How groundwater time series and aquifer property data explain heterogeneity in the Permo-Triassic sandstone aquifers of the Eden Valley, Cumbria, UK
File(s)
Published version
Author(s)
Colyer, Alex
Butler, Adrian
Peach, Denis
Hughes, Andrew
Type
Journal Article
Abstract
A novel investigation of the impact of meteorological and geological heterogeneity within the Permo-Triassic Sandstone
aquifers of the River Eden catchment, Cumbria (UK), is described. Quantifying the impact of heterogeneity on the water
cycle is increasingly important to sustainably manage water resources and minimise food risk. Traditional investigations on
heterogeneity at the catchment scale require a considerable amount of data, and this has led to the analysis of available time
series to interpret the impact of heterogeneity. The current research integrated groundwater-level and meteorological time
series in conjunction with aquifer property data at 11 borehole locations to quantify the impact of heterogeneity and inform
the hydrogeological conceptual understanding. The study visually categorised and used seasonal trend decomposition by
LOESS (STL) on 11 groundwater and meteorological time series. Decomposition components of the diferent time series
were compared using variance ratios. Though the Eden catchment exhibits highly heterogeneous rainfall distribution, comparative analysis at borehole locations showed that (1) meteorological drivers at borehole locations are broadly homogeneous
and (2) the meteorological drivers are not sufcient to generate the variation observed in the groundwater-level time series.
Three distinct hydrogeological regimes were identifed and shown to coincide with heterogeneous features in the southern
Brockram facies, which is the northern silicifed region of the Penrith Sandstone and the St Bees Sandstone. The use of STL
analysis in combination with detailed aquifer property data is a low-impact insightful investigative tool that helps guide the
development of hydrogeological conceptual models.
aquifers of the River Eden catchment, Cumbria (UK), is described. Quantifying the impact of heterogeneity on the water
cycle is increasingly important to sustainably manage water resources and minimise food risk. Traditional investigations on
heterogeneity at the catchment scale require a considerable amount of data, and this has led to the analysis of available time
series to interpret the impact of heterogeneity. The current research integrated groundwater-level and meteorological time
series in conjunction with aquifer property data at 11 borehole locations to quantify the impact of heterogeneity and inform
the hydrogeological conceptual understanding. The study visually categorised and used seasonal trend decomposition by
LOESS (STL) on 11 groundwater and meteorological time series. Decomposition components of the diferent time series
were compared using variance ratios. Though the Eden catchment exhibits highly heterogeneous rainfall distribution, comparative analysis at borehole locations showed that (1) meteorological drivers at borehole locations are broadly homogeneous
and (2) the meteorological drivers are not sufcient to generate the variation observed in the groundwater-level time series.
Three distinct hydrogeological regimes were identifed and shown to coincide with heterogeneous features in the southern
Brockram facies, which is the northern silicifed region of the Penrith Sandstone and the St Bees Sandstone. The use of STL
analysis in combination with detailed aquifer property data is a low-impact insightful investigative tool that helps guide the
development of hydrogeological conceptual models.
Date Issued
2022-03-01
Date Acceptance
2021-12-03
Citation
Hydrogeology Journal, 2022, 30, pp.445-462
ISSN
0941-2816
Publisher
Springer
Start Page
445
End Page
462
Journal / Book Title
Hydrogeology Journal
Volume
30
Copyright Statement
© The Author(s) 2021
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000736445500001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Physical Sciences
Geosciences, Multidisciplinary
Water Resources
Geology
Heterogeneity
Time series analysis
Groundwater statistics
Conceptual models
UK
SYSTEM
Publication Status
Published
Date Publish Online
2021-12-31