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<p>Effective drought monitoring is essential for sustainable water management and agricultural planning in semi-arid basins. This paper evaluates the performance of two satellite precipitation products (SPPs), CHIRPS and PERSIANN-CDR, for meteorological, agricultural, and hydrological drought assessment. The study focuses on the Moulouya Basin, a climatically heterogeneous and climate change–prone system located in northern Morocco. Precipitation accuracy was first examined against 28 observed rain gauge data. SPEI values at 3- and 12-month scales were computed from both SPPs and compared with gauge-based SPEI. Drought characteristics (duration, intensity, severity) were analyzed at pixel and basin scales, with a focus on the 2019–2023 event. Agricultural impacts were assessed using the Standardized Yield Residual Series (SYRS), and hydrological consistency through the Standardized Streamflow Index (SSI). Trend analyses were performed using the Mann–Kendall test and Sen’s slope estimator. Results show that CHIRPS generally outperforms PERSIANN in accuracy and bias balance, particularly at longer accumulation periods and in rainfed areas, while PERSIANN tends to overestimate precipitation in mountainous zones but performs better in irrigated systems for long-term trends. SPEI-based indices exhibited strong agreement with observed drought patterns (<i>r</i> &gt; 0.85) and effectively reflected agricultural and hydrological impacts. The 2019–2023 drought was clearly captured, with threshold adjustments enhancing spatial–temporal coherence in complex terrain. Trend analysis revealed progressive aridification, more pronounced at the 12-month scale and consistent across both SPPs and gauge observations. This integrated multi-index framework (meteorological-agricultural-hydrological) demonstrates that CHIRPS excels in event-scale detection and bias balance, while PERSIANN-CDR shows superior sensitivity to long-term cumulative anomalies. The system-specific agricultural analysis reveals differential climate sensitivity across irrigation regimes (R² = 0.19–0.56), enabling targeted adaptation strategies. The study provides the first comprehensive multi-dimensional drought characterization for the Moulouya Basin, establishing a replicable operational framework for integrated water-agriculture management under increasing drought severity in Mediterranean semi-arid regions.</p> Graphical Abstract <p></p> <p>The graphical abstract illustrates an integrated framework for multi-dimensional drought monitoring in the Moulouya Basin, located in northern Morocco, using satellite-based precipitation products. CHIRPS and PERSIANN-CDR precipitation datasets are evaluated against 28 rain gauge stations and combined with ERA5-Land temperature data to compute the Standardized Precipitation–Evapotranspiration Index (SPEI) at 3- and 12-month timescales. Meteorological drought signals are propagated to agricultural and hydrological systems using the Standardized Yield Residual Series (SYRS), based on long-term crop yield statistics (2000–2024), and the Standardized Streamflow Index (SSI), derived from observed streamflow records at Melg El Ouidane station (1983–2023).The framework enables the characterization of drought events in terms of duration, intensity, and severity at both pixel and basin scales, with particular emphasis on the extreme 2019–2023 drought episode. Results highlight the superior performance of CHIRPS for event-scale drought detection and bias balance, especially in rainfed areas, while PERSIANN-CDR shows higher sensitivity to long-term cumulative anomalies but tends to overestimate precipitation in mountainous regions. Strong coherence between SPEI, SYRS, and SSI confirms the ability of satellite-derived indices to capture agricultural and hydrological drought impacts.</p>

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Integrated Multi-scale Assessment of CHIRPS and PERSIANN-CDR for Meteorological, Agricultural, and Hydrological Drought Monitoring in Semi-arid Environments

  • 期刊论文

  • 发表日期：

    2026年3月21日

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  • Oussama Laassilia,
  • Soumia Saghiry,
  • Hadri Abdessamad,
  • Nabil Habitou,
  • Abdelrhani Ajraoui,
  • Amine Soufi,
  • Khlood Ghalib Alrasheedi,
  • Mahesh Bade

摘要

Effective drought monitoring is essential for sustainable water management and agricultural planning in semi-arid basins. This paper evaluates the performance of two satellite precipitation products (SPPs), CHIRPS and PERSIANN-CDR, for meteorological, agricultural, and hydrological drought assessment. The study focuses on the Moulouya Basin, a climatically heterogeneous and climate change–prone system located in northern Morocco. Precipitation accuracy was first examined against 28 observed rain gauge data. SPEI values at 3- and 12-month scales were computed from both SPPs and compared with gauge-based SPEI. Drought characteristics (duration, intensity, severity) were analyzed at pixel and basin scales, with a focus on the 2019–2023 event. Agricultural impacts were assessed using the Standardized Yield Residual Series (SYRS), and hydrological consistency through the Standardized Streamflow Index (SSI). Trend analyses were performed using the Mann–Kendall test and Sen’s slope estimator. Results show that CHIRPS generally outperforms PERSIANN in accuracy and bias balance, particularly at longer accumulation periods and in rainfed areas, while PERSIANN tends to overestimate precipitation in mountainous zones but performs better in irrigated systems for long-term trends. SPEI-based indices exhibited strong agreement with observed drought patterns (r > 0.85) and effectively reflected agricultural and hydrological impacts. The 2019–2023 drought was clearly captured, with threshold adjustments enhancing spatial–temporal coherence in complex terrain. Trend analysis revealed progressive aridification, more pronounced at the 12-month scale and consistent across both SPPs and gauge observations. This integrated multi-index framework (meteorological-agricultural-hydrological) demonstrates that CHIRPS excels in event-scale detection and bias balance, while PERSIANN-CDR shows superior sensitivity to long-term cumulative anomalies. The system-specific agricultural analysis reveals differential climate sensitivity across irrigation regimes (R² = 0.19–0.56), enabling targeted adaptation strategies. The study provides the first comprehensive multi-dimensional drought characterization for the Moulouya Basin, establishing a replicable operational framework for integrated water-agriculture management under increasing drought severity in Mediterranean semi-arid regions.

Graphical Abstract

The graphical abstract illustrates an integrated framework for multi-dimensional drought monitoring in the Moulouya Basin, located in northern Morocco, using satellite-based precipitation products. CHIRPS and PERSIANN-CDR precipitation datasets are evaluated against 28 rain gauge stations and combined with ERA5-Land temperature data to compute the Standardized Precipitation–Evapotranspiration Index (SPEI) at 3- and 12-month timescales. Meteorological drought signals are propagated to agricultural and hydrological systems using the Standardized Yield Residual Series (SYRS), based on long-term crop yield statistics (2000–2024), and the Standardized Streamflow Index (SSI), derived from observed streamflow records at Melg El Ouidane station (1983–2023).The framework enables the characterization of drought events in terms of duration, intensity, and severity at both pixel and basin scales, with particular emphasis on the extreme 2019–2023 drought episode. Results highlight the superior performance of CHIRPS for event-scale drought detection and bias balance, especially in rainfed areas, while PERSIANN-CDR shows higher sensitivity to long-term cumulative anomalies but tends to overestimate precipitation in mountainous regions. Strong coherence between SPEI, SYRS, and SSI confirms the ability of satellite-derived indices to capture agricultural and hydrological drought impacts.