Soil erosion modeled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco)
El Jazouli et al. Geosci. Lett.
Soil erosion modeled with USLE, GIS, and remote sensing: a case study of Ikkour watershed in Middle Atlas (Morocco)
Aafaf El Jazouli 0
Ahmed Barakat 0
Abdessamad Ghafiri
Saida El Moutaki
Abderrahim Ettaqy
Rida Khellouk 0
0 Georesources and Environment Laboratory, Faculty of Sciences and Techniques, Sultan My Slimane University , Béni-Mellal , Morocco
The Ikkour watershed located in the Middle Atlas Mountain (Morocco) has been a subject of serious soil erosion problems. This study aimed to assess the soil erosion susceptibility in this mountainous watershed using Universal Soil Loss Equation (USLE) and spectral indices integrated with Geographic Information System (GIS) environment. The USLE model required the integration of thematic factors' maps which are rainfall aggressiveness, length and steepness of the slope, vegetation cover, soil erodibility, and erosion control practices. These factors were calculated using remote sensing data and GIS. The USLE-based assessment showed that the estimated total annual potential soil loss was about 70.66 ton ha−1 year−1. This soil loss is favored by the steep slopes and degraded vegetation cover. The spectral index method, offering a qualitative evaluation of water erosion, showed different degrees of soil degradation in the study watershed according to FI, BI, CI, and NDVI. The results of this study displayed an agreement between the USLE model and spectral index approach, and indicated that the predicted soil erosion rate can be due to the most rugged land topography and an increase in agricultural areas. Indeed, these results can further assist the decision makers in implementation of suitable conservation program to reduce soil erosion.
Ikkour watershed; Soil erosion; USLE; Spectral indices; GIS
Introduction
Soil erosion is a naturally occurring process and it is
a normal geological phenomenon associated with the
hydrologic cycle. It is a gradual process which occurs
when the impact of water detaches and removes soil
particles causing the soil to deteriorate. Soil erosion in
catchment areas and the subsequent deposition in rivers,
lakes, and reservoirs are of great concern for two reasons.
Firstly , the rich and fertile soil is eroded in the catchment
areas. Secondly, there is a reduction in reservoir capacity
as well as degradation of downstream water quality. Soil
loss is the result of soil erosion. This, in turn, decreases
soil fertility and reduces crop yield. Soil erosion can
never be stopped completely, but it can be mitigated to
some extent. There is considerable potential for the use
of GIS technology as an aid to soil erosion inventory with
reference to soil erosion modeling and erosion hazard
assessment.
In Morocco, water erosion is the main cause of
degradation of the soil capital and the environment. It affects,
with varied intensities, about 40% of land in Morocco
(FAO 1990)
. Annual soil loss exceeds 20 ton ha−1 year−1
in the Mountainous regions of northern Morocco and
varies between 10 and 20 ton ha−1 year−1 in the
preRif regions and 5 and 10 ton ha−1 year−1 in Middle and
High Atlas regions
(MAEF 2001)
. In addition to soil loss,
water erosion degrades water quality and causes
siltingup of hydraulic infrastructure
(Ben-Ali 2000)
. This
erosion will only accelerate if adequate precautions are not
taken early enough to address this emergency. Indeed,
some scientific research on the vulnerability to climate
change in the Mediterranean Region including Morocco
indicates a trend toward an increasing aridity which
inevitably accelerates water erosion
(De Ploey et al. 1991;
Joftic et al. 1992)
. In this situation, quantification of soil
loss and delineation of degraded areas is necessary for
effective conservation planning (Yadav and Sidhu 2010).
In the last decade, many scientific works using remote
sensing and geographic information systems (GIS)
technologies have been carried out to characterize soil erosion
in large areas
(Haboudane et al. 2007; Rahman et al. 2009;
Meusburger et al. 2010; Benzer 2010; Biswas 2012; Dabral
et al. 2008; Pandey et al. 2007; Sheikh et al. 2011)
. These
works proved that these techniques provided very good
information about eroding areas, such as soil types,
lithological units, and vegetation cover, with reasonable costs
and accuracy. Integrated into GIS and remote sensing,
several models for predictive evaluation on soil erosion
by water have been reported in some literature
(e.g.,
Wischmeier and Smith 1978; Lal 2001; Fullen 2003; Merritt
et al. 2003)
. Universal Soil Loss Equation (USLE) is
considered as the best model and is being used worldwide for
the estimation of surface erosion
(e.g., Zhang et al. 2008;
Alexakis et al. 2013; Perović et al. 2013; Chatterjee et al.
2014; Kourgialas et al. 2016)
. Its revised version, RUSLE
(Renard et al. 1997), became mostly used to provide
estimates of soil loss
(Demirci and Karaburun 2012; Kumar
et al. 2014; Gana (...truncated)