TY - JOUR

T1 - GNSS-R monitoring of soil moisture dynamics in areas of severe drought

T2 - example of Dahra in the Sahelian climatic zone (Senegal)

AU - Ha, Minh-Cuong

AU - Darrozes, José

AU - Llubes, Muriel

AU - Grippa, Manuela

AU - Ramillien, Guillaume

AU - Frappart, Frédéric

AU - Baup, Frédéric

AU - Tagesson, Håkan Torbern

AU - Mougin, Eric

AU - Guiro, Idrissa

AU - Kergoat, Laurent

AU - Nguyen, Huu Duy

AU - Seoane, Lucia

AU - Dufrechou, Gregory

AU - Vu, Phuong-Lan

PY - 2023

Y1 - 2023

N2 - 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.

AB - 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.

KW - GNSS-R

KW - signal-to-noise ratio (SNR)

KW - Interference Pattern Technique (IPT)

KW - phase unwrapping

KW - soil moisture

KW - GPS-INTERFEROMETRIC REFLECTOMETRY

KW - LEAST-SQUARES

KW - SNR DATA

KW - RETRIEVAL

KW - VEGETATION

KW - GRASSLAND

KW - ALGORITHM

KW - WATER

KW - PARAMETERS

KW - INSAR

U2 - 10.1080/22797254.2022.2156931

DO - 10.1080/22797254.2022.2156931

M3 - Journal article

VL - 56

JO - European Journal of Remote Sensing

JF - European Journal of Remote Sensing

SN - 1129-8596

IS - 1

M1 - 2156931

ER -