Impact of model simplifications on soil erosion predictions: application of the GLUE methodology to a distributed event-based model at the hillslope scale
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Impact of model simplifications on soil erosion predictions: application of the GLUE methodology to a distributed event-based model at the hillslope scaleFecha
2016Centro/Dpto/Entidad
Enxeñaría da Auga e do Medio Ambiente (GEAMA)Cita bibliográfica
Cea, L., Legout, C., Grangeon, T., & Nord, G. (2016). Impact of model simplifications on soil erosion predictions: application of the GLUE methodology to a distributed event‐based model at the hillslope scale. Hydrological Processes, 30(7), 1096-1113. https://doi.org/10.1002/hyp.10697
Resumen
[Abstract:] In this paper, we analyse how the performance and calibration of a distributed event-based soil erosion model at the hillslope scale is affected by different simplifications on the parameterizations used to compute the production of suspended sediment by rainfall and runoff. Six modelling scenarios of different complexity are used to evaluate the temporal variability of the sedimentograph at the outlet of a 60 m long cultivated hillslope. The six scenarios are calibrated within the generalized likelihood uncertainty estimation framework in order to account for parameter uncertainty, and their performance is evaluated against experimental data registered during five storm events. The Nash–Sutcliffe efficiency, percent bias and coverage performance ratios show that the sedimentary response of the hillslope in terms of mass flux of eroded soil can be efficiently captured by a model structure including only two soil erodibility parameters, which control the rainfall and runoff production of suspended sediment. Increasing the number of parameters makes the calibration process more complex without increasing in a noticeable manner the predictive capability of the model.
Palabras clave
Soil erosion
Rainfall runoff
Physically-based model
Model calibration
Model validation
GLUE
Rainfall runoff
Physically-based model
Model calibration
Model validation
GLUE
Descripción
Versión aceptada de https://doi.org/10.1002/hyp.10697
Versión del editor
Derechos
© 2015 John Wiley & Sons, Ltd.
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