See more from this Session: ACS528 Diversity in Agronomy, Crop, Soil and Environmental Sciences Student Poster Competition
Monday, October 17, 2011
Henry Gonzalez Convention Center, Room 214B, Concourse Level
In spite of high spatio-temporal variability, if a field is repeatedly surveyed for soil water, some locations would always be wetter and some locations would be drier than the field average. Therefore, these locations maintain their rank and the spatial pattern will be similar. The objective of this study was to examine 1) the similarity of the spatial pattern of soil water storage over time and at depths and 2) the landscape characteristics of that similarity. Soil water storage at 20 cm intervals down to 140 cm was measured along a transect extending over several knoll–depression cycles in the hummocky landscape of the prairie pothole region of North America. High water storage in depressions and low water storage on the knolls created a spatial pattern that was inversely related to elevation. The pattern was stronger within any given season than between the same season of different years. However, a less similar spatial pattern was observed between different seasons. Stronger intra-seasonal patterns are thought to be due to the relative dominance of a given set of processes operating within a season than that between seasons. Similarity was stronger between the layers close in vertical distance than that of layers far apart. Large-scale (> 72 m) spatial pattern was similar between any time and depth and was controlled by alternating knolls and depressions or the macro-topography. However, the medium-scale (18 to 72 m) spatial pattern was controlled by micro-topography and landform elements. Though, the effect of landform elements was very similar between any two depths, it changed over time. The change in the similarity of the spatial patterns can be used to identify the change in the sampling domain as controlled by the hydrological processes operating at different scales and locations delivering the maximum information with minimum sampling effort.