Mapping Agricultural Subsurface Drainage by Proximal and Remote Sensing Technologies Integrated with a Satellite Navigation System - Invited Paper 351735
Allred, B., R. S. Freeland, D. Wishart, G. Rouse, and T. Williamson.  2018.  American Geophysical Union, Fall Meeting, Dec 10-14, Washington DC.  (invited)

Abstract:
To improve the soil water removal efficiency of drained farmland, and thereby increase crop yields, new drain lines are often installed between pre-existing drain lines, which in turn requires an understanding of the original drainage pipe locations. Furthermore, to better evaluate the overall environmental risks of nitrate and phosphate release into the environment from farm fields, the intensity of subsurface drainage practices within an agricultural landscape needs to be estimated, extending from individual operations to regional distributions. Consequently, here are both economic and environmental benefits to finding effective and efficient methods for mapping agricultural subsurface drainage systems. Finding drain lines with heavy trenching equipment causes pipe damage that leads to costly repairs, while the alternative of using a hand-held tile probe is time consuming and extremely tedious. Ground penetrating radar (GPR), a proximal sensing technology, integrated with a satellite navigation system, has proven capable of delineating drainage pipe patterns at agricultural field sites in Ohio, Indiana, and Maryland. While GPR is often successful for locating buried drainage pipes under a range of soil conditions, this approach can be inefficient for providing detailed maps of subsurface drainage systems over large agricultural fields greater than 50 ha. Remote sensing using Unmanned Aerial Vehicles (UAVs) with visible, near infrared, and thermal infrared sensors, all integrated with a satellite navigation system may have the capability for large-scale, drainage pipe mapping, given suitable field conditions. This UAV remote sensing technology, particularly thermal infrared imagery, has proven useful for drainage pipe mapping at agricultural fields in Ohio, Indiana, Iowa, and Michigan, although the degree of success has varied. Future research will focus on developing guidelines regarding field conditions (soil type, crop residue, tillage practice, ground wetness level, etc.) in which UAV imagery can be employed to map agricultural subsurface drainage systems.