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首页> 外文期刊>Earth Surface Processes and Landforms: The journal of the British Geomorphological Research Group >High-temporal resolution fluvial sediment source fingerprinting with uncertainty: a Bayesian approach
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High-temporal resolution fluvial sediment source fingerprinting with uncertainty: a Bayesian approach

机译：具有不确定性的高温分辨率河流沉积物源指纹图谱：贝叶斯方法

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This contribution addresses two developing areas of sediment fingerprinting research. Specifically, how to improve the temporal resolution of source apportionment estimates whilst minimizing analytical costs and, secondly, how to consistently quantify all perceived uncertainties associated with the sediment mixing model procedure. This first matter is tackled by using direct X-ray fluorescence spectroscopy (XRFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analyses of suspended particulate matter (SPM) covered filter papers in conjunction with automatic water samplers. This method enables SPM geochemistry to be quickly, accurately, inexpensively and non-destructively monitored at high-temporal resolution throughout the progression of numerous precipitation events. We then employed a Bayesian mixing model procedure to provide full characterization of spatial geochemical variability, instrument precision and residual error to yield a realistic and coherent assessment of the uncertainties associated with source apportionment estimates. Applying these methods to SPM data from the River Wensum catchment, UK, we have been able to apportion, with uncertainty, sediment contributions from eroding arable topsoils, damaged road verges and combined subsurface channel bank and agricultural field drain sources at 60- and 120-minute resolution for the duration of five precipitation events. The results presented here demonstrate how combining Bayesian mixing models with the direct spectroscopic analysis of SPM-covered filter papers can produce high-temporal resolution source apportionment estimates that can assist with the appropriate targeting of sediment pollution mitigation measures at a catchment level. (c) 2015 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.
机译：该贡献解决了沉积物指纹研究的两个发展领域。具体而言，如何提高源头分配估算的时间分辨率，同时最大程度地减少分析成本，其次，如何始终如一地量化与沉积物混合模型过程相关的所有不确定性。通过使用直接X射线荧光光谱（XRFS）和漫反射红外傅里叶变换光谱（DRIFTS）分析悬浮颗粒物（SPM）覆盖的滤纸并结合自动水采样器解决了第一件事。这种方法使SPM地球化学能够在众多降水事件的整个过程中，以高时间分辨率快速，准确，廉价且无损地监测。然后，我们采用贝叶斯混合模型程序来提供空间地球化学变异性，仪器精度和残留误差的完整特征，以对与源分配估算相关的不确定性进行现实且一致的评估。将这些方法应用于来自英国温苏姆河流域的SPM数据，我们能够在不确定的情况下分配侵蚀的可耕层表土，损坏的道路边缘以及60-120和120-五个降水事件持续时间的分钟分辨率。此处呈现的结果表明，如何将贝叶斯混合模型与SPM覆盖的滤纸的直接光谱分析相结合，可以产生高时间分辨率的源分摊估算值，从而有助于在流域水平上适当地确定沉积物污染缓解措施。 （c）2015作者。约翰·威利父子有限公司（John Wiley＆Sons Ltd.）发布的《地球表面过程和地形》

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