Defining the Agricultural Wet Season in Africa Using Soil Moisture From the Soil Moisture Active‐Passive Satellite

Abstract The wet season is commonly defined based on daily precipitation accumulation, which represents water inputs but does not account for losses from evaporation, infiltration, and runoff. Here, we estimate root‐zone soil moisture using observations from the Soil Moisture Active Passive (SMAP) satellite to capture year‐to‐year variations in seasonal soil moisture availability across Africa from 2016 to 2023 using a cumulative anomaly algorithm. Our analysis shows that seasonal soil moisture timing correlates more strongly (p 0.01) with seasonal vegetation timing than precipitation across African croplands with over 30% crop cover. Additionally, soil moisture‐based onsets capture small early season rainfall events that precipitation‐based methods misclassify as false onsets. However, 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. These findings highlight soil moisture as a valuable indicator for refining wet season definitions, particularly in agricultural regions.

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Publication Details

Journal
Geophysical Research Letters
Published
2025-09-16
DOI
https://doi.org/10.1029/2025gl118236
Primary Topic
Soil Moisture and Remote Sensing
Type
article
Field-Weighted Citation Impact
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article

Defining the Agricultural Wet Season in Africa Using Soil Moisture From the Soil Moisture Active‐Passive Satellite

Jingfeng Xiao, Yan Zhang, A. J. Rigden, Xing Li et al.
Geophysical Research Letters
Soil Moisture and Remote Sensing
article

Defining the Agricultural Wet Season in Africa Using Soil Moisture From the Soil Moisture Active‐Passive Satellite

Jingfeng Xiao, Yan Zhang, A. J. Rigden, Xing Li, Christopher Chalmers
article en

Abstract

Abstract The wet season is commonly defined based on daily precipitation accumulation, which represents water inputs but does not account for losses from evaporation, infiltration, and runoff. Here, we estimate root‐zone soil moisture using observations from the Soil Moisture Active Passive (SMAP) satellite to capture year‐to‐year variations in seasonal soil moisture availability across Africa from 2016 to 2023 using a cumulative anomaly algorithm. Our analysis shows that seasonal soil moisture timing correlates more strongly (p 0.01) with seasonal vegetation timing than precipitation across African croplands with over 30% crop cover. Additionally, soil moisture‐based onsets capture small early season rainfall events that precipitation‐based methods misclassify as false onsets. However, 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. These findings highlight soil moisture as a valuable indicator for refining wet season definitions, particularly in agricultural regions.

Geophysical Research LettersVol. 52(18)
Sun Yat-sen University (CN), University of New Hampshire (US), University of California, Irvine (US)
Openalex Percentile: Top 77%
Soil Moisture and Remote Sensing
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