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

Data Acquisition:

The climate data for this study was retrieved from the ESGF MetaGrid. We utilized a multi-model ensemble consisting of four downscaled and bias-adjusted regional climate models from the CORDEX framework: CNRM-CM5, EC-EARTH, IPSL-CM5A-MR, and MPI-ESM-LR. These were complemented by a regionally-configured Weather Research and Forecasting (WRF) model to capture climate data specific to Morocco. The variables extracted include monthly precipitation and minimum/maximum temperatures, which are essential for calculating climate indices with a 12-month lead time to assess long-term drought trends.

Meteorological Drought Assessment:

We employed three distinct indices to characterize atmospheric water deficits:

Standardized Precipitation Index (SPI): Calculated by fitting annual precipitation data to a Gamma distribution to quantify standardized anomalies.

Standardized Precipitation-Evapotranspiration Index (SPEI): Calculated using the Hargreaves method for Potential Evapotranspiration (PET) to integrate temperature-driven moisture demand.

De Martonne Aridity Index: A classic climatological measure used to classify the shift toward regional aridification based on annual temperature and precipitation.

Hydrological Drought Assessment
Future aquifer fluctuations and groundwater stress were evaluated through:

Groundwater Recharge Estimation: Applying established infiltration coefficients to precipitation data across three distinct aquifer zones (Coastal, Central, and Eastern).

Groundwater Recharge Drought Index (GRDI): A standardized metric conceptsually similar to SPI but applied to annual recharge time series. To ensure statistical robustness, recharge data were fitted to six candidate probability distributions (Gamma, Lognormal, Weibull, Extreme Value, Rician, and Nakagami), with the Kolmogorov–Smirnov (K–S) test used to identify the best-fit model for each climate scenario.