Laassilia et al. (2026) Integrated Multi-scale Assessment of CHIRPS and PERSIANN-CDR for Meteorological, Agricultural, and Hydrological Drought Monitoring in Semi-arid Environments

Identification

• Journal: Earth Systems and Environment
• Year: 2026
• Date: 2026-03-21
• Authors: Oussama Laassilia, Soumia Saghiry, Hadri Abdessamad, Nabil Habitou, Abdelrhani Ajraoui, Amine Soufi, Khlood Ghalib Alrasheedi, Mahesh Bade
• DOI: 10.1007/s41748-026-01120-8

Research Groups

• Laboratory of Engineering Sciences for Energy (LabSIPE), National School of Applied Sciences, Chouaib Doukkali University, El Jadida, Morocco
• Process Engineering and Environment Laboratory (LGPE), Faculty of Sciences and Techniques of Mohammedia, Hassan II University of Casablanca, Casablanca, Morocco
• International Water Research Institute, Mohamed VI Polytechnic University, Bengurir, Morocco
• Hydraulic Systems Analysis Laboratory, Department of Civil Engineering, Mohammadia School of Engineering, Mohammed V University, Rabat, Morocco
• Laboratory of Geosciences and Natural Resources, Faculty of Sciences, Ibn Tofail University, Kenitra, Morocco
• Laboratory of Applied Geophysics, Geotechnics, Geological Engineering, and Environmental Studies, Mohammadia School of Engineers, Mohammed V University, Rabat, Morocco
• School of Earth and Planetary Sciences (EPS), Spatial Sciences Discipline, Curtin University, Perth, Australia
• Department of Environmental Science, Baylor University, Waco, TX, USA

Short Summary

This paper evaluates two satellite precipitation products (CHIRPS and PERSIANN-CDR) for multi-scale meteorological, agricultural, and hydrological drought monitoring in the semi-arid Moulouya Basin, Morocco. The study found that CHIRPS generally outperforms PERSIANN in accuracy and event-scale detection, while both products effectively capture observed drought patterns and reveal a progressive aridification trend in the region.

Objective

• To comprehensively assess the performance of CHIRPS and PERSIANN-CDR satellite precipitation products for multi-scale meteorological, agricultural, and hydrological drought monitoring in the semi-arid Moulouya Basin, Morocco, and to characterize recent drought intensification and long-term aridification trends.

Study Configuration

• Spatial Scale: Moulouya Basin, northeastern Morocco, covering approximately 55,000 km². Data resolutions: CHIRPS v2.0 at 0.05° (approximately 5 km), PERSIANN-CDR at 0.25° (approximately 25 km), ERA5-Land at 0.1° (approximately 10 km). Point observations from 28 rain gauge stations and 4 meteorological stations.
• Temporal Scale:
  • Precipitation data: CHIRPS (1981–present), PERSIANN-CDR (1983–present).
  • Temperature data (ERA5-Land): Hourly estimates, used for monthly potential evapotranspiration (PET).
  • Rain gauge data: Up to August 2024, with varying start dates.
  • Agricultural yield data: 2000–2025.
  • Streamflow data: 1966–2023 (Melg El Ouidane station).
  • Drought analysis period: 1983–2023 (SPEI, trends), 2019–2023 (specific event), 2000–2024 (SYRS).

