Space-time scale sensitivity of the Sacramento model to radar-gage precipitation inputs

Finnerty, Bryce; Smith, Michael; Seo, Dong Jun; Koren, Victor; Moglen, Glenn E.

doi:10.1016/s0022-1694(97)00083-8

Cited by 141 publications

(86 citation statements)

References 17 publications

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“…Over complex terrain, the occurrence and frequency of runoff generation depends on the spatiotemporal characteristics of catchment topography, soils, climate, rainfall and antecedent wetness. Given this variability, it is recognized that watershed response can correspond to runoff production from multiple mechanisms arranged in spatially distinct areas or possibly due to a single dominant type in the basin (e.g., Freeze, 1974;Dunne, 1978;Smith and Hebbert, 1983). Runoff production from multiple mechanisms will vary with the rainfall and landscape factors influencing the coupled unsaturated-saturated dynamics.…”

Section: Runoff Generation Processesmentioning

confidence: 99%

“…The variability in rainfall duration, intensity and spatial distribution, in addition to prior wetness in the basin, leads to a complex runoff response during storms (Smith et al, 2004b). Multiple runoff mechanisms occur due to the heterogeneity in basin properties and lead to flood hydrographs of varying magnitudes (Finnerty et al, 1997;Carpenter et al, 2001;Ivanov et al, 2004b). Large flood events in the basin have a tendency to occur in early fall and late spring due to frontal storms (Bradley and Smith, 1994).…”

Section: Rainfall and Streamflow Observationsmentioning

confidence: 99%

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Controls on runoff generation and scale-dependence in a distributed hydrologic model

Vivoni

Entekhabi

Bras

et al. 2007

Hydrol. Earth Syst. Sci.

133

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Abstract. Hydrologic response in natural catchments is controlled by a set of complex interactions between storm properties, basin characteristics and antecedent wetness conditions. This study investigates the transient runoff response to spatially-uniform storms of varying properties using a distributed model of the coupled surface-subsurface system, which treats heterogeneities in topography, soils and vegetation. We demonstrate the control that the partitioning into multiple runoff mechanisms (infiltration-excess, saturationexcess, perched return flow and groundwater exfiltration) has on nonlinearities in the rainfall-runoff transformation and its scale-dependence. Antecedent wetness imposed through a distributed water table position is varied to illustrate its effect on runoff generation. Results indicate that transitions observed in basin flood response and its nonlinear and scaledependent behavior can be explained by shifts in the surfacesubsurface partitioning. An analysis of the spatial organization of runoff production also shows that multiple mechanisms have specific catchment niches and can occur simultaneously in the basin. In addition, catchment scale plays an important role in the distribution of runoff production as basin characteristics (soils, vegetation, topography and initial wetness) are varied with basin area. For example, we illustrate how storm characteristics and antecedent wetness play an important role in the scaling properties of the catchment runoff ratio.

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Section: Runoff Generation Processesmentioning

confidence: 99%

Section: Rainfall and Streamflow Observationsmentioning

confidence: 99%

Controls on runoff generation and scale-dependence in a distributed hydrologic model

Vivoni

Entekhabi

Bras

et al. 2007

Hydrol. Earth Syst. Sci.

133

View full text Add to dashboard Cite

show abstract

“…While errors due to both factors have received much recent attention in the literature [e.g., Finnerty et al, 1997;Butts et al, 2004;Carpenter and Georgakakos, 2004;Wagener and Gupta, 2005;Borga et al, 2006;Huard and Mailhot, 2006;Kavetski et al, 2006aKavetski et al, , 2006bKuczera et al, 2006;Oudin et al, 2006], data assimilation and ensemble forecasting frameworks are considered effective means of improving forecasts in the face of uncertainty [e.g., Kavetski et al, 2002;Vrugt et al, 2005;Carpenter and Georgakakos, 2006a;Kavetski et al, 2006a;Moradkhani et al, 2005aMoradkhani et al, , 2005bMoradkhani et al, , 2006Oudin et al, 2006;Russo et al, 2006;Vrugt et al, 2006;Ajami et al, 2007;Gabellani et al, 2007;Smith et al, 2008]. Both approaches require specification of realistic uncertainty descriptions for the hydrologic models and their rainfall input.…”

Section: Introductionmentioning

confidence: 99%

Product‐error‐driven generator of probable rainfall conditioned on WSR‐88D precipitation estimates

Villarini

Krajewski

Ciach

et al. 2009

Water Resources Research

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[1] The existence of large errors in precipitation products delivered by the network of Weather Surveillance Radar, 1988 Doppler (WSR-88D) radars is broadly recognized. However, their quantitative characteristics remain poorly understood. Recently, the authors developed a functional-statistical model that quantifies the relation between radar rainfall and the corresponding true rainfall in a way that is applicable to the probabilistic quantitative precipitation estimation planned for future use by the U.S. National Weather Service. The model consists of a deterministic distortion function and a random uncertainty factor, both conditioned on given radar rainfall values. It also accounts for the spatiotemporal correlations in the random uncertainty factor. The model components were estimated on the basis of a 6-year-long data sample that considers the effects of seasons, range from radar, and time scales. In this study, the authors present two different applications of the aforementioned uncertainty model: (1) the estimation of rainfall probability maps and (2) the generation of radar rainfall ensembles. In the former, maps of the rainfall exceedance probability for any threshold are produced, given a radar rainfall map. We also present the analytical derivation of the exceedance probability maps at coarser spatial scales. In the latter, the users can generate ensembles of probable true rainfall fields that are consistent with the observed radar rainfall and its error structure. Simulation of the random component is based on the Cholesky decomposition method. Finally, the authors discuss possible uses of these applications in hydrology and hydroclimatology.

