The effectiveness of beach mega-nourishment, assessed over three management epochs

J Environ Manage. 2016 Dec 15;184(Pt 2):400-408. doi: 10.1016/j.jenvman.2016.09.090. Epub 2016 Oct 11.

Abstract

Resilient coastal protection requires adaptive management strategies that build with nature to maintain long-term sustainability. With increasing pressures on shorelines from urbanisation, industrial growth, sea-level rise and changing storm climates soft approaches to coastal management are implemented to support natural habitats and maintain healthy coastal ecosystems. The impact of a beach mega-nourishment along a frontage of interactive natural and engineered systems that incorporate soft and hard defences is explored. A coastal evolution model is applied to simulate the impact of different hypothetical mega-nourishment interventions to assess their impacts' over 3 shoreline management planning epochs: present-day (0-20 years), medium-term (20-50 years) and long-term (50-100 years). The impacts of the smaller interventions when appropriately positioned are found to be as effective as larger schemes, thus making them more cost-effective for present-day management. Over time the benefit from larger interventions becomes more noticeable, with multi-location schemes requiring a smaller initial nourishment to achieve at least the same benefit as that of a single-location scheme. While the longer-term impact of larger schemes reduces erosion across a frontage the short-term impact down drift of the scheme can lead to an increase in erosion as the natural sediment drift becomes interrupted. This research presents a transferable modelling tool to assess the impact of nourishment schemes for a variety of sedimentary shorelines and highlights both the positive and negative impact of beach mega-nourishment.

Keywords: Beach mega-nourishment; Coastal evolution model; Coastal resilience; Dungeness; Shoreline evolution; Shoreline management planning.

MeSH terms

  • Bathing Beaches
  • Climate Change
  • Conservation of Natural Resources / methods*
  • Ecosystem*
  • Models, Theoretical
  • United Kingdom