This study documents river terraces from upstream reaches of the Dad es River, a major fluvial system draining the south-central High Atlas Mountains. Terraces occur as straths with bedrock bases positioned at 10 m altitudinal intervals up to 40 m (T1-T5) above the valley floor, becoming less common between 50 and 140 m. The rock strength, stratigraphy and structure of the mountain belt influences terrace distribution. Terraces are absent in river gorges of structurally thickened limestone; whilst welldeveloped, laterally continuous terraces (T1-T4) form along wide valleys occupying syncline structures dominated by weaker interbedded limestone-mudstone. Terrace staircases develop in confined canyons associated with weaker lithologies and influence from structural dip and stratigraphic configuration. Terraces comprise a bedrock erosion surface overlain by fluvial conglomerates, rare overbank sands and colluvium. This sequence with some OSL/IRSL age control, suggests terrace formation over a 100 ka climate cycle with valley floor aggradation during full glacials and incision during glacial-interglacial transitions. This integrates with other archives (e.g. lakes, glaciers, dunes), appearing typical of landscape development along the NW Saharan margin south of the High Atlas, and similar to patterns in the western-southern Mediterranean. The 100 ka climate cycle relationship suggests that the terrace sequence documents Late-Middle Pleistocene landscape development. Consistent altitudinal spacing of terraces and their distribution throughout the orogen suggests sustained base-level lowering linked to uplift-exhumation of the High Atlas. Low incision rates (<0.2 mm a À1) and general absence of terrace deformation suggests dominance of isostatically driven base-level lowering with relief generation being Early Pleistocene or older.

No abstract

Soil loss triggered by water erosion constitutes a major issue that causes several environmental and socioeconomic concerns. The Moroccan Western High Atlas is the most vulnerable area in the High Atlas Mountains, due to the existence of different forms of landslides, and evidences of erosion are widely observed. This study aims at estimating and quantifying the amount of soil loss as well as highlighting potential areas to erosion risk, using the Revised Universal Soil Loss Equation (RUSLE) combined with GIS and remote sensing. The RUSLE model provides a possibility of computing erosion susceptibility for each pixel on the basis of the controlling factors which are rainfall aggressivity, topography, vegetation cover, soil erodibility, and support practices. In this study, results show that the erosion rate varies between 0 and 227.67 t/ha/year, with an average annual soil loss of 40.38 t/ha/year, and the Beni Mohand River basin is subject to very high rates of erosion which can be irreversible since it exceeds the tolerable standard rate which is 1 t/ha/year. These findings will provide land use planners baseline for land use and risk management and will provide data within the Moroccan Western High Atlas Mountains.

No abstract

Soil erosion is a widespread problem that continues to expand in magnitude and scope due to ever-changing anthropogenic and climatic conditions. The High Atlas Mountains in Morocco are a typical case where this problem affects the ecological and socioeconomic activities of the region. The main objective of this study is to provide an erosion risk analysis of the Argana Corridor in the High Atlas of Morocco using GIS, Remote Sensing and the Revised Universal Soil Loss Equation (RUSLE). The erosion assessment is based on various controlling factors including climate, topography, vegetation cover, soil erodibility and soil conservation practices. Findings indicate that the study area is subjected to significant erosion, reaching an average annual soil loss rate of 47.52 t/ha/year, and an annual erosion amount of 5,233,840 tons. Collectively, the methodology and results provide a decision support system for stakeholders in the region, and a framework for studies in data-scarce regions.