Resumen de Detecting subsurface drainage systems and estimating drain spacing in intensively managed agricultural landscapes
Detailed location maps of tile drains in the Midwestern United States are generally not available, as the tile lines in these areas were laid more than 75 years ago. The objective of this study is to map individual tile drains and estimate drain spacing using a combination of GIS-based analysis of land cover, soil and topography data, and analysis of high resolution aerial photographs to within the Hoagland watershed in west-central Indiana. A decision tree classifier model was used to classify the watershed into potentially drained and undrained areas using land cover, soil drainage class, and surface slope data sets. After masking out the potential undrained areas from the aerial image, image processing techniques such as the first-difference horizontal and vertical edge enhance filters, and density slice classification were used to create a detailed tile location map of the watershed. Drain spacings in different parts of the watershed were estimated from the watershed tile line map. The decision tree identified 79% of the watershed as potential tile drained area while the image processing techniques predicted artificial subsurface drainage in approximately 50% of the Hoagland watershed. Drain spacing inferred from classified aerial image vary between 17 and 80 m. Comparison of estimated tile drained areas from aerial image analysis shows a close agreement with estimated tile drained areas from previous studies (50% versus 46% drained area) which were based on GIS analysis and National Resource Inventory survey. Due to lack of sufficient field data, the results from this analysis could not be validated with observed tile line locations. In general, the techniques used for mapping tile lines gave reasonable results and are useful to detect drainage extent from aerial image in large areas. These techniques, however, do not yield precise maps of the systems for individual fields and may not accurately estimate the extent of tile drainage in the presence of crop residue in agricultural fields and/or existence of other spatial features with similar spectral response as tile drains.
