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©Department of Geography. Valahia University of Targoviste Annals of Valahia University of Targoviste. Geographical Series Tome 15/2015 Issues 2: 101-24 http://fsu.valahia.ro/images/avutgs/home.html

QUANTITATIVE ASSESSMENT OF THE HYDRIC EROSION AND THE DEPOSITION IN A MARLY CATCHMENT OF THE EASTERN RIF

(CASE OF WADI TARMAST - MOROCCO)

Abdellatif TRIBAK1, Khalid ARARI1, Mohamed ABAHROUR1, Abdelkader EL GAROUANI2 and Zakaria AMHANI1

1 - LAGEA-DD, FLSH - Sais, Route d'Imouzzer, BP.59, Fès, Maroc., Université Sidi Mohamed ben

Abdellah Fès, Maroc. Tel : 212 0535618226 E-mail : tribakabdellatif@yahoo.fr - tribakabdellatif@gmail.com

2 - Faculté des Sciences et Techniques de Fès, Route d'Imouzzer, BP. 2202, Fès, Maroc. E-mail : el_garouani@yahoo.fr

Abstract In the Moroccan Rif Mountains, hydric erosion leads to disastrous consequences for both the potential production of land and for water resources management and pollution in downstream area. The main objective of this study is to illustrate on the one hand, the determining of the change of space occupation, and on the other hand, the modeling of the erosion and deposition of soils. The satellite data analysis was used to identify the different classes of land cover (uncultivated lands and badlands, annual crops, arboriculture / Olive trees, reforestation and forest) in the watershed of Tarmast with an area of 69.58 km2, located in the North-East of Morocco. After mapping the spatial and temporal evolution of land use over a period of 15 years, soil losses were estimated by the RUSLE model (Revised Universal Soil Loss Equation). These spatial assessments of soil loss were then used in a sedimentation algorithm that models the transport of these soil losses through the river to the outfall. These spatial movements were then evaluated to estimate the net erosion and deposition for each homogeneous basic plot of the basin. This approach, based on remote sensing data and GIS tool allows a spatial monitoring of erosion and deposition of soil in the context of a marly watershed subject to a strong human pressure. It is also an effective way for the localization of sediment source areas and understanding of the interrelationships between the various parameters of the erosional processes in a Mediterranean environment. Keywords: Erosion, Quantification, Deposition, RUSLE, Remote Sensing, Marly land, Rif, Morocco

1. INTRODUCTION

In Morocco, soil erosion is a serious problem with its negative consequences on the

environment and the many nuisances associated with it. In addition to the reduction in arable lands,

erosion has numerous offsite effects such as dam’s siltation. According to the National

Development Plan catchment (MCEF 1999) erosion affects much of the territory with a total area of

large ponds close to 20 million ha. Erosion high risk areas represent 75 %; and the annual siltation

of dams is estimated at 75 million m3. In the Rif Mountains Specific impairments are among the

highest in the world (Sabir et al, 2007):

The catchment of the wadi Tarmast, located in the Moroccan pre-Rif, is subject to intense

erosive dynamics whose terms are very varied. Losses of lands are therefore enormous and

alarming. In this work, we use data from remote sensing and geographic information system (GIS)

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for the quantitative evaluation and mapping of erosion and soil deposition. The main objective of

this work is the application of the assessment models of hydric erosion (RUSLE: Revised Universal

Soil Loss Equation) and deposition (Sedimentation) of soils, in order to locate priority areas for any

development action.

Figure 1. Localization and Digital Elevation Model of the Tarmast catchment

2 - A FRAGILE ENVIRONMENT PREDISPOSED TO THE EROSION HAZARDS

With an area of 69.58 km2, the wadi Tarmast catchment is part of the Eastern Prerif in

northern Morocco. It is characterized by a rugged topography which elevations varying from 560 m

at the outfall to 1330 m at the highest point. Hills and low mountains offer irregular shaped sides of

slopes, related to the complexity of the structure and the importance of quaternary legacies. Steep

slopes dominate; those that exceed 25% occupy 42.67% of the area of the basin (Table 1). The

geological context shows a clear predominance of soft materials, mainly marl, marly limestone, or

marly sandstone, in an overthrust napped structure.

