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To investigate the linkage between erosion process and channel network extent, we develop two simple erosion threshold theories driven by a steady state runoff model that are used in the digital terrain model TOPOG to predict the pattern of channelization. TOPOG divides the land surface into elements defined by topographic contours and flow lines, which can be classified as divergent, convergent and planar elements. The calibration parameter for the runott model is determined using empirical evidence that the divergent elements which comprise the ridges in our study area do not experience saturation overland flow, where as the convergent elements in the valleys do during significant runoff events. A threshold theory lor shallow landsliding predicts a pattern of instability consistent with the distribution of landslide scars in our 1.2 km2 study site and confirms the interpretation, based on field observa tions, that indicate the steeper channel heads to be at least partially controlled by slope instability. Most sites of predicted and observed slope instability do not, however, support a channel head, hence landslide instability alone is not sutficient for channelization. In contrast, most elements predicted to be eroded by saturation overland flow coincide with the observed location of the channel network. In addition, areas of predicted downslope decrease in relative sediment-transport capacity were found to correspond to locations where channels became discontinuous. The topographic threshold given by the saturation overland flow erosion theory varies with the third power of critical boundary shear stress, suggesting that critical shear stress, although difficult to quantify with much precision in the field, is a dominant control on the extent ot the channel network where saturation overland flow is significant. Current extent ot the channel network in our field site, tor example, may best \)c explained as resulting from grazing-induced reduction in surtace resistance.

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We propose a graphical technique to analyze the entirety of landforms in a catchment to define quantitatively the spatial variation in the dominance of different erosion processes. High-resolution digital elevation data of a 1.2 km2 hilly area where the channel network had been mapped in the field were used in the digital terrain model, TOPOG, to test threshold theories for erosion. The land surface was divided into-20 m2 elements whose shapes were then classified as convergent, planar, or divergent. The entire landscape plotted on a graph of area per unit contour length against surface gradient shows each planform plotting as a separate field. A simple steady-state hydrologic model was used to predict zones of saturation and areas of high pore pressure to mimic the extreme hydrologic events responsible for erosive instability of the land surface. The field observation that satu ration overland flow is rare outside convergent zones provided a significant constraint on the hydrologic parameter in the model. This model was used in threshold theories to predict areas of slope instabil ity and areas subject to erosion by saturation overland flow, both of which can contribute to channel initiation. The proportion of conver gent elements predicted to exceed the threshold varies greatly with relatively small changes in surface resistance, demonstrating a high sensitivity to land use such as cattle grazing. Overall, the landscape can be divided, using erosion threshold lines, into areas prone to channel instability due to runoff and stable areas where diffusive transport predominates.

Abstract:The high-resolution Experimental Advanced Airborne Research LIDAR (EAARL) is a new technology for cross-environment surveys of channels and floodplains. EAARL measurements of basic channel geometry, such as wetted cross-sectional area, are within a few percent of those from control field surveys. The largest channel mapping errors are along stream banks. The LIDAR data adequately support 1D and 2D computational fluid dynamics models and frequency domain analyses by wavelet transforms. Further work is needed to establish the stream monitoring capability of the EAARL and the range of water quality conditions in which this sensor will accurately map river bathymetry.