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X - 24LERAT ET AL.: VALUE OF UPSTREAM FLOW MEASUREMENTScontribution from the intermediate area INT and the routed upstream runoff from theupstream subcatchment. The third panel of Figure 9 shows the difference between similarcomponents from the two models.Figure 9 reveals that both simulations are nearly identical (differences on TOTAL lower440than 2 m 3 /s) with compensations between the two components: lower routed upstreamtel-00392240, version 1 - 5 Jun 2009445450455flows from the benchmark model (negative difference on ROUT ( ˆQ UP ) on Figure 9) is Figure 9compensated by higher intermediate runoff (RR(P INT , P E INT ) on the same figure). Theuse of upstream flow data during the calibration adds internal consistency to the UP-Sim model with better simulations on the UP point compared to the benchmark (seeTable 3), ... but this is not sufficient to increase the quality of downstream simulations Table 3on the TOTAL point. The additional value of the knowledge on upstream flows usedduring the calibration process appeared negligible to simulate downstream flows withour semidistributed model. This result reveals how difficult it is to increase the quality ofspatially explicit models: potential compensations between the components may overcomethe marginal value of additional internal information.6. ConclusionIn this work, we have studied the value of upstream flow measurements to simulatedownstream flow with a semidistributed model. Several experiments were conducted toverify the well-known advantage of including upstream flow data in spatially explicithydrological models. The key results are:1. With a test on 192 nested catchments in a temperate climate showing a wide diversityof configurations, we confirmed the advantage of using upstream flow measurements asan additional input. Comparing a model using this input and a benchmark model runD R A F T July 24, 2008, 3:43pm D R A F T
LERAT ET AL.: VALUE OF UPSTREAM FLOW MEASUREMENTS X - 25without it revealed a nearly systematic gain in the Nash-Sutcliffe criteria in validationmode. Of course, exceptions exist where the introduction of upstream flow measurements460fail to improve downstream simulations but these cases were very limited.2. The ratio between upstream and downstream flows appeared as the key driver forthis performance gain. Simple relationships between different formulations of this ratiowere proposed to give a preliminary estimate of the expected performance gain.3. A surprising result was obtained while conducting a sensitivity analysis on the quality465of upstream flow data: the corruption of these data with a power transform that increasestel-00392240, version 1 - 5 Jun 2009470475480the high upstream flow regime lead to a significant performance gain. It was found thatthis artifical increase induced a reduction of the rainfall-runoff component to the profitof the routing component and thus an increase in the upstream flow measurement weightin the downstream simulation. The value of upstream flow measurements then appearedhigher than the rainfall data to simulate streamflows at a catchment outlet.4. A final experiment was conducted to investigate situations where these upstreamflow measurements are no longer available in validation mode. Strinkingly, all performancegains obtained previously were annihilated due to compensations between the differentcomponents of the model. This conclusion revealed how difficult it is to build spatiallyexplicit hydrological model in the abscence of measurements of internal streamflow.To continue this work, we are particularly interested in testing different strategies toweight upstream flow measurements in the semidistributed model, and to extract as muchinformation as possible from this additional input. Also, tests could be enlarged to finertime-steps where flow routing becomes more complex and could introduce additional errorsthat were not significant in our experiments.D R A F T July 24, 2008, 3:43pm D R A F T
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Université Pierre et Marie CurieEc
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3Remerciementstel-00392240, version
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Table des matièresIntroduction gé
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TABLE DES MATIÈRES 7tel-00392240,
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TABLE DES MATIÈRES 9FGParamètres
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tel-00392240, version 1 - 5 Jun 200
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Introduction générale 13Contextet
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Introduction générale 15Probléma
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Introduction générale 17Crue de d
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Première partietel-00392240, versi
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Chapitre 1Apports latéraux dans le
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Chapitre 1. Apports latéraux dans
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Chapitre 2Présentation de l’éch
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Chapitre 2. Présentation de l’é
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Chapitre 3Choix des modèles hydrol
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Chapitre 3. Choix des modèles hydr
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Chapitre 4Stratégie de calage et d
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Chapitre 4. Stratégie de calage et
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Deuxième partietel-00392240, versi
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Chapitre 5Jusqu’où est-il néces
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Chapitre 5. Jusqu’où est-il néc
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Chapitre 6Sensibilité d’un modè
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Chapitre 6. Sensibilité d’un mod
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Chapitre 7Simplifications de la str
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Chapitre 7. Simplifications de la s
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Conclusion générale 177Dans le ca
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Conclusion générale 179Quel est l
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BibliographieAbbott, M. et Refsgaar
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BIBLIOGRAPHIE 183Brutsaert, W. (200
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BIBLIOGRAPHIE 185Jakeman, A. et Hor
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BIBLIOGRAPHIE 187MEEDDAT (2008). Ba
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BIBLIOGRAPHIE 189Oudin, L., Andréa
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BIBLIOGRAPHIE 191Shamseldin, A., O
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Annexe ATable de correspondance ent
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Annexe A. Table de correspondance e
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Annexe BCaractéristiques et cartes
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Annexe B. Caractéristiques et cart
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Légende des cartes8 kmMaillage SAF
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Annexe CLes débits négatifs dans
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Annexe C. Les débits négatifs dan
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Annexe DApproximation de la courbe
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Annexe D. Approximation de la courb
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Annexe EAlgorithmique et codes C de
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Annexe E. Algorithmique et codes C
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Annexe Ftel-00392240, version 1 - 5
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Annexe F. Paramètres et critères
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Annexe F. Paramètres et critères
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Annexe GParamètres et critères de
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Annexe G. Paramètres et critères
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Annexe G. Paramètres et critères
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Annexe Htel-00392240, version 1 - 5
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Towards robust methods to couple lu
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5forecasting (Smith et al., 2009, t
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tion for a hydraulic model.These tw
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Apart from these few examples, the
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150nel (see Figure 1.d).All the dat
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tributed. Accordingly, the differen
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4.2 Lumped Rainfall-Runoff Model245
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∫ tO(t) = Ψ(t)+0with: Ψ(t) = L[
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model. The main advantage of this p
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