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首页> 外文期刊>The Science of the Total Environment >Combining visible-based-color parameters and geochemical tracers to improve sediment source discrimination and apportionment
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Combining visible-based-color parameters and geochemical tracers to improve sediment source discrimination and apportionment

机译:结合可见光颜色参数和地球化学示踪剂以改善沉积物来源的判别和分配

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Parameter selection in fingerprinting studies are often time-consuming and costly because successful fingerprint properties are generally highly site-specific Recently, spectroscopy has been applied to trace sediment origin as a rapid, less expensive, non-destructive and straightforward alternative. We show in this study the first attempt to combine both geochemical tracers and color parameters derived from the visible (VIS) spectrum in a single estimate of sediment source contribution. Moreover, we compared the discrimination power and source apportionment using VIS-based-color parameters and using the whole ultra-violet-visible (UV-VIS) spectrum in partial last square regression (PLSR) models. This study was carried out in a small (1.19 km~2) rural catchment from southern Brazil. The sediment sources evaluated were crop fields, unpaved roads, and stream channels. Color parameters were only able to discriminate unpaved roads from the other sources, disabling its use to fingerprint sediment sources itself. Nonetheless, there was a great improvement in source discrimination combining geochemical tracers and color parameters. Unlike VIS-based-color parameters, the distances between sediment sources were always significantly different using the whole UV-VIS-spectrum. It indicates a loss of information and, consequendy, loss of discriminating power when using VIS-based-color parameters instead of the whole UV-VIS spectrum. Overall, there was good agreement in source ascription obtained with geochemical tracers alone, geochemical tracers coupled with color parameters, and UV-VIS-PLSR models, and all of them indicate clearly that the main sediment source was the crop fields, corresponding to 57 ± 14,48 ± 13, and 62 ± 18%, respectively. Prediction errors for UV-VIS-PLSR models (6.6 ± 1.1%) were very similar to those generated in a mixed linear model using geochemical tracers alone (6.4 ± 3.6%), but the combination of color parameters and geochemical tracers decreases the prediction error (5.4 ± 2.0%). Therefore, the use of VIS-based-color parameters combined to geochemical tracers can be a rapid and inexpensive way to improve source discrimination and precision of sediment source apportionment.
机译:指纹研究中的参数选择通常是耗时且昂贵的,因为成功的指纹特性通常是高度特定于地点的。最近,光谱法已被用作痕量沉积物的来源,是一种快速,廉价,无损且直接的替代方法。我们在这项研究中展示了将地球化学示踪剂和从可见(VIS)光谱得出的颜色参数结合在一起的首次尝试,它是对沉积物来源贡献的单一估计。此外,我们在部分最后平方回归(PLSR)模型中比较了基于VIS的颜色参数和整个紫外线(UV-VIS)光谱的分辨力和源分配。这项研究是在巴西南部的一个小乡村集水区(1.19 km〜2)中进行的。评估的沉积物来源是农田,未铺砌的道路和河道。颜色参数只能将未铺砌的道路与其他来源区分开,从而使其无法用于识别沉积物来源本身。尽管如此,结合地球化学示踪剂和颜色参数,在源识别方面有了很大的改进。与基于VIS的颜色参数不同,使用整个UV-VIS光谱,沉积物源之间的距离始终存在显着差异。当使用基于VIS的颜色参数而不是整个UV-VIS光谱时,它表明信息丢失,因此,也就失去了识别能力。总体而言,仅通过地球化学示踪剂,结合颜色参数的地球化学示踪剂和UV-VIS-PLSR模型获得的源归因有很好的一致性,所有这些都清楚地表明主要的沉积物来源是耕地,相当于57±分别为14,48±13和62±18%。 UV-VIS-PLSR模型的预测误差(6.6±1.1%)与仅使用地球化学示踪剂的混合线性模型中产生的预测误差(6.4±3.6%)非常相似,但是颜色参数和地球化学示踪剂的组合降低了预测误差(5.4±2.0%)。因此,结合使用基于VIS的颜色参数和地球化学示踪剂可以是一种快速而廉价的方法,可以提高源判别力和沉积物源分配的精度。

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