catchment

A dataset containing the different tracer properties of the different land uses in a Mediterranean catchment and one mixture sample located at the output of the catchment.
The variables are as follows:

datasets

Quantifies the provenance of the sediments in a catchment or study area. Based on a comprehensive characterization of the sediment sources and the end sediment mixtures a mixing model algorithm is applied to the sediment mixtures in order to estimate the relative contribution of each potential source. The package includes several statistical methods such as Kruskal-Wallis test, discriminant function analysis ('DFA'), principal component plot ('PCA') to select the optimal subset of tracer properties. The variability within each sediment source is also considered to estimate the statistical distribution of the sources contribution.

Ivan Lizaga

fingerPro

Sediment Source Fingerprinting

Borja Latorre

Leticia Gaspar

Ana Navas

Vince Q Vu

catchment function

A data frame with 22 rows and 23 variables:<dl class="dl-horizontal">
 <dt>id</dt><dd>reference number id of each sample analysed</dd>
 <dt>Land_Use</dt><dd>grouping variable, in this study refers to the different land uses in the catchment</dd>
 <dt>Pbex, K40, Bi214, Ra226, Th232, U238, Nb, Sr, Rb, Pb, Zn, Fe, Mn, Cr, V, Ti, Ca, K, Al, Si, Mg</dt><dd>value of the tracer property for each sample</dd>
</dl>

Format

Land use and fingerprinting properties in a Mediterranean catchment — catchment

A data frame with 22 rows and 23 variables:<dl class='dl-horizontal'>
 <dt>id</dt><dd>reference number id of each sample analysed</dd>
 <dt>Land_Use</dt><dd>grouping variable, in this study refers to the different land uses in the catchment</dd>
 <dt>Pbex, K40, Bi214, Ra226, Th232, U238, Nb, Sr, Rb, Pb, Zn, Fe, Mn, Cr, V, Ti, Ca, K, Al, Si, Mg</dt><dd>value of the tracer property for each sample</dd>
</dl>

catchment: Land use and fingerprinting properties in a Mediterranean catchment

Description

Usage

Arguments

Format