Modelling Long-Term Morphodynamics in Practice: Uncertainties and Compromises

Williams, Jon J.; Conduché, T.; Esteves, Luciana S.

doi:10.1142/9789814689977_0216

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…The second approach is the preferred, however, detailing a simulation to include all of the contributory coastal processes in full is not feasible, due to both limitation on data collection, resolution and also computer processing capability. Williams et al [17] states that a local conceptual understanding of sediment transport evolutionary behaviour is required for effective morphodynamic modelling at the decadal and centennial scale.…”

Section: Short Term or Event Based Modelling Of Morphology Has Been Successfullymentioning

confidence: 99%

Developing a Process Driven Morphological Model for Long Term Evolution of a Dynamic Coastal Embayment

O’Shea¹,

Murphy²

2020

OJMS

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Numerical modelling of coastal morphology is a complex and sometimes unrewarding exercise and often not yielding tangible results. Typically, the underlying drivers of morphology are not properly accounted for in numerical models. Such inaccuracies combined with a paucity of validation data create a difficulty for coastal planners/engineers who are required to interpret such morphological models to develop coastal management strategies. This study develops an approach to long term morphological modelling of a barrier beach system that includes the findings of over 10 years of coastal monitoring on a dynamic coastal system. The novel approach to predicting the long term evolution of the area combines a mix of short term hydrodynamic monitoring and long term morphological modelling to predict future changes in a breached barrier system. A coupled wave, wind, hydrodynamic and sediment transport numerical model was used to predict the coastal evolution in the dynamic barrier beach system of Inner Dingle Bay, Co. Kerry, Ireland. The modelling approach utilizes the schematisation of inputs to reflect observed trends. The approach is subject to two stages of validation both quantitative and qualitative. The study highlights the importance of considering all the parameters responsible for driving coastal evolution and the necessity to have long term monitoring results for trend based validation.

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Section: Short Term or Event Based Modelling Of Morphology Has Been Successfullymentioning

confidence: 99%

Developing a Process Driven Morphological Model for Long Term Evolution of a Dynamic Coastal Embayment

O’Shea¹,

Murphy²

2020

OJMS

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“…The results from the 06-GPS processing are further processed by software developed by TU Delft for NAM (Van Leijen et al, 2017). The objective of the software is: Decompose the continuous monitoring station time series into components including a secular trend, temperature influence, atmospheric loading, harmonic components, jumps and noise components; remove the components not related to ground deformation to obtain a clean series.Subsample the cleaned time series into one data point per year, coinciding with the mean epoch of the campaign measurements.Provide temperature corrections for the AWG-1 and AME-2 campaign measurements.Combine GPS and levelling data of the campaign clusters, and remove outliers.Compute the covariance matrix for the continuously operating and campaign monitoring stations using the model developed by Williams (2015). …”

Section: Measuring Subsidencementioning

confidence: 99%

“…Compute the covariance matrix for the continuously operating and campaign monitoring stations using the model developed by Williams (2015).…”

Section: Measuring Subsidencementioning

confidence: 99%

Subsidence in the Dutch Wadden Sea

Fokker

Leijen

Orlić

et al. 2018

Netherlands Journal of Geosciences

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Ground surface dynamics is one of the processes influencing the future of the Wadden Sea area. Vertical land movement, both subsidence and heave, is a direct contributor to changes in the relative sea level. It is defined as the change of height of the Earth's surface with respect to a vertical datum. In the Netherlands, the Normaal Amsterdams Peil (NAP) is the official height datum, but its realisation via reference benchmarks is not time-dependent. Consequently, NAP benchmarks are not optimal for monitoring physical processes such as land subsidence. However, surface subsidence can be regarded as a differential signal: the vertical motion of one location relative to the vertical motion of another location. In this case, the actual geodetic height datum is superfluous.In the present paper, we highlight the processes that cause subsidence, with specific focus on the Wadden Sea area. The focus will be toward anthropogenic causes of subsidence, and how to understand them; how to measure and monitor and use these measurements for better characterisation and forecasting; with some details on the activities in the Wadden Sea that are relevant in this respect. This naturally leads to the identification of knowledge gaps and to the formulation of notions for future research.

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“…When accounting for real coastal topography, the input data are usually 2D surveyed cross-sections of the coast, which are then integrated across multiple alongshore profiles to present a simplified 3D beach sediment budget [11]. As argued by [12], one of the main reasons why geomorphological models struggle to reproduce real-world behaviour in coastal settings is the predominance of short-term observations, which fail to understand the full character of longer-term morphological evolution, and therefore cannot fully quantify the main driving phenomena and constraints on coastal change [13]. Models accounting for more accurate long-term predictions of coastal change would, therefore, be useful, especially for site-specific cases where long-term 3D data are usually scarce [8].…”

Section: Introductionmentioning

confidence: 99%

Structure-from-Motion-Derived Digital Surface Models from Historical Aerial Photographs: A New 3D Application for Coastal Dune Monitoring

et al. 2020

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Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)- and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat.

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Modelling Long-Term Morphodynamics in Practice: Uncertainties and Compromises

Cited by 3 publications

References 15 publications

Developing a Process Driven Morphological Model for Long Term Evolution of a Dynamic Coastal Embayment

Developing a Process Driven Morphological Model for Long Term Evolution of a Dynamic Coastal Embayment

Subsidence in the Dutch Wadden Sea

Structure-from-Motion-Derived Digital Surface Models from Historical Aerial Photographs: A New 3D Application for Coastal Dune Monitoring

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