WP4 (leader JRC) has developed Data Indicators for Soil threats and soil functions: Soil Erosion, Soil Organic Carbon, Soil Sealing and Nitrogen Content. The objective of this development is to demonstrate the role of Critical Zone Obeservatories (CZOs) in the delineation of risk areas (hot spots). The aggregated values of the proposed indicators (per land use) are used as input for the Life Cycle Assessment (LCA) and further economic analysis and valuation of soil functions.
|The soil erosion risk map of Crete was estimated using a RUSLE-family model named G2. The model has produced month-step erosion risk maps at 300m resolution using as input rainfall intensity, soil erodibility time series of vegetation layers and topography.
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More information can be find in the article: Panagos, P., Karydas, CG., Ballabio, C., Gitas, IZ., 2014. Seasonal monitoring of soil erosion at regional scale: An application of the G2 model in Crete focusing on agricultural land uses. International Journal of Applied Earth Observations and Geoinformation 27PB (2014), pp. 147-155, DOI: 10.1016/j.jag.2013.09.012
|Rainfall Erosivity (R-factor):
Using the software module, the monthly R-factor was calculated for 4 weather stations in Crete (Emprosmeros, Nithafri, Archanes, Kalamavka), for which precipitation time series of 11 years (1969-1979) with 10-minute resolution data were available from Hydroscope. Next, a set of another 24 weather stations from SoilTrECproject with average monthly precipitation records for the same time period (1969-1979) was used. Monthly R-values have been estimated for the 24 stations (Fig. 2) based on their total precipitation and their proximity to the 4 stations with calculated R-values. The spatial distribution of rainfall erosivity to the island surface used the calculated R-factor of the 4 stations and the estimated R-factor of the additional 24 (total: 28 stations).
|Soil Erodibility (S-Factor):
By using 31 soil samples from the pan-European LUCAS topsoil dataset and an additional set of 60 soil samples of the SoilTrEC project , mainly located in the Koiliaris CZO, the soil organic matter and textural (silt, sand, clay) layers were calculated using regression Kriging techniques.
Soil Organic Carbon
|The dataset used in this study is made up of 97 soil samples collected from two different studies. Thirty one points from the Land Use/Cover Area frame Statistical Survey (LUCAS) and 66 samples from the study in Koiliaris CZO. Regression-Kriging method has been applied for assessing organic carbon distribution and producing a continuous map in Crete. Regression-Kriging is a spatial interpolation technique that combines a regression of the dependent variable (point data) on predictors and kriging of the regression residuals. In other words, Regression-Kriging is a hybrid method that combines either a simple or multiplelinear regression model with ordinary, or simple, kriging of the regression residuals .
More Information can be found in: Aksoy E., Panagos P., Montanarella L. Spatial prediction of soil organic carbon of crete by using geostatistics (2012) Digital Soil Assessments and Beyond - Proceedings of the Fifth Global Workshop on Digital Soil Mapping, pp. 149-153
|Map of built-up and non-built-up areas including continuous degree of soil sealing ranging from 0 - 100% in full spatial resolution (20 x 20 m) with the associated metadata. 9383 ha in the island of Crete are sealed. This represents 1.12% of the total area surface.
Source: Summarised from the Delivery Report of Greece (EEA FTSP Sealing Country Delivery Report GR, 2008)