The global change impacts on forest natural resources in Central Rif Mountains in northern Morocco: extensive exploration and planning perspective

Motaki, Hanifa El; El-Fengour, Abdelhak; Aissa, Elbouzidi; Madureira, Helena; Monteiro, Ana

doi:10.17127/got/2019.17.004

Cited by 2 publications

(3 citation statements)

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“…Due to its topographical conditions (i.e., slopes higher than 55 • ) and geological formations (shale, marl, and marl-limestone) [57][58][59], the watershed has suffered severe soil erosion and decline of forest ecosystems' resources [57] The study area belongs to the GHISS-Nekkor aquifer, which is an important source of groundwater in that region [60]. However, insufficient and poor sanitation facilities, as well as unsustainable agriculture in the study area, have resulted in deterioration of groundwater quality in this region [60,61].…”

Section: Study Areamentioning

confidence: 99%

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Hitouri

Varasano

Mohajane

et al. 2022

IJGI

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Gully erosion is a serious threat to the state of ecosystems all around the world. As a result, safeguarding the soil for our own benefit and from our own actions is a must for guaranteeing the long-term viability of a variety of ecosystem services. As a result, developing gully erosion susceptibility maps (GESM) is both suggested and necessary. In this study, we compared the effectiveness of three hybrid machine learning (ML) algorithms with the bivariate statistical index frequency ratio (FR), named random forest-frequency ratio (RF-FR), support vector machine-frequency ratio (SVM-FR), and naïve Bayes-frequency ratio (NB-FR), in mapping gully erosion in the GHISS watershed in the northern part of Morocco. The models were implemented based on the inventory mapping of a total number of 178 gully erosion points randomly divided into 2 groups (70% of points were used for training the models and 30% of points were used for the validation process), and 12 conditioning variables (i.e., elevation, slope, aspect, plane curvature, topographic moisture index (TWI), stream power index (SPI), precipitation, distance to road, distance to stream, drainage density, land use, and lithology). Using the equal interval reclassification method, the spatial distribution of gully erosion was categorized into five different classes, including very high, high, moderate, low, and very low. Our results showed that the very high susceptibility classes derived using RF-FR, SVM-FR, and NB-FR models covered 25.98%, 22.62%, and 27.10% of the total area, respectively. The area under the receiver (AUC) operating characteristic curve, precision, and accuracy were employed to evaluate the performance of these models. Based on the receiver operating characteristic (ROC), the results showed that the RF-FR achieved the best performance (AUC = 0.91), followed by SVM-FR (AUC = 0.87), and then NB-FR (AUC = 0.82), respectively. Our contribution, in line with the Sustainable Development Goals (SDGs), plays a crucial role for understanding and identifying the issue of “where and why” gully erosion occurs, and hence it can serve as a first pathway to reducing gully erosion in this particular area.

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Section: Study Areamentioning

confidence: 99%

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Hitouri

Varasano

Mohajane

et al. 2022

IJGI

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“…This technique was the basis of the DERRO project (El Motaki et al, 2019a). Fruit benches are contour ditches about 50 cm wide and deep, at the bottom of which fruit trees are planted (photo 1).…”

Section: The Benchesmentioning

confidence: 99%

“…The area of the cannabis is still growing up and more forests have been destroyed to spread the agriculture of cannabis (photo 7). The study we had to compare the superficies of the Oudka forest (Table III) demonstrated that in the last 30 years, the forest area of the Oudka massif has deteriorated in terms of areas and species (El Motaki et al, 2019a).…”

Section: Forest Management Assessmentmentioning

confidence: 99%

Sixty years of the development projects and combating the environment and natural resources degradation in arid and semi-arid areas in Rif mountains in Morocco

Motaki¹,

El-Fengour²,

Bouzidi³

2021

Geografia, Riscos E Proteção Civil. Homenagem Ao Professor Doutor Luciano Lourenço. Volume 2

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The development programs have been carried out to deal with the degradation phenomena since 1960 in Rif Mountains in northern Morocco. These conservation and preservation projects of natural resources implemented using either mechanical or biological techniques. The objective of this text is to evaluate the strategy undertaken for water and soil conservation to curb poor land-use practices and to assess the investment in water and soil conservation actions adopted the administrative approach that does not involve the locals by encouraging their effective participation in the identification, formulation, programming, execution, and monitoring of the actions to be carried out.

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The global change impacts on forest natural resources in Central Rif Mountains in northern Morocco: extensive exploration and planning perspective

Cited by 2 publications

References 0 publications

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Hybrid Machine Learning Approach for Gully Erosion Mapping Susceptibility at a Watershed Scale

Sixty years of the development projects and combating the environment and natural resources degradation in arid and semi-arid areas in Rif mountains in Morocco

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