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Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium)
Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614191/ https://www.ncbi.nlm.nih.gov/pubmed/34900423 http://dx.doi.org/10.7717/peerj.12494 |
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author | Georges, Blandine Michez, Adrien Piegay, Hervé Huylenbroeck, Leo Lejeune, Philippe Brostaux, Yves |
author_facet | Georges, Blandine Michez, Adrien Piegay, Hervé Huylenbroeck, Leo Lejeune, Philippe Brostaux, Yves |
author_sort | Georges, Blandine |
collection | PubMed |
description | Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events can be influenced by a set of environmental factors that reduce thermal sensitivity and (ii) the role played by those factors varies spatially. To test these hypotheses, we (i) determined which of the environmental variables reported to be the most influential affected WT and (ii)identified the spatial scales over which those environmental variables influenced WT. To this end, the influence of multi-scale environmental variables, namely land cover, topography (channel slope, elevation), hydromorphology (channel sinuosity, water level, watershed area, baseflow index) and shade conditions, was analyzed on the three model variables (day thermal sensitivity, night thermal sensitivity, and non-convective thermal flux) in the model developed by Georges et al. (2021) of the temporal thermal dynamics of daily maximum WT during extreme events. Values were calculated on six spatial scales (the entire upstream catchment and the associated 1 km and 2 km circular buffer, and 50 m wide corridors on each side of the stream with the associated 1 km and 2 km circular buffer). The period considered was 17 extreme days during the summer identified by Georges et al. (2021) based on WT data measured every 10 min for 7 years (2012–2018) at 92 measurement sites. Sites were located evenly throughout the Wallonia (southern Belgium) hydrological network. Results showed that shade, baseflow index (a proxy of the influence of groundwater), water level and watershed area were the most significant variables influencing thermal sensitivity. Since managers with finite financial and human resources can act on only a few environmental variables, we advocate restoring and preserving the vegetation cover that limits solar radiation on the watercourse as a cost-effective solution to reduce thermal sensitivity. Moreover, management at small spatial scale (50 m riparian buffer) should be strategically promoted (for finance and staffing) as our results show that a larger management scale is not more effective in reducing thermal sensitivity to extreme events. |
format | Online Article Text |
id | pubmed-8614191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-86141912021-12-09 Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) Georges, Blandine Michez, Adrien Piegay, Hervé Huylenbroeck, Leo Lejeune, Philippe Brostaux, Yves PeerJ Natural Resource Management Managers need to know how to mitigate rising stream water temperature (WT) due to climate change. This requires identifying the environmental drivers that influence thermal regime and determining the spatial area where interventions are most effective. We hypothesized that (i) extreme thermal events can be influenced by a set of environmental factors that reduce thermal sensitivity and (ii) the role played by those factors varies spatially. To test these hypotheses, we (i) determined which of the environmental variables reported to be the most influential affected WT and (ii)identified the spatial scales over which those environmental variables influenced WT. To this end, the influence of multi-scale environmental variables, namely land cover, topography (channel slope, elevation), hydromorphology (channel sinuosity, water level, watershed area, baseflow index) and shade conditions, was analyzed on the three model variables (day thermal sensitivity, night thermal sensitivity, and non-convective thermal flux) in the model developed by Georges et al. (2021) of the temporal thermal dynamics of daily maximum WT during extreme events. Values were calculated on six spatial scales (the entire upstream catchment and the associated 1 km and 2 km circular buffer, and 50 m wide corridors on each side of the stream with the associated 1 km and 2 km circular buffer). The period considered was 17 extreme days during the summer identified by Georges et al. (2021) based on WT data measured every 10 min for 7 years (2012–2018) at 92 measurement sites. Sites were located evenly throughout the Wallonia (southern Belgium) hydrological network. Results showed that shade, baseflow index (a proxy of the influence of groundwater), water level and watershed area were the most significant variables influencing thermal sensitivity. Since managers with finite financial and human resources can act on only a few environmental variables, we advocate restoring and preserving the vegetation cover that limits solar radiation on the watercourse as a cost-effective solution to reduce thermal sensitivity. Moreover, management at small spatial scale (50 m riparian buffer) should be strategically promoted (for finance and staffing) as our results show that a larger management scale is not more effective in reducing thermal sensitivity to extreme events. PeerJ Inc. 2021-11-22 /pmc/articles/PMC8614191/ /pubmed/34900423 http://dx.doi.org/10.7717/peerj.12494 Text en © 2021 Georges et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Natural Resource Management Georges, Blandine Michez, Adrien Piegay, Hervé Huylenbroeck, Leo Lejeune, Philippe Brostaux, Yves Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) |
title | Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) |
title_full | Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) |
title_fullStr | Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) |
title_full_unstemmed | Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) |
title_short | Which environmental factors control extreme thermal events in rivers? A multi-scale approach (Wallonia, Belgium) |
title_sort | which environmental factors control extreme thermal events in rivers? a multi-scale approach (wallonia, belgium) |
topic | Natural Resource Management |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8614191/ https://www.ncbi.nlm.nih.gov/pubmed/34900423 http://dx.doi.org/10.7717/peerj.12494 |
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