Tribune Libre : L'unicité de lieu, d'action et de temps

Beven, Keith; Musy, A.; Higy, Christophe

doi:10.7202/705431ar

Cited by 7 publications

(4 citation statements)

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“…It does not have measurement techniques to assess all the relevant variables at the different scales of interest and consequently tends to use causal theory developed at laboratory scales as if it applied at larger scales even though there are reasons to doubt the validity of this approach (see, for example, Beven, 2006b and discussion of the Darcy-Richards and Manning equations above). It has to deal with the fact that every catchment is unique in its detailed characteristics and therefore any causal model will have some parameters that need to be adjusted or calibrated to allow for this uniqueness (Beven, 2000;Beven et al, 2002;De Marsily, 1994;Ganoulis, 1996). In these features it is quite representative of the environmental sciences in general (see the general discussions in Beven, 2009;Morton, 1993).…”

Section: Compromise Between Model Acceptance and Model Rejection: A H...mentioning

confidence: 99%

Causal models as multiple working hypotheses about environmental processes

Beven

2012

Comptes Rendus. Géoscience

115

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Section: Compromise Between Model Acceptance and Model Rejection: A H...mentioning

confidence: 99%

Causal models as multiple working hypotheses about environmental processes

Beven

2012

Comptes Rendus. Géoscience

115

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“…Additional uncertainties arise when only few measured data are available, increasing equifinality thus weakening the physical meaning of parameters, as discussed by de Marsily [1994] and then Beven et al [2001] from a theoretical point of view. While intended to describe a wide set of often nonobservable events, the construction of a model is a deterministic process that relies on a limited series of scenarios and choices.…”

Section: Position Regarding Hydrology-erosion Modelsmentioning

confidence: 99%

“…[7] Sufficient complexity of underlying hydrological models is a prerequisite to accurate erosion modeling, at the risk of degraded performances due to overparameterization [Beven, 1989], especially for models involving spatially distributed parameters [Beven, 1993]. Additional uncertainties arise when only few measured data are available, increasing equifinality thus weakening the physical meaning of parameters, as discussed by de Marsily [1994] and then Beven et al [2001] from a theoretical point of view. While intended to describe a wide set of often nonobservable events, the construction of a model is a deterministic process that relies on a limited series of scenarios and choices.…”

Section: Position Regarding Hydrology-erosion Modelsmentioning

confidence: 99%

Sensitivity analysis of distributed erosion models: Framework

Cheviron

Bissonnais

Moussa

et al. 2010

Water Resources Research

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[1] We introduce the (P, R, p) procedure for analysis of distributed erosion models, evaluating separate sensitivities to input fluxes (precipitations P), to the propensity of soil to surface flow (runoff conditions R), and to specific erosion properties (descriptive parameters p). For genericity and easier comparisons between models, superparameters of equivalent slope and equivalent erodibility are assembled from innate descriptive parameters: parameterization is reduced to four coded integers that are arguments of the soil loss function. Directional sensitivities are calculated in a deterministic way, associated with any selected displacement in parameter space. In this multistage and risk-orientated procedure, special emphasis is placed on trajectories from best-case toward worst-case scenarios, involving one-at-a-time variations and Latin Hypercube samples. Sensitivity maps are produced in the superparameter plane, tracing risk isovalues and estimating the relative importance of the equivalent parameters and of their spatial distributions.

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“…We wish only to accept models that are likely to be robust to errors in prediction. This is a problem because of the lack of replicate observations when the system response may be unique with respect to time, place, and action (De Marsily, 1994;Beven et al, 2002). 4.…”

Section: Principles Of Hypothesis Testing By Setting Limits-of-acceptmentioning

confidence: 99%

Preferential flows and travel time distributions: defining adequate hypothesis tests for hydrological process models

Beven

2010

Hydrological Processes

102

109

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Abstract:This introduction to the second annual review issue of Hydrological Processes tries to put the collection of papers on preferential flows and travel time distributions into a more general context of testing models as hypotheses about how catchment systems function. It is suggested that, because of the possibilities of non-stationary and epistemic errors in both data and models, such tests could be carried out within a rejectionist limits-of-acceptability framework. The principles and difficulties of hypothesis testing within these particular research areas are discussed. An important point to take from this discussion is that the use of a formal testing framework, and the consequent rejection of models as hypotheses after allowing for uncertainties in the data, is the starting point for developing better theories and data sets. easy to suggest that one of the most productive frameworks for such an interaction might be in testing quantitative hydrological models as hypotheses about how a hydrological system is functioning (see also the earlier Hydrological Processes invited commentary of Beven, 2001). There is clearly no shortage of numerical models that might be considered as feasible hypotheses, the difficulty is differentiating between them as hypotheses so that we can work towards getting the right hydrological predictions for the right reasons. Field data, however, are not often collected in experimental catchments with this aim in mind, but rather with extending our perceptual understanding of how catchments work. The quantitative modelling often comes later, as an approximation.This has certainly been the case with the focus on the articles in this annual review issue of Hydrological Processes, which are concerned with preferential flows and travel time distributions. From the papers presented, it is clear that in both of these areas there is still significant progress to be made in the understanding and theoretical representation of the relevant processes in hypotheses and models. There is, as yet, no real consensus as to how to quantify the effects of preferential flow pathways at hillslope and catchment scales, nor as to what form of travel time distributions should be used in different conditions. We tend rather to resort to the fitting of different functions to whatever observational data are available, often without taking any explicit account of which underlying process mechanisms might be involved.

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Tribune Libre : L'unicité de lieu, d'action et de temps

Cited by 7 publications

References 0 publications

Causal models as multiple working hypotheses about environmental processes

Causal models as multiple working hypotheses about environmental processes

Sensitivity analysis of distributed erosion models: Framework

Preferential flows and travel time distributions: defining adequate hypothesis tests for hydrological process models

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