Chalmers et al. (2025) Defining the Agricultural Wet Season in Africa Using Soil Moisture From the Soil Moisture Active‐Passive Satellite

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

Identification

• Journal: Geophysical Research Letters
• Year: 2025
• Date: 2025-09-16
• Authors: Christopher Chalmers, Yan Zhang, Jingfeng Xiao, Xing Li, A. J. Rigden
• DOI: 10.1029/2025gl118236

Research Groups

Not available in the provided abstract.

Short Summary

This study estimates root-zone soil moisture across Africa using SMAP satellite data from 2016 to 2023 to redefine the wet season, finding that soil moisture timing correlates more strongly with vegetation timing than precipitation in African croplands and better captures early season rainfall events.

Objective

• To estimate year-to-year variations in seasonal root-zone soil moisture availability across Africa from 2016 to 2023 using SMAP satellite observations and a cumulative anomaly algorithm.
• To compare the timing of soil moisture-based wet season onsets with precipitation-based onsets and their correlation with seasonal vegetation timing, particularly in African croplands and Southern Hemisphere woodlands.

Study Configuration

• Spatial Scale: Africa, with specific analysis on African croplands (over 30% crop cover) and Southern Hemisphere woodlands.
• Temporal Scale: 2016 to 2023 (8 years).

Methodology and Data

• Models used: Cumulative anomaly algorithm for estimating root-zone soil moisture.
• Data sources: Soil Moisture Active Passive (SMAP) satellite observations for root-zone soil moisture; daily precipitation accumulation data (implied for comparison); seasonal vegetation timing data (implied for correlation analysis).

Main Results

• Seasonal soil moisture timing correlates more strongly (p < 0.01) with seasonal vegetation timing than precipitation across African croplands with over 30% crop cover.
• Soil moisture-based onsets effectively capture small early season rainfall events that precipitation-based methods often misclassify as false onsets.
• In Southern Hemisphere woodlands, neither soil moisture nor precipitation fully explains vegetation variability, likely due to deep-rooted trees accessing moisture beyond SMAP's detection limits (approximately the top 5 centimeters of soil).

Contributions

• Highlights soil moisture as a valuable and refined indicator for defining the wet season, particularly in agricultural regions, by accounting for water losses in addition to inputs.
• Demonstrates the utility of SMAP satellite observations for analyzing seasonal soil moisture availability and its impact on vegetation dynamics across Africa.
• Provides a new perspective on the limitations of precipitation-based wet season definitions, especially regarding early season rainfall events and deep-rooted vegetation.

Funding

Not mentioned in the provided abstract.

Citation

@article{Chalmers2025Defining,
  author = {Chalmers, Christopher and Zhang, Yan and Xiao, Jingfeng and Li, Xing and Rigden, A. J.},
  title = {Defining the Agricultural Wet Season in Africa Using Soil Moisture From the Soil Moisture Active‐Passive Satellite},
  journal = {Geophysical Research Letters},
  year = {2025},
  doi = {10.1029/2025gl118236},
  url = {https://doi.org/10.1029/2025gl118236}
}