Multielement geochemical modelling for pollution in the floodplains – quantifying the spatial relationship

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00027049%3A_____%2F18%3AN0000040" target="_blank" >RIV/00027049:_____/18:N0000040 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00027049:_____/18:N0000042

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Multielement geochemical modelling for pollution in the floodplains – quantifying the spatial relationship

Popis výsledku v původním jazyce

Whilst floodplain soils are renowned for their fertility attributable to nutrient inputs, the same enrichment process renders these soils vulnerable to contamination. Various pollution sources and (re)distributional processes may result in zones with distinct geochemical characteristics within the catchment. To visualise the catchment scale variability, which arises as a result of these processes, geochemical domains were defined using advisable subcompositions. Principal component analysis adapted to compositions was employed to understand this variability within the geochemical dataset from the Czech monitoring program supplying farmers with information on major nutrients in soil. After a spatial filtering of this dataset, we completed 130 samples with the comprehensive geochemical information on soil trace elements (Be, Cd, Co, Cr, Cu, Hg, Ni, Pb, V, Zn) in floodplains of the Eger River. The compositional covariance structure was then visually inspected for the spatial-suited patterns in the biplot as well as within the selected subcompositions in the ternary diagrams. For this, the data were classified according to the stream distance of the sampling sites from the river mouth. This explanatory practise proved the existence of some underlying spatial patterns of compositions along the river. Hence, we aimed at the quantitative measure of these spatial relations. For this purposes, the Aitchison distance matrix was related to the spatial matrices (stream and Euclidean distance matrices) using the Mantel correlation and the results were regionalised using the Mantel correlogram. The source-related interpretation of soil pollution implied that spatial connection and potential sources affinity were the main drivers of similarity in the observed patterns in the flood-prone soils.

Název v anglickém jazyce

Multielement geochemical modelling for pollution in the floodplains – quantifying the spatial relationship

Popis výsledku anglicky

Whilst floodplain soils are renowned for their fertility attributable to nutrient inputs, the same enrichment process renders these soils vulnerable to contamination. Various pollution sources and (re)distributional processes may result in zones with distinct geochemical characteristics within the catchment. To visualise the catchment scale variability, which arises as a result of these processes, geochemical domains were defined using advisable subcompositions. Principal component analysis adapted to compositions was employed to understand this variability within the geochemical dataset from the Czech monitoring program supplying farmers with information on major nutrients in soil. After a spatial filtering of this dataset, we completed 130 samples with the comprehensive geochemical information on soil trace elements (Be, Cd, Co, Cr, Cu, Hg, Ni, Pb, V, Zn) in floodplains of the Eger River. The compositional covariance structure was then visually inspected for the spatial-suited patterns in the biplot as well as within the selected subcompositions in the ternary diagrams. For this, the data were classified according to the stream distance of the sampling sites from the river mouth. This explanatory practise proved the existence of some underlying spatial patterns of compositions along the river. Hence, we aimed at the quantitative measure of these spatial relations. For this purposes, the Aitchison distance matrix was related to the spatial matrices (stream and Euclidean distance matrices) using the Mantel correlation and the results were regionalised using the Mantel correlogram. The source-related interpretation of soil pollution implied that spatial connection and potential sources affinity were the main drivers of similarity in the observed patterns in the flood-prone soils.

Druh

O - Ostatní výsledky

CEP obor

—

OECD FORD obor

10511 - Environmental sciences (social aspects to be 5.7)

Projekt

<a href="/cs/project/GA17-00859S" target="_blank" >GA17-00859S: Hodnocení dopadu rizikových prvků na životní prostředí, jejich pohyb a transformace v kontaminované oblasti</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů