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GEOLOGY, ECOLOGY, AND LANDSCAPES 2019, VOL. 3, NO. 1, 22–28 INWASCON https://doi.org/10.1080/24749508.2018.1481655 Mapping the water erosion risk in the Lakhdar river basin (central High Atlas, Morocco) a a b c d a Wafae Nouaim , Saïd Chakiri , Dimitri Rambourg , Ismail Karaoui , Abderrahim Ettaqy , Jamal Chao , a e e a Mohamed Allouza , Bouchra Razoki , Mohamed Yazidi and Fatima El Hmidi a b Faculty of Sciences, Laboratory “Geosciences of Natural Resources”, University Ibn Tofail, Kénitra, Morocco; Laboratory of Hydrology and Geochemistry of Strasbourg, University of Strasbourg, Strasbourg, France; Faculty of Sciences and Techniques, Team “Water Resources Management”, University Sultan Moulay Slimane, Beni Mellal, Morocco; Tadla-Azilal Water, Forest and Desertification Prevention Regional Office,” Planning and Development” Service, Beni-Mellal, Morocco; Regional Center for Education and Training Professions (CRMEF), Marrakech, Morocco ABSTRACT ARTICLE HISTORY Received 5 February 2018 The objective of this study is to develop a methodology using the remote sensing and Accepted 22 May 2018 Geographic Information System to map soil degradation by water erosion and highlighting the various levels of soil degradation in the Lakhdar river basin (central High Atlas) during the KEYWORDS period between 1987 and 2014. This allows producing a map of soil degradation risk, which Water erosion; spectral can be used as reference document for the decision-makers. The methodology develops a indices; remote sensing; geomatics approach based on the processing of satellite images, using the analysis and the Lakhdar river basin; central interpretation of spectral indices, such as the Form Index, the Coloration Index, the Brightness High Atlas; Morocco Index, and the Normalized Difference Vegetation Index (NDVI). The results show that the surface of soil strongly degraded decreased about 900 ha during the period of study whereas the surface of soil weakly and moderately degraded was subject of a progressive increase for an approximate total of 2800 ha over 27 years. Moreover, the method of spectral indices allowed us to assess and locate soil quantitative loss (organic matter, mineral salts, texture, fertility, etc.) due to the water erosion and climate change. These results are decisive when it comes to establish priority zonation for the interventions of erosion control. I. Introduction characterization of the state of grounds surface, espe- cially arid and semi-arid regions. One of the most Water erosion is a genuine menace for natural popular approaches is the spectral indices method, resources durability, for the quality and morphology using the Form Index (FI), the Coloration Index (CI), of surface water entities, as for the socioeconomic the Brightness Index (BI), and the Normalized growth of rural areas. In order to deal with this Difference Vegetation Index (NDVI) (Chikhaoui et al., issue, tools were developed allowing the identification 2007; Bannari, El-Harti, Haboudane, Bachaoui, & El- and the analysis of the processes of soil degradation, Ghmari, 2008; Escadafal, 1994; Haboudane, Miller, and therefore helping achieving a sustainable devel- Tremblay, Zarco-Tejada, & Dextraze, 2002; Mathieu, opment. In particular, areas of high risk in terms of Pouget, Cervelle, & Escadafal, 1998; Mattikalli, 1997). soil degradation must be located in order to resort to the adequate arrangements for the fight against the losses of this nonrenewable resource. II. Methodology In this context, the present study falls within the The methodology followed in this research consists to framework of the watershed management Program map the areas exposed to water erosion risks in (River Basin management plan) and the water policy Lakhdar river basin in the High Atlas Mountains of (National water plan). It is carried out in partnership Morocco by using the geomatics approach based on with the waters and forests department and aims at the processing of satellite images (Figure 1). first the evaluation of soil degradation caused, among The determination of the indices (BI, CI, FI, NDVI) others, by the water erosion and in second, the eva- refers to the shape of grounds spectral reflectance luation of the impact of the arrangements put in place curves. The analysis and the comparison of the various by the River Basin management plan. combinations of these indices led to create a neo-canal This study aims at mapping the high-risk areas of for mapping the soil degradation by water erosion. water erosion by remote sensing. Several works have In this study, two satellites image Landsat OLI and already attested the pertinence of this method in the TM are exploited for the calculation of the indices CONTACT Wafae Nouaim wafae.nouaim8@gmail.com Faculty of Sciences, Laboratory “Geosciences of Natural Resources, University Ibn Tofail, Kénitra, Morocco © 2018 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the International Water, Air & Soil Conservation Society (INWASCON). This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. GEOLOGY, ECOLOGY, AND LANDSCAPES 23 System to estimate the evolution of the soil degrada- tion risk over a period of 28 years (1987–2014). III. Geographical and geological context The study area is located in Moroccan Central Atlas, 30 km southwest of Azilal town. It consists of the upstream part of the Lakhdar river basin, ending in Hassan I dam. Its surface is of 6800 km (Figure 2). It is situated in the high domain atlasic, where grounds are dominated by carbonate formations. The upstream part of Lakhdar river basin is consti- tuted by high mountains (between 2000 and 4000 m of height), the central part of low mountain (around 1500 m) and the downstream, near the Hassan I dam, of low mountains (between 900 and 1200 m) (Sabir, Roose, Merzouk, & Nouri, 1999). The study region is characterized by a semi-arid climate with an average annual rainfall ranging Figure 1. The methodology flowchart. between 273 mm/y (Tabant station) and 575 mm/y (Sgat station). Hence, according to a pluviometric Table 1. Spectral index of TM and OLI sensor. gradient determined by the continental character; the Sensor TM Sensor OLI downstream of Lakhdar river basin is more endowed 2 TM3TM2TM1 2 OLI4OLI3OLI2 Form Index (FI) TM3TM1 OLI3OLI2 with precipitation than its upstream. pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2 2 2 Brightness Index (BI) TM3 þ TM4 OLI4 þ OLI5 The region contains particular geomorphological TM3TM2 OLI4OLI2 Coloration Index (CI) TM3 OLI4 structures and varied lithological formation, ranging TM4TM3 OLI5OLI3 Normalized Difference Vegetation in age from Trias to mid-Cretaceous (Cenomanian- TM4þTM3 OLI5þOLI3 Index (NDVI) Turonian). The essential lines of the central High Atlas are shaped by limestones formations. The Lias (Table 1). Firstly, these images were corrected from formations appear in the form of continuous bands radiometric and atmospheric effects. Secondly, they decametric, especially on the West, that is the regions were analyzed through a Geographic Information of Tabant (Ait Bouguemez) and Mesgounane. In the Figure 2. Geographical situation of Lakhdar river basin. 24 W. NOUAIM ET AL. center of the anticlines, which are generally broken ● satellite image sensor TM: bands (3–4) for the and asymmetrical, lay the highest summits of the area NDVI, (1–3) for the CI, (3–4) for the BI and (3– of Lakhdar river basin such as Jbel Azourki whose 2-1) for the FI; crests are monoclinal. Those crests are eroded, and ● satellite image sensor OLI: bands (4–5) for the this erosion settle the synclines plateaux of Jurassic NDVI, (2–4) for the CI, (4–5) for the BI and (4– limestones (Dogger). Those plateaux sometimes pre- 3-2) for the FI. sent undulations and fractures such as the plateau of Ait Mhamed. Those structures imply a strongly slop- The calculation of each spectral index led to the ing topography responsible for the dynamics of sur- following results (Figure 3): face, in particular the erosion forms (stripping of the Secondly, several combinations of colored ele- topsoil, diggings, landslides) (Sabir et al., 1999). ments in the system RGB were tested through the The lithostratigraphy shows two series of lime- image processing system ENVI 5.1, considering the stones alternating with three groups of imperme- various index (FI, CI, BI, NDVI) (Figure 4). able layers. Dolomitic basalts, sandstone, marls and The comparison and the analysis of the various com- saline clays constitute the Trias formations. The binations led to the creation of a neo-canal combining Jurassic formations are very susceptible to erosion the three indices FI, CI, NDVI. This neo-canal has a high hence the presence of ravines, like in Bernat and discrimination capacity in terms of soil degradation and Tabant areas. more generally of land use (Figures 5 and 6), attested by The Lias soils, made of limestone-marl, clays and field knowledge and studies done by the Forest and sandstone series, predominate the landscape. Their Desertification Prevention Regional Office. dark red or greenish layers, resistant to erosion but The grounds highly degraded are associated with always thin, are cored in monoclinally dipping. Over low FI values and high CI values, while the grounds the Upper Jurassic and the Lower Cretaceous grounds, lowly degraded show high FI values and low CI lie impermeable and bright-colored formations. values (Chikhaoui et al., 2007; Bannari et al., 2008; Erosion drew monotonous structural reliefs, exploited Haboudane et al., 2002; Parenteau, Bannari, El-Harti, by mankind, even if grounds are in stiff slope, resulting Bachaoui, & El-Ghmari, 2003). In this semi-arid con- to recurring disastrous episodes for farms due to water text, the NDVI demonstrated its potential in the erosion (Ibouh, El Bchari, Bouabdelli, Souhel, & mapping of soil degradation area (Maimouni, Youbi, 2001). Bannari, El-Harti, & El-Ghmari, 2011). The soil degradation distributions resulting from