Mapping of Agricultural Subsurface Drainage Systems Using a Frequency-Domain Ground Penetrating Radar and Evaluating Its Performance Using a Single-Frequency Multi-Receiver Electromagnetic Induction Instrument

Subsurface drainage systems remove excess water from the soil profile thereby improving crop yields in poorly drained farmland. Knowledge of the position of the buried drain lines is important: 1) to improve understanding of leaching and offsite release of nutrients and pesticides, and 2) for the installation of a new set of drain lines between the old ones for enhanced soil water removal efficiency. Traditional methods of drainage mapping involve the use of tile probes and trenching equipment. While these can be effective, they are also time-consuming, labor-intensive, and invasive, thereby entailing an inherent risk of damaging the drainpipes. Non-invasive geophysical soil sensors provide a potential alternative solution. Previous research has focused on the use of time-domain ground penetrating radar (GPR), with variable success depending on local soil and hydrological conditions and the central frequency of the specific equipment employed. The objectives of this study were 1) to test the use of a stepped-frequency continuous wave (SFCW) 3D-GPR (GeoScope Mk IV 3D-Radar with DXG1820 antenna array) for subsurface drainage mapping, and 2) to evaluate the performance of a 3D-GPR with the use of a single-frequency multi-receiver electromagnetic induction (EMI) sensor (DUALEM) in-combination. The 3D-GPR system offers more flexibility for application to different (sub)surface conditions due to the coverage of wide frequency bandwidth. The EMI sensor simultaneously provides information about the apparent electrical conductivity (ECa) for different soil volumes, corresponding to different depths. This sensor combination was evaluated on twelve different study sites with various soil types with textures ranging from sand to clay till. While the 3-D GPR showed a high success rate in finding the drainpipes at five sites (sandy, sandy loam, loamy sand, and organic topsoils), the results at the other seven sites were less successful due to limited penetration depth (PD) of the 3D-GPR signal. The results suggest that the electrical conductivity estimates produced by the inversion of ECa data measured by the DUALEM sensor could be a useful proxy to explain the success achieved by the 3D-GPR in finding the drain lines. The high attenuation of electromagnetic waves in highly conductive media limiting the PD of the 3D-GPR can explain the findings obtained in this research.

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Mapping of Agricultural Subsurface Drainage Systems Using a Frequency-Domain Ground Penetrating Radar and Evaluating Its Performance Using a Single-Frequency Multi-Receiver Electromagnetic Induction Instrument

Sensors ◽

10.3390/s20143922 ◽

2020 ◽

Vol 20 (14) ◽

pp. 3922 ◽

Cited By ~ 3

Author(s):

Triven Koganti ◽

Ellen Van De Vijver ◽

Barry J. Allred ◽

Mogens H. Greve ◽

Jørgen Ringgaard ◽

...

Keyword(s):

Electrical Conductivity ◽

Ground Penetrating Radar ◽

Electromagnetic Induction ◽

Subsurface Drainage ◽

Single Frequency ◽

Drainage Systems ◽

Local Soil ◽

3D Gpr ◽

Ground Penetrating ◽

Emi Sensor

Subsurface drainage systems are commonly used to remove surplus water from the soil profile of a poorly drained farmland. Traditional methods for drainage mapping involve the use of tile probes and trenching equipment that are time-consuming, labor-intensive, and invasive, thereby entailing an inherent risk of damaging the drainpipes. Effective and efficient methods are needed in order to map the buried drain lines: (1) to comprehend the processes of leaching and offsite release of nutrients and pesticides and (2) for the installation of a new set of drain lines between the old ones to enhance the soil water removal. Non-invasive geophysical soil sensors provide a potential alternative solution. Previous research has mainly showcased the use of time-domain ground penetrating radar, with variable success, depending on local soil and hydrological conditions and the central frequency of the specific equipment used. The objectives of this study were: (1) to test the use of a stepped-frequency continuous wave three-dimensional ground penetrating radar (3D-GPR) with a wide antenna array for subsurface drainage mapping and (2) to evaluate its performance with the use of a single-frequency multi-receiver electromagnetic induction (EMI) sensor in-combination. This sensor combination was evaluated on twelve different study sites with various soil types with textures ranging from sand to clay till. While the 3D-GPR showed a high success rate in finding the drainpipes at five sites (sandy, sandy loam, loamy sand, and organic topsoils), the results at the other seven sites were less successful due to the limited penetration depth of the 3D-GPR signal. The results suggest that the electrical conductivity estimates produced by the inversion of apparent electrical conductivity data measured by the EMI sensor could be a useful proxy for explaining the success achieved by the 3D-GPR in finding the drain lines.

