Soil Erosion Assessment - Mind the Gap. Kim, J.; Ivanov, V. Y.; and Fatichi, S. 43(24):2016GL071480+.
Soil Erosion Assessment - Mind the Gap [link]Paper  doi  abstract   bibtex   
Accurate assessment of erosion rates remains an elusive problem because soil loss is strongly nonunique with respect to the main drivers. In addressing the mechanistic causes of erosion responses, we discriminate between macroscale effects of external factors – long studied and referred to as ” geomorphic external variability”, and microscale effects, introduced as ” geomorphic internal variability.” The latter source of erosion variations represents the knowledge gap, an overlooked but vital element of geomorphic response, significantly impacting the low predictability skill of deterministic models at field-catchment scales. This is corroborated with experiments using a comprehensive physical model that dynamically updates the soil mass and particle composition. As complete knowledge of microscale conditions for arbitrary location and time is infeasible, we propose that new predictive frameworks of soil erosion should embed stochastic components in deterministic assessments of external and internal types of geomorphic variability.
@article{kimSoilErosionAssessment2016,
  title = {Soil Erosion Assessment - {{Mind}} the Gap},
  author = {Kim, Jongho and Ivanov, Valeriy Y. and Fatichi, Simone},
  date = {2016-12},
  journaltitle = {Geophys. Res. Lett.},
  volume = {43},
  pages = {2016GL071480+},
  issn = {0094-8276},
  doi = {10.1002/2016gl071480},
  url = {http://mfkp.org/INRMM/article/14257841},
  abstract = {Accurate assessment of erosion rates remains an elusive problem because soil loss is strongly nonunique with respect to the main drivers. In addressing the mechanistic causes of erosion responses, we discriminate between macroscale effects of external factors -- long studied and referred to as ” geomorphic external variability”, and microscale effects, introduced as ” geomorphic internal variability.” The latter source of erosion variations represents the knowledge gap, an overlooked but vital element of geomorphic response, significantly impacting the low predictability skill of deterministic models at field-catchment scales. This is corroborated with experiments using a comprehensive physical model that dynamically updates the soil mass and particle composition. As complete knowledge of microscale conditions for arbitrary location and time is infeasible, we propose that new predictive frameworks of soil erosion should embed stochastic components in deterministic assessments of external and internal types of geomorphic variability.},
  keywords = {*imported-from-citeulike-INRMM,~INRMM-MiD:c-14257841,~to-add-doi-URL,erodibility,local-scale,modelling-uncertainty,soil-erosion,soil-resources,uncertainty},
  number = {24}
}
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