these calcu- lations are shown in the following table (Table 2): According to the results, a deterioration of the IV. Results and discussions Lakhdar river basin soils is noticeable between 1987 Firstly, for a better estimation of the intensity of and 2014, the overall surface of degraded soil having erosion in Lakhdar river basin, the most appropriate increased from 89.78% to 90.93%. On another hand, spectral bands of each satellite image were chosen for the class of grounds highly degraded decreased about the calculations of the spectral indices: 900 ha during the period. This could be explained by Figure 3. Results of the spectral index (BI, CI, FI, NDVI). GEOLOGY, ECOLOGY, AND LANDSCAPES 25 Figure 4. Examples of spectral index combinations tested. Figure 5. Soil degradation map (1987). the efforts deployed in the course of the Lakhdar river Torrential correction, essentially consisting in basin development project, a pilot project aiming the the preparation of dams, and protection of improvement of land productivity while ensuring the ravines with gabions and dry stones. natural resources good management in mountain areas. DRS fruit-bearing forest, an action aiming to The spatial distribution of soil degradation in 2014 improve the productivity of lands and the soil shows that grounds strongly degraded are generally preservation by hindering runoff and increasing situated in cleared areas. While the grounds averagely the infiltration.Itwas putintopracticeover795 ha; degraded cover areas of low to moderately slope and Silvo-pastoral scheme consisting in creating partially covered with vegetation. The lowly degraded favorable to the development of natural forage soil cover areas of deep soil with arboreal, shrubby, or species and introducing other essences with high herbaceous vegetation cover. The realizations of the forage value in order to reconstitute land cover, project were made in the priority zones with highest improve the productivity of rangeland, and degradation levels identified beforehand. The record ensure water and soil conservation. The scheme of these physical realizations is as follows: was realized on 120 ha. 26 W. NOUAIM ET AL. Figure 6. Soil degradation map (2014). leaving the tree crown cover intact, thereby strength- Table 2. States of grounds degradation and corresponding ening soil cohesion and favoring infiltration of water. surfaces in 1987 and 2014. The zones of negative evolution are located at high 1987 2014 altitudes with steep slopes. There, environmental con- Area (ha) % Area (ha) % Nondegraded soil 17,187.76 10.22 15,223.05 9.07 ditions are extremely unfavorable which, combined Low degraded soil 26,409.42 15.72 28,572.03 16.99 with the other human and natural factors (topography, Moderately degraded soil 65,032.65 38.68 65,704.41 39.08 soil friability, rainfall erosivity, land cover, etc.), lead to Highly degraded soil 59,481.27 35.38 58,611.51 34.86 Total 168,111 100 168,111 100 an intense soil degradation. The present study allowed to characterize the state of grounds degradation by adopting spectral index Thus, the total balance is 915 ha, that is a surface approach. The obtained results checked against the close to the calculated decrease of highly degraded soils. field data accorded a better precision to this approach. In spite of these efforts, a progressive evolution of the The calculation of spectral index gives more precision grounds lowly and moderately degraded surface on and describes rather faithfully the reality of the ground approximately 2800 ha occurred over 28 years. (Chikhaoui et al., 2007). However, certain provisions Moreover, moderately and highly degraded soils pre- must be upstream taken, because choice of the ade- dominate in the study region (respectively 39% and 34% quate bands combination allowing better distinguish in 2014). This shows the extent of the degradation pro- of the various levels of grounds degradation is a long cess and the degree of grounds sensibility to the erosion. and crucial stage which requires an expertise and a According to the global change map (Figure 7) and good knowledge of the environment being studied. its related table (Table 3), the period 1987–2014, knew a surface change equal between area with posi- tive change and area with negative change. While the IV. Verification of results unchangeable area are insignificant. The spatialized evolution of grounds degradation The results shown on the following maps are represented shows that positive change is correlated with an in 3D (Figure 8) with three times the exaggeration of the improvement of land cover: reforestation activities vertical. They highlight four thematic classes namely the and implementation of good farming techniques lead- vegetation (light green), the soil lowly degraded (light ing to revegetation and bare soils valorization. Also, blue), the soil moderately degraded (green), and the soil shade-grown methods (culture under forest cover) highly degraded (pink). These computed classes of soil knew