Modelling regional geochemistry and As–Bi–Co–Cu–Fe–Ni mineralization using G-BASE in the Lake District, UK

Geochemical data for the UK Lake District including both Geochemical Baseline Survey of the Environment (G-BASE) stream sediment data and newly collected samples are shown here as a tool for modelling whole-rock geochemistry at a regional scale and as a case study for identifying potential As–Bi–Co–Cu–Fe–Ni mineralization. Regional whole-rock concentrations for the Skiddaw Group and Borrowdale Volcanic Group were modelled using G-BASE stream sediment data and found to align closely with newly collected in situ X-ray fluorescence measurements of host-rock samples. Average concentrations of elements such as Ag, Al, As, Fe, Ni and Ti differed by only 1–2 wt% or ∼20 ppm between the two datasets. Six areas identified by G-BASE as potential As–Co–Cu–Ni targets were visited. Of these, Keld and Devoke Water showed evidence for sulfide dissemination within the host rock rather than visible veins, while Black Combe, Seathwaite, Coniston and Tilberthwaite were confirmed to host vein-type, quartz–sulfide mineralization geochemically similar to known deposits at Dale Head North, Scar Crag and Ulpha. This study highlights the successful application of G-BASE data for regional geochemical modelling and exploration targeting. The workflow could be adapted for other areas covered by preexisting stream sediment geochemical data or integrated into exploration strategies for new regions.

Authors

Institutions

Publication Details

Journal
Geochemistry Exploration Environment Analysis
Published
2025-10-21
DOI
https://doi.org/10.1144/geochem2025-006
Primary Topic
Geochemistry and Geologic Mapping
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling regional geochemistry and As–Bi–Co–Cu–Fe–Ni mineralization using G-BASE in the Lake District, UK

Max Webb, Sean Johnson, Adam Eskdale, Amy Gough
Geochemistry Exploration Environment Analysis
Geochemistry and Geologic Mapping
article

Modelling regional geochemistry and As–Bi–Co–Cu–Fe–Ni mineralization using G-BASE in the Lake District, UK

Max Webb, Sean Johnson, Adam Eskdale, Amy Gough
article en

Abstract

Geochemical data for the UK Lake District including both Geochemical Baseline Survey of the Environment (G-BASE) stream sediment data and newly collected samples are shown here as a tool for modelling whole-rock geochemistry at a regional scale and as a case study for identifying potential As–Bi–Co–Cu–Fe–Ni mineralization. Regional whole-rock concentrations for the Skiddaw Group and Borrowdale Volcanic Group were modelled using G-BASE stream sediment data and found to align closely with newly collected in situ X-ray fluorescence measurements of host-rock samples. Average concentrations of elements such as Ag, Al, As, Fe, Ni and Ti differed by only 1–2 wt% or ∼20 ppm between the two datasets. Six areas identified by G-BASE as potential As–Co–Cu–Ni targets were visited. Of these, Keld and Devoke Water showed evidence for sulfide dissemination within the host rock rather than visible veins, while Black Combe, Seathwaite, Coniston and Tilberthwaite were confirmed to host vein-type, quartz–sulfide mineralization geochemically similar to known deposits at Dale Head North, Scar Crag and Ulpha. This study highlights the successful application of G-BASE data for regional geochemical modelling and exploration targeting. The workflow could be adapted for other areas covered by preexisting stream sediment geochemical data or integrated into exploration strategies for new regions.

Geochemistry Exploration Environment AnalysisVol. 26(1)
University College Dublin (IE), Royal Holloway University of London (GB), Heriot-Watt University (GB), Heriot-Watt University Malaysia (MY)
Openalex Percentile: Top 84%
Geochemistry and Geologic Mapping
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.