Monitoring Soil Water Content Using Time‐Lapse Horizontal Borehole GPR Data at the Field‐Plot Scale

Klotzsche, Anja; Lärm, Lena; Vanderborght, Jan; Cai, Gaochao; Morandage, Shehan; Zörner, Miriam; Vereecken, Harry; Kruk, Jan van der

doi:10.2136/vzj2019.05.0044

Cited by 31 publications

(31 citation statements)

References 54 publications

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“…Finally, other geophysical methods such as acoustic–seismic (Lu, 2014), ground‐penetrating radar (Akinsunmade, Tomecka‐Suchoń, & Pysz, 2019; Algeo, Slater, Binley, Van Dam, & Watts, 2018; Klenk, Jaumann, & Roth, 2015; Klotzsche et al., 2019), or even nuclear magnetic resonance (Paetzold, Matzkanin, & Santos, 1985) are emerging methods that have potential for agricultural applications.…”

Section: Discussionmentioning

confidence: 99%

Time‐lapse geophysical assessment of agricultural practices on soil moisture dynamics

Blanchy

Watts

Richards

et al. 2020

Vadose Zone Journal

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Geophysical surveys are now commonly used in agriculture for mapping applications. High-throughput collection of geophysical properties such as electrical conductivity (inverse of resistivity) can be used as a proxy for soil properties of interest (e.g., moisture, texture, salinity). Most applications only rely on a single geophysical survey at a given time. However, time-lapse geophysical surveys have greater capabilities to characterize the dynamics of the system, which is the focus of this work. Assessing the impact of agricultural practices through the growth season can reveal important information for the crop production. In this work, we demonstrate the use of time-lapse electrical resistivity tomography (ERT) and electromagnetic induction (EMI) surveys through a series of three case studies illustrating common agricultural practices (cover crops, compaction with irrigation, and tillage with N fertilization). In the first case study, time-lapse EMI reveals the initial effect of cover crops on soil drying and the absence of effect on the subsequent main crop. In the second case study, compaction leading to a shallower drying depth for potatoes (Solanum tuberosum L.) was imaged by timelapse ERT. In the third case study, larger changes in electrical conductivity over time were observed in conventional tillage compared with direct drill using timelapse EMI. In addition, different N application rates had a significant effect on the yield and leaf area index but only ephemeral effects on the dynamics of electrical conductivity, mainly after the first application. Overall, time-lapse geophysical surveys show great potential for monitoring the impact of different agricultural practices that can influence crop yield.

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Section: Discussionmentioning

confidence: 99%

Time‐lapse geophysical assessment of agricultural practices on soil moisture dynamics

Blanchy

Watts

Richards

et al. 2020

Vadose Zone Journal

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“…For the zero-offset profiling (ZOP) measurements, we followed the same acquisition, processing and analysis strate-gies as presented in Klotzsche et al (2019). To conduct the ZOP survey, the transmitter (Tx) and receiver (Rx) antenna were first pushed to the end of the horizontal boreholes (7 m) at the same depth.…”

Section: Horizontal Borehole Ground Penetrating Radar Data Acquisition and Processingmentioning

confidence: 99%

“…Standard ray-based analysis methods can then be used to obtain a one-dimensional velocity profile between the two boreholes. Recently, several time-lapse plot-scale studies focused on SWC variation using horizontal borehole GPR measurements at specific depths, which ensures a good control on the vertical resolution of the obtained SWC profile information (Cai et al, 2016;Klotzsche et al, 2019). These studies mainly investigated seasonal SWC variations for different soils, surface treatments and the influence of plant types.…”

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confidence: 99%

“…These studies mainly investigated seasonal SWC variations for different soils, surface treatments and the influence of plant types. It was found that the horizontal borehole GPR measurements did not provide accurate information close to the soil surface (0-10 cm) because of interference between the critically refracted airwave and the direct wave (Klotzsche et al, 2019). This is obviously problematic when investigating infiltration processes, because the top soil is the most dynamic area with the strongest SWC changes.…”

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confidence: 99%

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Measuring vertical soil water content profiles by combining horizontal borehole and dispersive surface ground penetrating radar data

