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Temporary Dataset Download: Global Rainfall Erosivity

Dataset Access Expires on

25-January-2026

Notifications

  1. The data provided has been prepared for use by internal research activities in the Joint Research Centre (JRC) Ispra. The data have been produced in 2013-2017 in collaboation between European Commission (Joint Research Centre), University of Basel and Meteorological and Environmental Institutions from 63 countries all over the World.
  2. The data are the result of JRC research activities and are primarily made available for further research. The JRC does not accept any liability whatsoever for any error, missing data or omission in the data, or for any loss or damage arising from its use. The JRC agrees to provide the data free of charge but is not bound to justify the content and values contained in the databases.
  3. The input data is the GloREDa Database (you are reccomended to download the 4,000 stations data which includes monthly values as well).
  4. The permission to use the data specified above is granted on condition that, under NO CIRCUMSTANCES are these data passed to third parties. They can be used for any purpose, including commercial gain.
  5. The user agrees to:
    • make proper reference to the source of the data when disseminating the results to which this agreement relates;
    • Participate in the verification of the data (e.g. by noting and reporting any errors or omissions discovered to the JRC).

 

Global R-factor

The new global erosivity map is a critical input to global and continental assessments of soil erosion by water, flood risk and natural hazard prevention. Current global estimates of soil erosion by water are very uncertain, ranging over one order of magnitude (from around 20 to over 200 Pg per year). More accurate global predictions of rill and interrill soil erosion rates can only be achieved when the rainfall erosivity factor is thoroughly computed. The global erosivity map is publicly available and can be used by other research groups to perform national, continental and global soil erosion modelling.

Title: Rainfall Erosivity in the World
Description: This map provides a complete rainfall erosivity dataset for the whole World based on 3,625 precipitation stations and around 60,000 years of rainfall records at high temporal resolution (1 to 60 minutes). Gaussian Process Regression(GPR) model was used to interpolate the rainfall erosivity values of single stations and to generate the R-factor map.
Spatial coverage: World
Pixel size: 30 arc-seconds (~1 km at the Equator).
Measurement Unit: MJ mm ha-1 h-1 yr-1
Projection: ETRS89 Lambert Azimuthal Equal Area
Temporal coverage: 30-40 years - Predominant in the last decade: 2000 - 2010

References:

A complete description of the methodology and the application in World is described in the paper:

Panagos P., Borrelli P., Meusburger K., Yu B., Klik A., Lim K.J., Yang J.E, Ni J., Miao C., Chattopadhyay N., Sadeghi S.H., Hazbavi Z., Zabihi M., Larionov G.A., Krasnov S.F., Garobets A., Levi Y., Erpul G., Birkel C., Hoyos N., Naipal V., Oliveira P.T.S., Bonilla C.A., Meddi M., Nel W., Dashti H., Boni M., Diodato N., Van Oost K., Nearing M.A., Ballabio C., 2017. Global rainfall erosivity assessment based on high-temporal resolution rainfall records.  Scientific Reports 7: 4175. DOI: 10.1038/s41598-017-04282-8.

Panagos, P., Hengl, T., Wheeler, I., Marcinkowski, P., Rukeza, M.B., Yu, B., Yang, J.E., Miao, C., Chattopadhyay, N., Sadeghi, S.H. and Levi, Y., et al. 2023. Global Rainfall Erosivity database (GloREDa) and monthly R-factor data at 1km spatial resolution. Data in Brief, 50, Art.no.109482. DOI: 10.1016/j.dib.2023.109482

Information about the alternative methods for satellite based erosivity can be found in this paper:

Bezak, N., Borrelli, P. and Panagos, P., 2022. Exploring the possible role of satellite-based rainfall data in estimating inter-and intra-annual global rainfall erosivity. Hydrology and Earth System Sciences, 26(7): 1907-1924.

Data

Global Rainfall Erosivity (850 MB)

Two alternatives for erosivity map based on a) satellite-based rainfall data and b)  erosivity density concept.

Data on the Global assessment of storm disaster-prone areas  (Projection: WGS84; Cell size: 0.578 Decimal degrees -around 60km2).

Global Rainfall Erosivity

 

Panagos P., Borrelli P., Meusburger K., Yu B., Klik A., Lim K.J., Yang J.E, Ni J., Miao C., Chattopadhyay N., Sadeghi S.H., Hazbavi Z., Zabihi M., Larionov G.A., Krasnov S.F., Garobets A., Levi Y., Erpul G., Birkel C., Hoyos N., Naipal V., Oliveira P.T.S., Bonilla C.A., Meddi M., Nel W., Dashti H., Boni M., Diodato N., Van Oost K., Nearing M.A., Ballabio C., 2017. Global rainfall erosivity assessment based on high-temporal resolution rainfall records.  Scientific Reports 7: 4175. DOI: 10.1038/s41598-017-04282-8.

Panagos, P., Hengl, T., Wheeler, I., Marcinkowski, P., Rukeza, M.B., Yu, B., Yang, J.E., Miao, C., Chattopadhyay, N., Sadeghi, S.H. and Levi, Y., et al. 2023. Global Rainfall Erosivity database (GloREDa) and monthly R-factor data at 1km spatial resolution. Data in Brief, 50, Art.no.109482. DOI: 10.1016/j.dib.2023.109482

Bezak, N., Borrelli, P. and Panagos, P., 2022. Exploring the possible role of satellite-based rainfall data in estimating inter-and intra-annual global rainfall erosivity. Hydrology and Earth System Sciences, 26(7): 1907-1924.

Joint Research Centre - European Soil Data Centre (ESDAC)
ID 123603
Date - Time Sun, 01/11/2026 - 12:04
Name of User Yinan Li
Organization Nanjing Normal University
Type of Organization University
-- Other
E-mail 1075242667@qq.com
Purpose intend to use the Global Rainfall Erosivity dataset provided by the European Commission for academic research. The dataset will be integrated with the InVEST model and GIS-based spatial analysis to investigate the spatiotemporal patterns of rainfall erosivity at the watershed scale in the Nanjing Metropolitan Area and its impacts on ecosystem services. The data will be used solely for non-commercial scientific research and thesis preparation.
Notes

When making reference to the ESDAC

  • Panagos, P., Van Liedekerke, M., Borrelli, P., Köninger, J., Ballabio, C., Orgiazzi, A., Lugato, E., Liakos, L., Hervas, J., Jones, A.  Montanarella, L. 2022. European Soil Data Centre 2.0: Soil data and knowledge in support of the EU policies. European Journal of Soil Science, 73(6), e13315. DOI: 10.1111/ejss.13315
  • Panagos P., Van Liedekerke M., Jones A., Montanarella L., “European Soil Data Centre: Response to European policy support and public data requirements”; (2012) Land Use Policy, 29 (2), pp. 329-338. doi:10.1016/j.landusepol.2011.07.003
  • European Soil Data Centre (ESDAC), esdac.jrc.ec.europa.eu, European Commission, Joint Research Centre