Multifrequency electromagnetic geophysical tools for evaluating the hydrologic conditions and performance of evapotranspiration barriers

Mangel, Adam R.; Linneman, Dorothy; Sprinkle, Parker; Jaysaval, Piyoosh; Thomle, Jonathan N.; Strickland, Christopher E.

doi:10.1016/j.jenvman.2021.114123

Cited by 7 publications

(3 citation statements)

References 36 publications

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“…Some of these technologies employed for detecting underground utilities are ground-penetrating radar (GPR) and electromagnetic induction (EMI) sensors [147]. However, the low resolution of GPR and EMI sensors makes data interpretation problematic [148]. In addition, due to their limited sensitivity, GPR and EMI sensors have difficulty detecting small or non-metallic utilities, such as plastic pipes and fiber-optic cables.…”

Section: The Challengesmentioning

confidence: 99%

Sensors in Civil Engineering: From Existing Gaps to Quantum Opportunities

Kantsepolsky,

Aviv

2024

Smart Cities

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The vital role of civil engineering is to enable the development of modern cities and establish foundations for smart and sustainable urban environments of the future. Advanced sensing technologies are among the instrumental methods used to enhance the performance of civil engineering infrastructures and address the multifaceted challenges of future cities. Through this study, we discussed the shortcomings of traditional sensors in four primary civil engineering domains: construction, energy, water, and transportation. Then, we investigated and summarized the potential of quantum sensors to contribute to and revolutionize the management of civil engineering infrastructures. For the water sector, advancements are expected in monitoring water quality and pressure in water and sewage infrastructures. In the energy sector, quantum sensors may facilitate renewables integration and improve grid stability and buildings’ energy efficiency. The most promising progress in the construction field is the ability to identify subsurface density and underground structures. In transportation, these sensors create many fresh avenues for real-time traffic management and smart mobility solutions. As one of the first-in-the-field studies offering the adoption of quantum sensors across four primary domains of civil engineering, this research establishes the basis for the discourse about the scope and timeline for deploying quantum sensors to real-world applications towards the quantum transformation of civil engineering.

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Section: The Challengesmentioning

confidence: 99%

Sensors in Civil Engineering: From Existing Gaps to Quantum Opportunities

Kantsepolsky,

Aviv

2024

Smart Cities

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“…in [9] and has been widely employed in several works. Some recent research in geophysical and agricultural science show its application [10] , [11] , [12] . Therefore, our test consists in the measurement of the dielectric permittivity of the soil under test (SUT), with different water content percentages, through our TDT sensor system directly inserted in the soil under analysis, compared with the dielectric permittivity estimation formula given by Topp and the permittivity obtained ( Fig.…”

Section: Validation and Characterizationmentioning

confidence: 99%

Time-domain transmission sensor system for on-site dielectric permittivity measurements in soil: A compact, low-cost and stand-alone solution

Pérez¹,

Méndez²,

Avellaneda³

et al. 2023

HardwareX

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“…Various surface geophysical methods are directly or indirectly sensitive to VWC. Ground penetrating radar (GPR) is strongly sensitive to VWC, as water content typically dominates soil dielectric permittivity, which in turn controls radar wave velocity (e.g., Mangel et al, 2022 ). Electrical resistivity tomography (ERT) and frequency domain electromagnetic induction (FDEM) are both techniques for mapping two-dimensional/three-dimensional (2D/3D) subsurface bulk electrical conductivity (EC) variations that can be used for moisture estimation if porewater possesses an electrical contrast from the soil (e.g., Shanahan et al, 2015 ).…”

Section: Introductionmentioning

confidence: 99%

Field evaluation of semi‐automated moisture estimation from geophysics using machine learning

Terry

Day‐Lewis

Lane

et al. 2023

Vadose Zone Journal

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Geophysical methods can provide three-dimensional (3D), spatially continuous estimates of soil moisture. However, point-to-point comparisons of geophysical properties to measure soil moisture data are frequently unsatisfactory, resulting in geophysics being used for qualitative purposes only. This is because (1) geophysics requires models that relate geophysical signals to soil moisture, (2) geophysical methods have potential uncertainties resulting from smoothing and artifacts introduced from processing and inversion, and (3) results from multiple geophysical methods are not easily combined within a single soil moisture estimation framework. To investigate these potential limitations, an irrigation experiment was performed wherein soil moisture was monitored through time, and several surface geophysical datasets indirectly sensitive to soil moisture were collected before and after irrigation: ground penetrating radar, electrical resistivity tomography (ERT), and frequency domain electromagnetics (FDEM). Data were exported in both raw and processed form, and then snapped to a common 3D grid to facilitate moisture prediction by standard calibration techniques, multivariate regression, and machine learning. A combination of inverted ERT data, raw FDEM, and inverted FDEM data was most informative for predicting soil moisture using a random regression forest model (one-thousand 60/40 training/test cross-validation folds produced root mean squared errors ranging from 0.025-0.046 cm 3 /cm 3 ). This cross-validated model was further supported by a separate evaluation using a test set from a physically separate portion of the study area. Machine learning was conducive to a semi-automated model-selection process that could be used for other sites and datasets to locally improve accuracy.

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Multifrequency electromagnetic geophysical tools for evaluating the hydrologic conditions and performance of evapotranspiration barriers

Cited by 7 publications

References 36 publications

Sensors in Civil Engineering: From Existing Gaps to Quantum Opportunities

Sensors in Civil Engineering: From Existing Gaps to Quantum Opportunities

Time-domain transmission sensor system for on-site dielectric permittivity measurements in soil: A compact, low-cost and stand-alone solution

Field evaluation of semi‐automated moisture estimation from geophysics using machine learning

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