DATASET

LF522 - Soil retention (LUISA Platform REF2014)

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

Description

Soil retention, is calculated as soil loss without vegetation cover minus soil loss including the current land use/cover pattern. Specifically, this indicator takes into account climate data (observed measurements for rainfall and modelled for snow), topographic aspects, soil properties and the presence or not of the vegetation cover.The level of detail of this indicator is per NUTS0 and NUTS2.

Additional Publications:

1. Wischmeier W.H. and Smith D.D.

(1978). "Predicting Rainfall Erosion Losses – A Guide to Conservation Planning". Agriculture Handbook, No. 537, USDA, Washington DC.http://naldc.nal.usda.gov/download/CAT79706928/PDF

2. Bosco C., de Rigo D., Dewitte O. and Montarella L.. (2011). "Towards the reproducibility in soil erosion modeling: a new Pan-European soil map". Wageningen conferences on applied Soil Science, 18-22 September 2011. http://figshare.com/articles/Towards_the_reproducibility_in_soil_erosion_modelling_a_new_Pan_European_soil_erosion_map/936872

Contact

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

Contributors

How to cite

Lavalle, Carlo; Perpina Castillo, Carolina; Mari Rivero, Ines; Maes, Joachim (2015): LF522 - Soil retention (LUISA Platform REF2014). European Commission, Joint Research Centre (JRC) [Dataset] PID: http://data.europa.eu/89h/jrc-luisa-lf522-soil-retention-ref-2014

Keywords

CLC 2006 EU Reference Scenario 2014 LUISA MedREM NUTS NUTS0 NUTS2 RUSLE equation Soil erosion Soil framework directive State

Data access

LF522 -Soil retention (Europe)
Download 
  • The compressed zip file contains the projected soil retention

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

LF522 -Soil retention (Danube)
Download 
  • The compressed zip file contains the projected soil retention

    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 2012
Bias Correction of the ENSEMBLES High Resolution Climate Change Projections for Use by Impact Models: Analysis of the Climate Change Signal
Dosio A, Paruolo P, Rojas Mujica R. Bias Correction of the ENSEMBLES High Resolution Climate Change Projections for Use by Impact Models: Analysis of the Climate Change Signal. JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES 117; 2012. p. D17110. JRC71978
  • AMER GEOPHYSICAL UNION, WASHINGTON, USA
Publication page 
  • Abstract

    A statistical bias correction technique is applied to twelve high-resolution climate change simulations of temperature and precipitation over Europe, under the SRES A1B scenario, produced for the EU project ENSEMBLES. The bias correction technique is based on a transfer function, estimated on current climate, which affects the whole Probability Distribution Function (PDF) of variables, and which is assumed constant between the current and future climate. The impact of bias correction on 21st Century projections, their inter-model variability, and the climate change signal is investigated, with focus being on discrepancies between the original and the bias-corrected results. As assessing the impact of climate change is significantly dependent on the frequency of extreme events, we also analyze the evolution of the shape of the PDFs, and extreme events indices. Results show that the ensemble mean climate change signal and its inter-model variability are generally conserved. However, the impact of the bias correction varies amongst regions, seasons and models, and differences up to 0.5 C for the summer temperature climate change signal are found in Southern Europe. Finally the bias correction is found to influence the probability of extreme events like extremely hot or frost days, which also impacts the climate change signal.

Publication
MedREM, a rainfall erosivity model for the Mediterranean region
Lavalle, Carlo; Perpina Castillo, Carolina; Mari Rivero, Ines; Maes, Joachim

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-lf522-soil-retention-ref-2014
Popularity