Journal article
Catchment woodland planting and the benefits to flood reduction
- Abstract:
- Tree planting is considered to be an effective, low maintenance approach for reducing flood risk in catchments, primarily by interception, increasing water infiltration and surface roughness. Identifying optimal tree planting scenarios for hydrological benefits is an important aspect of developing wider and long-term woodland planting strategies in relation to natural flood management and nature-based solutions interventions. In this study, we apply a spatially distributed hydrological model to explore six different woodland planting scenarios that are limited to between 10% and 2% of the catchment area. We evaluate which approach is the most effective in reducing overland flow, reducing downstream flow volumes and flood peaks and delaying those peaks for three UK catchments: the Lowther, Ennerdale, and Colne valleys. We further explore whether the possibility of identifying target areas for tree planting can be achieved by exploring the physical properties of the areas of woodland that individually achieve the greatest flood attenuation. Large randomly located areas of planting are shown to have the highest overall benefit (10% peak flow reduction); however, planting schemes that focus on river corridors are more effective when considering the hydrological benefit per hectare (~2–3 times more effective). No single underlying characteristic or combination of characteristics are found to define better performing regions of planting, indicating that designing optimized planting schemes will be location specific, and require detailed modeling.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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- Files:
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(Preview, Version of record, pdf, 3.3MB, Terms of use)
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- Publisher copy:
- 10.1093/forestry/cpaf055
Authors
+ Natural Environment Research Council
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- Funder identifier:
- https://ror.org/02b5d8509
- Publisher:
- Oxford University Press
- Journal:
- Forestry More from this journal
- Article number:
- cpaf055
- Publication date:
- 2025-09-24
- Acceptance date:
- 2025-08-17
- DOI:
- EISSN:
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1464-3626
- ISSN:
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0015752X and 0015-752X
- Language:
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English
- Keywords:
- Source identifiers:
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3309596
- Deposit date:
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2025-09-24
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