Thu Oct 08, F. Flechtner
• Sorted by Date • Sorted by Last Name of First Author •
Yap, Loudi, Kusche, Jürgen, Oloruntoba, Bamidele, Gerdener, Helena, and Hendricks Franssen, Harrie–Jan, 2026. Retrieving root–zone soil moisture from land surface modelling and GRACE/–FO and validating its dynamics with in–situ data over West Africa. Hydrology and Earth System Sciences, 30(15):5023–5047, doi:10.5194/hess-30-5023-2026.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2026HESS...30.5023Y,
author = {{Yap}, Loudi and {Kusche}, J{\"u}rgen and {Oloruntoba}, Bamidele and {Gerdener}, Helena and {Hendricks Franssen}, Harrie-Jan},
title = "{Retrieving root-zone soil moisture from land surface modelling and GRACE/-FO and validating its dynamics with in-situ data over West Africa}",
journal = {Hydrology and Earth System Sciences},
year = 2026,
month = aug,
volume = {30},
number = {15},
pages = {5023-5047},
abstract = "{Rainfall variability in West Africa, driven by the West African Monsoon,
poses significant challenges to agricultural productivity and
livelihoods. In this context, understanding root-zone soil
moisture (RZSM) dynamics is crucial since it serves as the
primary water source for crops. While surface soil moisture
(SSM) has been widely studied, research on RZSM remains limited.
This study investigates RZSM dynamics across West Africa from
2003 to 2019 using multiple satellite-derived and model-based
datasets, including ESA CCI v0.81, GLWS2.0, WaterGAP, CLM5.0,
and in-situ observations. Results indicate that ESA CCI exhibits
the strongest temporal and spatial alignment with ground
measurements, whereas CLM5.0 and GLWS2.0 effectively capture
latitudinal soil moisture (SM) gradients associated with
climatic zones. A novel application of an analytical solution to
Richards' equation was employed to translate surface moisture
signals to deeper soil layers, demonstrating GLWS2.0's superior
ability to reproduce seasonal patterns at various depths,
notably in Benin and Niger. Despite challenges posed by sparse
in-situ data and vegetation-induced signal attenuation, the
study highlights the significant benefits of GRACE/-FO data
assimilation in enhancing model accuracy. The proposed depth-
projection methodology improves the vertical representation of
SM, offering new insights into the dynamics of surface and
subsurface water storage. These findings have important
implications for agricultural forecasting, sustainable water
resource management, and climate adaptation strategies in
regions where accurate SM data are essential for resilience
planning.}",
doi = {10.5194/hess-30-5023-2026},
adsurl = {https://ui.adsabs.harvard.edu/abs/2026HESS...30.5023Y},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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Thu Oct 08, F. Flechtner