Natural flood management, lag time and catchment scale: Results from an empirical nested catchment study

Andrew Black*, Leo Peskett, Alan MacDonald, Andy Young, Chris Spray, Tom Ball, Huw Thomas, Alan Werritty

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

23 Citations (Scopus)
13 Downloads (Pure)

Abstract

Natural flood management (NFM) techniques attract much interest in flood risk management science, not least because their effectiveness remains subject to considerable uncertainty, particularly at larger catchment and event scales. This derives from a paucity of empirical studies which can offer either longitudinal or comparison data sets in which changes can be observed. The Eddleston catchment study, with 13 stream gauges operated continuously over 9 years, is based on both longitudinal and comparison data sets. Two years of baseline monitoring have been followed by 7 years of further monitoring after a range of NFM interventions across the 69 km2 catchment. This study has examined changes in lag as an index of hydrological response which avoids dependence on potentially significant uncertainties in flow data. Headwater catchments up to 26 km2 showed significant delays in lag of 2.6–7.3 hr in catchments provided with leaky wood structures, on-line ponds and riparian planting, while larger catchments downstream and those treated with riparian planting alone did not. Two control catchments failed to show any such changes. The findings provide important evidence of the catchment scale at which NFM can be effective and suggest that effects may increase with event magnitude.

Original languageEnglish
Article numbere12717
JournalJournal of Flood Risk Management
Volume14
Issue number3
Early online date4 May 2021
DOIs
Publication statusPublished - Sept 2021

Keywords

  • catchment scale
  • Eddleston
  • empirical analysis
  • lag
  • natural flood management

ASJC Scopus subject areas

  • Environmental Engineering
  • Geography, Planning and Development
  • Safety, Risk, Reliability and Quality
  • Water Science and Technology

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