M. Andrea Ficchí An adaptive hydrological model for multiple time-steps

281 Pages·2017·6.5 MB·English

THESE DE DOCTORAT DE
L’UNIVERSITÉ PIERRE ET MARIE CURIE

Ecole doctorale 398 Géosciences, ressources naturelles et environnement

Présentée par

M. Andrea Ficchí

Pour obtenir le grade de

DOCTEUR de l’UNIVERSITÉ PIERRE ET MARIE CURIE

An adaptive hydrological model for multiple time-steps:
Diagnostics and improvements based on fluxes consistency

soutenue le 27 février 2017

devant le jury composé de :

Mme Agnès Ducharne CNRS, Paris Présidente
M. Marco Borga Université de Padoue (Italie) Rapporteur
M. Nicolas Masséi Université de Rouen Rapporteur
M. Lionel Berthet DREAL Centre-Val de Loire, Orléans Examinateur
M. Hubert Savenije Université de Delft (Pays-Bas) Examinateur
Mme Isabella Zin Obs. des Sciences de l’Univers, Grenoble Examinatrice
M. Vazken Andréassian Irstea, Antony Directeur de thèse
M. Charles Perrin Irstea, Antony Co-encadrant
“L'acqua che tocchi de' fiumi è l'ultima di quella che andò
e la prima di quella che viene.
Cosí il tempo presente.”

Leonardo da Vinci

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Acknowledgments
I want to express here my gratitude to the people who contributed to make my PhD journey
pleasant and successful.
First, I would like to warmly thank my two supervisors, Charles Perrin and Vazken
Andréassian, for assigning me this interesting research project and for the careful guidance
and expert advice during the three years spent at Irstea. Thank you for the inspiring
discussions and suggestions, your teachings in hydrology and beyond, and for the trust and
freedom conferred on my creativity. Your contagious enthusiasm and your positive attitude
helped me to keep high motivation and optimism from the sources until the end (the sea?) of
this adventure (apparently also the hydrological poems had an effect!). Also, I am grateful for
your quick and effective reviewing of the thesis manuscript (fortunately, your reading flow
rate was appropriate to the length of my chapters!).
I would like to thank the members of my jury for the discussions at the PhD defence, and for
the interest and the positive feedback on my work. I was honoured by the two rapporteurs,
Marco Borga and Nicolas Massei, for agreeing to evaluate my dissertation, and I want to
thank them for the constructive and relevant remarks on my work and on the manuscript.
Thanks to Agnès Ducharne, serving as Chair of the committee, and to Hubert Savenije,
Isabella Zin and Lionel Berthet for sharing relevant comments and appropriate suggestions to
improve the manuscript.
I would also like to thank the members of my PhD guidance committees, Nicolas Le Moine,
Charles Obled, Federico Garavaglia, Pierre Javelle, Rémi Lamblin, and Flora Branger who
participated to the two mid-term meetings on my research work. They shared their
independent point of view and ideas on the possible directions to follow in this research and
helped me to choose some good paths. Special thanks are owed to Nicolas for agreeing to
represent my doctoral school (ED GRNE, UPMC) for these committees, and for the other
inspiring discussions we had on other occasions. Many thanks also to Maria-Helena Ramos
and Guillaume Thirel for participating in the discussions of the guidance committees, as
permanent members of the team, and for the suggestions on other occasions. Thanks also to
Bernard Cappelaere for his comments and exchanges by email for my mid-term committee.
This PhD research work was financed by Irstea and SCHAPI (Service central
d’hydrométéorologie et d’appui à la prévision des inondations). I owe thanks to the people at
SCHAPI who believed in this project and agreed to support it, and particularly to Bruno Janet,
Rémi Lamblin and Léa Garandeau, who significantly contributed to this.
SCHAPI and Météo-France provided the hydro-climatic data used in this thesis and they need
to be thanked for the essential steps of data collection and provision. I contacted also some
French hydrological services of DREAL (regional environment agencies) and SPCs (flood
forecasting services), to retrieve additional information on the streamflow data and I received
many kind replies by managers and technicians. I owe my thanks to all of them.
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Working in the Catchment Hydrology team at Irstea (Antony) was an unforgettable
experience and it is difficult to leave such a great team! The list of colleagues I had the chance
to meet in these three years is long. I would like to mention all “les hydros”, but here I will do
my best in remembering the names of all of those with whom I spent more time… Carine,
Philippe, Louise, Laure, Alban, François, Florent, Pierre N., Olivier, Julie, Pierre B., Laurent,
Carina, Angelica, Léonard, Cédric, Manon, Morgane, Jose, Helena, Guillaume, Charles,
Vazken, David, Arnaud, Gaia, Julien, Damien, Sylvia, Audrey, Tito, Louise II, Cuan, and
Jeff. My regards also go to all the nice people staying for a shorter time, as the stagiaires, for
participating to the very nice ambiance, the sport activities, the socio-hydrological events at
Chez Mamane, and the NASH celebrations for the new hydrological year. Special thanks to
Alban and Julien for the nice scientific collaboration, to Olivier for sharing his multiple
expertise in R, GIS, and statistics, and to the “anciens”, particularly François and Florent, for
their good example and their support in the beginning. A friendly thought to all the PhD
mates for the good moments, the coffee breaks, and the mutual support. I am already missing
my “super colocs”, Philippe, Carine, Louise, and Manon (what a good company… sharing
sweets and magic pears in the end!). Now I wish a successful continuation to the next PhD
adventurers!
I cannot forget all who shared many nice moments at Irstea playing Ultimate Frisbee and
Football! In particular, thanks to the many people from my research unit HBAN. Thanks to
the “MPG” players for the funny moments in real and simulated games. Thanks to the
administrative and informatics team at Irstea, in particular to Roger, Sylvain, Nathalie,
Laurence and Elizabeth, for their kind and expert support.
Thanks to Dovy Tristani, François Baudin and Loïc Labrousse for the kind support, the
opportunity of participating to the “stage de terrain”, and the training sessions of the Ecole
Doctorale “Géosciences, Ressources Naturelles et Environnement”.
Thanks also to David Dorchies, Pierre-Olivier Malaterre, Luciano Raso, and Francesca
Pianosi for the inspiring collaboration during my MSc thesis which prompted me to embark
on this journey.
Thanks to my friends, “les cocos”, and my Parisian family of “Moulinois(es)” who made
these years so lovely and rich of good times, music, cooking, and laughs. Heartfelt thanks to
Anne, Diana, John, Thomas, Justine, Ulvika, and Ankur.
Finally, last but not least, I would like to thank my family, especially my parents, and
Massimo and Mari, for the continuous encouragement, love and great support over the years.
Special thanks to my uncle Donato, for the support in the last days before the PhD defence.
My highest thoughts go to my aunt, Maria, who passed away too soon, for her smile and
positive approach to life that I will keep with me.
Thank you all! Merci beaucoup! Grazie mille!

