 |
| Titel |
Modelling soil erosion at European scale: towards harmonization and reproducibility |
| VerfasserIn |
C. Bosco, D. de Rigo, O. Dewitte, J. Poesen, P. Panagos |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1561-8633
|
| Digitales Dokument |
URL |
| Erschienen |
In: Natural Hazards and Earth System Sciences ; 15, no. 2 ; Nr. 15, no. 2 (2015-02-04), S.225-245 |
| Datensatznummer |
250119314
|
| Publikation (Nr.) |
 copernicus.org/nhess-15-225-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
| 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, because a systematic knowledge of local climatological
and soil parameters is often unavailable. A new approach for modelling soil
erosion at regional 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 data sets 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 soil erosion maps is also provided. |
| |
|
| Teil von |
|
|
|
|
|
|
|
|