Abstract
Erosion is the main threat to sustainable water and soil management in Morocco. Located in the Souss-Massa watershed, the rural municipality of El Faid remains an area where gully erosion is a major factor involved in soil degradation and flooding. The aim of this study is to predict the spatial distribution of gully erosion at the scale of this municipality and to evaluate the predictive capacity of three prediction methods (frequency ratio (FR), logistic regression (LR), and random forest (RF)) for the characterization of gullying vulnerability. Twelve predisposing factors underlying gully formation were considered and mapped (elevation, slope, aspect, plane curvature, slope length (SL), stream power index (SPI), composite topographic index (CTI), land use, topographic wetness index (TWI), normalized difference vegetation index (NDVI), lithology, and vegetation cover (C factor). Furthermore, 894 gullies were digitized using high-resolution imagery. Seventy-five percent of the gullies were randomly selected and used as a training dataset, whereas the remaining 25% were used for validation purposes. The prediction accuracy was evaluated using area under the curve (AUC). Results showed that the factor that most contributed to the prevalence of gullying was topographic (slope, CTI, LS). Furthermore, the fitted models revealed that the RF model had a better prediction quality, with the best AUC (91.49%). The produced maps represent a valuable tool for sustainable management, land conservation, and protecting human lives against natural hazards (floods).
Highlights
Issues related to climatic hazards and water management have major importance given their impacts on the rural environment [1,2]
El Faid consists of two contrasting areas: (1) Mountains, with more than 30% of the municipality surface characterized by a steep slope constituting the upstream areas where the gullies that feed the main streams are located; and (2) The flat plain where most of the streams meet, representing the dynamic center with important equipment and infrastructures
Erosion vulnerability mapping is an essential element which, by illustrating risk,The provides a tool for awareness land management, and support decision comparison of the frequency ratio (FR), logistic regression (LR), raising, and random forest (RF) susceptibility models proved thatfor the model making and action
Summary
Issues related to climatic hazards and water management have major importance given their impacts on the rural environment [1,2]. In Morocco, climate change will produce more frequent and intense extreme events [4,5], which will lead to an increased probability of floods and droughts [6]. Water erosion is one of the most frequent soil degradation processes in Morocco, especially in semi-arid areas [11,12]. The frequency ratio is a method based on calculating the gully density weighting values for each class of factors [80]. The ratio of the probability of occurrence of a gully to a non-occurrence with respect to a given attribute [81] is as follows: Npix Si,j / ∑ j Npix Si,j (5) FRi,j =. The prediction rate is considered as high if (0.6 ≤ PR); moderate if (0.4 ≤ PR < 0.6), and low if (PR < 0.4)
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