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Abstract

This thesis aims at exploring the question of temporal scaling in lumped conceptual
hydrological modelling. The main objectives of the thesis are to: (i) study the effects of
varying the modelling time step on the performance, parameters and structure of hydrological
models; (ii) develop a hydrological model operating at different time steps, from daily to sub-
hourly, through a unified, robust and coherent modelling framework at different time scales.
Our starting point is the chain of conceptual rainfall-runoff models called ‘GR’, developed at
Irstea, and in particular the daily ‘GR4J’ lumped model. The GR4J model will be the baseline
model to be effectively downscaled up to sub-hourly time steps following a top-down
approach. An hourly adaptation of this model had already been proposed in previous research
studies, but some questions on the optimality of the structure at sub-daily time steps were still
open. This thesis builds on these previous studies on the hourly model and responds to the
operational expectations of improving and adapting the model at multiple sub-daily and sub-
hourly time steps, which is particularly interesting for flood forecasting applications. For our
modelling tests, we built a database of 240 unregulated catchments in metropolitan France, at
multiple time steps, from 6-minute to 1 day, using fine time step hydro-climatic datasets
available: (i) 6-min rain gauges and higher spatial-density daily reanalysis data for
precipitation; (ii) daily temperature data for potential evapotranspiration (making assumptions
on sub-daily patterns); (iii) sub-hourly variable time step streamflow data. We investigated
the impact of the inputs temporal distribution on model outputs and performance in a flood
simulation perspective based on 2400 selected flood events. Then our model evaluation
focused on the consistency of model internal fluxes at different time steps, in order to ensure
obtaining a satisfactory model performance by a coherent model functioning at multiple time
steps. Our model diagnosis led us to identify and test a significant improvement of the model
structure at sub-daily time steps based on the complexification of the interception component
of the model. Thus, we propose a new version of the model at multiple sub-daily time steps,
with the addition of an interception store without extra free parameters. Our tests also confirm
the suitability at multiple time steps of a modified groundwater exchange function proposed
earlier, leading to overall improved model accuracy and coherence.

