Dari et al. (2020) Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Remote Sensing
• Year: 2020
• Authors: Jacopo Dari, Luca Brocca, Pere Quintana Seguí, Maria‐José Escorihuela, Vivien Stefan, Renato Morbidelli
• DOI: 10.3390/rs12162593

Research Groups

Not explicitly stated in the paper text, but the study utilizes data and models associated with the European Space Agency (ESA, SMOS) and NASA (SMAP), and the Food and Agriculture Organization (FAO).

Short Summary

This study proposes a methodology using the SM2RAIN algorithm, enhanced with FAO evapotranspiration modeling, to estimate high-resolution (1 km) irrigation amounts in a Spanish pilot area using downscaled SMAP and SMOS soil moisture data. The method successfully reproduced the magnitude and timing of irrigation events in most pilot districts, highlighting the critical role of accurate evapotranspiration modeling.

Objective

• To propose and validate a methodology utilizing remotely sensed soil moisture and an improved SM2RAIN algorithm to accurately estimate the magnitude, spatial distribution, and timing of anthropogenic irrigation water consumption at high resolution (1 km).

Study Configuration

• Spatial Scale: Pilot area in Spain; high resolution (1 km).
• Temporal Scale: SMAP experiment: January 2016 to September 2017. SMOS experiment: extended back to 2011.

Methodology and Data

• Models used: SM2RAIN algorithm (modified to improve evapotranspiration term), DISPATCH (DISaggregation based on Physical And Theoretical scale CHange), FAO model (used for crop evapotranspiration improvement).
• Data sources: Remotely sensed soil moisture; DISPATCH downscaled SMAP (Soil Moisture Active Passive) at 1 km; DISPATCH downscaled SMOS (Soil Moisture and Ocean Salinity) at 1 km.

Main Results

• The proposed method successfully reproduced the magnitudes of the actual irrigation amounts in four of the five pilot irrigation districts for both the SMAP and SMOS experiments.
• The SMAP experiment provided satisfactory results in representing both the spatial distribution and the timing of the irrigation events.
• Investigation into the SM2RAIN algorithm terms demonstrated that the correct representation of the evapotranspiration process is the leading factor in accurately determining the amount of water entering the soil as irrigation.

Contributions

Provides a novel methodology for estimating high-resolution (1 km) irrigation amounts globally by integrating remotely sensed soil moisture (SMAP/SMOS) with an improved, physically-based hydrological algorithm (SM2RAIN), thereby addressing the worldwide lack of detailed information regarding anthropogenic water consumption for irrigation.

Funding

Not explicitly stated in the paper text.

Citation

@article{Dari2020Exploiting,
  author = {Dari, Jacopo and Brocca, Luca and Quintana‐Seguí, Pere and Escorihuela, Maria‐José and Stefan, Vivien and Morbidelli, Renato},
  title = {Exploiting High-Resolution Remote Sensing Soil Moisture to Estimate Irrigation Water Amounts over a Mediterranean Region},
  journal = {Remote Sensing},
  year = {2020},
  doi = {10.3390/rs12162593},
  url = {https://doi.org/10.3390/rs12162593}
}

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