[HTML][HTML] An accurate snow cover product for the Moroccan Atlas Mountains: Optimization of the MODIS NDSI index threshold and development of snow fraction …

M Bousbaa, A Boudhar, C Kinnard, H Elyoussfi… - International Journal of …, 2024 - Elsevier
In semi-arid Mediterranean areas, a significant proportion of the population living
downstream depends on water resources from snowmelt and precipitation as their main …

Assessment of the impact of climate change on Argan tree in the Mediterranean GIAHS site, Morocco: Current and future distributions

O Hakam, V Ongoma, A Beniaich, B Meskour… - Modeling Earth Systems …, 2024 - Springer
Climate change significantly challenges the sustainability of forest ecosystems, with broad
socio-ecological impacts insufficiently assessed. This study examines one such critical …

Predictive modelling on Spatial–temporal Land Use and Land Cover changes at the Casablanca-Settat Region in Morocco

A Sabri, H Bahi, L Bounoua, M Tahiri, S Tweed… - Modeling Earth Systems …, 2024 - Springer
Urban Population growth coupled with human activities are the main drivers inducing land
use and land cover changes (LU/LCC), which impact earth's landscapes dynamics. In the …

Physics-informed neural networks for enhanced reference evapotranspiration estimation in Morocco: Balancing semi-physical models and deep learning

C El Hachimi, S Belaqziz, S Khabba, A Daccache… - Chemosphere, 2025 - Elsevier
Reference evapotranspiration (ET o) is essential for agricultural water management, crop
productivity, and irrigation systems. The Penman-Monteith (PM) equation is the standard …

Modeling the impact of climate change on wheat yield in Morocco based on stacked ensemble learning

S Eddamiri, EH Bouras, A Amazirh, O Hakam… - Modeling Earth Systems …, 2024 - Springer
Climate change increases the frequency and intensity of extreme events such as droughts,
heat waves, and floods, posing a significant challenge to Morocco's agriculture and food …

[HTML][HTML] Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data

H Elyoussfi, A Boudhar, S Belaqziz, M Bousbaa… - Journal of Hydrology …, 2025 - Elsevier
Study regions The study area encompasses two distinct sub-basins within the High Atlas
Mountains: Oukaimeden in the Rheraya and Tichki in the Mgoun Valley. Study focus The …

Machine Learning Approaches for Predicting Reference Evapotranspiration: A Comparative Study Using Ground and Gridded Climate Data in Fes Region

M Mustapha, M Zineddine, M Gmira… - World Water …, 2025 - Wiley Online Library
Climate data are essential for agricultural planning and water resource management;
however, their availability is limited in numerous regions of Africa. Gridded climate data …

A Hybrid Surrogate Deep Learning Model for Actual Evapotranspiration Prediction

A Aieb, A Jacob, A Liotta… - 2024 Fifth International …, 2024 - ieeexplore.ieee.org
The estimation of hydrological components on a spatiotemporal scale poses a challenge for
researchers as they develop data-driven tools that can be transferred to different regions …

Assessing the performance of Random Forest Regression to predict snow depth using Sentinel-1 SAR and field measurements in a sub-arctic alpine region

T Sigurjónsson - 2024 - diva-portal.org
This study aims to investigate the potential of using SAR images from Sentinel-1 to predict
snow depth in sub-arctic alpine regions by employing Random Forest regression. In addition …