The study of land use/land cover (LULC) has become an increasingly important stage in the development of forest ecosystems strategies. Hence, the main goal of this study was to describe the vegetation change of Azrou Forest in the Middle Atlas, Morocco, between 1987 and 2017. To achieve this, a set of Landsat images, including one Multispectral Scanner (MSS) scene from 1987; one Enhanced Thematic Mapper Plus (ETM+) scene from 2000; two Thematic Mapper (TM) scenes from 1995 and 2011; and one Landsat 8 Operational Land Imager (OLI) scene from 2017; were acquired and processed. Ground-based survey data and the normalized difference vegetation index (NDVI) were used to identify and to improve the discrimination between LULC categories. Then, the maximum likelihood (ML) classification method was applied was applied, in order to produce land cover maps for each year. Three classes were considered by the classification of NDVI value: low-density vegetation; moderate-density vegetation, and high-density vegetation. Our study achieved classification accuracies of 66.8% (1987), 99.9% (1995), 99.8% (2000), 99.9% (2011), and 99.9% (2017). The results from the Landsat-based image analysis show that the area of low-density vegetation was decreased from 27.4% to 2.1% over the past 30 years. While, in 2017, the class of high-density vegetation was increased to 64.6% of the total area of study area. The results of this study show that the total forest cover remained stable. The present study highlights the importance of the image classification algorithms combined with NDVI index for better understanding the changes that have occurred in this forest. Therefore, the findings of this study could assist planners and decision-makers to guide, in a good manner, the sustainable land development of areas with similar backgrounds.

Groundwater is a most important resource in arid and semi-arid regions and is required for drinking, irrigation and industrialization. Assessing the potential zone of groundwater recharge is extremely crucial for the protection of water quality and the management of groundwater systems. To identify the groundwater potential zone in the study area, thematic layers of lithology, slope, karst degrees, land cover, lineament and drainage density were generated using topographic maps, thematic maps, field data and satellite image, and were prepared, classified, weighted and integrated in a geographic information system (GIS) environment by the means of fuzzy logic. The fuzzy membership values have been assigned to different thematic layers according to their classification on respect for their contribution and their occurrence in groundwater. Based on the generated groundwater potential map, it was found that about 8% of the investigation area was categorized as very high potential for groundwater recharge, 31% as high, 28% as moderate, 17% as low and 16% as very low potential for groundwater recharge. Finally, the results were verified using well-yield data. The highest recharge potential area is located towards the downstream regions related to more fractured and karstified limestone.

Soil erosion is an increasingly issue worldwide, due to several factors including climate variations and humans’ activities, especially in Mediterranean ecosystems. Therefore, the aim of this paper is: (i) to quantify and to predict soil erosion rate for the baseline period (2000–2013) and a future period (2014–2027), using the Revised Universal Soil Loss Equation (RUSLE) and the Soil and Water Assessment Tool (SWAT) model in the R’Dom watershed in Morocco, based on the opportunities of Remote Sensing (RS) techniques and Geographical Information System (GIS) geospatial tools. (ii) we based on classical statistical downscaling model (SDSM) for rainfall prediction. Due to the lack of field data, the model results are validated by expert knowledge. As a result of this study, it is found that both agricultural lands and bare lands are most affected by soil erosion. Moreover, it is showed that soil erosion in the watershed was dominated by very low and low erosion. Although the area of very low erosion and low erosion continued to decrease. Hence, we hereby envisage that our contribution will provide a more complete understanding of the soil degradation in this study area and the results of this research could be a crucial reference in soil erosion studies and also may serve as a valuable guidance for watershed management strategies.

No abstract

The preservation of soil resources is a primary global concern and a permanent challenge for all Mediterranean countries. In Morocco, the capacity of dam reservoirs continues to decline from one year to the next due to the rate of siltation, mainly due to the phenomenon of water erosion. Indeed, the origins of this erosion are generally related to land use planning, deforestation, agricultural practices and low vegetation cover. However, it is imperative to quantify soil erosion and its spatial distribution to achieve sustainable land use and governance of this resource. The SWAT hydro-agricultural model and the integrated RUSLE model were used to assess soil losses and characterize the degraded areas of the M’dez watershed, located in the upper Sebou, north of the Middle Atlas, and extend on an area of 3350 km2. The results obtained during this work show that the average soil losses estimated by the two models are consistent. For the SWAT model, the specific degradation of the watershed is estimated at 3.95 t/ha/year, whereas for the RUSLE model, the average loss of the basin is estimated at 2.94 t/ha/year). However, the use of these two models (SWAT and RUSLE), for the assessment and characterization of degraded areas at the level of Moroccan watersheds, has become a much sought-after approach for good soil conservation management.