The soils derived from these geological formations belong mostly to classes of soil erosion

slightly evolved on steep slopes occupying about 70% of the basin surface. The remaining area is

occupied by calcimagnesic and vertisols on tertiary marl and marly-limestone formations that

outcrop in some hollows and depressions. Furthermore, alluvial soils develop on the terraces

bordering the water course (Tribak 2000).

Code Slope Classes Areas (Km²) %

1

Low slope <5%

1,97 2,83

2 Average slopes 5-15% 13,28 19,08

3 Steep sloopes 15-25% 24,64 35,41

4

Very Steep sloopes >

25% 29,69 42,67

Total 69,58 100,00

Table 1. Slopes classes areas in Wadi Tarmast cathcment

This inherent vulnerability of the environment is exacerbated by a marked concentration of

extreme weather events in time, supplying various erosion processes. The local climate of the

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region is characterized by strong seasonal contrasts with brutal and concentrated rains in time.

Annual averages are between 363 mm for the station of Ain Boukellal (1959-2013) and 596 mm for

the Taza station (1959-2013). The statistical study by category of daily rainfall recorded in the

station of Taza, in the period 1979-2013 shows that this region is occasionally subject to daily

maximum heights, sometimes exceeding the 100 mm threshold, and are often causing hydrological

dynamics and particularly erosive power (Tribak et al 2012).

Figure 2. Slopes of the Wadi Tarmast catchment

Figure 3. Lithological formations of the Wadi

Tarmast catchment

Figure 4. Rates of spatial distribution of lithological formations in the basin

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Human densities are important in this region (42 h / km2 in 2004) and The human footprint

and land conquests are spectacular. Most slopes are totally bare and cultured. Thus, Human pressure

has transformed initial forest landscapes in a mosaic of various agrarian plots with some fragments

of degraded forests at mountaintops and badly eroded landscapes. Overuse of cleared land, fueled

by strong population growth, explains the expansion of farming into areas with steep slopes witch

result in accelerated erosion in this fragile environment.. The mapping and diachronic study of land

use (2000 - 2014) shows a modification of the countryside with increased areas of fruit tree crops (

85.27 %) , an extension of strongly eroded soils ( badlands and uncultivated land) ( 8.74% ) and a

reduction of annual crop areas ( -26.55 %) and forest/reforestation (-37.57 %) ( Table 2) .

3. METHODOLOGY

To achieve the objectives of this study that leads mainly to the quantification of hydric

erosion in the watershed of wadi Tarmast, we firstly made an exploration of the physical

environment through field studies. Then we conducted spatial hydric erosion by considering the

parameters that influence the erosive dynamics in the concerned area. The recommended

methodology is based on the collection, processing and spatial analysis of data concerning the

physical constraints, land use and geomorphology of the watershed. We, therefore, have proceeded

by extracting thematic informations from satellite images, and performing a digital elevation model

(DEM) and derived data such as the inclination and the length of the slopes. In this work we used

the ArcGIS 10.1 software for scanning all layers of information required, and spatial data analysis

(Lewis et al., 2007). Furthermore, we used the software Erdas Imagine and Arc Gis 10.1 for the

treatment of remote sensing imagery for mapping land cover. For modeling processes of erosion

and deposition of soil we opted for the use of Idrisi Andes Software 9.2. 3.1. Using pictures of remote sensing for mapping land cover

The identification of the spatial and temporal variation in land use in the under study area,

was conducted from the classification of satellite images Landsat-5 TM and Landsat-7 ETM +

(between 2000 and 2014). The acquired data is processed and analyzed by the image processing

software Erdas Imagine and Arc Gis 10.1. In a first step, these images were georeferenced

according to Lambert Conformal Conic and clamped according to the reference coordinate system

of Merchich northern zone (North of Morocco System. Thus, a cutting image was performed by

selecting the parts corresponding to the same portion of space from the geographical coordinates of

our study area. These geometric pretreatments have allowed the integration of satellite imagery in

the GIS of the concerned area and the performing of the required analyzes. In addition,

enhancement operations and combinations of channels have been made to improve the visual

quality of images and to increase the separability of thematic classes for a good photo interpretation.

