[1] Valley bottoms function as hydrological buffers that significantly affect runoff behavior. Distinguishing valley bottoms from hillslopes is an important first step in identifying and characterizing sediment deposits for hydrologic and geomorphic purposes. Valley bottoms occur at a range of scales from a few meters to hundreds of kilometers in extent. This paper describes an algorithm for using digital elevation models to identify valley bottoms based on their topographic signature as flat low-lying areas. The algorithm operates at a range of scales and combines the results at different scales into a single multiresolution index. This index classifies degrees of valley bottom flatness, which may be related to depth of deposit. The index can also be used to identify groundwater constrictions and to delineate hydrologic and geomorphic units.

Soil erosion is a major environmental issue in Australia. It reduces land productivity and has off-site effects of decreased water quality. Broad-scale spatially distributed soil erosion estimation is essential for prioritising erosion control programs and as a component of broader assessments of natural resource condition. This paper describes spatial modelling methods and results that predict sheetwash and rill erosion over the Australian continent using the revised universal soil loss equation (RUSLE) and spatial data layers for each of the contributing environmental factors. The RUSLE has been used before in this way but here we advance the quality of estimation. We use time series of remote sensing imagery and daily rainfall to incorporate the effects of seasonally varying cover and rainfall intensity, and use new digital maps of soil and terrain properties. The results are compared with a compilation of Australian erosion plot data, revealing an acceptable consistency between predictions and observations. The modelling results show that: (1) the northern part of Australia has greater erosion potential than the south; (2) erosion potential differs significantly between summer and winter; (3) the average erosion rate is 4.1 t/ha.year over the continent and about 2.9 × 109 tonnes of soil is moved annually which represents 3.9% of global soil erosion from 5% of world land area; and (4) the erosion rate has increased from 4 to 33 times on average for agricultural lands compared with most natural vegetated lands.

Analysis of the behavior of specific catchment area in a stream tube leads to a simple nonlinear differential equation describing the rate of change of specific catchment area along a flow path. The differential equation can be integrated numerically along a flow path to calculate specific catchment area at any point on a digital elevation model without requiring the usual estimates of catchment area and width. The method is more computationally intensive than most grid‐based methods for calculating specific catchment area, so its main application is as a reference against which conventional methods can be tested. This is the first method that provides a benchmark for more approximate methods in complex terrain with both convergent and divergent areas, not just on simple surfaces for which analytical solutions are known. Preliminary evaluation of the D8, M8, digital elevation model networks (DEMON), and D∞ methods indicate that the D∞ method is the best of those methods for estimating specific catchment area, but all methods overestimate in divergent terrain.

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