The Upper Ziz basin located in the southeast of Morocco, has a total area of 4,351 km2. The surface water feeds El Hassan Addakhil dam, which insures water supply for the downstream cities of Errachidia, Rissani, Erfoud and others along the Ziz valley. This study aimed to evaluate the availability of water resources in this basin known by its arid climate and strong climatic changes. Several global hydrological models at different times were used to simulate the discharge at the outlet. The Statistical Downscaling Model (SDSM) method has been used to reduce the average rainfall and the temperature to predict future climate change related to various Representative Concentration Pathway (RCP) scenarios such as RCP 4.5 and RCP 8.5. The results of the hydrologic models are available, with an NSE of 0.8 for the monthly model during calibration and 0.77 at validation. Future precipitation shows an increasing trend in both scenarios. As for future mean temperature, it will recognize great seasonal variability, such as warming winter and spring and cooling summer and autumn. As a result, simulated future discharge will decrease by 26% under RCP 4.5 and by 24% under RCP 8.5 in the near future.
Soil erosion has been severely affecting soil and water resources in semi-arid areas like the Mediterranean. In Morocco, this natural process is accelerated by anthropogenic activities, such as unsustainable soil management, overgrazing, and deforestation. With a drainage area of 395,600 ha, the Bouregreg River Watershed extends from the Middle Atlas Range (Jebel Mtourzgane) to the Sidi Mohamed Ben Abdellah (SMBA) dam reservoir south-east of Rabat. Its contrasted eco-geomorphological landscapes make it susceptible to unprecedented soil erosion due to climate change. Resulting changes in erosive dynamics led to huge amounts of solid loads transported to the catchment outlet and, thus, jeopardised the SMBA dam lifespan due to siltation. The research aims to quantify the average annual soil losses in this watershed using the Revised Universal Equation of Soil Losses (RUSLE) within a GIS environment. To highlight shifts in land use/land cover patterns and their effects on erosional severity, we have resorted to remote sensing through two Landsat 8 satellite images captured in 2004 and 2019. The C factor was combined with readily available local data regarding major erosion factors, e.g. rainfall aggressiveness (R), soil erodibility (K), topography (LS), and conservation practices (P). The helped to map the erosion hazard and determine erosion prone areas within the watershed where appropriate water and conservation measures are to be considered. Accordingly, from 2004 to 2019, average annual soil losses increased from 11.78 to 18.38 t∙ha-1∙y-1, as the watershed area affected by strong erosion (>30 t∙ha-1∙y-1) evolved from 13.57 to 39.39%.
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