Publication Date:
2013-03-05
Description:
There is widespread recognition that spatially-distributed information on soil surface roughness (SSR) is required for hydrological and geomorphological applications. Such information is necessary to describe variability in soil structure, which is highly heterogeneous in time and space, to parameterise hydrology and erosion models and to understand the temporal evolution of the soil surface in response to rainfall. This paper demonstrates how results from semi-variogram analysis can quantify key elements of SSR for such applications. Three soil types (silt, silt loam and silty clay) were used to show how different types of structural variance in SSR evolve during simulated rainfall events. All three soil types were progressively degraded using artificial rainfall to produce a series of roughness states. A calibrated laser profiling instrument was used to measure SSR over a 10 x 10 cm spatial extent, at a 2 mm resolution. These data were geostatistically analysed in the context of aggregate breakdown and soil crusting. The results show that such processes are represented by a quantifiable decrease in sill variance, from 8.01 (control) to 0.74 (after 60 minutes of rainfall). Soil surface features such as soil cracks, tillage lines and erosional areas were quantified by local maxima in semi-variance at a given length-scale. This research demonstrates that semi-variogram analysis can retrieve spatio-temporal variations in soil surface condition; in order to provide information on hydrological pathways. Consequently, geostatistically-derived SSR shows strong potential for inclusion as spatial information in hydrology and erosion models to represent complex surface processes at different soil structural scales.
Print ISSN:
0043-1397
Electronic ISSN:
1944-7973
Topics:
Architecture, Civil Engineering, Surveying
,
Geography
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