Study of Vulnerable and Water Erosion Risk Areas in Sareg Catchment (Central Tunisia) Using Remote Sensing, GIS and P.A.P/R.A.C. Qualitative Approach

Year 2020, Volume: 7 Issue: 1, 33 - 44, 26.04.2020

Bedoui Chokri

https://doi.org/10.30897/ijegeo.623877

Abstract

The study of water erosion has always been a major concern for
human societies. Efforts to reduce resulting forms of degradation and to
understand their extent have not ceased. This article aims to identify
vulnerable and water-erosion-prone areas in the study area. This is achieved
through a predictive and descriptive approach leading to the integration of
main physical parameters from various sources with direct observation data. The
use of remote sensing, GIS and direct observation according to PAP/RAC
guidelines has made it possible to prioritize areas at risk of erosion. The
basin's lands show a general predisposition to water erosion, with 80% of them
experiencing significant, high or very high erosion, including 20% for the last
two categories. This situation is linked to a high erodibility of the
geological outcrops of the basin (81%), with a low to very low degree of soil
protection through vegetation cover (80% of the surface). The descriptive phase
shows eroded surfaces of about 18%, a proliferation of ravines (12% of the
surfaces) of which 6% are hierarchical ravines and bad lands. The integration
phase, while confirming most of the previous data, provides an overview of the
trend towards the extension of gullies observed during the descriptive phase to
neighboring lands that were not initially subject to erosion. This study shows
that a good integration of descriptive and predictive methods can lead to a
good understanding of water erosion, which will facilitate solutions to control
this phenomenon. It also shows the importance of GIS, remote sensing and their
integration with direct field observation in order to produce a document that
can be used, at a low cost, as a decision support tool.

Keywords

Water erosion, PAP/RAC, GIS, Remote sensing, Tunisia

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