FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912299658> ?p ?o ?g. }

• W2912299658 endingPage "96" @default.
• W2912299658 startingPage "78" @default.
• W2912299658 abstract "Reliable quantitative information about sediment sources is a key requirement for river catchment management, especially in settings with high sediment loads. This study explores the potential for using source fingerprinting techniques to establish the relative contribution of three sub-basins to the sediment deposited in a reservoir impounded by an earth dam located at the outlet of the Lavar watershed, in Hormozgan Province, southern Iran. The three sub-basins feeding the reservoir are characterized by complex topography and underlying geology. The source material and target sediment samples were analyzed for 53 potential geochemical tracers, including trace elements and rare earth elements (REEs) and their ratios. Stepwise discriminant function analysis (DFA) was applied to select optimum composite fingerprints from those fingerprint properties passing the range test and we compared two different modelling procedures to estimate the relative contribution of the three sub-basins to the sediment deposited in the reservoir. The first involves a Bayesian mixing model within a Markov Chain Monte Carlo framework (BM) and, the second, an un-mixing model within a Monte Carlo simulation framework (UM). The latter model permits the use of ratio properties, which represents a novel aspect of our study. Particular attention was directed to the uncertainty associated with the source contribution estimates provided by the two models. A goodness of fit estimator was employed to evaluate the results of the UM. Both modelling procedures demonstrated that the southern sub-basin was the main source of the majority of samples we collected from the reservoir. The BM model indicated that the central sub-basin was the dominant source of two samples (S6 and S8). Overall, the results provided by the BM model for the source of seven sediment samples (S1, S2, S3, S4, S5, S7 and S9) are compatible with those provided by the UM model and the central sub-basin was recognized as the most important source supplying sediment in the study area. Both approaches offer potential for using geochemical fingerprinting to quantify spatial sediment source contributions and the uncertainty associated with those estimates." @default.
• W2912299658 created "2019-02-21" @default.
• W2912299658 creator A5025171623 @default.
• W2912299658 creator A5043499560 @default.
• W2912299658 creator A5068310918 @default.
• W2912299658 creator A5069325081 @default.
• W2912299658 date "2019-05-01" @default.
• W2912299658 modified "2023-10-14" @default.
• W2912299658 title "Fingerprinting sources of reservoir sediment via two modelling approaches" @default.
• W2912299658 cites W1505314834 @default.
• W2912299658 cites W1517555081 @default.
• W2912299658 cites W1569961924 @default.
• W2912299658 cites W1580623970 @default.
• W2912299658 cites W1608524194 @default.
• W2912299658 cites W1916101866 @default.
• W2912299658 cites W1940460656 @default.
• W2912299658 cites W1972070902 @default.
• W2912299658 cites W1977376298 @default.
• W2912299658 cites W1977472753 @default.
• W2912299658 cites W1979587564 @default.
• W2912299658 cites W1981289397 @default.
• W2912299658 cites W1982918087 @default.
• W2912299658 cites W1984700711 @default.
• W2912299658 cites W1991190000 @default.
• W2912299658 cites W1994019761 @default.
• W2912299658 cites W1994782029 @default.
• W2912299658 cites W2001009258 @default.
• W2912299658 cites W2004682770 @default.
• W2912299658 cites W2039544721 @default.
• W2912299658 cites W2054575374 @default.
• W2912299658 cites W2054705476 @default.
• W2912299658 cites W2065775350 @default.
• W2912299658 cites W2071754162 @default.
• W2912299658 cites W2074536655 @default.
• W2912299658 cites W2075527217 @default.
• W2912299658 cites W2080338846 @default.
• W2912299658 cites W2092276841 @default.
• W2912299658 cites W2097980524 @default.
• W2912299658 cites W2111441677 @default.
• W2912299658 cites W2112556614 @default.
• W2912299658 cites W2115792662 @default.
• W2912299658 cites W2116193387 @default.
• W2912299658 cites W2137980061 @default.
• W2912299658 cites W2148634168 @default.
• W2912299658 cites W2160352226 @default.
• W2912299658 cites W2173576123 @default.
• W2912299658 cites W2255891306 @default.
• W2912299658 cites W2298869788 @default.
• W2912299658 cites W2400896631 @default.
• W2912299658 cites W2416827589 @default.
• W2912299658 cites W2509271748 @default.
• W2912299658 cites W2603269482 @default.
• W2912299658 cites W2611293014 @default.
• W2912299658 cites W2676340125 @default.
• W2912299658 cites W2750937951 @default.
• W2912299658 cites W2761194276 @default.
• W2912299658 cites W2783664392 @default.
• W2912299658 cites W2789273604 @default.
• W2912299658 cites W2800739582 @default.
• W2912299658 cites W2905769569 @default.
• W2912299658 doi "https://doi.org/10.1016/j.scitotenv.2019.01.327" @default.
• W2912299658 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/30710787" @default.
• W2912299658 hasPublicationYear "2019" @default.
• W2912299658 type Work @default.
• W2912299658 sameAs 2912299658 @default.
• W2912299658 citedByCount "25" @default.
• W2912299658 countsByYear W29122996582019 @default.
• W2912299658 countsByYear W29122996582020 @default.
• W2912299658 countsByYear W29122996582021 @default.
• W2912299658 countsByYear W29122996582022 @default.
• W2912299658 countsByYear W29122996582023 @default.
• W2912299658 crossrefType "journal-article" @default.
• W2912299658 hasAuthorship W2912299658A5025171623 @default.
• W2912299658 hasAuthorship W2912299658A5043499560 @default.
• W2912299658 hasAuthorship W2912299658A5068310918 @default.
• W2912299658 hasAuthorship W2912299658A5069325081 @default.
• W2912299658 hasConcept C105795698 @default.
• W2912299658 hasConcept C109007969 @default.
• W2912299658 hasConcept C111350023 @default.
• W2912299658 hasConcept C114793014 @default.
• W2912299658 hasConcept C119857082 @default.
• W2912299658 hasConcept C126645576 @default.
• W2912299658 hasConcept C127313418 @default.
• W2912299658 hasConcept C127413603 @default.
• W2912299658 hasConcept C146978453 @default.
• W2912299658 hasConcept C150547873 @default.
• W2912299658 hasConcept C187320778 @default.
• W2912299658 hasConcept C19499675 @default.
• W2912299658 hasConcept C204323151 @default.
• W2912299658 hasConcept C205649164 @default.
• W2912299658 hasConcept C2816523 @default.
• W2912299658 hasConcept C33923547 @default.
• W2912299658 hasConcept C39432304 @default.
• W2912299658 hasConcept C41008148 @default.
• W2912299658 hasConcept C58640448 @default.
• W2912299658 hasConcept C76886044 @default.
• W2912299658 hasConceptScore W2912299658C105795698 @default.
• W2912299658 hasConceptScore W2912299658C109007969 @default.

• next