The search for the optimal spatial scale for observing landforms to understand physical processes is a fundamental issue in geomorphology. Topographic attributes derived from Digital Terrain Models (DTMs) such as slope, curvature and drainage area provide a basis for topographic analyses. The slope–area relationship has been used to distinguish diffusive (hillslope) from linear (valley) processes, and to infer dominant sediment transport processes. In addition, curvature is also useful in distinguishing the dominant landform process. Recent topographic survey techniques such as LiDAR have permitted detailed topographic analysis by providing high-quality DTMs. This study uses LiDAR-derived DTMs with a spatial scale between 1 and 30 m in order to find the optimal scale for observation of dominant landform processes in a headwater basin in the eastern Italian Alps where shallow landsliding and debris flows are dominant. The analysis considered the scaling regimes of local slope versus drainage area, the spatial distribution of curvature, and field observations of channel head locations. The results indicate that: i) hillslope-to-valley transitions in slope–area diagrams become clearer as the DTM grid size decreases due to the better representation of hillslope morphology, and the topographic signature of valley incision by debris flows and landslides is also best displayed with finer DTMs; ii) regarding the channel head distribution in the slope–area diagrams, the scaling regimes of local slope versus drainage area obtained with grid sizes of 1, 3, and 5 m are more consistent with field data; and iii) the use of thresholds of standard deviation of curvature, particularly at the finest grid size, were proven as a useful and objective methodology for recognizing hollows and related channel heads.
Geomorphology – Elsevier
Published: Dec 1, 2009
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