Abstract
Over recent decades, dissolved organic carbon (DOC) concentrations in rivers have increased across the Northern Hemisphere. Climate change contributes to altered thermal, hydrological, and biogeochemical processes. Understanding climatic drivers of DOC production and export is crucial to project future water discolouration and disinfection by-product formation risks. Using raw (untreated) water data from 127 Scottish river and lake catchments, carbon concentrations were related to climate parameters. Based on correlations of total organic carbon (as proxy for DOC), rainfall and temperature data, five “sensitivity” categories were identified. Climate projections using UKCP18 (2041–2060) enabled the identification of those catchments most susceptible to future DOC losses and the prioritisation of anticipatory adaptation actions. Catchments in southeast Scotland were particularly highlighted as at-risk due to summer rainfall reductions. This analysis supports an understanding of climate change risks and informs policy development on land management, water treatment investment, and adaptive management to maintain pre-treatment water quality and ecosystem resilience.
| Original language | English |
|---|---|
| Pages (from-to) | 1-15 |
| Number of pages | 15 |
| Journal | Hydrological Sciences Journal |
| Early online date | 15 Jan 2026 |
| DOIs | |
| Publication status | E-pub ahead of print - 15 Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 13 Climate Action
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SDG 15 Life on Land
Keywords
- annual accumulated temperature
- classification
- drinking water quality
- Spearman’s rank correlation
- summer effective rainfall
- total organic carbon
ASJC Scopus subject areas
- Water Science and Technology
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Dive into the research topics of 'Assessing climate change risks to dissolved organic carbon concentrations in drinking water sources using a catchment sensitivity approach'. Together they form a unique fingerprint.Datasets
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Climate change risk to raw water quality data set 5: TOC & climate data
Vorstius, C. (Creator), University of Dundee, 2023
DOI: 10.15132/10000201
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