter: Prof. Dr. Taha B.M.J. Ouarda, Ph.D.


Tag der mündlichen Prüfung: 19. Juli 2007









Institut für Wasserbau der Universität Stuttgart
2007





Heft 164 Distributed Conceptual
Hydrological Modelling -
Simulation of Climate, Land
Use Change Impact and
Uncertainty Analysis


von
Dr.-Ing.
Jens Götzinger













Eigenverlag des Instituts für Wasserbau der Universität Stuttgart D93 Distributed Conceptual Hydrological Modelling -Simulation of Climate,
Land Use Change Impact and Uncertainty Analysis























Titelaufnahme der Deutschen Bibliothek


Götzinger, Jens:
Distributed Conceptual Hydrological Modelling - Simulation of Climate, Land Use
Change Impact and Uncertainty Analysis / von Jens Götzinger. Institut für
Wasserbau, Universität Stuttgart. Stuttgart: Inst. für Wasserbau, 2007

(Mitteilungen / Institut für Wasserbau, Universität Stuttgart: H. 164)
Zugl.: Stuttgart, Univ., Diss., 2007)
ISBN 3-933761-68-9
NE: Institut für Wasserbau <Stuttgart>: Mitteilungen


Gegen Vervielfältigung und Übersetzung bestehen keine Einwände, es wird lediglich
um Quellenangabe gebeten.




Herausgegeben 2007 vom Eigenverlag des Instituts für Wasserbau
Druck: Sprint-Druck, Stuttgart Acknowledgements
During the preparation of this thesis I have become indebted to too many people
to mention them all in this section. The first is my supervisor Prof. Dr. rer. nat.
Dr.-Ing. Andr´as B´ardossy who has given me the chance to work in his group and
has supported me with enough ideas for at least another Ph.D. thesis. Second,
Prof. Dr. Taha B.M.J. Ouarda, Ph.D. for accepting to co-supervise my thesis and
the interesting discussions we had, not only about hydrology, during his time in
Stuttgart.
Many thanks are due to all co-workers in RIVERTWIN for the good atmosphere
and cooperation; especially to Thomas Gaiser for managing this extremely diverse
consortium and keeping us all on track and in time; to Johanna Jagelke and Roland
Barthelwhohavedevelopedthegroundwatermodelforthefruitfulteamwork; toAn-
dreas Printz and Hans-Georg Schwarz-von Raumer who solved many GIS problems
and provided the land use scenarios and other datasets and to Martha Fernandez for
the irrigation water demand time series.
Jur¨ gen Brommundt, Ferdinand Beck, Jan Bliefernicht and Christian Ebert have
helped a lot by proof-reading and giving valuable suggestions which improved the
finalversion. ThehelpofMichelleBesterwiththeEnglishlanguageisalsogratefully
acknowledged. Furthermore, thanks to all colleagues at the Institute for Hydraulic
Engineering for the overall good working atmosphere and the indispensable coffee
breaks.
Most of the research this thesis is based on was funded by the European Union in
the Sixth Framework Program through the project RIVERTWIN. Data was kindly
provided by the State Institute for Environmental Protection Baden-Wurttemberg¨
and the Direction de l’Hydraulique, Benin.
Last but not least, I want to thank my partner Caro for her continuous support,
help and understanding during this project.
iiiContents
Acknowledgements iii
List of Figures vii
List of Tables xi
List of Abbreviations xiii
List of symbols xiv
Zusammenfassung xv
1 Introduction 1
1.1 Motivation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1
2 Hydrological Modelling 3
2.1 Why model?. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
2.2 Modelling change . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
2.3 Integrated water resources management . . . . . . . . . . . . . . . . . 7
2.4 LARSIM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.5 HBV . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
2.6 Uncertainty estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
3 Data 13
3.1 The Neckar basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
3.2 The Ou´em´e basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
4 Integrated modelling of climate and land use change 25
4.1 The distributed HBV model . . . . . . . . . . . . . . . . . . . . . . . . 26
4.2 Regionalisation of distributed model parameters . . . . . . . . . . . . 28
4.2.1 Transfer functions . . . . . . . . . . . . . . . . . . . . . . . . . 29
4.2.2 The modified Lipschitz condition . . . . . . . . . . . . . . . . . 30
4.2.3 The monotony condition . . . . . . . . . . . . . . . . . . . . . . 31
4.2.4 The combination of both conditions . . . . . . . . . . . . . . . 32
4.2.5 Examples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
4.3 Integration of surface and groundwater models . . . . . . . . . . . . . 33
4.3.1 MODFLOW . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
4.4 Scenarios of climate and land use change . . . . . . . . . . . . . . . . . 35
4.4.1 Climate change scenarios . . . . . . . . . . . . . . . . . . . . . 36
ivContents
4.4.2 Land use change scenarios . . . . . . . . . . . . . . . . . . . . . 38
5 Results 43
5.1 Regionalisation of distributed model parameters . . . . . . . . . . . . 43
5.1.1 Neckar basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
5.1.2 Ou´em´e basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
5.2 Integration of surface and groundwater models . . . . . . . . . . . . . 49
5.2.1 Neckar basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
5.2.2 Ou´em´e basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56
5.3 The impact of climate and land use change . . . . . . . . . . . . . . . 60
5.3.1 Neckar basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60
5.3.2 Ou´em´e basin . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
6 Uncertainty Analysis 69
6.1 Methodology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
6.2 Meteorological sources of uncertainty . . . . . . . . . . . . . . . . . . . 70
6.2.1 Conditional precipitation and temperature simulation . . . . . 71
6.3 Process and parameter related uncertainty . . . . . . . . . . . . . . . . 76
6.4 Case Study . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
6.4.1 Comparison of maximum likelihood and bi-objective optimiza-
tion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 83
6.4.2 Validation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
6.5 Results and discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . 88
7 Summary and conclusions 91
7.1 Can we model the impact of global change on the water resources and
what kind of models are necessary to predict the effect of land use
change on the water balance of a catchment? . . . . . . . . . . . . . . 91
7.2 Is it possible to integrate models on the regional scale to simulate and
evaluate interdisciplinary water management scenarios? . . . . . . . . 92
7.3 What will be the impact of climate and land use change? . . . . . . . 93
7.4 How can we quantify uncertainties? . . . . . . . . . . . . . . . . . . . . 93
7.5 Outlook . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
v