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“…Documented research has demonstrated that the spatial/temporal resolutions of climate, geographical and ecological factors may lead to noticeably different outputs (Su et al, 1999;Yang et al, 2001;Xu & Yan, 2005), and the scaling effects of surface heat fluxes increase with land surface heterogeneity (Sridhar et al, 2003), since spatial information may get lost with a coarse grid size in modelling (Schoorl et al, 2000). It has been reported that simulated runoff increased and actual evapotranspiration (ET) decreased, while grid size changed from coarse to fine (Famiglietti & Wood, 1994;Arola & Lettenmaier, 1996;Finnerty et al, 1997;Becker & Braun, 1999;Kuo et al, 1999;Cerdan et al, 2004;Hessel, 2005). Model performance efficiency is dependent on the parameters calibrated at a specific grid size (Vazquez et al, 2002), which should converge as the grid size becomes finer (Miller et al, 1994).…”

Section: Introductionmentioning

confidence: 99%

Grid-size effects on estimation of evapotranspiration and gross primary production over a large Loess Plateau basin, China

Liu

Chen

et al. 2009

Hydrological Sciences Journal

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A distributed eco-hydrological model based on soil vegetation atmosphere transfer processes is applied to estimate actual evapotranspiration (ET) and gross primary production (GPP) over the Wuding River basin, Loess Plateau, China, based on digital elevation model, vegetation and soil information between 2000 and 2003 over three grid sizes: 250 m, 1 km and 8 km. The spatial patterns of annual ET and GPP are related to precipitation variability and land-use/cover conditions. The grid size is shown to affect the spatial patterns of annual ET and GPP, the effect on GPP being more significant than that on ET. Geostatistical and regression analyses demonstrate that precipitation and vegetation influence the scaling effect of ET and GPP in a complex way. When precipitation is high, the scaling effect of ET is more dependent on precipitation. The scaling effect of ET and GPP from 1-km to 8-km grid size is much larger than that from 250-m to 1-km grid size, showing the 1-km grid size to be a feasible choice for simulation of their spatial patterns. Although the annual GPP is more sensitive to the grid size than annual ET, both daily ET and daily GPP averaged over the whole basin seem to be insensitive to the grid size, illustrating that the coarse grid size can be used to simulate spatially-averaged variables without losing much accuracy.Key words distributed eco-hydrological model; scaling effect; evapotranspiration; gross primary production Effets de la résolution du maillage spatial sur l'estimation de l'évapotranspiration et de la production primaire brute au sein d'un grand bassin versant du Plateau Loessique Résumé Un modèle éco-hydrologique distribué, basé sur les processus de transfert dans le continuum solplante-atmosphère, est appliqué pour estimer l'évapotranspiration réelle (ET) et la production primaire brute (PPB) au sein du bassin versant de la Rivière Wuding, dans le Plateau Loessique chinois. L'application s'appuie sur un modèle numérique de terrain et des informations relatives à la végétation et au sol de la période 2000-2003, pour trois résolutions de maillage: 250-m, 1-km et 8-km. Les organisations spatiales de l'ET et de la PPB annuelles sont corrélées avec la variabilité des précipitations et avec l'occupation du sol. La résolution du maillage se révèle avoir de l'influence sur l'organisation de l'ET et de la PPB annuelles, l'effet sur la PPB étant plus significatif que sur l'ET. Des analyses géostatistiques et par régression mettent en évidence que les précipitations et la végétation influencent l'effet d'échelle de l'ET et de la PPB d'une façon complexe. Lorsque les précipitations sont importantes, l'effet d'échelle de l'ET est plus dépendant des précipitations. L'effet d'échelle de l'ET et de la PPB entre les résolutions de maillage de 1 et de 8 km est plus fort qu'entre les résolutions de 250 m et de 1 km, ce qui montre que la résolution de 1 km est un choix possible pour la simulation de leurs organisations spatiales. Bien que la PPB annuelle soit plus sensible à la résolution de la ...

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Space-time scale sensitivity of the Sacramento model to radar-gage precipitation inputs

Cited by 141 publications

References 17 publications

Controls on runoff generation and scale-dependence in a distributed hydrologic model

Controls on runoff generation and scale-dependence in a distributed hydrologic model

Product‐error‐driven generator of probable rainfall conditioned on WSR‐88D precipitation estimates

Grid-size effects on estimation of evapotranspiration and gross primary production over a large Loess Plateau basin, China

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