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001050414 005__ 20260112202639.0
001050414 037__ $$aFZJ-2026-00184
001050414 1001_ $$0P:(DE-Juel1)180553$$aLärm, Lena$$b0$$eCorresponding author$$ufzj
001050414 1112_ $$aAdvancing Critical Zone science, 3rd OZCAR TERENO International Conference$$cParis$$d2025-09-29 - 2025-10-02$$wFrance
001050414 245__ $$aCoupling gprMax and CPlantBox: A Novel Framework to Simulate Electromagnetic Waves Linked to Soil-Root Interactions
001050414 260__ $$c2025
001050414 3367_ $$033$$2EndNote$$aConference Paper
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001050414 3367_ $$0PUB:(DE-HGF)6$$2PUB:(DE-HGF)$$aConference Presentation$$bconf$$mconf$$s1768211503_5404$$xAfter Call
001050414 520__ $$aThe interaction between soil, water, and agricultural crops is crucial in governing the processes that influence plant growth and productivity. As climate change continues to affect agricultural systems, it becomes increasingly essential to understand these processes, particularly to enhance productivity while minimizing environmental impact. Quantifying the effects of climate change and farming practices on crop growth requires an understanding of crop root system dynamics. The opaque nature of soil makes in situ root phenotyping difficult, destructive, and often unrepeatable. Agrogeophysical investigation techniques, such as ground-penetrating radar (GPR), are becoming popular for non-invasively monitoring soil water content and root presence. We used gprMax, open-source finite-difference time-domain electromagnetic (EM) simulation software, to mimic GPR data for agricultural soils and quantify the effect of crop roots on the signal. To incorporate root presence into EM modeling, we calculated the permittivity for a four-phase soil system, including the soil matrix, water, air, and roots. For our first case study, we used field-acquired root distribution data. Trench root counts were measured to derive the root volume fraction, which allowed us to calculate the dielectric permittivity of the four-phase system. We observed that the presence of roots affects the arrival times, amplitudes, and phase of the EM wave. Since the field data were limited to one cultivar, time step, and soil water content during the growing season, we extended our study to use a root model to investigate other influences at various time steps. We coupled gprMax with CPlantBox, a plant growth and soil water simulation model, to simulate the dynamic effects of root growth and water uptake in various scenarios. These scenarios included different crop cultivars, varying soil water conditions, and different growth stages during the vegetation period. The distributions of water content and roots in the soil, as simulated by CPlantBox, can then be converted into a dielectric permittivity distribution and implemented as input for gprMax. With this novel framework, we can investigate the simulated GPR signals further for different crop cultivars, time steps during the growing season, and soil water content conditions. This allows us to quantify their effects on the first arrival times, amplitudes, and phase of the EM wave. This framework has several advantages, including the ability to account for the dynamic effects of root growth and water uptake on soil dielectric properties. The coupled model has been validated against experimental data and shows promising results in simulating the complex interactions between soil, roots, and EM waves.
001050414 536__ $$0G:(DE-HGF)POF4-2173$$a2173 - Agro-biogeosystems: controls, feedbacks and impact (POF4-217)$$cPOF4-217$$fPOF IV$$x0
001050414 536__ $$0G:(BMBF)390732324$$aEXC 2070:  PhenoRob - Robotics and Phenotyping for Sustainable Crop Production (390732324)$$c390732324$$x1
001050414 7001_ $$0P:(DE-Juel1)165987$$aLandl, Magdalena$$b1$$ufzj
001050414 7001_ $$0P:(DE-Juel1)157922$$aSchnepf, Andrea$$b2$$ufzj
001050414 7001_ $$0P:(DE-Juel1)129549$$aVereecken, Harry$$b3$$ufzj
001050414 7001_ $$0P:(DE-Juel1)129483$$aKlotzsche, Anja$$b4$$ufzj
001050414 8564_ $$uhttps://ozcartereno2025.sciencesconf.org/
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