@article{SisLab4815, volume = {0}, number = {0}, month = {December}, author = {Minh-Cuong Ha and Jos{\'e} Darrozes and Muriel Llubes and Manuela Grippa and Guillaume Ramillien and Fr{\'e}d{\'e}ric Frappart and Fr{\'e}d{\'e}ric Baup and H{\r a}kan Torbern Tagesson and Eric Mougin and Idrissa Guiro and Laurent Kergoat and Huu Duy Nguyen and Lucia Seoane and Gregory Dufrechou and Phuong-Lan Vu}, title = {GNSS-R monitoring of soil moisture dynamics in areas of severe drought: example of Dahra in the Sahelian climatic zone (Senegal)}, publisher = {Taylor \& Francis}, year = {2022}, journal = {European Journal of Remote Sensing}, doi = {https://doi.org/10.1080/22797254.2022.2156931}, pages = {1--19}, url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4815/}, abstract = {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 {\texttt{\char126}}3\% to {\texttt{\char126}}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.} }