The aim of this research was to enable hillslope-scale soil erosion to be predicted from measurements made at the laboratory-scale. The successful prediction of hillslope-scale soil erosion traditionally involves extensive data collection from field rainfall simulation programs, or from field plots under natural rainfall. Recognizing the high costs and inconvenience associated with field-based studies, two alternative methods were developed and tested for predicting hillslope-scale soil erosion from laboratory- scale measurements:
• Hillslope erosion models were calibrated with data from laboratory simulations of erosion processes so as to enable erosion prediction in new areas to be made with a minimal set of laboratory experiments. Predictions were tested against field observations.
• Equations were developed for the prediction of erodibility values from the physical and chemical properties of the soils and overburdens. These equations allow erosion predictions to be made in new areas from simple tests of media properties.
A review of literature indicated the major erosion processes at the hillslope scale were likely to be rill and interill, and the vii2i]ox factors affecting these processes were likely to be media properties and slope steepness. These processes and factors were investigated using a bare laboratory plot (0.8 x 3.0 m) within a tilting flume (5 to 30% slope) subjected to simulated rainfall (100 mm/h) and overland flow (0.1 to 1.8 L/s).
Interill-only slope steepness experiments found that increases in sediment delivery rates from 5% to 30% slope were approximately double the predictions based on existing published interill functions. The interill+rill experiments found a response to slope that was similar to existing functions (eg. Nearing 1997a). These findings represent a mean slope response for all media, yet the response of individual media varied dramatically from a 2.5x to a 50x increase in erosion over the range of slopes studied. New slope adjustment equations are proposed as an improvement to the existing functions.
Overland flow experiments showed that the parameterization of erosion models containing specific functions for rill erosion was possible at the laboratory scale. Predicted sediment delivery rates based on models parameterized with laboratory data were compared to observed sediment delivery rates from 12 m long field rills on the same media types. Using a discharge-based model, predictions were within 35%) of observed values for half the 32 media tested. At worst, field values were over-predicted by 100%) or under-predicted by 65%.
For soils, high clay (not smectitic) and organic matter contents were associated with low erodibility; for overburdens, high rock content (> 30%)) was associated with very low erodibilities. However, further analysis showed that correlations between media properties and sediment delivery varied with slope steepness and media type. It was concluded that a single regression equation could not be used to predict erodibility under all conditions. Instead, four equations were developed to predict rill and interill erodibility, for soils and overburdens separately. The need for separate regression equations was attributed to the presence of different erosive sub-processes for specific combinations of medium type and slope gradient.
Predicted sediment delivery rates based on a process model parameterized with laboratory data were tested against field measurements of erosion from 12 m long plots under simulated rainfall at 100 mm/h on slopes ranging from 5% to 30%. Regression analysis showed a strong relationship (r = 0.74) between predicted and measured sediment delivery rates, demonstrating that erosion at the hillslope-scale can successfully be predicted from laboratory-scale measurements of erodibility.
From a practical perspective, the results of this research are to be applied by environmental officers on mine-sites to predict potential erosion rates from a range of landform design options. For ease of use within this industry, a user friendly computer application, entitled MINErosion, was developed to provide a simple method for the rapid assessment of potential erosion from unvegetated, post-mining landscapes. MINErosion can best be used to answer the question; "How much hillslope erosion can I expect from a 1 in x (eg. 5, 10, 20) year storm, given a particular combination of media type, slope steepness and slope length?". Alternative design scenarios can then be evaluated, and design parameters selected, to achieve acceptable levels of soil erosion.
The laboratory-based methods and tools described in this thesis will greatly reduce the cost, effort, and time-frames associated with hillslope-scale erosion prediction.