Simulations to optimize sampling of aeolian sediment transport in space and time for mapping

Abstract

The sampling frequency in space and time is often inadequate to estimate the accuracy and precision of aeolian sediment transport. The problem stems from a lack of knowledge about the spatial and temporal scale of variation in aeolian transport and is compounded by a shortage of resources (aeolian sediment traps and labour). This study developed a geostatistical methodology for estimating sediment transport at unsampled locations and tested the extent to which it was dependent on sampling networks (nested, grid and random) and frameworks (mobile or static sampling framework between wind erosion events). Aeolian transport data were collected in an area of Australia influenced by wind erosion (Diamantina Lakes National Park, southwestern Queensland) to evaluate the combination of events used for mapping transport. Insufficient wind erosion events occurred to test sediment sampling strategies and hence simulated sampling was conducted using maps of sediment transport produced with existing models of aeolian sediment transport in the same study area. Independent validation data were used to test the estimation performance.The results suggested that sampling networks that did not include information on the spatial scale of variation (i.e. grid and random sampling) did not represent adequately the sediment transport population. In contrast, a bespoke nested sampling network performed consistently better than the other networks. Overall the static framework with a nested network was recommended for estimation and mapping of sediment transport with few resources and was likely to be especially important for use over large areas. This approach has the advantage of requiring only a single pooled within-event variogram for sediment transport to be used to derive the model parameters for kriging or stochastic simulation for each event.