The potential for reference site resampling in estimating sediment redistribution and assessing landscape stability by the caesium-137 method
✍ Scribed by Ross A. Sutherland
- Book ID
- 101282501
- Publisher
- John Wiley and Sons
- Year
- 1998
- Tongue
- English
- Weight
- 275 KB
- Volume
- 12
- Category
- Article
- ISSN
- 0885-6087
No coin nor oath required. For personal study only.
✦ Synopsis
The objective of this study was to examine a new resampling methodology for estimating reference levels of 137 Cs in uneroded locations. Accurate and precise measurement of 137 Cs 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 dicult for land managers to make optimal decisions to ensure landscape sustainability. To determine the in¯uence of 137 Cs reference site sampling, particularly undersampling, 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 72 (+95% con®dence band) and a coecient of variation of 18%. The two approaches used to determine the eect 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 con®dence bands were calculated; and (2) random subsamples (n 3 to n 36) were selected from the total 137 Cs 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% con®dence bands were established. Caesium-137 activities determined from each approach were input into equations to estimate SRD from two cultivated ®elds. Results indicate that the one-time random sampling approach for subsamples of size 412 signi®cantly over-or under-estimated net SRD, particularly from the gently sloping agricultural ®eld. Computer-intensive resampling produced signi®cantly 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 ®elds into areas exhibiting erosion, stability and deposition, was better approximated for both ®elds by applying resampling.