Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

Tramblay, Yves; Bouvier, Christophe; Ayral, Pierre‐Alain; Marchandise, Arthur

doi:10.5194/nhess-11-157-2011

Cited by 69 publications

(70 citation statements)

References 46 publications

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“…However, hydrological simulations are "imperfect" [5] in the sense that they contain uncertainties which are mainly related to (i) the quality and quantity of the hydrological data used to drive the models [6][7][8] as well as representativeness errors due to scale incompatibility [9]; (ii) the simple representation of the real physical processes leading to inevitable assumptions and simplifications and thus unavoidably imperfect approximations to the complex reality [5] and (iii) errors in parameter estimates which can result in huge errors in the model outputs [10]. As a result, there is an urgent need for techniques that effectively and efficiently assimilate new sources of information into the models to produce less uncertain hydrological predictions.…”

Section: Introductionmentioning

confidence: 99%

Data Assimilation of Satellite Soil Moisture into Rainfall-Runoff Modelling: A Complex Recipe?

et al. 2015

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Data assimilation (DA) of satellite soil moisture (SM) observations represents a great opportunity for improving the ability of rainfall-runoff models in predicting river discharges. Many studies have been carried out so far demonstrating the possibility to reduce model prediction uncertainty by incorporating satellite SM observations. However, large discrepancies can be perceived between these studies with the result that successful DA is not only related to the quality of the satellite observations but can be significantly controlled by many methodological and morphoclimatic factors. In this article, through an experimental study carried out on the Tiber River basin in Central Italy, we explore how the catchment area, soil type, climatology, rescaling technique, observation and model error selection may affect the results of the assimilation and can be the causes of the apparent discrepancies obtained in the literature. The results show that: (i) DA of SM generally improves discharge predictions (with a mean efficiency of about 30%); (ii) unlike catchment area, the soil type and the catchment specific characteristics might have a remarkable influence on the results; (iii) simple rescaling techniques may perform equally well to more complex ones; (iv) an accurate quantification of the model error is paramount for a correct choice of the observation error and, (v) SM temporal variability has a stronger influence than the season itself. On this basis, we advise that DA of SM may be not a simple task and one should carefully test the optimality of the assimilation experiment prior to drawing any general conclusions. OPEN ACCESSRemote Sens. 2015, 7 11404

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Section: Introductionmentioning

confidence: 99%

Data Assimilation of Satellite Soil Moisture into Rainfall-Runoff Modelling: A Complex Recipe?

et al. 2015

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“…In this version, the contribution of soil drainage to delayed flows is ignored. Tramblay et al (2011) showed that it gives satisfactory results for 16 events at the Anduze station. In addition to this last observation, this version was chosen because it has a low number of adjustment parameters, which is an important criterion for flood forecasting.…”

Section: Scs-lr Hydrologic Modelmentioning

confidence: 99%

“…It is an event-based, distributed, conceptual model with reservoirs, based on a discretisation of the catchment in regular square cells. It has been used in many studies of Mediterranean watersheds of a limited area, in particular concerning the Gardon d'Anduze River basin (Bouvier et al, 2004(Bouvier et al, , 2006Marchandise, 2007;Marchandise and Viel, 2009;Coustau, 2011;Tramblay et al, 2011). It proves to be successful for modelling typical floods in Mediterranean watersheds, particularly compared with other models (Bouvier et al, 2006;Marchandise, 2007;Coustau, 2011).…”

Section: Scs-lr Hydrologic Modelmentioning

confidence: 99%

“…This model is a simplified version of the complete SCS-LR model of the ATHYS platform, and is identical to the one used by Tramblay et al (2011). In this version, the contribution of soil drainage to delayed flows is ignored.…”

Section: Scs-lr Hydrologic Modelmentioning

confidence: 99%

“…Also, it must be adapted to the context of floods of Mediterranean catchments. Particularly, studies of Mediterranean basins showed clear improvements in modelling when spatially distributed rainfall data are used at the entrance of the hydrologic model Anquetin et al, 2010;Zoccatelli et al, 2010;Tramblay et al, 2011). Thus, we choose a conceptual and distributed model based on a simplified but physically based description of the catchment.…”

Section: The Choice Of the Modelsmentioning

confidence: 99%

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A coupling of hydrologic and hydraulic models appropriate for the fast floods of the Gardon River basin (France)

Laganier¹,

Ayral²,

Salze³

et al. 2014

Nat. Hazards Earth Syst. Sci.