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Mapping Subsurface Drainage in Agricultural Areas Using a Frequency-Domain Ground Penetrating Radar

10.5194/egusphere-egu2020-1887 ◽

2020 ◽

Author(s):

Triven Koganti ◽

Ellen Van De Vijver ◽

Barry J. Allred ◽

Mogens H. Greve ◽

Jørgen Ringgaard ◽

...

Keyword(s):

Antenna Array ◽

Ground Penetrating Radar ◽

Continuous Wave ◽

Subsurface Drainage ◽

High Attenuation ◽

Local Soil ◽

Increased Risk ◽

3D Gpr ◽

Ground Penetrating ◽

Agricultural Areas

<p>Artificial subsurface drainage systems are installed in agricultural areas to remove excess water and convert poorly naturally drained soils into productive cropland. Some of the most productive agricultural regions in the world are a result of subsurface drainage practices. Drain lines provide a shortened pathway for the release of nutrients and pesticides into the environment, which presents a potentially increased risk for eutrophication and contamination of surface water bodies. Knowledge of drain line locations is often lacking. This complicates the understanding of the local hydrology and solute dynamics and the consequent planning of mitigation strategies such as constructed wetlands, saturated buffers, bioreactors, and nitrate and phosphate filters. In addition, accurate knowledge of the existing subsurface drainage system is required in designing the installation of a new set of drain lines to enhance soil water removal efficiency. The traditional methods of drainage mapping involve the use of tile probes and trenching equipment which are time-consuming, tiresome, and invasive, thereby carrying an inherent risk of damaging the drain pipes. Non-invasive geophysical sensors provide a potential alternative solution to the problem. Previous research has focused on the use of time-domain ground penetrating radar (GPR) with variable success depending on local soil and hydrological conditions and the center frequency of the specific equipment used. For example, 250 MHz antennas proved to be more suitable for drain line mapping. Recent technological advancements enabled the collection of high-resolution spatially exhaustive data. In this study, we present the use of a stepped-frequency continuous wave (SFCW) 3D-GPR (GeoScope Mk IV 3D-Radar with DXG1820 antenna array) mounted in a motorized survey configuration with real-time georeferencing for subsurface drainage mapping. The 3D-GPR system offers more flexibility for application to different (sub)surface conditions due to the coverage of wide frequency bandwidth (60-3000 MHz). In addition, the wide array swathe of the antenna array (1.5 m covered by 20 measurement channels) enables effective coverage of three-dimensional (3D) space. The surveys were performed on twelve different study sites with various soil types with textures ranging from sand to clay till. While we achieved good success in finding the drainage pipes at five sites with sandy, sandy loam, loamy sand and organic topsoils, the results at the other seven sites with more clay-rich soils were less successful. The high attenuation of electromagnetic waves in highly conductive clay-rich soils, which limits the penetration depth of the 3D-GPR system, can explain our findings obtained in this research.</p>

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Mapping of Agricultural Subsurface Drainage Systems Using Unmanned Aerial Vehicle Imagery and Ground Penetrating Radar

Sensors ◽

10.3390/s21082800 ◽

2021 ◽

Vol 21 (8) ◽

pp. 2800

Author(s):

