Dynamic systems: modelling the coastal environment

Dr Andres Payo is a coastal geoscientist at the British Geological Survey. He specialises in applying quantitative geomorphology methods to coastal protection approaches to ensure that coastal communities continue to thrive in a sustainable manner. He is currently developing the Coastal Modelling Environment (CoastalME) software, which can simulate and predict coastal responses to human activity to inform stakeholders in coastal development and protection venture

Communicating simulation outputs of mesoscale coastal evolution to specialist and non-specialist audiences

Coastal geomorphologists and engineers worldwide are increasingly facing the non-trivial challenge of visualising and communicating mesoscale modelling assumptions, uncertainties and outcomes to both coastal specialists and decision-makers. Visualisation of simulation outcomes is a non-trivial problem because the more abstract scientific visualisation techniques favoured by specialists for data exploration and hypothesis-testing are not always as successful at engaging decision-makers and planners. In this paper, we show how the risk of simulation model outcomes becoming disconnected from more realistic visualisations of model outcomes can be minimised by using the Coastal Modelling Environment (CoastalME). CoastalME is a modelling framework for coastal mesoscale morphological modelling that can achieve close linkages between the scientific model abstractions, in the form of lines, areas and volumes, and the 3D representation of topographic and bathymetric surfaces and shallow sub-surface sediment composition. We propose and illustrate through the study case of Happisburgh (eastern England, UK), a transparent methodology to merge the required variety of data types and formats into a 3D-thickness model that is used to initialise a simulation. We conclude by highlighting some of the barriers to the adoption of the methodology proposed

Passive Seismic Surveys for Beach Thickness Evaluation at Different England (UK) Sites

In an era of environmental change leading to rising sea levels and increased storminess, there is a need to quantify the volume of beach sediment on the coast of Britain in order to assess the vulnerability to erosion using cheap, easy-to-deploy and non-invasive methods. Horizontal-to-vertical spectral ratio (HVSR) is a technique that uses the natural background seismic ‘noise’ in order to determine the depth of underlying geological interfaces that have contrasting physical properties. In this study, the HVSR technique was deployed at a number of settings on the coast of England that represented a range of different compositions, geomorphology, and underlying bedrock. We verified the results by comparison to other survey techniques, such as ground-penetrating RADAR, multichannel analysis of surface waves (MASW), and cone penetration tests. At locations where there was sufficient contrast in physical properties of the beach material compared to the underlying bedrock, the beach thickness (and therefore the volume of erodible material) was successfully determined, showing that HVSR is a useful tool to use in these setting

A Method to Extract Measurable Indicators of Coastal Cliff Erosion from Topographical Cliff and Beach Profiles: Application to North Norfolk and Suffolk, East England, UK

Recession of coastal cliffs (bluffs) is a significant problem globally, as around 80% of Earth’s coastlines are classified as sea cliffs. It has long been recognised that beaches control wave energy dissipation on the foreshore and, as a result, can provide protection from shoreline and cliff erosion. However, there have been few studies that have quantified the relationship between beach levels and cliff recession rates. One of the few quantitative studies has shown that there is a measurable relationship between the beach thickness (or beach wedge area (BWA) as a proxy for beach thickness) and the annual cliff top recession rate along the undefended coast of North Norfolk and Suffolk in eastern England, United Kingdom (UK). Additionally, previous studies also found that for profiles with low BWA, the annual cliff top recession rate frequency distribution follows a bimodal distribution. This observation suggests that as BWA increases, not only does cliff top recession rate become lower, but also more predictable, which has important implications for coastal stakeholders particularly for planning purposes at decadal and longer time scales. In this study, we have addressed some of the limitations of the previous analysis to make it more transferable to other study sites and applicable to longer time scales. In particular, we have automatised the extraction of cliff tops, toe locations, and BWA from elevation profiles. Most importantly, we have verified the basic assumption of space-for-time substitution in three different ways: (1) Extending the number or years analysed in a previous study from 11 to 24 years, (2) extending the number of locations at which cliff top recession rate and BWA are calculated, and (3) exploring the assumption of surface material remaining unchanged over time by using innovative 3D subsurface modelling. The present study contributes to our understanding of a poorly known aspect of cliff–beach interaction and outlines a quantitative approach that allows for simple analysis of widely available topographical elevation profiles, enabling the extraction of measurable indicators of coastal erosion

Modeling daily soil salinity dynamics in response to agricultural and environmental changes in coastal Bangladesh

Understanding the dynamics of salt movement in the soil is a prerequisite for devising appropriate management strategies for land productivity of coastal regions, especially low-lying delta regions, which support many millions of farmers around the world. At present, there are no numerical models able to resolve soil salinity at regional scale and at daily time steps. In this research, we develop a novel holistic approach to simulate soil salinization comprising an emulator-based soil salt and water balance calculated at daily time steps. The method is demonstrated for the agriculture areas of coastal Bangladesh (∼20,000 km2). This shows that we can reproduce the dynamics of soil salinity under multiple land uses, including rice crops, combined shrimp and rice farming, as well as non-rice crops. The model also reproduced well the observed spatial soil salinity for the year 2009. Using this approach, we have projected the soil salinity for three different climate ensembles, including relative sea-level rise for the year 2050. Projected soil salinity changes are significantly smaller than other reported projections. The results suggest that inter-season weather variability is a key driver of salinization of agriculture soils at coastal Bangladesh

