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Mediterranean countries are strongly affected by reduced surface water resources. This study aims to assess the climate change impacts on runoff supply to the Bin El Ouidane dam in Morocco, the largest in the country in terms of hydropower production. A water balance model coupled with a stochastic calibration method to provide confidence intervals on simulated discharge is used to reproduce discharge using observed and bias-corrected ECMWF Reanalysis 5th Generation (ERA5) rainfall (WFDE5). Five regional climate models from the EURO-CORDEX initiative are considered to estimate the climate change impacts on surface runoff for the Representative Concentration Pathway (RCP4.5) and RCP8.5 scenarios. Results indicate a future increase in evapotranspiration (+15 to +36%) associated with a decrease in precipitation (−16 to −34%) in both climate scenarios. The hydrological projections indicated a significant decrease in runoff (−57 to −86%), more severe when the model is driven by WFDE5 compared to observed precipitation. Consequently, the strong decline of surface water resources imply a change in water ressource management for hydropower production and local agriculture to adapt to the future climatic conditions. [ABSTRACT FROM AUTHOR]

The snow melt from the High Atlas represents a crucial water resource for crop irrigation in the semiarid regions of Morocco. Recent studies have used assimilation of snow cover area data from high‐resolution optical sensors to compute the snow water equivalent and snow melt in other mountain regions. These techniques however require large model ensembles, and therefore it is a challenge to determine the adequate model resolution that yields accurate results with reasonable computation time. Here we study the sensitivity of an energy balance model to the resolution of the model grid for a pilot catchment in the High Atlas. We used a time series of 8‐m resolution snow cover area maps with an average revisit time of 7.5 days to evaluate the model results. The digital elevation model was generated from Pléiades stereo images and resampled from 8 to 30, 90, 250, 500, and 1,000 m. The results indicate that the model performs well from 8 to 250 m but the agreement with observations drops at 500 m. This is because significant features of the topography were too smoothed out to properly characterize the spatial variability of meteorological forcing, including solar radiation. We conclude that a resolution of 250 m might be sufficient in this area. This result is consistent with the shape of the semivariogram of the topographic slope, suggesting that this semivariogram analysis could be used to transpose our conclusion to other study regions. Key Points: A distributed energy balance snow model is applied in the High Atlas for the first timeThe model performance decreases at resolution coarser than 250 mThis result is consistent with the semivariogram of the topographic slope [ABSTRACT FROM AUTHOR]

This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km2) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989‒2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049‒2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (−22% to −31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (−19% to −63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.EDITOR M.C. AcremanASSOCIATE EDITOR R. Hirsch [ABSTRACT FROM PUBLISHER]

The spatio-temporal distribution of snow cover metrics in a mountainous area is mainly related to the climatic conditions as well as to the prevailing morphological conditions. The present study aimed to investigate the altitudinal sensitivity of snow cover metrics using the MODIS Terra snow cover product (MOD10A1 v5). Annual snow metrics, including start of snow season (SOSS), end of snow season (EOSS), and snow cover duration (SCD) were extracted from snow-covered area (SCA) maps, which had been pre-processed using a cloud removal algorithm; the maps were of the Atlas Mountains, taken from the period of 2001–2016. In addition, a linear regression was applied to derive an annual altitudinal gradient for each snow metric in relation to various spatial scales in order to analyze the interdependency between snow and topography, and especially to assess the potential temporal trend of the snow gradient. Results indicated that elevation was the principal regulator of snow presence where snow was mostly accumulated above 2500 m. The annual altitudinal gradients for EOSS and SCD showed a marked negative trend beginning in 2007. However, the SOSS altitudinal gradient was marked by a positive trend. The mean SCD gradient for the entire Atlas Mountains decreased from 6 days/100 m to 3 days/100 m. This is a new and important finding since it may indicate the impact of climate change on the dynamics of snow metrics and provides guidance for water managers to better manage the snowmelt water with different terrain features. [ABSTRACT FROM AUTHOR]

Melt water runoff from seasonal snow in the High Atlas range is an essential water resource in Morocco. However, there are only few meteorological stations in the high elevation areas and therefore it is challenging to estimate the distribution of snow water equivalent (SWE) based only on in situ measurements. In this work we assessed the performance of ERA5 and MERRA-2 climate reanalysis to compute the spatial distribution of SWE in the High Atlas. We forced a distributed snowpack evolution model (SnowModel) with downscaled ERA5 and MERRA-2 data at 200 m spatial resolution. The model was run over the period 1981 to 2019 (37 water years). Model outputs were assessed using observations of river discharge, snow height and MODIS snow-covered area. The results show a good performance for both MERRA-2 and ERA5 in terms of reproducing the snowpack state for the majority of water years, with a lower bias using ERA5 forcing. [ABSTRACT FROM AUTHOR]