Massari et al. (2026) Detecting Irrigation From Spectral Differences Between Satellite and Modeled Soil Moisture Across the Contiguous United States

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Identification

• Journal: Geophysical Research Letters
• Year: 2026
• Date: 2026-09-08
• Authors: Christian Massari, Sara Modanesi, Zdenko Heyvaert, Louise Busschaert, Pierre Laluet, Martina Natali, Jacopo Dari, Luca Brocca, Wouter Dorigo, Clément Albergel, Gabriëlle De Lannoy
• DOI: 10.1029/2026gl123183

Research Groups

Not specified in the provided text.

Short Summary

The study presents a wavelet-based method to detect irrigation by analyzing spectral differences between Noah-MP model simulations and SMOS satellite soil-moisture observations across the contiguous United States.

Objective

• To develop a scalable framework for detecting irrigation and improving its representation in Earth system models by leveraging land-surface water-balance dynamics rather than indirect proxies.

Study Configuration

• Spatial Scale: Contiguous United States (CONUS).
• Temporal Scale: Seasonal to sub-seasonal variability, specifically focusing on the 6–18-month spectral band.

Methodology and Data

• Models used: Noah-MP (land surface model).
• Data sources: SMOS (Soil Moisture and Ocean Salinity) satellite observations.

Main Results

• Irrigation detection is achievable by identifying spectral differences in soil-moisture time series between "irrigation-off" model simulations and satellite observations, particularly within the 6–18-month band.
• The soil-moisture-based irrigation classification complements existing high-resolution optical datasets while remaining consistent with the coarse-scale resolution of SMOS data.
• Incorporating this detection method into Noah-MP simulations leads to an improved spatial distribution of simulated irrigation water use.

Contributions

• Introduces a novel, scalable approach to irrigation detection based on observed water-balance dynamics.
• Provides a method to refine the representation of irrigation within Earth system models, reducing reliance on indirect proxies or static inventories.

Funding

Not specified in the provided text.

Citation

@article{Massari2026Detecting,
  author = {Massari, Christian and Modanesi, Sara and Heyvaert, Zdenko and Busschaert, Louise and Laluet, Pierre and Natali, Martina and Dari, Jacopo and Brocca, Luca and Dorigo, Wouter and Albergel, Clément and Lannoy, Gabriëlle De},
  title = {Detecting Irrigation From Spectral Differences Between Satellite and Modeled Soil Moisture Across the Contiguous United States},
  journal = {Geophysical Research Letters},
  year = {2026},
  doi = {10.1029/2026gl123183},
  url = {https://doi.org/10.1029/2026gl123183}
}