This study forms part of a collaborative project designed to validate the long-term erosion predictions of the SIBERIA landform evolution model on rehabilitated mine sites. The SIBERIA catchment evolution model can simulate the evolution of landforms resulting from runoff and erosion over many years. SIBERIA needs to be calibrated before evaluating whether it correctly models the observed evolution of rehabilitated mine landforms. A field study to collect data to calibrate SIBERIA was conducted at the abandoned Scinto 6 uranium mine located in the Kakadu Region, Northern Territory, Australia. The data were used to fit parameter values to a sediment loss model and a rainfall–runoff model. The derived runoff and erosion model parameter values were used in SIBERIA to simulate 50 years of erosion by concentrated flow on the batters of the abandoned site. The SIBERIA runs correctly simulated the geomorphic development of the gullies on the man-made batters of the waste rock dump. The observed gully position, depth, volume, and morphology on the waste rock dump were quantitatively compared with the SIBERIA simulations. The close similarities between the observed and simulated gully features indicate that SIBERIA can accurately predict the rate of gully development on a man-made post-mining landscape over periods of up to 50 years. SIBERIA is an appropriate model for assessment of erosional stability of rehabilitated mine sites over time spans of around 50 years.
The recently released Shuttle Radar Topography Mission (SRTM) 3-arc second digital elevation data set provides a complete global coverage of the Earth's land surface. In this paper we examine the SRTM data for three catchments in Australia over a range of climates, geology and resultant geomorphology. To test this new data set the SRTM data are compared with high resolution digital elevation models. We use basic hydrological and geomorphological statistics and descriptors such as the area-slope relationship, cumulative area distribution and hypsometric curve, along with Strahler and networking statistics. The above measures describe the surface morphology of a catchment, therefore integrating catchment geology, climate and vegetation. The SRTM data were also assessed as input into the SIBERIA landscape evolution and soil erosion model as were runoff properties, using a wetness index. The results demonstrate that the 90 m SRTM data provide a poor catchment representation. Hillslopes appear as a linked set of facets and display little of the complex curvature that is observed in high resolution data. While catchment area-slope and areaelevation (hypsometry) properties are largely correct, catchment area, relief and shape (as measured by the width function) are poorly captured by the SRTM data. Catchment networking statistics are also variable. The large grid size of the SRTM data also results in incorrect drainage network patterns and different runoff properties. Consequently, care must be used for quantitative assessment of catchment hydrology and geomorphology, as in all cases SRTM-derived catchment area is incorrect and smaller digital elevation grid sizes are required for accurate catchment-wide assessment. While only a limited number of catchments have been examined, we believe our findings are applicable to other areas. © Crown Figure 1. Tin Camp Creek catchment with a high resolution 10 m by 10 m DEM (top), regridded 90 m by 90 m DEM (middle), and 90 m by 90 m SRTM DEM (bottom). is located in the wet/dry tropics region and has a climate very similar to Tin Camp Creek (Saynor et al., 2004). The catchment is located on the Arnhem Land sandstone plateau and flows to the Magela Creek floodplain. In this study we examine a major tributary of Swift Creek -East Tributary. The upper reaches of the study catchment flow through a sandstone-bedrock-confined channel on the plateau. The catchment then flows onto a wooded lowland Digital elevation models in catchment geomorphology and hydrology 1397 Figure 2. Swift Creek catchment with high resolution 20 m by 20 m DEM (top), regridded 90 m by 90 m DEM (middle), and 90 m by 90 m SRTM DEM (bottom). The 10 m grid digital elevation model for Tin Camp Creek displays well-rounded hillslope of regular curvature and hillslope length over the entire domain, and is well dissected by a regularly spaced drainage network (Figure 1). Digital elevation models in catchment geomorphology and hydrology 1401 Figure 4. Area-slope relationship for Tin Camp Creek (top), Swift Creek (middle) an...
Landscape evolution models provide a way to determine erosion rates and landscape stability over times scales from tens to thousands of years. The SIBERIA and CAESAR landscape evolution models both have the capability to simulate catchment-wide erosion and deposition over these time scales. They are both cellular, operate over a digital elevation model of the landscape, and represent fl uvial and slope processes. However, they were initially developed to solve research questions at different time and space scales and subsequently the perspective, detail and process representation vary considerably between the models. Notably, CAESAR simulates individual events with a greater emphasis on fl uvial processes whereas SIBERIA averages erosion rates across annual time scales. This paper describes how both models are applied to Tin Camp Creek, Northern Territory, Australia, where soil erosion rates have been closely monitored over the last 10 years. Results simulating 10 000 years of erosion are similar, yet also pick up subtle differences that indicate the relative strengths and weaknesses of the two models. The results from both the SIBERIA and CAESAR models compare well with independent fi eld data determined for the site over different time scales. Representative hillslope cross-sections are very similar between the models. Geomorphologically there was little difference between the modelled catchments after 1000 years but signifi cant differences were revealed at longer simulation times. Importantly, both models show that they are sensitive to input parameters and that hydrology and erosion parameter derivation has long-term implications for sediment transport prediction. Therefore selection of input parameters is critical. This study also provides a good example of how different models may be better suited to different applications or research questions.
Abstract:One year of instantaneous suspended sediment concentration, C, and instantaneous discharge, Q, data collected at Ngarradj downstream of the Jabiluka mine site indicate that the use of a simple C-Q rating curve is not a reliable method for estimating suspended sediment loads from the Ngarradj catchment. The C-Q data are not only complicated by hysteresis effects within the rising and falling stages of individual events, but also by variable depletion of available suspended sediment through multipeaked runoff events.Parameter values were fitted to an event-based suspended sediment load-Q relationship as an alternative to the C-Q relationship. Total suspended sediment load and Q data for 10 observed events in the Ngarradj stream catchment were used to fit parameter values to a suspended sediment load-Q relationship, using (a) log-log regression and (b) iterative parameter fitting techniques. A more reliable and statistically significant prediction of suspended sediment load from the Ngarradj catchment is obtained using an event-based suspended sediment load-Q relationship. Fitting parameters to the event-based suspended sediment load-Q relationship using iterative techniques better predicts longterm suspended sediment loads compared with log-log regression techniques.
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