Methodology and Data

• Models used:
  • Standardized Precipitation Evapotranspiration Index (SPEI) at 3- and 12-month scales.
  • Hargreaves–Samani equation for Potential Evapotranspiration (PET).
  • Run Theory for drought event characterization (duration, intensity, severity).
  • Standardized Yield Residual Series (SYRS) with quadratic polynomial regression for detrending.
  • Standardized Streamflow Index (SSI) at 3- and 12-month scales.
  • Mann–Kendall test (modified for autocorrelation) and Sen’s Slope Estimator for trend analysis.
  • Statistical metrics: Correlation Coefficient (CC), Root Mean Square Error (RMSE), Mean Error (ME), Relative Bias (RBIAS), Nash–Sutcliffe Efficiency (NSE), Coefficient of Determination (R²), p-value, Spearman rank correlation (ρ).
• Data sources:
  • Satellite precipitation: CHIRPS v2.0, PERSIANN-CDR.
  • Reanalysis temperature: ERA5-Land.
  • Ground observations: 28 daily rain gauge stations, 4 meteorological stations for temperature (Melloulou Guercif, Zaida, Laksob, Outat El Haj).
  • Agricultural data: Annual cereal yield data (soft wheat, durum wheat, barley) for 2000–2025, differentiated by irrigation zones (Large-scale irrigation, Small/medium-scale irrigation, Rainfed agriculture).
  • Hydrological data: Monthly inflow data (in million cubic meters) for Melg El Ouidane station (1966–2023).

Main Results

• CHIRPS generally outperformed PERSIANN-CDR in precipitation accuracy (RMSE 50–70% lower) and bias balance (–1% to +107% vs. 85–200% overestimation for PERSIANN-CDR), particularly at longer accumulation periods and in rainfed areas.
• SPEI derived from both SPPs showed substantially improved performance, with SPEI-12 exhibiting strong agreement with observed drought patterns (CC: 0.80–0.97; NSE: 0.57–0.94). CHIRPS-derived SPEI generally outperformed PERSIANN-CDR.
• The 2019–2023 drought was clearly captured; lowering the SPEI detection threshold from -1.0 to -0.7 significantly improved spatial-temporal coherence in complex mountainous terrain.
• Agricultural impacts showed highest SPEI-SYRS correlations in small/medium-scale irrigation and rainfed agriculture zones (|r̄| = 0.62), with SPEI-12 for June being the most effective predictor of cereal yields (R² = 0.54–0.56 in SMSI; 0.34–0.36 in RA).
• Strong hydroclimatic coherence between SPEI and SSI was observed, with correlations strengthening at longer timescales (r = 0.671 for SPEI12/SSI12 vs. 0.604 for SPEI3/SSI3).
• Trend analysis revealed a quasi-generalized progressive aridification across the basin, more pronounced for SPEI-12 (Sen’s slopes ≈ −0.003 to −0.009 month⁻¹) than for SPEI-3 (≈ −0.001 to −0.005 month⁻¹), indicating intensifying long-term droughts.

Contributions

• Integrated evaluation of CHIRPS and PERSIANN-CDR across meteorological, agricultural, and hydrological drought domains within a unified operational framework.
• System-specific agricultural drought analysis differentiating large-scale irrigation, small/medium-scale irrigation, and rainfed agriculture, enabling targeted adaptation strategies.
• Threshold-adjusted drought event characterization (using -0.7 instead of -1.0) to address artificial event fragmentation in topographically complex terrain.
• Demonstration of complementary satellite product strengths: CHIRPS for event-scale precision and bias balance, PERSIANN-CDR for cumulative anomaly sensitivity and long-term trends.
• Comprehensive documentation of recent drought intensification (2019–2023) and long-term aridification trends in the Moulouya Basin, establishing a replicable operational framework for integrated water-agriculture management in Mediterranean semi-arid regions.

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Citation

@article{Laassilia2026Integrated,
  author = {Laassilia, Oussama and Saghiry, Soumia and Abdessamad, Hadri and Habitou, Nabil and Ajraoui, Abdelrhani and Soufi, Amine and Alrasheedi, Khlood Ghalib and Bade, Mahesh},
  title = {Integrated Multi-scale Assessment of CHIRPS and PERSIANN-CDR for Meteorological, Agricultural, and Hydrological Drought Monitoring in Semi-arid Environments},
  journal = {Earth Systems and Environment},
  year = {2026},
  doi = {10.1007/s41748-026-01120-8},
  url = {https://doi.org/10.1007/s41748-026-01120-8}
}