Modelling the response of soft cliffs to climate change: A statistical, process-response model using accumulated excess energy

Hackney, Christopher; Darby, Stephen E.; Leyland, Julian

doi:10.1016/j.geomorph.2013.01.005

Cited by 53 publications

(53 citation statements)

References 66 publications

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“…The strength of the platform widening loop has been found to be O(−10 −4 to −10 Table 1, from Hackney et al 2013). The difference between the erosion rates with and without the feedback is O[0.75(1-0.999)~10 −4 ] which is well within the uncertainty of the erosion rates.…”

Section: Discussionmentioning

confidence: 66%

“…Since this decrease is not randomly distributed but consistent over time, by taking into account the cliff toe energy depletion loop, a systematic reduction of the erosion will eventually occur over large time scales. The differences between the estimated erosion with and without the feedback will be bigger than the actual position uncertainty, (O(±1.5 m) from Table 2 in Hackney et al 2013), by times scales on the order of 2000 to 4500 years. Other feedback loops, such as the beach cover protection loop have been found to have shorter associated time scales, suggesting stronger feedback strengths.…”

Section: Discussionmentioning

confidence: 90%

“…This applies over time scales encompassing multiple cycles of slumping and toe erosion. As noted by Hackney et al (2013) the decrease of correlation for the harder material within their dataset might indicate that the 10 years' time used to compute the erosion rates might be too short. We have assumed that the cliff retreats while keeping the platform slope constant.…”

Section: Discussionmentioning

confidence: 98%

“…Hackney et al (2013), proposed and validated with field data a simple relationship between soft cliff erosion rate and wave energy. Based on the premise that an 'Accumulated Excess Energy' (AEE) parameter can be used to represent the process of hydraulic erosion at the base of the cliff, the relationship between backwearing erosion rate and wave energy is given by;…”

Section: Strength Of Cliff Toe Energy Depletion Loopmentioning

confidence: 99%

“…Accordingly, it is important to ensure that the calibration of any model based on the principles of BEPC is conducted over a large enough temporal scale (i.e., multiple cycles of hydraulically controlled undercutting, mass wasting, and removal of the slumped debris) to ensure that hydraulic activity at the toe is the dominant factor controlling slope retreat. For a time scale of about 10 year, and for the different wave environments and geologies around the Isle of Wight and Suffolk coast in UK, Hackney et al (2013) found that Eq. (1) is best fitted by;…”

Section: Strength Of Cliff Toe Energy Depletion Loopmentioning

confidence: 99%

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Feedback structure of cliff and shore platform morphodynamics

Payo

Dickson

Walkden³

2014

J Coast Conserv

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It has been suggested that studies of geomorphological systems should identify potential system feedbacks, determine their direction of influence, and assess their relative importance. In this paper we show how a core set of processes and feedback loops can be distilled from existing literature on rock coast morphodynamics. The structure has been represented using Causal Loop Diagrams and a methodology to estimate the strength of a single feedback loop is presented. The backwearing erosion rate (cliff horizontal erosion) has been found to be controlled by at least four feedback loops; three balancing (cliff toe wave energy depletion, ground-water pore pressure diminution and cliff deposit protection) and one positive loop (abrasion enhancement). The downwearing erosion rate (vertical erosion) has been found to be controlled by at least three balancing feedback loops (weathering limited, shear depletion, cover-protection). Mean sea level directly influences the downwearing rate, through the water depth relative to the wave base, and indirectly influences the backwearing erosion rate through the wave energy dissipation that determines the amount of energy reaching the cliff toe. The offshore wave non-linearity parameter is proposed to capture the complex interaction between waves and shore platform geometries. The strength of the cliff toe energy depletion loop is assessed by reasoning on its causal pathway and found to be O(−10 −10 to −10 −4 ) for poorly lithified rock coasts. By understanding how the individual and overall feedback strengths are influenced by different future environmental and human intervention scenarios we could provide better assessment at the time scales needed for coastal management.

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Section: Discussionmentioning

confidence: 66%

Section: Discussionmentioning

confidence: 90%

Section: Discussionmentioning

confidence: 98%

Section: Strength Of Cliff Toe Energy Depletion Loopmentioning

confidence: 99%

Section: Strength Of Cliff Toe Energy Depletion Loopmentioning

confidence: 99%

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Feedback structure of cliff and shore platform morphodynamics

Payo

Dickson

Walkden³

2014

J Coast Conserv

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Storm Impacts on Cliffed Coastlines

Brooks

Spencer

2017

Coastal Storms

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Landscapes on the edge: examining the role of climatic interactions in shaping coastal watersheds using a coastal–terrestrial landscape evolution model

Hackney

Darby

Leyland

2014

Earth Surf Processes Landf

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Incised coastal gullies (ICGs) are dynamic features found at the terrestrial‐coastal interface. Their geomorphic evolution is driven by the interactions between processes of fluvial knickpoint migration and coastal cliff erosion. Under scenarios of future climate change the frequency and magnitude of the climatological drivers of both terrestrial (fluvial and hillslope) and coastal (cliff erosion) processes are likely to change, with an adjunct impact on these types of coastal features. Here we explore the response of an incised coastal gully to changes in both terrestrial and coastal climate in order to elucidate the key process interactions which drive ICG evolution. We modify an extant landscape evolution model, CHILD, to incorporate processes of soft‐cliff erosion. This modified version, termed the Coastal‐Terrestrial‐CHILD (CT‐CHILD) model, is then employed to explore the interactions between changing terrestrial and coastal driving forces on the future evolution of an ICG found on the south‐west Isle of Wight, UK. It was found that the magnitude and frequency of storm events will play a key role in determining the future trajectory of ICGs, highlighting a need to understand the role of event sequencing in future projections of landscape evolution. Furthermore, synergistic (positive) and antagonistic (negative) interactions were identified between coastal and terrestrial parameters, such as wave height intensity and precipitation duration, which act to modulate the impact of changes in any one parameter. Of note was the role played by wave height intensity in driving coastal erosion, which was found to play a more important role than sea‐level rise in determining rates of coastal erosion. This highlights the need for a greater focus on wave height in studies of soft‐cliff erosion. Copyright © 2014 John Wiley & Sons, Ltd.

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Modelling the response of soft cliffs to climate change: A statistical, process-response model using accumulated excess energy

Cited by 53 publications

References 66 publications

Feedback structure of cliff and shore platform morphodynamics

Feedback structure of cliff and shore platform morphodynamics

Storm Impacts on Cliffed Coastlines

Landscapes on the edge: examining the role of climatic interactions in shaping coastal watersheds using a coastal–terrestrial landscape evolution model

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