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SIGNATURES OF RESILIENCE IN HUMAN-ALTERED COASTAL SYSTEMS

Lead Research Organisation: University of Southampton
Department Name: Sch of Geography & Environmental Sci

Abstract

More than 85% of the world's coastline has been somehow altered by human activities. These activities and their consequences are concentrated in the Low Elevation Coastal Zone: a ribbon of coastal land below 10 m elevation that hosts as many as 1 billion people and a disproportionate share of the planet's physical infrastructure. Such pronounced exposure of people and infrastructure along low-lying coastlines means that these environments sustain severe impacts from coastal hazards (e.g., erosion, storm surge, flooding, sea-level rise). Moreover, population growth, infrastructural expansion, and climate change only make hazard impacts worse.

As coastal risk - defined as the exposure of people and infrastructure to natural hazards - has increased, so has broad scientific interest in coastal resilience, as an alternative to conventional engineering approaches to protecting human-altered coastlines from natural hazards.

Here, coastal resilience is defined as how a coastal system - the physical, ecological, and human components of a coastal environment, and the relationships among those components that sustain their functioning - recovers from disturbances, like extreme storms, over time. At the seaward edge of the Low Elevation Coastal Zone, environments characterised by beaches, dunes, floodplains, and wetlands take their physical shape from the storm events that they absorb. Despite their precarity to natural hazards, many low-lying coastlines are extensively built upon and intensively altered by human activities. However, human-altered coastlines are almost never examined as dynamic environments in their own right.

Understanding human-altered coastlines as dynamic systems is essential to predicting hazard impacts, anticipating effects of climate change, and reducing coastal risk. Previous work has used computer modelling to suggest that unlike their natural counterparts, human-altered coastlines evolve over time to become increasingly vulnerable to storm damage and functionally dependent on engineered hazard defences - thus rendering them less resilient than natural barriers. But that difference in how human-altered and natural coastlines evolve, and what that means for their resilience, has not yet been demonstrated and examined with observations and measurements from real places. This project addresses that gap, by testing theory with empirical evidence.

The aim of this project is to identify and measure indicators of resilience in human-altered and natural low-lying coastal settings around the world - all at the exposed, seaward edge of the Low Elevation Coastal Zone - using new methods for analysing decades of satellite imagery. I will measure the physical "signatures" that distinguish human-altered from natural coastlines, relate those physical signatures to patterns of coastal development over time, and combine that information to determine the relative "stability" of these human-altered versus natural coastal settings. This project will be first to quantify coastal resilience this way, and at this scale, derived entirely from observational data from real settings.

Overall, with its focus on human-altered coastlines and its novel analytical approach, this project will deliver new, observation-driven insights into resilience in vulnerable low-lying coastal environments worldwide. The methods and findings that emerge from this project will enable future interdisciplinary research into how coastal resilience could be deliberately enhanced in targeted, efficient, effective ways to reduce coastal risk.

Publications

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Sengupta D (2023) Rapid seaward expansion of seaport footprints worldwide in Communications Earth & Environment

 
Description What were the most significant achievements from the award? - The most significant achievements from this *exploratory award* were: (1) testing emerging satellite-derived shoreline change tools as a "superuser" and learning more about their current limitations; (2) pivoting to think laterally and creatively about the concept of resilience in human-altered coastal systems; (3) developing an exploratory agent-based numerical model of direct mechanised intervention into coastal hazard impacts, and using the model to extract dynamical signatures of resilience that may be tested empirically in future work.

To what extent were the award objectives met? If you can, briefly explain why any key objectives were not met - I had intended to create an empirical map of divergent shoreline-change dynamics on built versus "natural" coastal barrier systems, using an emerging tool for extracting shoreline position from ~four decades of satellite imagery. I soon found that the tool I intended to use - by Vos et al. (2019: https://doi.org/10.1016/j.envsoft.2019.104528) - requires far more manual intervention than is feasible for large-scale geospatial analysis or replicability. That led me to collaborating with a project team within the USGS on an improved tool called CoastSeg (https://github.com/SatelliteShorelines/CoastSeg - I am listed [@elazarus] as a "contributor"), for which I am a kind of "superuser" (deeply familiar with the concept and process, but involved at the downstream end of the tool development). The issue with CoastSeg (and many of these satellite-derived tools for shoreline detection) is that the signal of shoreline change it yields is exceedingly noisy - too noisy to be useful - and on low-sloping coastlines, very difficult to correct. Beach slope and tide correction becomes essential to determining shoreline position, but beach slope is highly variable and there are no spatio-temporal data suitable for corrections going back decades. Tide correction is also problematic, as tide models may be poorly aligned with local beach conditions as captured in a given satellite image. Tools for satellite-derived shoreline detection will continue to improve, but their progress is slower than the time scale of this award. The fundamental premise of this exploratory work remains valid: I could detect beach-nourishment signals even in the "uncorrected" shorelines, but at present there is no way to consider an extensive sample of natural versus human-altered shorelines in a methodologically consistent, reproducible way, using current state-of-the-art tools for satellite-derived shorelines.

