DATASET

LF521 - Capacity of ecoystems to avoid soil erosion (LUISA Platform REF2014)

Collection: LUISA : Land-Use based Integrated Sustainability Assessment modelling platform 

Description

The indicator measures the capacity of ecosystems to avoid soil erosion assigning values ranging from 0 to 1 at pixel level, covering the EU-28 territory. This indicator is related to the capacity of a given land cover type to provide soil protection.The level of detail of this indicator is per NUTS0 and NUTS2.

Additional publications:

1. Van der Knijff, J., Jones, R., Montanarella, L. (1999). "Soil erosion risk assessment in Italy".

Joint Research Centre. European Commission. http://www.preventionweb.net/files/1581_ereurnew2.pdf

Contact

Email
JRC-KCTP (at) ec.europa.eu

Contributors

How to cite

Lavalle, Carlo; Perpina Castillo, Carolina; Mari Rivero, Ines; Maes, Joachim (2015): LF521 - Capacity of ecoystems to avoid soil erosion (LUISA Platform REF2014). European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/jrc-luisa-lf521-capacity-of-ecoystems-to-avoid-soil-erosion-ref-2014

Keywords

CLC 2006 LUISA NUTS EU Reference scenario 2014 NUTS0 NUTS2 RUSLE equation Soil degradation Soil framework directive State TESI

Data access

LF521 - Capacity of ecoystems to avoid soil erosion (Europe)
Download 
  • The compressed zip file contains the projected capacity of ecosystems to avoid soil erosion

    at NUTS0 and NUTS2 , from 2010 to 2050. The data is stored in .csv format.

LF521 - Capacity of ecoystems to avoid soil erosion (Danube)
Download 
  • The compressed zip file contains the projected capacity of ecosystems to avoid soil erosion for the Danube region at NUTS0 and NUTS2 , from 2010 to 2050. The data is stored in .csv format.

Land-Use-based Integrated Sustainability Assessment’ modelling platform (LUISA)
URL 
  • LUISA webpage (European Commission - JRC Science Hub)

Publications

Publication 2011
Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate
Dosio A, Paruolo P. Bias correction of the ENSEMBLES high-resolution climate change projections for use by impact models: Evaluation on the present climate. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 116 (D16106); 2011. JRC65181
  • AMER GEOPHYSICAL UNION, WASHINGTON, UNITED STATES OF AMERICA
Publication page 
  • Abstract

    A statistical bias correction technique is applied to a set of high resolution climate change simulations for Europe from 11 state-of-theart regional climate models (RCMs) from the project ENSEMBLES. Modelled and observed daily values of mean, minimum and maximum temperature and total precipitation are used to construct transfer functions for the period 1961-1990, which are then applied to the decade 1991-2000, where the results are evaluated. By using a large ensembles of model runs and a long construction period, we take into account both inter-model variability, and longer (e.g. decadal) natural climate variability. Results show that the technique performs successfully for all variables over large part of the European continent, for all seasons. In particular, the probability distribution functions (PDFs) of both temperature and precipitation are greatly improved, especially in the tails, i.e., increasing the capability of reproducing extreme events. When the statistics of bias corrected results are ensemble-averaged, the result is very close to the observed ones. The bias correction technique is also able to improve statistics that depend strongly on the temporal sequence of the original field, such as the number of consecutive dry days and the total amount of precipitation in consecutive heavy precipitation episodes, which are quantities that may have a large influence on e.g. hydrological or crop impact models. Bias-corrected projections of RCMs are hence found to be potentially useful for the assessment of impacts of climate change over Europe.

Publication
Predicting Rainfall Erosion Losses - A Guide to Conservation Planning
Lavalle, Carlo; Perpina Castillo, Carolina; Mari Rivero, Ines; Maes, Joachim
URL 

Geographic areas

European Union

Temporal coverage

From date To date
2010-01-01 2050-12-31

Additional information

Published by
European Commission, Joint Research Centre
Created date
2018-12-14
Modified date
2024-01-17
Issued date
2015-04-22
Landing page
https://ec.europa.eu/jrc/en/luisa 
Language(s)
English
Data theme(s)
Environment, Science and technology
Update frequency
annual
Identifier
http://data.europa.eu/89h/jrc-luisa-lf521-capacity-of-ecoystems-to-avoid-soil-erosion-ref-2014
Popularity
23 Feb 2024: 1 visits