Towards the Reproducibility in Soil Erosion Modeling: A New Pan-European Soil Erosion Map. Bosco, C.; de Rigo, D.; Dewitte, O.; and Montanarella, L. In Keesstra, S. D. and Mol, G., editors, Wageningen Conference on Applied Soil Science : 'Soil Science in a Changing World'. Wageningen University.
Towards the Reproducibility in Soil Erosion Modeling: A New Pan-European Soil Erosion Map [link]Paper  doi  abstract   bibtex   
Soil erosion by water is a widespread phenomenon throughout Europe and has the potentiality, with his on-site and off-site effects, to affect water quality, food security and floods. Despite the implementation of numerous and different models to estimate soil erosion by water in Europe, there is still a lack of harmonization of assessment methodologies. Very often, different approaches give soil erosion rates significantly different and even when the same model is applied to the same region the results may be different. This can be due to the way the model is implemented (i.e. with the selection of different algorithms when available) and/or to the use of datasets having different resolution or accuracy. [\n] Scientific computation is emerging as one of the central topic of the scientific method, to overcome these problems there is thus the necessity to develop reproducible computational method where codes and data are available. The present study is an illustration of such an approach. Using only public available datasets, we applied the Revised Universal Soil loss Equation (RUSLE) to locate the most sensitive areas to soil erosion in Europe. A significant effort was made to select the better simplified equations to be used when a strict application of the RUSLE model is not possible. In particular for the computation of the Rainfall Erosivity factor (R) the reproducible research paradigm was applied. The calculation of the R factor was implemented using public datasets and the GNU R language and an easily reproducible validation procedure based on measured precipitation time series was applied using Matlab language. [\n] Designing the computational modeling architecture with the aim to ease as much as possible the future reuse of the model in analyzing climate change scenarios is also a challenging goal of the research.
@incollection{boscoReproducibilitySoilErosion2011a,
  title = {Towards the Reproducibility in Soil Erosion Modeling: A New Pan-{{European}} Soil Erosion Map},
  booktitle = {Wageningen Conference on Applied Soil Science : '{{Soil Science}} in a {{Changing World}}'},
  author = {Bosco, Claudio and de Rigo, Daniele and Dewitte, Olivier and Montanarella, Luca},
  editor = {Keesstra, Saskia D. and Mol, Gerben},
  date = {2011},
  publisher = {{Wageningen University}},
  location = {{Wageningen, The Netherlands}},
  doi = {10.6084/m9.figshare.936872},
  url = {https://doi.org/10.6084/m9.figshare.936872},
  abstract = {Soil erosion by water is a widespread phenomenon throughout Europe and has the potentiality, with his on-site and off-site effects, to affect water quality, food security and floods. Despite the implementation of numerous and different models to estimate soil erosion by water in Europe, there is still a lack of harmonization of assessment methodologies. Very often, different approaches give soil erosion rates significantly different and even when the same model is applied to the same region the results may be different. This can be due to the way the model is implemented (i.e. with the selection of different algorithms when available) and/or to the use of datasets having different resolution or accuracy.

[\textbackslash n] Scientific computation is emerging as one of the central topic of the scientific method, to overcome these problems there is thus the necessity to develop reproducible computational method where codes and data are available. The present study is an illustration of such an approach. Using only public available datasets, we applied the Revised Universal Soil loss Equation (RUSLE) to locate the most sensitive areas to soil erosion in Europe. A significant effort was made to select the better simplified equations to be used when a strict application of the RUSLE model is not possible. In particular for the computation of the Rainfall Erosivity factor (R) the reproducible research paradigm was applied. The calculation of the R factor was implemented using public datasets and the GNU R language and an easily reproducible validation procedure based on measured precipitation time series was applied using Matlab language.

[\textbackslash n] Designing the computational modeling architecture with the aim to ease as much as possible the future reuse of the model in analyzing climate change scenarios is also a challenging goal of the research.},
  archivePrefix = {arXiv},
  eprint = {1402.3847},
  eprinttype = {arxiv},
  isbn = {978-94-6173-168-5},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-11264002,computational-science,duplicated-entry-to-be-removed,environmental-modelling,gis,gnu-octave,gnu-r,mastrave-modelling-library,relative-distance-similarity,semantic-array-programming,semap,similarity,soil-erosion,soil-resources},
  options = {useprefix=true}
}
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