When the empirical analysis proved less useful than I had hoped, I looked for a way to develop a exploratory numerical model that might capture and reflect some of the dynamics I had imagined would be evident in the satellite-derived shoreline data. I created DOZER, an exploratory numerical model of mechanised intervention in storm-driven coastal morphodynamics. In typological terms, DOZER is a participatory agent-based model of a complex adaptive system, in which the mechanisms for adaptive agent behaviour are handled by a human user rather than through evolutionary computation. The model is in late-stage development, but at the time of this report I am drafting a manuscript for submission in summer 2025; this award will be credited in that work.

How might the findings be taken forward and by whom? - My contributions as a CoastSeg "superuser" are helping inform tool development by the USGS project team. My contribution of a novel, exploratory complex adaptive system model that demonstrates signatures of resilience in a human-altered coastal system is already setting up new collaborative possibilities and opportunities for engagement. Primarily, because the model is a tool for insight, it has high potential to be used as a hands-on teaching exercise, and for working with practitioners (e.g., in workshops dedicated to considering future planning and management scenarios under climate-driven coastal change).
Exploitation Route Discussed above.
Sectors Education

Environment

 
Title Data for "Rapid seaward expansion of seaport footprints worldwide" 
Description Data used in "Rapid seaward expansion of seaport footprints worldwide" (Sengupta & Lazarus, 2023: https://doi.org/10.31223/X5SD3T). Data include five csv files: 'Sengupta_Lazarus_2023_F1_b' - total reclaimed area (km^2) in 2020, ranked by magnitude 'Sengupta_Lazarus_2023_F2_a' - normalised reclaimed area versus time for 68 seaports 'Sengupta_Lazarus_2023_F2_b' - series of ranks by different metrics: Lloyd's List 2020 (Lloyd's, 2021), total reclaimed area in 2020, area under normalised curves of reclaimed area through time, and coastal & cyclone hazard (Verschuur et al., 2023). 'Sengupta_Lazarus_rec_TEU_2011_2020' - data for container volume (in millions TEU) relative to reclamation area, 2011-2020; data for container volume sourced from UNCTD and the World Shipping Council. 'Sengupta_Lazarus_time_series_rec_data' - data (raw and smoothed) for seaport reclamation (km^2), 1990-2020 The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Mapping_Coastal_land_reclamation Code for plotting these data are available here: https://github.com/edlazarus/Seaports 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/7674076
 
Title Data for "Rapid seaward expansion of seaport footprints worldwide" 
Description [updated July 2023] This dataset comprises data and code used in "Rapid seaward expansion of seaport footprints worldwide" (Sengupta & Lazarus, 2023; preprint: https://doi.org/10.31223/X5SD3T). The data include four csv files: 'Sengupta_Lazarus_REC_1990_2020_v02.csv' - annual time series of seaward expansion (km^2) between 1990-2020 through coastal reclamation for 66 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed]. To produce the smoothed data, the raw data are passed through a Savitzky-Golay filter. 'Sengupta_Lazarus_REC_TEU_2011_2020_v02.csv' - annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011-2020 for 43 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed with a Savitzky-Golay filter], and TEU (millions), collated from archived Lloyd's List reports. 'Sengupta_Lazarus_REC_TEU_totals_v02.csv' - Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 66 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [smoothed with a Savitzky-Golay filter], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd's List rank in 2020 (Lloyd's List, 2021). 'Sengupta_Lazarus_2023_ports_excluded.csv' - contains list of 34 ports excluded from thus analysis because they are either not on an open coastline (e.g. estuarine, riverine) or expanded less than 1 km^2 seaward between 1990-2020. 'RECLAIM_port_trajectories_v7.ipynb' - Jupyter notebook for data wrangling and plotting figures presented in Sengupta & Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Mapping_Coastal_land_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/8158703
 
