@article{vanSchaikBronstertdeJongetal.2014,
  author    = {van Schaik, N. Loes M. B. and Bronstert, Axel and de Jong, S. M. and Jetten, V. G. and van Dam, J. C. and Ritsema, C. J. and Schnabel, Susanne},
  title     = {Process-based modelling of a headwater catchment in a semi-arid area: the influence of macropore flow},
  series = {Hydrological processes},
  volume    = {28},
  journal   = {Hydrological processes},
  number    = {24},
  publisher = {Wiley-Blackwell},
  address   = {Hoboken},
  issn      = {0885-6087},
  doi       = {10.1002/hyp.10086},
  pages     = {5805 -- 5816},
  year      = {2014},
  abstract  = {Subsurface stormflow is thought to occur mainly in humid environments with steep terrains. However, in semi-arid areas, preferential flow through macropores can also result in a significant contribution of subsurface stormflow to catchment runoff for varying catchment conditions. Most hydrological models neglect this important subsurface preferential flow. Here, we use the process-oriented hydrological model Hillflow-3D, which includes a macropore flow approach, to simulate rainfall-runoff in the semi-arid Parapunos catchment in Spain, where macropore flow was observed in previous research. The model was extended for this study to account for sorptivity under very dry soil conditions. The results of the model simulations with and without macropore flow are compared. Both model versions give reasonable results for average rainfall situations, although the approach with the macropore concept provides slightly better results. The model results for scenarios of extreme rainfall events (>13.3mm30min(-1)) however show large differences between the versions with and without macropores. These model results compared with measured rainfall-runoff data show that the model with the macropore concept is better. Our conclusion is that preferential flow is important in controlling surface runoff in case of specific, high intensity rainfall events. Therefore, preferential flow processes must be included in hydrological models where we know that preferential flow occurs. Hydrological process models with a less detailed process description may fit observed average events reasonably well but can result in erroneous predictions for more extreme events. Copyright (c) 2013 John Wiley \& Sons, Ltd.},
  language  = {en}
}