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Identification, mapping, and characterisation of a mature artificial mole channel network using ground-penetrating radar

Author

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  • Deuss, Kirstin Ella
  • Almond, Peter C.
  • Carrick, Sam
  • Kees, Lawrence John

Abstract

Mole channel drainage is a cost-effective and efficient way to drain slowly permeable agricultural soils. Artificial drainage has the potential to significantly influence catchment hydrology and contaminant source areas, but there is little information available about the extent, connectivity, layout, density or longevity of mole channel networks, which are commonly estimated to deteriorate within 5–20 years. Such information is important for understanding landscape hydrodynamics but, currently, there are no established techniques for calibrating estimates of mole network characteristics at the paddock or larger scale. This study characterised a 30-plus-year-old mole channel network in a small agricultural basin in Southland, New Zealand, and tested the utility of ground-penetrating radar (GPR) for identifying, mapping, and characterising mole channel drainage. A dual frequency GPR antenna (700 and 250 MHz), connected to a high-precision, real-time kinematic global positioning system, was tested and proved effective at locating mole channels and a tile drain with high lateral precision and accuracy. Surveying of six plots demonstrated that the mole network was complex in design and had a high density (1.6 m m−2) of interconnected, multidirectional mole channels. Significantly, the mole channels were predominantly in good condition and spatially well connected. Visual observations found no evidence that the blade slot and secondary soil fractures, formed by the mole plough during installation, persisted after 30 years. However, root growth and worm burrowing into the mole channels suggest they are hydraulically connected to the surrounding soil through natural macropores. Our results provide the first attempt at mapping and characterising mature, multi-generational mole channel networks in slowly permeable loess soils. The results have significance for understanding catchment-scale hydrodynamics in mole-drained landscapes, especially considering that the life span of these artificial drainage networks is shown to be considerably longer than previous estimates for loess-derived, silt loam soils.

Suggested Citation

  • Deuss, Kirstin Ella & Almond, Peter C. & Carrick, Sam & Kees, Lawrence John, 2023. "Identification, mapping, and characterisation of a mature artificial mole channel network using ground-penetrating radar," Agricultural Water Management, Elsevier, vol. 288(C).
  • Handle: RePEc:eee:agiwat:v:288:y:2023:i:c:s0378377423003426
    DOI: 10.1016/j.agwat.2023.108477
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    References listed on IDEAS

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    1. Jha, Madan Kumar & Koga, Kiyoshi, 1995. "Mole drainage: Prospective drainage solution to Bangkok clay soils," Agricultural Water Management, Elsevier, vol. 28(3), pages 253-270, November.
    2. Goss, M. J. & Harris, G. L. & Howse, K. R., 1983. "Functioning of mole drains in a clay soil," Agricultural Water Management, Elsevier, vol. 6(1), pages 27-30, March.
    3. Barry Allred & DeBonne Wishart & Luis Martinez & Harry Schomberg & Steven Mirsky & George Meyers & John Elliott & Christine Charyton, 2018. "Delineation of Agricultural Drainage Pipe Patterns Using Ground Penetrating Radar Integrated with a Real-Time Kinematic Global Navigation Satellite System," Agriculture, MDPI, vol. 8(11), pages 1-14, October.
    4. Youngs, E. G., 1985. "An analysis of the effect of the vertical fissuring in mole-drained soils on drain performances," Agricultural Water Management, Elsevier, vol. 9(4), pages 301-311, March.
    5. Allred, Barry & Martinez, Luis & Fessehazion, Melake K. & Rouse, Greg & Williamson, Tanja N. & Wishart, DeBonne & Koganti, Triven & Freeland, Robert & Eash, Neal & Batschelet, Adam & Featheringill, Ro, 2020. "Overall results and key findings on the use of UAV visible-color, multispectral, and thermal infrared imagery to map agricultural drainage pipes," Agricultural Water Management, Elsevier, vol. 232(C).
    6. Woo, Dong Kook & Song, Homin & Kumar, Praveen, 2019. "Mapping subsurface tile drainage systems with thermal images," Agricultural Water Management, Elsevier, vol. 218(C), pages 94-101.
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