4.3 Article

GNSS-R monitoring of soil moisture dynamics in areas of severe drought: example of Dahra in the Sahelian climatic zone (Senegal)

Journal

EUROPEAN JOURNAL OF REMOTE SENSING
Volume -, Issue -, Pages -

Publisher

TAYLOR & FRANCIS LTD
DOI: 10.1080/22797254.2022.2156931

Keywords

GNSS-R; signal-to-noise ratio (SNR); Interference Pattern Technique (IPT); phase unwrapping; soil moisture

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Funding

  1. Vietnam National Foundation for Science and Technology Development (NAFOSTED) [105.08-2020.17]

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With population growth, water resources will increase significantly in the coming decades. Accurate soil moisture monitoring is essential for optimizing agricultural water use. Recent GNSS-R studies use navigation signals emitted by the GNSS constellations to track changes in soil moisture. However, during drought periods, the penetration of GNSS waves into the soil reduces the accuracy of surface moisture measurements.
With population growth, water will increase in the following decades tremendously. The optimization of water allocation for agriculture requires accurate soil moisture (SM) monitoring. Recent Global Navigation Satellite System Reflectometry (GNSS-R) studies take advantage of continuously emitted navigation signals by the Global Navigation Satellite System (GNSS) constellations to retrieve spatiotemporal soil moisture changes for soil with high clay content. It presents the advantage of sensing a whole surface around a reference GNSS antenna. This article focuses on sandy SM monitoring in the driest condition observed in the study field of Dahra, (Senegal). The area consists of 95% sand and in situ volumetric soil moisture (VSM) range from similar to 3% to similar to 5% durinf the dry to the rainy season. Unfortunately, the GNSS signals' waves penetrated deep into the soil during the dry period and strongly reduced the accuracy of GNSS reflectometry (GNSS-R) surface moisture measurements. However, we obtain VSM estimate at low/medium penetration depth. The correlation reaches 0.9 with VSM error lower than 0.16% for the 5-10-cm-depth probes and achieves excellent temporal monitoring to benefit from the antenna heights directly correlated to spatial resolution. The SM measurement models in our research are potentially valuable tools that contribute to the planning of sustainable agriculture, especially in countries often affected by drought.

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