Alcalde et al. (2025) Remote Sensing Standardized Soil Moisture Index for Drought Monitoring: A Case Study in the Ebro Basin

Identification

• Journal: Remote Sensing
• Year: 2025
• Date: 2025-12-03
• Authors: Guillem Sánchez Alcalde, Maria‐José Escorihuela
• DOI: 10.3390/rs17233916

Research Groups

• isardSAT, Barcelona, Spain

Short Summary

This study evaluates the satellite-derived Standardized Soil Moisture Index (SSI) for drought monitoring across various timescales in the Ebro Basin, demonstrating its robustness and superior spatial resolution compared to precipitation-based indices, and its capability to monitor hydrological droughts without relying on in situ measurements.

Objective

• To evaluate the remote sensing-derived Standardized Soil Moisture Index (SSI) as a versatile tool for monitoring meteorological, agricultural, and hydrological droughts across multiple timescales.
• To analyze the temporal relationship between satellite-derived SSI and the Standardized Precipitation Index (SPI) across different integration timescales and lags.
• To demonstrate the applicability of satellite-derived SSI for characterizing hydrological droughts and its potential as a high-resolution, globally applicable drought indicator in data-scarce regions.

Study Configuration

• Spatial Scale: Ebro Basin, Spain (over 85,000 km²); 1 km spatial resolution for SSI and gridded SPI.
• Temporal Scale: June 2010 to May 2023 (13-year record); monthly data for indices, with integration times from 1 to 24 months.

Methodology and Data

• Models used:
  • DISPATCh (DISaggregation based on Physical And Theoretical scale Change) algorithm for soil moisture downscaling.
  • Beta distribution function for fitting monthly soil moisture data to calculate SSI.
  • Gamma distribution function for fitting precipitation data to calculate SPI.
• Data sources:
  • Satellite Soil Moisture: SMOS (Soil Moisture and Ocean Salinity) Level-2 soil moisture product (version 700, 40 km resolution), disaggregated to 1 km.
  • Optical/Thermal Data for Downscaling: MODIS (MODerature resolution Imaging Spectroradiometer) 1 km products (MOD11A1, MYD11A1 for Land Surface Temperature; MOD13A2 for Normalized Difference Vegetation Index).
  • In Situ Precipitation: Monthly precipitation data from 239 meteorological stations of the SAIH Ebro (Sistema Automático de Información Hidrológica del Ebro) network.
  • Gridded Precipitation: LCSC (Laboratorio de Climatología y Servicios Climáticos) gridded SPI dataset (1.1 km spatial resolution, weekly frequency, aggregated to monthly), calibrated using AEMET and SIAR station data.
  • Land Cover: ECOCLIMAP Second Generation map (300 m spatial resolution).

Main Results

• The satellite-derived SSI showed good correlations (R > 0.6) with the in situ SPI across all integration times (1 to 24 months).
• SSI consistently achieved the highest correlation when compared to SPI integrated over an additional month (e.g., SSI-n vs. SPI-(n+1)), reflecting soil moisture's inherent inertia. Correlations ranged from 0.618 to 0.667 for these optimal comparisons.
• Bias between SSI and SPI was negligible (generally within ±0.01), indicating comparable drought severity values. Slope values were consistently below 1 (0.613 to 0.666), suggesting SSI responds slower than SPI to high values.
• The 1 km disaggregated SSI provided enhanced spatial detail and granularity, capturing localized hydrological dynamics such as snowmelt in the Pyrenees and irrigation practices in the Ebro Delta, which are not fully represented by precipitation-based indices.
• The SSI successfully identified three major hydrological droughts in the Ebro basin since 2010 (2011–2012, 2017–2018, and starting in 2022).
• Vegetation density showed a slight influence on correlations, with higher correlations in bare soils (R = 0.68 ± 0.01 for 0.2 < NDVI ≤ 0.4) and lower in dense vegetation (R = 0.58 ± 0.03 for 0.6 < NDVI ≤ 0.8), but no dominant systematic control by vegetation type was observed.

Contributions

• This study extends the utility of satellite-derived SSI beyond short-term drought monitoring to effectively characterize long-term hydrological droughts, a key novelty.
• It demonstrates that SSI can serve as a robust and versatile drought indicator with high spatial resolution (1 km) and global applicability, as it relies solely on satellite observations and is not site-calibrated, making it valuable for data-scarce regions.
• The research provides a thorough analysis of the temporal relationship between remote sensing-derived SSI and SPI, highlighting the optimal integration time lag for soil moisture's inertia.

Funding

• European Union’s Next Generation EU program (Investigo grant: 2021-C23.I01.P03.S0020-0000007) awarded to Guillem Sánchez.

Citation

@article{Alcalde2025Remote,
  author = {Alcalde, Guillem Sánchez and Escorihuela, Maria‐José},
  title = {Remote Sensing Standardized Soil Moisture Index for Drought Monitoring: A Case Study in the Ebro Basin},
  journal = {Remote Sensing},
  year = {2025},
  doi = {10.3390/rs17233916},
  url = {https://doi.org/10.3390/rs17233916}
}

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