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Résumé
Cette thèse vise à explorer la question du changement d’échelle temporelle en modélisation
hydrologique conceptuelle globale. Les principaux objectifs de la thèse sont : (i) étudier les
effets du changement du pas de temps sur les performances, les paramètres et la structure des
modèles hydrologiques ; (ii) mettre au point un modèle pluie-débit applicable à différents pas
de temps, allant du journalier à l’infra-horaire, au travers d’un cadre de modélisation unifié,
robuste et cohérent à différents pas de temps. Notre point de départ est la chaîne de modèles
‘GR’, développée à Irstea, et plus particulièrement le modèle global journalier GR4J. Ce
modèle a été choisi comme le modèle de référence à adapter à d’autres résolutions plus fines,
jusqu'à des pas de temps infra-horaires, en suivant une approche descendante. Une adaptation
horaire de ce modèle avait déjà été proposée dans des travaux antérieurs, mais certaines
questions sur l’optimalité de la structure à des pas de temps infra-journaliers restent ouvertes.
Cette thèse s’appuie sur ces études antérieures sur le modèle horaire et est une réponse aux
attentes opérationnelles d’améliorer et d’adapter le modèle à des pas de temps infra-journalier
et infra-horaires, ce qui est particulièrement intéressant pour la prévision des crues. Pour nos
tests de modélisation, nous avons construit une base de données de 240 bassins versants non
influencés en France métropolitaine, à différents pas de temps allant de 6 minutes à 1 jour, en
utilisant des jeux de données disponibles à pas de temps fin : (i) les données pluviométriques
à 6 minutes et la réanalyse des lames d’eau journalières à plus haute résolution spatiale ; (ii)
les données de température journalière pour le calcul de l’évapotranspiration potentielle ; (iii)
les données hydrométriques à pas de temps variable. Nous avons étudié l'impact de la
distribution temporelle des entrées sur les sorties et les performances du modèle en se
focalisant sur la simulation de crue, sur la base de 2400 événements. Ensuite, notre évaluation
du modèle a porté sur l’analyse de la cohérence des flux internes du modèle à différents pas
de temps, afin d'assurer une performance satisfaisante à travers un fonctionnement du modèle
cohérent. Notre diagnostic du modèle nous a permis d’identifier et de tester une amélioration
de la structure du modèle à différents pas de temps infra-journaliers basée sur la
complexification de la composante d’interception du modèle. Ainsi, nous proposons une
nouvelle version du modèle, fonctionnant à différents pas de temps infra-journaliers, avec
l’ajout d’un réservoir d’interception sans paramètre libre additionnel. Nos tests confirment
aussi l’adéquation à pas de temps multiples d’une fonction d’échanges souterrains proposée
précédemment, conduisant à une meilleure qualité et cohérence globale du modèle.

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Contents

Introduction 1
1 State-of-the-art of rainfall-runoff modelling and scale issues in hydrology:
A critical overview 9
1.1 Catchment hydrology 11
1.2 Rainfall-runoff modelling 14
1.2.1 Hydrological modelling framework 14
1.2.2 Hydrological modelling limitations and temporal averaging effects 19
1.2.3 Objectives of modelling: simulation and forecast over a wide range of time scales 21
1.2.4 Types of models: towards a scale-dependent process-based classification 22
1.2.5 Desirable properties of rainfall-runoff models 30
1.2.6 The fixed and flexible modelling paradigms and our model choice 32
1.3 The space and time scale issues in hydrology 33
1.3.1 General concepts and typical scales of hydrological processes 33
1.3.2 The importance of spatial and temporal rainfall distribution 36
1.3.3 Catchment characteristic time scales 38
1.4 State-of-the-art on the temporal scale issue in rainfall-runoff modelling 39
1.4.1 Relation between process, observation and modelling scale 39
1.4.2 Effects of time steps on model parameters and performance 40
1.4.3 Model structures 45
1.5 Synthesis and resulting research objectives 52
2 Material and methods 55
2.1 Introduction 57
2.2 Building-up the hydro-climatic database 57
2.2.1 Precipitation data 57
2.2.2 Streamflow data 64
2.2.3 Evapotranspiration data 66
2.3 Catchment selection criteria 67
2.3.1 Criteria on catchment characteristics 68
2.3.2 Criteria on rainfall data 69
2.3.3 Criteria on flow data 73
2.3.4 Additional catchments recovered for particular reasons 75
2.4 Summary of the characteristics of our catchment sample 77
2.4.1 Morphological and hydro-climatic characteristics 77
2.4.2 Hydrological regimes 82
2.4.3 Operational interest of our catchment sample 85
2.4.4 Synthesis of the catchment characteristics 86
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