Geometrical analysis of the inland topography to assess the likely response of wave-dominated coastline to sea level: application to Great Britain

The need for quantitative assessments at a large spatial scale (103 km) and over time horizons of the order 101 to 102 years have been reinforced by the 2019 Special Report on the Ocean and Cryosphere in a Changing Climate, which concluded that adaptation to a sea-level rise will be needed no matter what emission scenario is followed. Here, we used a simple geometrical analysis of the backshore topography to assess the likely response of any wave-dominated coastline to a sea-level rise, and we applied it along the entire Great Britain (GB) coastline, which is ca. 17,820 km long. We illustrated how the backshore geometry can be linked to the shoreline response (rate of change and net response: erosion or accretion) to a sea-level rise by using a generalized shoreline Exner equation, which includes the effect of the backshore slope and differences in sediment fractions within the nearshore. To apply this to the whole of GB, we developed an automated delineation approach to extract the main geometrical attributes. Our analysis suggests that 71% of the coast of GB is best described as gentle coast, including estuarine coastline or open coasts where back-barrier beaches can form. The remaining 39% is best described as cliff-type coastlines, for which the majority (57%) of the backshore slope values are negative, suggesting that a non-equilibrium trajectory will most likely be followed as a response to a rise in sea level. For the remaining 43% of the cliffed coast, we have provided regional statistics showing where the potential sinks and sources of sediment are likely to be

The role of data within coastal resilience assessments: an East Anglia, UK, case study

Embracing the concept of resilience within coastal management marks a step change in thinking, building on the inputs of more traditional risk assessments, and further accounting for capacities to respond, recover and implement contingency measures. Nevertheless, many past resilience assessments have been theoretical and have failed to address the requirements of practitioners. Assessment methods can also be subjective, relying on opinion-based judgements, and can lack empirical validation. Scope exists to address these challenges through drawing on rapidly emerging sources of data and smart analytics. This, alongside the careful selection of the metrics used in assessment of resilience, can facilitate more robust assessment methods. This work sets out to establish a set of core metrics, and data sources suitable for inclusion within a data-driven coastal resilience assessment. A case study region of East Anglia, UK, is focused on, and data types and sources associated with a set of proven assessment metrics were identified. Virtually all risk-specific metrics could be satisfied using available or derived data sources. However, a high percentage of the resilience-specific metrics would still require human input. This indicates that assessment of resilience is inherently more subjective than assessment of risk. Yet resilience assessments incorporate both risk and resilience specific variables. As such it was possible to link 75% of our selected metrics to empirical sources. Through taking a case study approach and discussing a set of requirements outlined by a coastal authority, this paper reveals scope for the incorporation of rapidly progressing data collection, dissemination, and analytical methods, within dynamic coastal resilience assessments. This could facilitate more sustainable evidence-based management of coastal regions

Responding to climate change around England's coast: the scale of the transformational challenge

Around the world coastal communities face an unprecedented challenge in responding to sea level rise and associated changes. For many responding through incremental adaptation may be appropriate (although not without limits). This may include progressively raising defences, nourishing beaches, and other conventional management measures. Such actions are well supported by existing governance structures and investment vehicles. For others however, continuing to provide protection from flooding may not be technically feasible or financially viable. For these communities, transformational adaptation will be needed (including realignment or relocation). Implementing transformational change, however, is difficult and requires a clarity of long-term planning and a means of supporting communities to take early action in making this transition

Sediment Thickness Model of Andalusia’s Nearshore and Coastal Inland Topography

This study represents the first attempt to map the sediment thickness spatial distribution along the Andalusian coastal zone by integrating various publicly available datasets. While prior studies have presented bedform- and sediment-type syntheses, none have attempted to quantify sediment thickness at the scale and resolution performed in this study. The study area has been divided into 18 physiographic zones, and we have used BGS Groundhog Desktop v2.6 software for 3D modeling and sediment thickness model calculations. We present here the modeling workflow, model results, and the challenges that we have encountered, including discrepancies in geological maps, difficulty managing data input for grain size/consolidation, and the need for additional geological information. We have compared the modeled sediment fractions of the unconsolidated material with 4194 seabed samples distributed along the study area and found that the differences between the modeled versus the sampled emphasized the importance of incorporating river contributions, particularly from the Guadalquivir River, into the model for more accurate results. The model intermediate and final outputs and the software routines used to query the sediment thickness model are provided as publicly accessible datasets and tools. The modeled sediment thickness could contribute to making quantitative predictions of morphological change at a scale that is relevant to longer-term strategic coastal management in Andalusia. The methodology and tools used for this study are transferable to any study area.CHAMFER project (NE/W004992/1