## 3 Data Collection and Elaboration
### Gully Erosion predisposing Factors  
Selecting predisposing factors is an important step for implementing a reliable gully erosion susceptibility model [20,22]. Numerous geo-environmental features, such as geology, soil, topography, hydrology, and land cover/use, control the gully's occurrence [1,11,13,46]. However, no universal guideline exists regarding the predisposing factors that should be used in the gully erosion prediction models. Several studies employed different geo-environmental variables based on the availability, reliability, and practicality of the data [13,20,24,25,47,48]. In this study, the predisposing factors were rationally selected, considering the data availability, previous knowledge of the study area, and concerning the relevant literature [23,24,26,46]. Using this procedure, a set of 12 predisposing factors was selected, including lithology, soil texture, soil bulk density, land use, drainage density, slope gradient, aspect, length-slope (LS) factor, plan curvature, stream power index (SPI), topographic position index (TPI), and topographic wetness index (TWI).  
The geological map of the Calabria region at scale 1:25,000 was used to create the lithology layer (Figure 3a). The data concerning the soil texture and soil bulk density (Figure 3b,c) were extracted from the digital soil map of Calabria (scale 1:250,000) [44]. Regarding the land use layer (Figure 3d), it was extracted from the Corine Land Cover map of Italy (scale 1:100,000), downloaded from the website of ISPRA ([[http://www.sinanet.isprambiente.it](http://www.sinanet.isprambiente.it)]([http://www.sinanet.isprambiente.it](http://www.sinanet.isprambiente.it)), accessed on 13 February 2021).  
The drainage density map (Figure 3e), defined as the total length of the hydrographic network per unit area (1 km\({}^{2}\) in this study), was obtained by interpolating the hydrographic network using the line density tool implemented in ArcGIS 10.8 software. Instead, the topographic factors such as slope gradient, aspect, LS, plan curvature, SPI, TPI, and TWI (Figure 3f-l) were elaborated from a digital terrain model (DTM) with a spatial resolution of 5 \(\times\) 5 m, using the software SAGA-GIS version 8.0.1 [49].  
The data regarding the hydrographic network and DTM were downloaded from the website of the Cartographic Center of Calabria region ([[http://geoportale.regione.calabria.it/opendata](http://geoportale.regione.calabria.it/opendata)]([http://geoportale.regione.calabria.it/opendata](http://geoportale.regione.calabria.it/opendata)), accessed on 10 March 2021).  
For the analysis of gully erosion susceptibility, the thematic layers elaborated for each predisposing factor were transformed in raster layers with a pixel size of 5 m.  
Figure 2: (a) Intense soil erosion in arable land after heavy rains with concentrated runoff; (b) permanent gullies characterised by steep and bare flanks.  
Figure 3: Predisposing factors’ thematic maps used in the gully erosion susceptibility analysis: (**a**) lithology map (legend: 1—alluvial deposits, 2—eluvial/colluvial deposits, 3—silty clays, 4—congglomerates and sands, 5—sandstones, 6—evaporitic limestones, 7—genesis, 8—granite); (**b**) soil texture map (legend: 1—loam; 2—silty loam; 3—sandy loam; 4—loamy sand); (**c**) soil bulk density map; (**d**) land use map (legend: 1—artificial and/or urban areas, 2—arable areas, 3—heterogeneous agricultural areas, 4—fruit and olive grove areas, 5—scrub and/or herbaceous areas, 6—forest areas); (**e**) drainage density map; (**f**) slope gradient map; (**g**) aspect map; (**h**) LS factor map; (**i**) plan curvature map; (**j**) SPI factor map; (**k**) TPI factor map; (**l**) TWI factor map.