Better management zoning with elevation than with three soil classifications in a periodically waterlogged plot

Following a comparison of the practical applicability of USDA Soil Taxonomy (ST), Hungarian soil classification (HU), and WRB in a slightly saline alluvial plot (Tóth et al., 2021), in this study, we compared the polygon alignment derived from the three systems, relative to the pattern of elevation and mean NDVI. The final objective focused on delineating potential management zones. The study plot is the largest salt-affected plot in the country (0.9 km 2 ). Within this plot, 85 undisturbed, 1 m deep profiles were collected, sampled, described and classified using a 100 × 100 m grid. We described the polygon alignment qualitatively and through the use of landscape metrics. Additionally, we evaluated number of classes and polygons, and delineated potential management zones based on environmental variables. Large dominant polygons were found at level 1, the least detailed of all three classifications. The polygons became increasingly fragmented at levels 2, 3 and 4, where isolated single raster cell polygons dominated the plot in each classification: 96 % in WRB, 73 % in HU and 70 % in ST, compared to the total number of polygons. Landscape metrics proved that ST exhibited the best north–south orientation (the orientation of highs/lows), length, perimeter, area, aggregation and interspersion/juxtaposition of polygons. HU showed an intermediate performance, while WRB had the least satisfactory alignment with the north–south orientation, length, perimeter and area, as well as patch cohesion and aggregation of polygons. After analyzing the scatterplot of elevation versus mean NDVI, and also elevation versus long-term NDVI range, we noted a cutpoint of 95.47 m, which separated the more productive and less variable zone from the lower lying less productive less certain zone, given its periodical precipitation-related waterlogging. • Polygons were formed from contiguous raster cells of the same class. • Polygon alignment was similar only at the least-detailed level of the classifications. • Landscape metrics showed the best aggregation for Soil Taxonomy classes. • More than half of the WRB polygons were isolated single raster cells at every level. • Only the Hungarian Classification can separate a few distinct management zones. • Elevation data outperformed all classifications in delineating management zones.