a clear improvement in the region of study. degradation (map of 2014) were confronted with pictures Such practice optimizes the use of fertile soils while illustrating the field reality. GEOLOGY, ECOLOGY, AND LANDSCAPES 27 Figure 7. Map of soil degradation evolution in the Lakhdar river basin (1987–2014). Table 3. Change of soil degradation state and corresponding that every spectral index has its own behavior relatively to surfaces (1987–2014). the level of soil degradation. The soils highly degraded are Area (ha) % Area associated with high CI and low FI and NDVI, signature Zone of positive change 79,266.67 47.15 of a reflectancecurve dueabedrockoutcrop.Onthe Unchangeable zone 7706.75 4.58 contrary, the soils lowly degraded are associated with Zone of negative change 81,137.62 48.26 Total 168,111 100 low CI and high FI and NDVI. Therefore, this exploita- tion of satellite data allows mapping the environment state, and more specifically the soil degradation level. V. Conclusion The combined use of these variables allows a good dis- The spectral indices method is suitable to represent the crimination of the various soil states, attested by field data various levels of soil degradation. This method showed comparison. Figure 8. Aspect of water erosion in the Lakhdar river basin. 28 W. NOUAIM ET AL. The results of ground degradation computed for the et des indices spectraux en utilisant des données aster. Revue Télédétection, 7(1–2), 3–4. Lakhdar river basin show a progressive increase of lowly Escadafal, R. (1994). Soil spectral properties and their rela- and moderately degraded soils (approximately 2800 ha tionships with environmental parameters-examples from over 27 years), while the surface of highly degraded soils arid regions. In Imaging spectrometry—A tool for envir- decreased about 900 ha during the same period. This is onmental observations (pp. 71–87). Springer. consistent with the Lakhdar river basin development Haboudane, D., Miller, J. R., Tremblay, N., Zarco-Tejada, P. J., & Dextraze, L. (2002). Integrated narrow-band project efforts focused on the areas with the highest vegetation indices for prediction of crop chlorophyll deterioration levels. content for application to precision agriculture. Remote This methodology can be developed, on a pilot basis, Sensing of Environment, 81(2–3), 416–426. by the competent authorities to estimate the state of Ibouh,H.,El Bchari,F.,Bouabdelli, M.,Souhel,A.,& grounds degradation in river basins. It can be an adequate Youbi, N. (2001). L’accident tizal-azourki haut atlas tool of planning for monitoring and assessing ground central du maroc: Déformations synsedimentaires lia- siques en extension et conséquences du serrage atlas- degradation in order to conserve this valuable resource. ique. Estudios Geologicos, 57(1–2), 15–30. Maimouni,S.,Bannari,A.,El-Harti, A., &El-Ghmari,A. (2011). Potentiels et limites des indices spectraux pour Acknowledgments caractériser la dégradation des sols en milieu semi- aride. Canadian Journal of Remote Sensing, 37(3), The author thanks the Director of Regional Water and 285–301. Forests Administration (Beni Mellal, Morocco), specially Mathieu, R., Pouget, M., Cervelle, B., & Escadafal, R. Mr Abderrahim Ettaqy from the same administration and (1998). Relationships between satellite-based radiometric the director of Hydraulic Basin Agency (Beni Mellal, indices simulated using laboratory reflectance data and Morocco), for their relevant facilities and support. typic soil color of an arid environment. Remote Sensing of Environment, 66(1), 17–28. Mattikalli, N. M. (1997). Soil color modeling for the visible Disclosure statement and near-infrared bands of Landsat sensors using labora- tory spectral measurements. Remote Sensing of No potential conflict of interest was reported by the authors. Environment, 59(1), 14–28. Parenteau, M. P., Bannari, A., El-Harti, A., Bachaoui, M., & El-Ghmari, A. (2003). Characterization of the state of References soil degradation by erosion using the hue and coloration indices. In Geoscience and remote sensing symposium, Bannari, A., El-Harti, A., Haboudane, D., Bachaoui, M., & 2003. IGARSS’03. Proceedings. 2003 IEEE International El-Ghmari, A. (2008). Intégration des variables spec- (Vol. 4, p. 2284–2286). IEEE. trales et géomorphométriques dans un SIG pour la car- Sabir,M.,Roose,E.,Merzouk,A.,&Nouri,A.(1999). tographie des zones exposées à l’érosion. Revue Techniques traditionnelles de gestion de l’eau et Télédétection, 7(1–4), 393–404. de lutte anti-érosive dans deux terroirs du rif occi- Chikhaoui, M., Bonn, F., Merzouk, A., Lacaze, B., & dental (maroc). Bull. Réseau Érosion, Montpellier, 19, Mejjati, A. M. (2007). Cartographie de la dégradation 456–471. des sols à l’aide des approches du spectral angle mapper
Geology Ecology and Landscapes – Taylor & Francis
Published: Jan 2, 2019
Keywords: Water erosion; spectral indices; remote sensing; Lakhdar river basin; central High Atlas; Morocco
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