Triven Koganti ◽

Ehsan Ghane ◽

Luis Rene Martinez ◽

Bo V. Iversen ◽

Barry J. Allred

Keyword(s):

Unmanned Aerial Vehicle ◽

Ground Penetrating Radar ◽

Spatial Scales ◽

Drainage System ◽

Cost Effective ◽

Subsurface Drainage ◽

Large Field ◽

Drainage Systems ◽

Aerial Vehicle ◽

Ground Penetrating

Agricultural subsurface drainage systems are commonly installed on farmland to remove the excess water from poorly drained soils. Conventional methods for drainage mapping such as tile probes and trenching equipment are laborious, cause pipe damage, and are often inefficient to apply at large spatial scales. Knowledge of locations of an existing drainage network is crucial to understand the increased leaching and offsite release of drainage discharge and to retrofit the new drain lines within the existing drainage system. Recent technological developments in non-destructive techniques might provide a potential alternative solution. The objective of this study was to determine the suitability of unmanned aerial vehicle (UAV) imagery collected using three different cameras (visible-color, multispectral, and thermal infrared) and ground penetrating radar (GPR) for subsurface drainage mapping. Both the techniques are complementary in terms of their usage, applicability, and the properties they measure and were applied at four different sites in the Midwest USA. At Site-1, both the UAV imagery and GPR were equally successful across the entire field, while at Site-2, the UAV imagery was successful in one section of the field, and GPR proved to be useful in the other section where the UAV imagery failed to capture the drainage pipes’ location. At Site-3, less to no success was observed in finding the drain lines using UAV imagery captured on bare ground conditions, whereas good success was achieved using GPR. Conversely, at Site-4, the UAV imagery was successful and GPR failed to capture the drainage pipes’ location. Although UAV imagery seems to be an attractive solution for mapping agricultural subsurface drainage systems as it is cost-effective and can cover large field areas, the results suggest the usefulness of GPR to complement the former as both a mapping and validation technique. Hence, this case study compares and contrasts the suitability of both the methods, provides guidance on the optimal survey timing, and recommends their combined usage given both the technologies are available to deploy for drainage mapping purposes.

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Mapping an Agricultural Field Experiment by Electromagnetic Induction and Ground Penetrating Radar to Improve Soil Water Content Estimation

Agronomy ◽

10.3390/agronomy9100638 ◽

2019 ◽

Vol 9 (10) ◽

pp. 638 ◽

Cited By ~ 1

Author(s):

Daniela De Benedetto ◽

Francesco Montemurro ◽

Mariangela Diacono

Keyword(s):

Field Experiment ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Ground Penetrating Radar ◽

Electromagnetic Induction ◽

Gravimetric Method ◽

Sensor Data ◽

Ground Penetrating ◽

Emi Sensor

A growing interest in proximal sensing technologies for estimating soil water content (SWC) will be highlighted. On this matter the objectives of this study were: (1) to use both the combined electromagnetic induction (EMI) sensor and Ground Penetrating Radar (GPR) to characterize an innovative field experiment located in southern Italy, in which different agricultural practices are tested, including a soil hydraulic arrangement; (2) to implement a geostatistical approach in order to merge different geophysical sensor data as auxiliary variables for SWC estimation. The multi-sensor recorded data were: (1) SWC data measured by gravimetric method; (2) Differential Global Positioning System height; (3) apparent electrical conductivity measured by an EMI sensor; (4) depths of soil discontinuities individuated by GPR radargrams interpretation; and (5) amplitude of GPR signal data at two different frequencies. Geostatistical techniques were used both to map all variables and improve the SWC estimation. The findings of this research indicate that: (1) the GPR radargrams identified four reflection events as a consequence of interfaces; (2) the EMI and GPR mapping provided identification of areas with high potential for water stagnation; and (3) the outputs of geophysical sensors can be effectively used as auxiliary tools to supplement the sampling of the target variable and to improve water content estimation.

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