From the above observations, we performed a supervised classification in order to obtain a land use

map. Themes are defined based on soil characteristics, vegetation and agricultural land use

references observed in the field.

3.2. Modeling of erosion and soil deposition

RUSLE Model: The quantifying of hydric erosion in the Tarmast catchment is performed

by the integrated RUSLE model in the Idrisi software. This model allowed us to estimate the

average annual erosion rate throughout the watershed, depending on the distribution of rainfall

aggressiveness of soil erodibility, topography, soil occupation and crop management practices.

Under this model, the erosion rate (A t / ha / year) is a multiplicative function of rainfall

erosivity (R) which is equal to the potential energy that multiplies the resistance of the medium or

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erodibility soil (K), the topographic factor (SL), plant cover and cropping practices (C) and erosion

control practices (P). A = R.K. SL.C.P

The R value used for the study area was based on the formula of Rango & Arnoldus (1987)

and derived by using 1979–2013 data from the Ain Boukallal weather station.

The K value was derived using the Wischmeier equation, the pedological map of the study

area, and the area’s infiltration and soils properties as developed by (Tribak 2000 and Tribak et al.

(2009).

The LS factor is computed by the GIS software. It utilizes the DEM to calculate the slope

and slope lengths, as well as the orientation of the slopes used in developing the patches (Chen et

al., 2008).

The C value used was based on results of previous similar studies concerning some

catchments areas in the Rif moutains (Tribak et al 2009, Sadiki et al 2004, Naimi et al 2004), and

also by using satellite images, as well as field observations.

The P factor ranges from 1 for no conservation to 0.1 for heavily mulched grounds (Roose,

1996). No conservation is practiced in the study area, so a value of 1 was assigned to the whole

study area.

After having determined all necessary parameters, estimation and mapping of soil losses are

made using the integrated model RUSLE in Idrisi Andes Software (Lewis et al. 2005).

Sedimentation Model:

The model Sedimentation uses homogeneous polygons resulting from the calculation of the

RUSLE model to assess the net movement of soil (erosion or deposit) in plots or watersheds (Lewis

et al., 2005). If the data is analyzed at the scale of the watershed, a report from the issuance of the

sediment can be entered to determine the amount of sediment out of the basin. The implementation

of this model will come after the RUSLE model results. Sedimentation requires to show firstly

whether the data are to be analyzed at the field or at watershed level, and then to introduce the MNT

and the identification images of homogeneous polygons and the soil losses images resulting from

RUSLE equation.

The determination of net erosion or deposition begins with the calculation of total soil loss

for each homogeneous product polygon from the RUSLE model. The model Sedimentation

determines first the average altitude for each polygon and then the location of the highest altitude in

the catchment area or in the relevant plot. The direction of movement of the soil is then determined

by the relative differences in elevation between adjacent polygons. So the movement is always in

the direction of the downward slope. The amount of soil loss that enters the surrounding lower

polygon is proportional to the length of the common border between the top of the polygon and the

lower one (Eastman, 2006). Then, soil loss or net deposits in all lower polygons are calculated as

well. Using the results of the RUSLE model, soil loss for the top polygon is compared to the lower

one. The difference amounts of soil loss between the top of the polygon and the lower one

constitute the loss or the net deposition soils in the lower polygon.

4. RESULTS AND DISCUSSION

4.1. Evolution of land use

This part was intended to diachronic analysis of land use to estimate the scale of landscape

modifications due to the degradation of natural resources and to highlight the major changes of the

environment within the basin. We performed the analysis and interpretation of remote sensing

images for two years (2000 and 2014) to develop land use maps and to detect its change over time.

The results of this analysis allowed us to identify four classes of occupation and land use:

arboriculture/ Olive trees, badlands and uncultivated land, annual crops, Forest/ Reforestation

From the standpoint of land use, the analysis shows a modification of the countryside with

an increase of olive areas, an extension of the highly eroded areas (badlands and uncultivated land)

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and reduced annual crops areas to benefit of arboriculture. The surfaces occupied by scrub and

reforestation suffered a slight reduction. Thus, The mapping and diachronic study of land use (2000

- 2014) shows very clearly increased areas of fruit tree crops (85.27%), an extension of heavily

eroded soils (badlands and wasteland ) (8.74%) and a reduction of annual crop areas (-26.55%) and

forest/ reforestation (-37.54%) (Table 2)

The significant expansion of uncultivated land and consequently the badlands is closely

related to phenomena of abandonment of agricultural land because of the accelerated process of

rural depopulation. In the Currently abandoned plots, the soil structures are considerably degraded.

