4.7 Article

Apportioning catchment scale sediment sources using a modified composite fingerprinting technique incorporating property weightings and prior information

期刊

GEODERMA
卷 155, 期 3-4, 页码 249-261

出版社

ELSEVIER
DOI: 10.1016/j.geoderma.2009.12.008

关键词

Sediment source fingerprinting; Uncertainty; Monte Carlo; Prior information; Sediment mitigation; Cross sector; England Catchment Sensitive Farming; Delivery Initiative

资金

  1. EU
  2. Environment Agency

向作者/读者索取更多资源

Sediment fingerprinting techniques provide a means of assembling valuable reliable information on the principal sources of sediment problems at catchment scale. However, there is a need to refine existing approaches to take account of a variety of sources of uncertainty and to incorporate prior information. To address this need,a modified mass balance model incorporating a Monte Carlo approach for representing the uncertainty surrounding source and sediment sampling, as well as weightings to take account of the within-source variability and discriminatory power of individual tracer properties and prior information on bank erosion, was used to apportion recent sediment sources in sub-catchments of the Somerset Levels, south west UK. Sensitivity tests confirmed that the precision of source apportionment was improved by incorporating the weightings and prior information into the mixing model. Estimates of the overall mean contributions from individual Source types, bounded by 95% confidence limits, were assessed to be 42 +/- 2% (pasture topsoils), 22 +/- 2% (cultivated topsoils), 22 +/- 1% (channel banks/subsurface sources), 12 +/- 2% (damaged road verges) and 2 +/- 1% (STWs). Respective estimates of net sediment delivery to water courses, Provided by integrating the Source ascription results with estimated sediment yield ranges and sub-catchment or land use areas, ranged between 33-829 kg ha(-1) yr(-1), 30-1995 kg ha(-1) yr(-1), 2-315 kg ha(-1) yr(-1), 0-217 kg ha(-1) yr(-1), and 0-28 kg ha(-1) yr(-1). Sediment fingerprinting should always include uncertainty analysis but on the understanding that the latter will be conditional on the assumptions used. (C) 2009 Elsevier B.V. All rights reserved.

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