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Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices
STUDY REGION: The Kamish River catchment (308 km(2)); a mountainous agricultural catchment under dry-land and rangeland farming located in Kermanshah province, in western Iran. STUDY FOCUS: The main objective of this study was to apportion sub-basin spatial source relative contributions to target ch...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686636/ https://www.ncbi.nlm.nih.gov/pubmed/31417849 http://dx.doi.org/10.1016/j.ejrh.2019.100613 |
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author | Raigani, Zeinab Mohammadi Nosrati, Kazem Collins, Adrian L. |
author_facet | Raigani, Zeinab Mohammadi Nosrati, Kazem Collins, Adrian L. |
author_sort | Raigani, Zeinab Mohammadi |
collection | PubMed |
description | STUDY REGION: The Kamish River catchment (308 km(2)); a mountainous agricultural catchment under dry-land and rangeland farming located in Kermanshah province, in western Iran. STUDY FOCUS: The main objective of this study was to apportion sub-basin spatial source relative contributions to target channel bed sediment samples using a composite fingerprinting procedure including a Bayesian un-mixing model. In total, thirty-four geochemical tracers, eleven elemental ratios and different weathering indices were measured or estimated for 43 tributary sediment samples collected to characterise three sub-basin spatial sediment sources and eleven target bed sediment samples collected at the outlet of the main basin. Statistical analysis was used to select three different composite signatures. NEW HYDROLOGICAL INSIGHTS FOR THE REGION: Using a composite signature based on KW-H and DFA, the respective relative contributions (with uncertainty ranges) from tributary sub-basins 1, 2 and 3 were estimated as 54.3% (47.8–62.0), 11.4% (4.2–18.7) and 34.3% (27.6–39.9), compared to 72.0% (61.6–82.7), 13.6% (9.0–18.5) and 14.2% (3.1–25.4) using a combination of KW-H and data mining, and 50.8% (42.8–59.9), 28.7% (20.2–37.3) and 20.3% (12.7–27.2) using a fingerprint selected by KW-H and PCCA. The root mean square difference between these source estimates highlighted sensitivity to the composite signatures. Evaluation of the un-mixing model predictions using virtual mixture tests confirmed agreement between modelled and known source proportions. |
format | Online Article Text |
id | pubmed-6686636 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier B.V |
record_format | MEDLINE/PubMed |
spelling | pubmed-66866362019-08-13 Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices Raigani, Zeinab Mohammadi Nosrati, Kazem Collins, Adrian L. J Hydrol Reg Stud Article STUDY REGION: The Kamish River catchment (308 km(2)); a mountainous agricultural catchment under dry-land and rangeland farming located in Kermanshah province, in western Iran. STUDY FOCUS: The main objective of this study was to apportion sub-basin spatial source relative contributions to target channel bed sediment samples using a composite fingerprinting procedure including a Bayesian un-mixing model. In total, thirty-four geochemical tracers, eleven elemental ratios and different weathering indices were measured or estimated for 43 tributary sediment samples collected to characterise three sub-basin spatial sediment sources and eleven target bed sediment samples collected at the outlet of the main basin. Statistical analysis was used to select three different composite signatures. NEW HYDROLOGICAL INSIGHTS FOR THE REGION: Using a composite signature based on KW-H and DFA, the respective relative contributions (with uncertainty ranges) from tributary sub-basins 1, 2 and 3 were estimated as 54.3% (47.8–62.0), 11.4% (4.2–18.7) and 34.3% (27.6–39.9), compared to 72.0% (61.6–82.7), 13.6% (9.0–18.5) and 14.2% (3.1–25.4) using a combination of KW-H and data mining, and 50.8% (42.8–59.9), 28.7% (20.2–37.3) and 20.3% (12.7–27.2) using a fingerprint selected by KW-H and PCCA. The root mean square difference between these source estimates highlighted sensitivity to the composite signatures. Evaluation of the un-mixing model predictions using virtual mixture tests confirmed agreement between modelled and known source proportions. Elsevier B.V 2019-08 /pmc/articles/PMC6686636/ /pubmed/31417849 http://dx.doi.org/10.1016/j.ejrh.2019.100613 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Raigani, Zeinab Mohammadi Nosrati, Kazem Collins, Adrian L. Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices |
title | Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices |
title_full | Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices |
title_fullStr | Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices |
title_full_unstemmed | Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices |
title_short | Fingerprinting sub-basin spatial sediment sources in a large Iranian catchment under dry-land cultivation and rangeland farming: Combining geochemical tracers and weathering indices |
title_sort | fingerprinting sub-basin spatial sediment sources in a large iranian catchment under dry-land cultivation and rangeland farming: combining geochemical tracers and weathering indices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686636/ https://www.ncbi.nlm.nih.gov/pubmed/31417849 http://dx.doi.org/10.1016/j.ejrh.2019.100613 |
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