Their compaction, in the absence of basic maintenance and protection works, allows a concentration

of runoff that contributes to the onset of dense networks of incisions. So it constitutes the seat of

major runoff coefficients and are, therefore, a preferred location of the increase in the erosion

process and excessive sediment output.

Code Land use Areas (Km²)

2000 %

Areas (Km²)

2014 %

Evolution

2000-2014

4

badlands and

wasteland 27,70 39,81 30,12 43,29 8,74

3 Annual croops 32,49 46,70 23,86 34,30 -26,55

2 Arboriculture 7,92 11,39 14,68 21,10 85,27

1 forest/ reforestation 1,47 2,11 0,92 1,32 -37,54

Total 69,58 100,00 69,58 100,00

Tableau 2. diachronic evolution of the land use during the period 2000-2014

Figure 5. Land use of Wadi Tarmast - 2000

Figure 6. Land use of Wadi Tarmast - 2014

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4.2. Estimation and mapping of soil loss

The soil loss map was determined by multiplying the various required parameters (R, K, LS,

C and P) which constitute the Wischmeier amended universal soils loss equation (RUSLE). This

map shows both the extent of losses in land in the basin and their variability from one sector to

another. The weighted average loss per surface is 78 t / ha / year for a total of 542 943 t / year for

the entire basin. These results show excessive sediment production that exceeds farly the tolerance

threshold. This remains closely linked to the considerable extension of marly material offering

steep, bare and intensely exploited slopes. For comparison the average losses are estimated in the

valley of Wadi Tlata (eastern Prerif) to 61 t / ha / year on marly bare and cultured hillsides (Tribak

et al 2009). In the watershed of Wadi Nakhla in the Western Rif losses reach the average of 65

t/ha/year at the level of the field (Naimi et al 2004). The spatial distribution of soil loss shows that

more than 32 t / ha / year class is predominant occupying 21.7 km2 (31.3%) of the basin area.

Conversely the class of losses less than 7t / ha / year occupies only 16.9 km2 (24.2%) of the total

area of the basin (Table 5).

Watersheds Area

(Km2)

Lithology Average soil

loss

(t/ha/year)

Wadi Tleta

(Eastern Prerif)

(Tribak 2009)

123

marls, limestone marl and sandy marls

61

Oued Nakhla

(Western rif)

(Naili 2004)

111 marls and flysch 60

Oued Boussouab

(Eastern Rif )

(Sadiki 2004)

252 Dark pelites, marls and limestone marl

55

Oued El Mellah

(Central Prerif)

(Laroussi 2013)

34 Calcareous ,sandstone marls with

interbedded sandstone, Pliocene

conglomerates

41

Table 3. Soil loss in other rifain wshedsater

From Table (4) illustrating the loss of land by type of occupation, losses are ranged from

2.19 t / ha / year as the minimum value measured in forests and 140.86 t / ha / year as maximum

value recorded in wastelands and badlands. They generally correspond to Regosols or less evolved

erosion soils located essentially on marly steep slopes which sometimes exceeds 25%. Land

reserved for annual crops and tree crops also exhibit high susceptibility to erosion, with respective

annual losses of 37.11 t / ha and 21.9 t / ha / year. The role of human activities and land use patterns

is an important element explaining the acceleration of erosion phenomena and their spatial

distribution. Furthermore, the extension of the area of uncultivated land and badlands in the basin, is

due to the abandonment of certain areas, which is a recent phenomenon related to migration within

the region. Field observations show that actually abandoned plots, especially on southern

exposures, are intensely pickled and ravaged by gullies and so can produce huge amounts of

sediment.

As we can see, the RUSLE model displays relatively high soil losses related to the

combination of physical parameters (steep slopes, rugged terrain, and dominance of marly

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formations and almost total absence of vegetation cover) and human parameters manifested by

strong pressure on the slopes.

