High-frequency spatial sediment source fingerprinting using in situ absorbance data

Sediment fingerprinting is a commonly applied approach to quantify catchment suspended sediment (SS) source contributions. However, due to the high workloads and costs involved in SS sampling and laboratory analyses, traditional procedures often result in a limited number of samples and sampling campaigns, which can hamper the capacity to capture the intra- and inter-storm variations in SS source activation and deactivation. A better understanding of the temporal dynamics in source contributions is needed, however, to improve the understanding of dynamic sediment generation and delivery processes for selecting management practices. In recognition of the extant need to improve high-frequency source estimates and to permit long duration measurement campaigns, the work reported herein presents a sediment fingerprinting procedure using UV–Vis absorbance spectra measured in situ with submersible spectrophotometer probes to estimate spatial SS source contributions based on a confluence-based monitoring strategy. The high-frequency (5-minute intervals) measurements were used to fingerprint SS sources during seven selected periods with varying hydrological conditions. Source apportionment estimates (MixSIAR model) were validated using an independent sediment budget. The results showed a mean deviation of 9.4 ± 6.0 %, compared with the sediment budget, for the seven periods combined (n = 7,282 time steps). The most accurate results (mean absolute error of 5.3 ± 4.3 %) were obtained for the period covering the July 2021 flood event in central Europe (return period for the monitored catchment > 20 years). Overall, modelled variations in SS source contributions mostly followed the sediment budget dynamics. This novel work highlights the potential for using spectrophotometer absorbance data for high-frequency and long-term sediment fingerprinting purposes. We argue that the presented method can lead to new opportunities to improve our understanding of SS sources and their dynamics.

Authors

Institutions

Publication Details

Journal
Journal of Hydrology
Published
2024-09-02
DOI
https://doi.org/10.1016/j.jhydrol.2024.131930
Citations
2
Primary Topic
Soil erosion and sediment transport
Type
article
Field-Weighted Citation Impact
0.67

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

High-frequency spatial sediment source fingerprinting using in situ absorbance data

Niels F. Lake, Peter J. Shaw, Núria Martínez‐Carreras, Adrian L. Collins
2 citations
Journal of Hydrology
Soil erosion and sediment transport
0.67
article

High-frequency spatial sediment source fingerprinting using in situ absorbance data

Niels F. Lake, Peter J. Shaw, Núria Martínez‐Carreras, Adrian L. Collins
article en
2 citations

Abstract

Sediment fingerprinting is a commonly applied approach to quantify catchment suspended sediment (SS) source contributions. However, due to the high workloads and costs involved in SS sampling and laboratory analyses, traditional procedures often result in a limited number of samples and sampling campaigns, which can hamper the capacity to capture the intra- and inter-storm variations in SS source activation and deactivation. A better understanding of the temporal dynamics in source contributions is needed, however, to improve the understanding of dynamic sediment generation and delivery processes for selecting management practices. In recognition of the extant need to improve high-frequency source estimates and to permit long duration measurement campaigns, the work reported herein presents a sediment fingerprinting procedure using UV–Vis absorbance spectra measured in situ with submersible spectrophotometer probes to estimate spatial SS source contributions based on a confluence-based monitoring strategy. The high-frequency (5-minute intervals) measurements were used to fingerprint SS sources during seven selected periods with varying hydrological conditions. Source apportionment estimates (MixSIAR model) were validated using an independent sediment budget. The results showed a mean deviation of 9.4 ± 6.0 %, compared with the sediment budget, for the seven periods combined (n = 7,282 time steps). The most accurate results (mean absolute error of 5.3 ± 4.3 %) were obtained for the period covering the July 2021 flood event in central Europe (return period for the monitored catchment > 20 years). Overall, modelled variations in SS source contributions mostly followed the sediment budget dynamics. This novel work highlights the potential for using spectrophotometer absorbance data for high-frequency and long-term sediment fingerprinting purposes. We argue that the presented method can lead to new opportunities to improve our understanding of SS sources and their dynamics.

Journal of HydrologyVol. 643
Rothamsted Research (GB), Luxembourg Institute of Science and Technology (LU), University of Southampton (GB)
Biotechnology and Biological Sciences Research Council
Openalex Percentile: Top 27%
Soil erosion and sediment transport
0.67
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.