GHAZZAR (2025) Hydro-climatic Projections and Computational Framework for the Maamora Aquifer: SPI, SPEI, GRDI, and De Martonne Aridity Index Datasets using CORDEX and WRF

Identification

• Journal: Mendeley Data
• Year: 2025
• Date: 2025-12-30
• Authors: Ayoub GHAZZAR
• DOI: 10.17632/s7zs8rhvtn

Research Groups

• Universite Mohammed V de Rabat
• Ecole Mohammadia d'Ingenieurs

Short Summary

This paper presents a computational framework and dataset for hydro-climatic projections and drought assessment in the Maamora Aquifer, Morocco, utilizing CORDEX and WRF models to generate future meteorological and hydrological drought indices under RCP4.5 and RCP8.5 scenarios.

Objective

• To provide a computational framework and datasets for assessing future meteorological and hydrological drought conditions in the Maamora Aquifer, Morocco, using multiple climate indices derived from CORDEX and WRF model projections under different Representative Concentration Pathway (RCP) scenarios.

Study Configuration

• Spatial Scale: Maamora Aquifer, Morocco, with specific consideration for its Coastal, Central, and Eastern zones.
• Temporal Scale: Projections for future climate scenarios (RCP4.5 and RCP8.5), with climate indices calculated using a 12-month lead time to assess long-term drought trends.

Methodology and Data

• Models used:
  • CORDEX multi-model ensemble (CNRM-CM5, EC-EARTH, IPSL-CM5A-MR, MPI-ESM-LR)
  • Regionally-configured Weather Research and Forecasting (WRF) model
• Data sources:
  • ESGF MetaGrid (for raw CORDEX and WRF climate data)
  • Derived datasets: Monthly precipitation, minimum and maximum temperatures.
  • Calculated indices: Standardized Precipitation Index (SPI), Standardized Precipitation-Evapotranspiration Index (SPEI), De Martonne Aridity Index, Groundwater Recharge Drought Index (GRDI).
  • Groundwater recharge estimated using zone-specific infiltration coefficients.
  • Statistical fitting of recharge data to six probability distributions (Gamma, Lognormal, Weibull, Extreme Value, Rician, Nakagami) with Kolmogorov–Smirnov (K–S) test for best-fit selection.

Main Results

• The study provides processed datasets, calculation templates, and computational scripts (MATLAB, R-studio, Excel) for evaluating climate-driven drought in the Maamora Aquifer.
• It offers hydro-climatic projections, including SPI, SPEI, GRDI, and De Martonne Aridity Index datasets, under RCP4.5 and RCP8.5 scenarios.
• The framework includes robust methods for meteorological drought assessment (SPI with Gamma distribution fitting, SPEI using the Hargreaves method for potential evapotranspiration, and the De Martonne Aridity Index) and hydrological drought assessment (groundwater recharge estimation and GRDI with statistically validated distribution fitting).

Contributions

• Development of a comprehensive and reproducible computational framework and associated datasets for multi-index drought assessment specifically tailored to the Maamora Aquifer, Morocco.
• Integration of a multi-model regional climate ensemble (CORDEX and WRF) with a diverse set of meteorological and hydrological drought indices.
• Provision of open-source scripts and templates, enhancing the transparency, reproducibility, and applicability of the methodology for future hydro-climatic studies in the region.
• Generation of future drought projections under RCP4.5 and RCP8.5 scenarios, offering critical data for informed water resource management and climate change adaptation strategies.

Funding

• Not explicitly mentioned in the provided paper text.

Citation

@article{GHAZZAR2025Hydroclimatic,
  author = {GHAZZAR, Ayoub},
  title = {Hydro-climatic Projections and Computational Framework for the Maamora Aquifer: SPI, SPEI, GRDI, and De Martonne Aridity Index Datasets using CORDEX and WRF},
  journal = {Mendeley Data},
  year = {2025},
  doi = {10.17632/s7zs8rhvtn},
  url = {https://doi.org/10.17632/s7zs8rhvtn}
}