# Soil Erosion Estimates in Arid Region: A Case Study of the Koutine Catchment, Southeastern Tunisia
## 3 Materials and Methods
### Soil Characteristics and Erodibility (K)  
Since the 1930s, the majority of studies have defined soil erodibility according to inherent soil properties. They focused on the role of soil texture, chemical properties such as soil organic matter and soil profile descriptors such as structure and permeability [43]. The factor \(K\) expresses the vulnerability of the soil to be eroded by rain. It depends on the physical and chemical properties of the soil (such as particle size distribution, aggregation, structural stability, porosity, organic matter content and soil moisture). The soil texture is determined in different sites of the catchment by the mass percentage of sand, silt and clay particles in selected soil samples. The soil particle size distribution determines whether it is sand, silt (loam) or clay. Sand particles have a diameter of 0.05 mm to 2 mm, the diameter of a silt particle ranges from 0.002 mm to 0.05 mm and the diameter of clay particles is smaller than 0.002 mm. [PERSON] and [PERSON] [22] and [PERSON] et al. [23] recommend an algebraic estimation of the soil permeability that includes five soil parameters (texture, organic matter, coarse fragments, structure and permeability) in the below equation (Equation (6)):  
\[K=2.173\times(2.1\times 10^{-4}\ M^{1.14}(12-OM)+3.25(s-2)+2.5(p-3))/100 \tag{6}\]  
where \(K\) is erodibility (t ha h/ha/MJ/mm), \(M\) is textural factor, which is equal to \((m_{silt}+m_{\text{\tiny{effs}}})\times(100-m_{c})\), \(m_{c}\) (%) is clay fraction content (<0.002 mm), \(m_{silt}\) (%) is silt fraction content (0.002-0.05 mm), \(m_{\text{\tiny{effs}}}\) (%) is very fine sand fraction content (0.05-0.1 mm), \(OM\) (%) is organic matter content, \(s\) is soil structure class (\(s=1\) for very fine granular, \(s=2\) for fine granular, \(s=3\) for medium or coarse granular and \(s=4\) for blocky, platy or massive), \(p\) is permeability class (\(p=1\) for very rapid and \(p=6\) for very slow). Six classes are distinguished [44]: (1) rapid, (2) moderate to rapid, (3) moderate, (4) moderate to slow, (5) slow and (6) very slow. In this study, the soil map (Figure 3), based on the French soil classification system (CPCS) [45], was used to locate and collect soil samples from Wadi Koutine catchment (Figure 4). The physicochemical analyses were determined in the soil laboratory of Arid Regions Institute (IRA) of Medenine. For each sample, the particle size analysis was performed in three classes (sand, silt and clay) using [PERSON]'s pipette method [46]. Organic carbon was quantified by the Walkley-Black wet dichromate oxidation [47] and converted to organic matter by multiplying it by 1.724. Soil permeability (hydraulic conductivity) was determined using the flow rate per unit area, measured perpendicular to the direction of flow, at a constant gradient of hydraulic pressure and soil texture was obtained using Soil Textural Pyramid [48]. \begin{table}
\begin{tabular}{c c c c c c c} \hline
**Station** & **X (m)** & **Y (m)** & **Period** & **P** & **Type** & **Source * \\ \hline Beni Khedache & 611,653 & 3,679,340 & 1969–2018 & 234.2 & Weather station & IRA \\ Ksar Hallouf & 606,756 & 3,682,374 & 1969–2017 & 178.9 & Rain gauge & CRDA \\ Ksar Jedid & 620,637 & 3,685,121 & 1969–2017 & 172.8 & Rain gauge & CRDA \\ Toujane Dkhila & 609,157 & 3,699,761 & 1969–2017 & 193.1 & Rain gauge & CRDA \\ Alamat & 623,390 & 3,695,498 & 1969–2017 & 162.2 & Rain gauge & CRDA \\ Koutine & 627,980 & 3,701,600 & 1969–2017 & 173.1 & Rain gauge & CRDA \\ Medenine & 638,440 & 3,689,600 & 1969–2018 & 169.9 & Weather station & INM \\ Sidi Makhlouf & 637,412 & 3,707,889 & 1969–2017 & 179.1 & Rain gauge & CRDA \\ \hline \end{tabular}
* IRA: Instiut des Régions Arides, INM: National Institute of Meteorology, CRDA: Regional department of the Ministry of Agriculture.  
\end{table} 
Table 1: Weather and rain-gauge stations and their corresponding data collection periods. P refers to the mean annual rainfall values generated from daily data.