Author:
Anderton S. P.,Latron J.,White S. M.,Llorens P.,Gallart F.,Salvany C.,O’Connell P. E.
Abstract
Abstract. An evaluation of the performance of a physically-based distributed model of a small Mediterranean mountain catchment is presented. This was carried out using hydrological response data, including measurements of runoff, soil moisture, phreatic surface level and actual evapotranspiration. A-priori model parameterisation was based as far as possible on property data measured in the catchment. Limited model calibration was required to identify an appropriate value for terms controlling water loss to a deeper regional aquifer. The model provided good results for an initial calibration period, when judged in terms of catchment discharge. However, model performance for runoff declined substantially when evaluated against a consecutive, rather drier, period of data. Evaluation against other catchment responses allowed identification of the problems responsible for the observed lack of model robustness in flow simulation. In particular, it was shown that an incorrect parameterisation of the soil water model was preventing adequate representation of drainage from soils during hydrograph recessions. This excess moisture was then being removed via an overestimation of evapotranspiration. It also appeared that the model underestimated canopy interception. The results presented here suggest that model evaluation against catchment scale variables summarising its water balance can be of great use in identifying problems with model parameterisation, even for distributed models. Evaluation using spatially distributed data yielded less useful information on model performance, owing to the relative sparseness of data points, and problems of mismatch of scale between the measurement and the model grid. Keywords: physically-based distributed model, SHETRAN, parameterisation, Mediterranean mountain catchment, internal evaluation, multi-response
Subject
General Earth and Planetary Sciences,General Engineering,General Environmental Science
Cited by
38 articles.
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