Modelling soil erosion at European scale: towards harmonization and reproducibility. Bosco, C., de Rigo, D., Dewitte, O., Poesen, J., & Panagos, P. Natural Hazards and Earth System Sciences Discussions, 2(4):2639--2680, April, 2014.
Modelling soil erosion at European scale: towards harmonization and reproducibility [link]Paper  doi  abstract   bibtex   
Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale. A new approach for modelling soil erosion at large spatial scale is here proposed. It is based on the joint use of low data demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation (RUSLE) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. Pan-European soil erosion rates by water have been estimated through the use of publicly available datasets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country level statistics of pre-existing European maps of soil erosion by water is also provided.
@article{ citeulike:13133263,
  abstract = {Soil erosion by water is one of the most widespread forms of soil degradation. The loss of soil as a result of erosion can lead to decline in organic matter and nutrient contents, breakdown of soil structure and reduction of the water holding capacity. Measuring soil loss across the whole landscape is impractical and thus research is needed to improve methods of estimating soil erosion with computational modelling, upon which integrated assessment and mitigation strategies may be based. Despite the efforts, the prediction value of existing models is still limited, especially at regional and continental scale. A new approach for modelling soil erosion at large spatial scale is here proposed. It is based on the joint use of low data demanding models and innovative techniques for better estimating model inputs. The proposed modelling architecture has at its basis the semantic array programming paradigm and a strong effort towards computational reproducibility. An extended version of the Revised Universal Soil Loss Equation ({RUSLE}) has been implemented merging different empirical rainfall-erosivity equations within a climatic ensemble model and adding a new factor for a better consideration of soil stoniness within the model. {Pan-European} soil erosion rates by water have been estimated through the use of publicly available datasets and locally reliable empirical relationships. The accuracy of the results is corroborated by a visual plausibility check (63% of a random sample of grid cells are accurate, 83% at least moderately accurate, bootstrap p ≤ 0.05). A comparison with country level statistics of pre-existing European maps of soil erosion by water is also provided.},
  author = {Bosco, Claudio and de Rigo, Daniele and Dewitte, Olivier and Poesen, Jean and Panagos, Panos},
  citeulike-article-id = {13133263},
  citeulike-linkout-0 = {http://dx.doi.org/10.5194/nhessd-2-2639-2014},
  citeulike-linkout-1 = {http://scholar.google.com/scholar?cluster=15027909135920483528},
  citeulike-linkout-2 = {http://dx.doi.org/10.5194/nhessd-2-2639-2014},
  day = {11},
  doi = {10.5194/nhessd-2-2639-2014},
  issn = {2195-9269},
  journal = {Natural Hazards and Earth System Sciences Discussions},
  keywords = {bias-toward-primacy-of-theory-over-reality, computational-science, continental-scale, data-integration, empirical-equation, ensemble, environmental-modelling, erosivity, europe, geospatial-semantic-array-programming, gis, integrated-modelling, knowledge-integration, mastrave-modelling-library, modelling, relative-distance-similarity, reproducibility, reproducible-research, rusle, semantic-array-programming, soil-erosion, soil-resources, stoniness, uncertainty, visual-assessment},
  month = {April},
  number = {4},
  pages = {2639--2680},
  posted-at = {2014-04-11 08:54:44},
  priority = {2},
  title = {Modelling soil erosion at {E}uropean scale: towards harmonization and reproducibility},
  url = {http://dx.doi.org/10.5194/nhessd-2-2639-2014},
  volume = {2},
  year = {2014}
}
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