Klotzsche

Weihermüller

et al. 2020

Near Surface Geophysics

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To investigate transient dynamics of soil water redistribution during infiltration, we conducted horizontal borehole and surface ground penetrating radar measurements during a 4-day infiltration experiment at the rhizontron facility in Selhausen, Germany. Zero-offset ground penetrating radar profiling in horizontal boreholes was used to obtain soil water content information at specific depths (0.2, 0.4, 0.6, 0.8 and 1.2 m). However, horizontal borehole ground penetrating radar measurements do not provide accurate soil water content estimates of the top soil (0-0.1 m depth) because of interference between direct and critically refracted waves. Therefore, surface ground penetrating radar data were additionally acquired to estimate soil water content of the top soil. Due to the generation of electromagnetic waveguides in the top soil caused by infiltration, a strong dispersion in the ground penetrating radar data was observed in 500 MHz surface ground penetrating radar data. A dispersion inversion was thus performed with these surface ground penetrating radar data to obtain soil water content information for the top 0.1 m of the soil. By combining the complementary borehole and surface ground penetrating radar data, vertical soil water content profiles were obtained, which were used to investigate vertical soil water redistribution. Reasonable consistency was found between the ground penetrating radar results and independent soil water content data derived from time domain reflectometry measurements. Because of the improved spatial representativeness of the ground penetrating radar measurements, the soil water content profiles obtained by ground penetrating radar better matched the known water storage changes during the infiltration experiment. It was concluded that the combined use of borehole and surface ground penetrating radar data convincingly revealed spatiotemporal soil water content variation during infiltration. In addition, this setup allowed a better quantification of water storage, which is a prerequisite for future applications, where, for example, the soil hydraulic properties will be estimated from ground penetrating radar data.

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“…In recent years, electrical and EM methods have given more emphasis to characterizing soil electrical properties and SWC monitoring in space and time [ 18 , 19 ]. Ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) methods have been developed to map the spatial variability of SWC at the plant to the field scale [ 20 ]. But, as these methods are not amenable for automation and use empirical models to estimate SWC, there is a need for advanced techniques that can assess field- to catchment-scale soil moisture with high spatiotemporal resolution [ 5 ].…”

Section: Introductionmentioning

confidence: 99%

Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor

Peddinti

Hopmans

Najm

et al. 2020

Sensors

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Low-cost, accurate soil water sensors combined with wireless communication in an internet of things (IoT) framework can be harnessed to enhance the benefits of precision irrigation. However, the accuracy of low-cost sensors (e.g., based on resistivity or capacitance) can be affected by many factors, including salinity, temperature, and soil structure. Recent developments in wireless sensor networks offer new possibilities for field-scale monitoring of soil water content (SWC) at high spatiotemporal scales, but to install many sensors in the network, the cost of the sensors must be low, and the mechanism of operation needs to be robust, simple, and consume low energy for the technology to be practically relevant. This study evaluated the performance of a resistivity–capacitance-based wireless sensor (Sensoterra BV, 1018LE Amsterdam, Netherlands) under different salinity levels, temperature, and soil types in a laboratory. The sensors were evaluated in glass beads, Oso Flaco sand, Columbia loam, and Yolo clay loam soils. A nonlinear relationship was exhibited between the sensor measured resistance (Ω) and volumetric soil water content (θ). The Ω–θ relationship differed by soil type and was affected by soil solution salinity. The sensor was extremely sensitive at higher water contents with high uncertainty, and insensitive at low soil water content accompanied by low uncertainty. The soil solution salinity effects on the Ω–θ relationship were found to be reduced from sand to sandy loam to clay loam. In clay soils, surface electrical conductivity (ECs) of soil particles had a more dominant effect on sensor performance compared to the effect of solution electrical conductivity (ECw). The effect of temperature on sensor performance was minimal, but sensor-to-sensor variability was substantial. The relationship between bulk electrical conductivity (ECb) and volumetric soil water content was also characterized in this study. The results of this study reveal that if the sensor is properly calibrated, this low-cost wireless soil water sensor has the potential of improving soil water monitoring for precision irrigation and other applications at high spatiotemporal scales, due to the ease of integration into IoT frameworks.

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Monitoring Soil Water Content Using Time‐Lapse Horizontal Borehole GPR Data at the Field‐Plot Scale

Cited by 31 publications

References 54 publications

Time‐lapse geophysical assessment of agricultural practices on soil moisture dynamics

Time‐lapse geophysical assessment of agricultural practices on soil moisture dynamics

Measuring vertical soil water content profiles by combining horizontal borehole and dispersive surface ground penetrating radar data

Assessing Effects of Salinity on the Performance of a Low-Cost Wireless Soil Water Sensor

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