Sediment source fingerprinting: are we going in the right direction?

Owens, Philip N.

doi:10.1007/s11368-022-03231-x

Cited by 9 publications

(1 citation statement)

References 66 publications

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“…Composite fingerprinting methods have been extensively used in sediment source identification (Barthod et al, 2015; Huang et al, 2022; Lizaga et al, 2019; Poleto et al, 2009; J. Q. Zhang et al, 2017). The results of sediment source contributions obtained by the fingerprinting model can not only indicate the potential sources of sediment but also reflect the effectiveness of land management in the source areas and the quality of soil erosion control in different periods (Nosrati et al, 2014; Owens, 2022; Porto et al, 2011). As the questions of model‐relevant fingerprint datasets become complex, the verification of mixing model outputs becomes increasingly important (Gaspar et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Validating the accuracy of multiple sediment fingerprinting methods

Dai

Chen

et al. 2022

Land Degrad Dev

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Sediment source fingerprinting provides an effective and reliable way for targeted control of soil erosion. However, the accuracy of source contribution predictions of different fingerprinting methods has not been well verified, which affects the further application of these methods. Here, compared with the real sediment sources measured by indoor simulated scouring experiments, we verified the accuracy of two tracers (geochemical elements and n-alkanes) and three mixing models (Walling model, MixSIAR, and Landwehr model). The results showed that geochemical properties have high accuracy in identifying sediment sources, with the mean absolute error (MAE) ranging from 3.5%-5.9%, while poor results were shown for n-alkanes (MAE values 7.5%-45.7%). The Walling model and MixSIAR showed higher accuracy of contribution prediction, and the MAE was 3.5%-5.9% and 0.7%-3.5%, respectively.Although Landwehr also presented high accuracy of model output, it was relatively less robust compared with the former two mixing models (the MAE range was 3.8%-9.7%). Furthermore, the mixing model with three correction factors (particle size, organic matter (OM), and particle size with OM) showed poor output results for scouring experiments. This study provides a reference for the selection and determination of tracers, mixing models, and correction factors in field experiments.

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Section: Introductionmentioning

confidence: 99%

Validating the accuracy of multiple sediment fingerprinting methods

Dai

Chen

et al. 2022

Land Degrad Dev

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A new flow path: eDNA connecting hydrology and biology

URycki,

Kirtane,

Aronoff

et al. 2024

WIREs Water

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Environmental DNA (eDNA) has revolutionized ecological research, particularly for biodiversity assessment in various environments, most notably aquatic media. Environmental DNA analysis allows for non‐invasive and rapid species detection across multiple taxonomic groups within a single sample, making it especially useful for identifying rare or invasive species. Due to dynamic hydrological processes, eDNA samples from running waters may represent biodiversity from broad contributing areas, which is convenient from a biomonitoring perspective but also challenging, as hydrological knowledge is required for meaningful biological interpretation. Hydrologists could also benefit from eDNA to address unsolved questions, particularly concerning water movement through catchments. While naturally occurring abiotic tracers have advanced our understanding of water age distribution in catchments, for example, current geochemical tracers cannot fully elucidate the timing and flow paths of water through landscapes. Conversely, biological tracers, owing to their immense diversity and interactions with the environment, could offer more detailed information on the sources and flow paths of water to the stream. The informational capacity of eDNA as a tracer, however, is determined by the ability to interpret the complex biological heterogeneity at a study site, which arguably requires both biological and hydrological expertise. As eDNA data has become increasingly available as part of biomonitoring campaigns, we argue that accompanying eDNA surveys with hydrological observations could enhance our understanding of both biological and hydrological processes; we identify opportunities, challenges, and needs for further interdisciplinary collaboration; and we highlight eDNA's potential as a bridge between hydrology and biology, which could foster both domains.This article is categorized under: Science of Water > Hydrological Processes Science of Water > Methods Water and Life > Nature of Freshwater Ecosystems

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