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Abstract. Mediterranean catchments are regularly affected by fast and flash floods. Numerous hydrologic models have been developed, and allow modelling of these floods. However, these approaches often concern average-size basins of a few hundred km 2 . At larger scales (> 1000 km 2 ), coupling of hydrologic and hydraulic models appears to be an adapted solution. This study has as its first objective the evaluation of the performances of a coupling of models for flood hydrograph modelling. Secondly, the coupling results are compared with those of other modelling options. The aim of these comparisons is to clear up the following points. (1) Is a simplified routing model (lag and route) as efficient as a full hydraulic model for the modelling of hydrographs, in the intermediary downstream part of the stream? (2) Is adding lateral inflows necessary for all studied events? (3) What is the impact of the qualities of upstream hydrologic modelling feeding the coupling? The coupling combines the SCS-LR (Soil Conservation Service-lag-and-route) hydrologic model of the ATHYS platform and the MASCARET 1-D hydraulic model based on full Saint-Venant equations. It is applied to the Gardon River basin (2040 km 2 ) in the south of France. For the seven studied events, the results of the coupling are satisfactory, the calculated Nash indexes varying between 0.61 and 0.97. The comparisons with the other modelling options show the important role of the spatial distribution of rains during events: when rains are centered on the intermediary downstream part of the catchment, adding lateral inflows is necessary; when rains are more important in the upstream part, the quality of the hydrologic modelling upstream of the coupling has a strong impact. Furthermore, the used coupling of models seems well adapted for water rising and flooded area forecasting. The future developments of the tool will concentrate on this point.

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Filling in the gaps: Inferring spatially distributed precipitation from gauge observations over complex terrain

Livneh

Deems

Schneider

et al. 2014

Water Resources Research

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In recent decades, computational hydrology has trended toward higher-resolution distributed models of the land surface. The accuracy of these models is limited, by uncertainty in distributed precipitation forcings. In this research, different precipitation distribution schemes were compared through inter-station transfer experiments, as well as within a distributed hydrologic model applied at 150 m resolution over four study catchments in complex terrain. Distributed precipitation estimates were derived using multiplicative spatial scaling (MSS) and map-based precipitation (MBP) techniques including both climatological and timevarying spatial information from a range of native spatial resolutions (500 m-4 km). The primary interest was to evaluate a novel application of satellite-based snow water equivalent (SWE) reconstruction (RSWE) as a surrogate for cold season precipitation against a common source of spatial precipitation information: the Parameter-elevation Regressions on Independent Slopes Model (PRISM). An elevation-based orographic precipitation gradient and simple inverse-distance interpolation were also included as a baseline. For the case of RSWE, MSS was very sensitive to differences between observed SWE and reconstructed SWE, producing positive biases in the catchment water balance. Over 12 year simulations, daily streamflow correlations from the uncalibrated model were highest for RSWE when adjusted for accumulation-season sublimation, and for monthly PRISM, both achieving R50.8, where the former performed better during anomalous years for both MSS and MBP. Annual water balance ratios were much more sensitive to the choice of distribution scheme, with large overestimates, > 30%, for RSWE products using the MSS techniques versus MBP (< 15%). Overall, PRISM performed best using MSS, while RSWE performed best using MBP.

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Impact of rainfall spatial distribution on rainfall-runoff modelling efficiency and initial soil moisture conditions estimation

Cited by 69 publications

References 46 publications

Data Assimilation of Satellite Soil Moisture into Rainfall-Runoff Modelling: A Complex Recipe?

Data Assimilation of Satellite Soil Moisture into Rainfall-Runoff Modelling: A Complex Recipe?

A coupling of hydrologic and hydraulic models appropriate for the fast floods of the Gardon River basin (France)

Filling in the gaps: Inferring spatially distributed precipitation from gauge observations over complex terrain

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