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X - 30LERAT ET AL.: VALUE OF UPSTREAM FLOW MEASUREMENTStel-00392240, version 1 - 5 Jun 2009Table 1.CharacteristicCharacteristics of the 192 catchment datasetPercentile Median Mean Percentile25 th 75 thDistance between stations along the riverDistance UP - TOTAL (km) 18 34 52 71Catchment areaUP (km 2 ) 78 170 258 334TOTAL (km 2 ) 534 1160 1771 2288Ratio S UP /S T OT AL (%) 7 17 22 33Annual discharge (mm)Station UP 300 395 480 530Station TOTAL 310 385 425 490Annual precipitation (mm)Catchment UP 860 940 1000 1080Catchment TOTAL 860 930 970 1040Annual PE (mm)Catchment UP 620 650 650 680Catchment TOTAL 630 660 660 690Table 2.The three semidistributed models tested. θ, θ ′ and θ ′′ are parameter sets for therainfall-runoff model. ρ and ρ ′ are parameter sets for the routing model.Model Parameters Parameters Inputson the UP on the INTsub-catch. interm. areaBenchmark θ θ P UP , P INTρUP-Meas - θ ′ P UP , P INTρ ′UP-Sim θ ′′ θ ′ P UP , P INTρ ′D R A F T July 24, 2008, 3:43pm D R A F T
LERAT ET AL.: VALUE OF UPSTREAM FLOW MEASUREMENTS X - 31Table 3.Performance of models in calibration and validation modes over the 192 catchments(Classical Nash-Sutcliffe efficiency CEff on 384 periods). Efficiency of upstream simulations cannotbe calculated for the UP-Meas model because the model uses measured upstream dischargestel-00392240, version 1 - 5 Jun 2009as input (see Figure 2).Models Benchmark UP-Meas UP-SimInputs P UP ,E UP , Q UP , P UP ,E UP ,P INT ,E INT P INT ,E INT P INT ,E INTCal. Ver. Cal. Ver. Cal. Ver.Upstream simulations (UP)25% quantile 0.47 0.46 - - 0.73 0.70Mean 0.59 0.57 - - 0.79 0.75Median 0.69 0.68 - - 0.83 0.7975% quantile 0.80 0.77 - - 0.88 0.85Downstream simulations (TOTAL)25% quantile 0.82 0.79 0.87 0.84 0.81 0.78Mean 0.86 0.83 0.90 0.88 0.84 0.81Median 0.88 0.86 0.92 0.90 0.88 0.8675% quantile 0.92 0.90 0.94 0.93 0.92 0.91Table 4.Results of the linear regression between the physical descriptors and the relativeefficiency REff(UP-Meas/Benchmark) in validation mode.Descriptor Regression Standardformula r 2 Deviation(least square) of residualsSurface REff = 0.62 0.08ratio (RS) 0.65 × RSMean Flow REff = 0.64 0.08ratio (RQM) 0.60 × RQM99% flow percentile REff = 0.67 0.08ratio(RQ99) 0.57 × RQ99D 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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tel-00392240, version 1 - 5 Jun 200
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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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that the robustness of the method c
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425no. 2, 7 and 11, see Table 1). O
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performance between low (one tribut
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