Land use Forest/Reforestation arboriculture/

Olive trees

annual crops Badlands and

uncultivated land

Areas km2 0.92 14,68 23.86 30.12

% 1,32 21,10 34,30 43.29

losses/RUSLE

(t/ha/an) 2014

2,219 21 ,931 31,117 140,106

Table 4. Annual average soil loss by type of occupation (RUSLE) 2014

Figure 7. net soil losses established by the RUSLE model for the year 2014 (t/ha/year)

Classes Areas (Km²) %

< 7 t/ha/Year 16,90 24,29

7 - 20 t/ha/Year 14,60 20,98

20 - 32 t/ha/Year 16,30 23,43

> 32 t/ha/Year 21,78 31,30

Total 69,58 100,00

Table 5. areas average losses of soil according to the RUSLE model (2014)

Figure 8. net soil losses established by the

sedimentation model for the year 2014 (t/ha/year)

Classes Areas(Km²) %

Sédiment 5,58 8,02

< 7 t/ha/an 24,38 35,07

7 - 20 t/ha/an 28,06 40,35

20 - 32 t/ha/an 10,16 14,61

> 32 t/ha/an 1,35 1,95

Total 69,52 100,00

Table 6. areas average losses of soil according to the Sedimentation model (2014)

Indeed, in this model all the pixels deliver a quantity, greater than or equal to zero loss in

soil, without considering the possibility of deposition at the downstream and the slope change area.

This led us to consider the possibility of integrating the deposition phenomenon to estimate the net

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soil loss in the study area. The Sedimentation model results are shown in Figure 8. These results of

net soil losses are significantly lower than those estimated by RUSLE. This is logical with the fact

of existing compensation between adjacent plots.

Comparing these results with previous studies (El Garouani et al 2003, Tribak, 2009, 2012;

Esadiki 2004, Heusch, 1970) shows that the consideration of the temporal variability of the erosion

process and the deposition phenomenon usually leads to decrease soil erosion value. According to

the results, that we see that the class of losses 7-20 t / ha / year predominates, with 28.06 km2

(40.35%), however the upper class of 32 t / ha / year occupies only 1.35 Km2 (1.95%) of the basin

(Table 6). based on the averages of certain types of land use, there is an increased risk of erosion

over time in high slope areas of the basin. Nevertheless, the lowlands, the basal sections of certain

slopes and the terraces bordering the river are the site of accumulation and settling considerable

amounts of fine elements that enrich soils and compensate accelerated erosion on steep slopes,

generally barren. Thus It appears from the field observations that these deposition zones allow some

fairly developed soils such as isohumic soils or vertisol rich in silt and clay. They take, in the

landscape, some dark colors that contrast sharply with the bright colors that characterize highly

eroded soils on steep slopes (photos 1-2).

Photo 1: South facing slopes heavily

devastated by erosional processes (Wadi Tarmast catchment, May 2015 )

Photo 2 : Sedimentation areas benefiting from

developed soils (Wadi Tarmast catchment, May 2015 )

5. CONCLUSION

The mapping of changes in land use from remote sensing data, on one hand, and quantitative

assessment of the hydric erosion and deposition on the other, in this region of the Rif, shows great

fragility of these environments. Soils and surface formations derived from essentially marly and

mostly bared lands exude susceptibility to various erosional processes. According to the RUSLE

model average soils losses above-mentioned, exceed significantly the thresholds loss tolerances,

although they are around the ablation rates in some regions of the Moroccan Rif. This reflects the

importance of the accelerated rate of erosion in the entire basin and the contribution of the various

factors analyzed above. The production of sediments in this Rifain catchment is excessive,

threatening the soil capital and infrastructure located downstream within the Inaouène basin.

Nevertheless the use of the sedimentation model for quantifying erosion helped us to highlight the

importance of the deposition phenomenon in the determination of net soil loss. Comparison of these

results with previous studies show that taking into account the time variability of the process of

erosion and deposition phenomenon leads to reduce the soil erosion value considerably. In this way

the low funds, ledges and concave slopes and terraces bordering the rivers are seats of landing

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considerable amounts of fine elements that enrich soils and compensate accelerated erosion on steep

slopes generally barren.

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