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Investigating the importance of recreational roads as a sediment source in a mountainous catchment using a fingerprinting procedure with different multivariate statistical techniques and a Bayesian un-mixing model

机译:使用具有不同多元统计技术和贝叶斯混合模型的指纹识别程序研究休闲道路作为山区流域沉积物来源的重要性

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摘要

Road construction associated with land development generally increases erosion and sediment yields. Construction of unpaved roads has the potential to alter hydro-sedimentological behavior and catchment sediment source dynamics and, to date, this has largely been investigated in forested environments. The objective of this study, therefore, was to assess the relative importance of unpaved recreational roads as a sediment source alongside hillslope surface soils and stream channel banks in a non-forested mountainous catchment in northern Tehran, Iran, using a fingerprinting procedure. Eleven geochemical tracers were measured on 27 samples collected to characterise the sediment sources and five suspended sediment samples collected at the study catchment outlet. The statistical analysis employed to select three different composite fingerprints for discriminating the sediment sources comprised: (1) the Kruskal–Wallis H test (KW-H), (2) a combination of KW-H and discriminant function analysis (DFA), and (3) a combination of KW-H and principal components & classification analysis (PCCA). A Bayesian un-mixing model was used to ascribe sediment source contributions using the three composite fingerprints. Using the KW-H composite signature, the respective relative contributions (with uncertainty ranges) from recreational roads, hillslope surface soils and channel banks were estimated as 64.5% (57.7–73.1), 1.1% (0.1–4.9), and 33.9% (24.9–41.0), compared to 55.3% (45.5–68.5), 1.9% (0.1–7.9) and 42.1% (27.8–52.4) using a composite signature selected using a combination of KW-H and DFA, or 82.0% (69.7–93.8), 8.2% (0.7–22.7) and 7.3% (0.7–21.0) using a fingerprint selected using KW-H and PCCA. The root mean square difference between the apportionment results using the fingerprints identified on the basis of the three different statistical approaches ranged from 5.5% to 25.7%, highlighting the sensitivity of source estimates to the tracers used. Regardless, the different composite signatures all suggested that unpaved recreational roads were the dominant source of the suspended sediment samples, underscoring the need for mitigation measures targeting these anthropogenic features of the catchment system, including closure to permit re-vegetation, surface ripping and/or mulching to improve infiltration or gravel re-surfacing to reduce exposure of bare surfaces to sediment mobilisation.
机译:与土地开发相关的道路建设通常会增加侵蚀和沉积物的产量。未铺砌的道路的建设有可能改变水成沉积行为和集水区沉积物源的动态,迄今为止,在森林环境中已对此进行了大量研究。因此,本研究的目的是使用指纹识别程序,评估伊朗北部德黑兰的一个非森林山区流域中,未铺砌的休闲道路作为沉积物源以及山坡地表土壤和河流通道堤岸的相对重要性。在收集的27个样品上测量了11个地球化学示踪剂以表征沉积物来源,并在研究集水口处收集了5个悬浮的沉积物样品。用于选择三种不同的复合指纹以区分沉积物来源的统计分析包括:(1)Kruskal–Wallis H检验(KW-H),(2)KW-H和判别函数分析(DFA)的组合,以及(3)KW-H与主成分和分类分析(PCCA)的结合。贝叶斯非混合模型用于使用三个复合指纹来归因于沉积物源贡献。使用KW-H复合特征,休闲道路,山坡表层土壤和河道堤岸的相对贡献(不确定范围)分别为64.5%(57.7–73.1),1.1%(0.1–4.9)和33.9%( 24.9–41.0),而使用KW-H和DFA组合选择的复合签名则为55.3%(45.5-68.5),1.9%(0.1–7.9)和42.1%(27.8-52.4),或82.0%(69.7) –93.8),使用KW-H和PCCA选择的指纹分别为8.2%(0.7-22.7)和7.3%(0.7-21.0)。使用基于三种不同统计方法确定的指纹的分配结果之间的均方根差在5.5%到25.7%之间,突显了源估计对于所使用的示踪剂的敏感性。无论如何,不​​同的复合特征都表明未铺设的休闲路是悬浮沉积物样品的主要来源,强调需要针对集水系统这些人为特征的缓解措施,包括封闭以允许重新植被,地表剥落和/或覆盖以改善渗透或砾石重铺以减少裸露表面对沉积物动员的暴露。

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