Soil Erosion Modelling. Elaboration of the soil erosion risk map of Sicily by calibration and validation of an USLE model

Transcription

1 Soil Erosion Modelling JRC Ispra March 2017 Elaboration of the soil erosion risk map of Sicily by calibration and validation of an USLE model Maria Fantappiè, CREA-ABP, Italy

2 Materials and study area 2100 data on absence of soil erosion 4050 data on presence of soil erosion

3 Calibration erosivity factor R Root Mean Squared Errors of R (Mj mm ha -1 h -1 y -1 ) estimated with 5 different formula, against R measured at 5 meteorological stations by Agnese et al. (2006) (Ferro et al. (Arnoldous 1999) 1977) (Yu and Rosewell 1996) (Renard and Freimund 1994) (Arnoldous 1980) R.5249F R F R 3.82F R F R 4.17* F152* F F F N j F 12 j dove Fj 1 N i1 P 2 ij P j F 12 i1 2 Pi P Pi monthly mean precipitations (mm) of the i th month. Pij monthly mean precipitations (mm) of the i th month of the j th year. Pj yearly mean precipitations (mm) of the jth year. F F mean of Fj for a period of N years.

4 Methods adopted for LS and K factors L factor, as McCool et al. (1989) L sl S factor, as McCool et al. (1987) The chosen formula gives negative values for slope gradients <3%, so that it is possible to delineate flat and depositional areas S m 16.8* sen 0. 5 m 1 sen sen sl tan ps ps θ is the slope gradient expressed as radians. sl is the slope length expressed as meters, ps is the pixel size expressed as meters. K factor, with Stone and Hilborn (2012) coefficients, converted to tons hour MJ -1 mm -1 USDA Soil Texture Classes Sand Loamy sand Sandy loam Loam Silt loam Silt Sandy clay loam Clay loam Silty clay loam Sandy clay Silty clay Clay Organic Matter Content Less than 2% More than 2% K factor correction for gravel content with Poesen et al. (1994). e 0.04 R 10 K factor set at 0.08 for volcanic soils following Van der Knijff et al. (1999) c Rc (%) is the gravel content, stoniness and rockiness.

5 Elaboration of potential soil erosion Ep

6 Calibration of land cover factor C Definition: the ratio of soil loss from land cropped under specified conditions to the corresponding loss from clean-tilled, continuous fallow. This factor measures the combined effect of all the interrelated cover and conventional management variables (but excluding the adoption of specific soil protection measures, which constitute the P factor) C L E tl Ep L 0 C L is the C factor calibrated for each one of the 9 groups (L) of land use considered; μep L0 is the mean value (μ) of potential soil erosion (Ep) calculated for each land use group (L), on the base of the punctual Ep values estimated at each one of the 2100 field evidences of soil erosion absence; E tl is the actual soil erosion, assumed to be 2 ton ha -1 y -1 at the 2100 sites with absence of soil erosion. This values is considered as a treshold for tolerable soil erosion rate (a), therefore constitutes a soil erosion rate presumably not visible to the naked eye. (a) Jones, A., et al. (2012). The state of soil in Europe. A contribution of the JRC to the EEA Environment State and Outlook Report - SOER Report EUR EN. ISBN DOI: / Office for Official Publications of the European Communities, Brussels, Luxembourg, 76 pp. (online)

7 Result: the calibrated C factors Corine Land Cover codes Decoding C factors 211, 212, 213 Arable crops , 243 Complex cultivations Vineyards , 324, 333, 334 Shrublands and post fire vegetation , 222, 224 Olive groves, fruit trees, Eucalyptus plantations , 321, 322 Pastures and natural grasslands Coniferous forests , 313 Broad leaved and mixed forests Citrus 0.253

8 Elaboration of actual soil erosion Ea E Ep C P

9 The concept of soil erosion risk We calculated the risk as years necessary to completely lose the soil cover up to the effective rooting depth. The concept is that risk is harsher on thinnest soils. Y Qs E where Qs is the mass of soil cover to the effective rooting depth (tons ha -1 ) calculated as Qs B D where µb is the mean bulk density (g dm -3 ), and µd is the mean effective rooting depth (dm) of the soils in each delineation of the Soil Map of Sicily. Four empirical erosion risk classes were defined, considering how much it could affect a human life span: (i) Low risk or not appreciable soil erosion > than 500 years; (ii) Moderate risk, years; (iii) High risk, years; (iv) Very high risk, < 10 years.

10 The map of soil erosion risk of Sicily published on JOURNALS OF MAPS Fantappiè M., Priori S., Costantini E.A.C., (2014). Soil erosion risk, Sicilian Region (1:250,000 scale). Journal of Maps, Taylor and Francis. DOI: /

11 Bayesan validation Applying the Bayes theorem it is possible to calculate the positive (pred+) and negative (pred-) predictivity, that is the probability of occurance of the investigated phenomena in case the model estimated its occurance, and the probability of not occurance in case the model estimated its not occurance. Results Prev Se Se* prev pred Se* prev (1 S )*(1 prev) Sp *(1 prev) pred Sp *(1 prev) (1 Se)* prev p Se( sensitivity ) prev( prevalence) y _ ok y _ tot n _ ok Sp( specificity ) n _ tot y _ to y _ tot n _ tot Sp Pred Pred Where y_ok is the number of occurences correctly predicted, n_ok is the number of not occurances correclty predicted, y_tot is the number of real occurences, n_tot is the number of real not occurences.