Pachón-Acuña et al. (2026) Automated Dynamic Adjustment of Runoff Threshold in Ungauged Basins Using Remote Sensing Data

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Identification

• Journal: Remote Sensing
• Year: 2026
• Date: 2026-02-15
• Authors: Laura D. Pachón-Acuña, Jorge López Rebollo, Junior A. Calvo-Montañez, Susana Del Pozo, Diego González-Aguilera
• DOI: 10.3390/rs18040616

Research Groups

Not explicitly mentioned in the provided text.

Short Summary

This study introduces an automated Google Earth Engine methodology to dynamically adjust the runoff threshold (P0) using satellite soil moisture, land cover, and precipitation data, demonstrating its superior ability to capture real-time soil saturation and adapt to varying moisture conditions compared to static methods.

Objective

• To propose an automated methodology utilising Google Earth Engine to dynamically adjust the runoff threshold (P0) by integrating daily soil moisture data from SMAP L4, land cover from MODIS, and precipitation from GSMaP.

Study Configuration

• Spatial Scale: Regional (two sub-basins within the Guadiana River basin, Spain)
• Temporal Scale: Daily to event-based (daily soil moisture updates, immediate post-rainfall adjustments)

Methodology and Data

• Models used: Google Earth Engine (platform), Soil Conservation Service Curve Number (basis for P0 calculation), historical percentiles (for moisture condition classification)
• Data sources: SMAP L4 (daily soil moisture), MODIS (land cover), GSMaP (precipitation)

Main Results

• Static regulatory P0 values remained invariant (36 mm and 48 mm) in the validated sub-basins.
• The proposed dynamic model revealed significant fluctuations in P0, ranging from over 50 mm in dry periods down to less than 14 mm during saturation.
• The dynamic method effectively captures real-time soil saturation, exhibiting adaptability with reductions in P0 of up to 72% immediately following rainfall events.

Contributions

• Development of an automated, satellite-based methodology using Google Earth Engine for dynamic P0 adjustment.
• Integration of daily SMAP L4 soil moisture, MODIS land cover, and GSMaP precipitation for real-time P0 updates based on historical percentiles, moving beyond static antecedent precipitation proxies.
• Enhanced reliability of hydrological modelling in data-scarce regions by providing a scalable, physically consistent alternative to conventional static runoff potential assessments.

Funding

Not explicitly mentioned in the provided text.

Citation

@article{PachónAcuña2026Automated,
  author = {Pachón-Acuña, Laura D. and Rebollo, Jorge López and Calvo-Montañez, Junior A. and Pozo, Susana Del and González-Aguilera, Diego},
  title = {Automated Dynamic Adjustment of Runoff Threshold in Ungauged Basins Using Remote Sensing Data},
  journal = {Remote Sensing},
  year = {2026},
  doi = {10.3390/rs18040616},
  url = {https://doi.org/10.3390/rs18040616}
}