The potential for reference site resampling in estimating sediment redistribution and assessing landscape stability by the caesium-137 method

The objective of this study was to examine a new resampling methodology for estimating reference levels of ¹³⁷Cs in uneroded locations. Accurate and precise measurement of ¹³⁷Cs is required from reference locations to estimate long-term (c. 40 years) sediment redistribution (SRD) and landscape stability. Without reliable long-term, quantitative erosion data it is extremely difficult for land managers to make optimal decisions to ensure landscape sustainability. To determine the influence of ¹³⁷Cs reference site sampling, particularly under-sampling, on SRD and landscape stability, two statistical approaches were applied to a grid-based data set. Caesium-137 inventories in the reference location (n=36) indicated that data were normally distributed, with a mean inventory of 2150±130 Bq m⁻² (±95% confidence band) and a coefficient of variation of 18%. The two approaches used to determine the effect of under sampling included: (1) one-time random subsampling from the total sample collected, subsamples ranged from n=3 to n=30; from these data means and parametric confidence bands were calculated; and (2) random subsamples (n=3 to n=36) were selected from the total ¹³⁷Cs reference sample, and each subsample was in turn resampled 1000 times with replacement to establish a sampling distribution of means. Thus, an empirically derived mean and 95% confidence bands were established. Caesium-137 activities determined from each approach were input into equations to estimate SRD from two cultivated fields. Results indicate that the one-time random sampling approach for subsamples of size ≤12 significantly over- or under-estimated net SRD, particularly from the gently sloping agricultural field. Computer-intensive resampling produced significantly better estimates of net SRD when compared with the random one-sample approach, especially when a subsample of size three was used. Landscape stability, based on partitioning the agricultural fields into areas exhibiting erosion, stability and deposition, was better approximated for both fields by applying resampling. © 1998 John Wiley & Sons, Ltd.