Title Data for "Rapid seaward expansion of seaport footprints worldwide" 
Description [updated July 2023] This dataset comprises data and code used in "Rapid seaward expansion of seaport footprints worldwide" (Sengupta & Lazarus, 2023; preprint: https://doi.org/10.31223/X5SD3T). The data include three csv files: 'Sengupta_Lazarus_REC_1990_2020_v02.csv' - annual time series of seaward expansion (km^2) between 1990-2020 through coastal reclamation for 66 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed]. To produce the smoothed data, the raw data are passed through a Savitzky-Golay filter. 'Sengupta_Lazarus_REC_TEU_2011_2020_v02.csv' - annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011-2020 for 43 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed with a Savitzky-Golay filter], and TEU (millions), collated from archived Lloyd's List reports. 'Sengupta_Lazarus_REC_TEU_totals_v02.csv' - Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 66 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [smoothed with a Savitzky-Golay filter], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd's List rank in 2020 (Lloyd's List, 2021). 'RECLAIM_port_trajectories_v7.ipynb' - Jupyter notebook for data wrangling and plotting figures presented in Sengupta & Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Mapping_Coastal_land_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/8158579
 
Title Data for "Rapid seaward expansion of seaport footprints worldwide" 
Description [updated November 2023] This dataset comprises data and code used in "Rapid seaward expansion of seaport footprints worldwide" (Sengupta & Lazarus, 2023; https://doi.org/10.1038/s43247-023-01110-y). This repository includes three .csv files, one .xlsx file, and a .ipynb file: 'Sengupta_Lazarus_REC_1990_2020_v05.csv' - annual time series of seaward expansion (km^2) between 1990-2020 through coastal reclamation for 65 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, and Reclaimed area (km^2) [raw measurement].  'Sengupta_Lazarus_REC_TEU_2011_2020_v03.csv' - annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011-2020 for 43 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and TEU (millions), collated from archived Lloyd's List reports. 'Sengupta_Lazarus_REC_TEU_totals_v04.csv' - Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 65 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd's List rank in 2020 (Lloyd's List, 2021). 'Sengupta_Lazarus_2023_ports_excluded_v2.xlsx' - contains list of 35 ports excluded from thus analysis because they are either not on an open coastline (e.g. estuarine, riverine) or expanded less than 1 km^2 seaward between 1990-2020. 'RECLAIM_port_trajectories_v11.ipynb' - Jupyter notebook for data wrangling and plotting figures presented in Sengupta & Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Seaport_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/doi/10.5281/zenodo.10201300
 
Title Data for "Rapid seaward expansion of seaport footprints worldwide" 
Description [updated November 2023] This dataset comprises data and code used in "Rapid seaward expansion of seaport footprints worldwide" (Sengupta & Lazarus, 2023; https://doi.org/10.1038/s43247-023-01110-y). This repository includes three .csv files, one .xlsx file, and a .ipynb file: 'Sengupta_Lazarus_REC_1990_2020_v05.csv' - annual time series of seaward expansion (km^2) between 1990-2020 through coastal reclamation for 65 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, and Reclaimed area (km^2) [raw measurement].  'Sengupta_Lazarus_REC_TEU_2011_2020_v03.csv' - annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011-2020 for 43 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and TEU (millions), collated from archived Lloyd's List reports. 'Sengupta_Lazarus_REC_TEU_totals_v04.csv' - Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 65 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd's List rank in 2020 (Lloyd's List, 2021). 'Sengupta_Lazarus_2023_ports_excluded_v2.xlsx' - contains list of 35 ports excluded from thus analysis because they are either not on an open coastline (e.g. estuarine, riverine) or expanded less than 1 km^2 seaward between 1990-2020. 'RECLAIM_port_trajectories_v11.ipynb' - Jupyter notebook for data wrangling and plotting figures presented in Sengupta & Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Seaport_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/doi/10.5281/zenodo.7674075
 
Title Data for "Rapid seaward expansion of seaport footprints worldwide" 
Description [updated October 2023] This dataset comprises data and code used in "Rapid seaward expansion of seaport footprints worldwide" (Sengupta & Lazarus, 2023; preprint: https://doi.org/10.31223/X5SD3T). The data include four csv files: 'Sengupta_Lazarus_REC_1990_2020_v05.csv' - annual time series of seaward expansion (km^2) between 1990-2020 through coastal reclamation for 66 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed]. To produce the smoothed data, the raw data are passed through a Savitzky-Golay filter. 'Sengupta_Lazarus_REC_TEU_2011_2020_v03.csv' - annual time series of seaward expansion (km^2) and reported container throughput (millions TEU) between 2011-2020 for 43 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Year, Seaport, Country, Region, Reclaimed area (km^2) [raw measurement], and Reclaimed area (km^2) [smoothed with a Savitzky-Golay filter], and TEU (millions), collated from archived Lloyd's List reports. 'Sengupta_Lazarus_REC_TEU_totals_v04.csv' - Simplified dataset listing total seaward expansion (km^2) and container throughput in 2020 for 66 of the world's top 100 container seaports in 2020, as ranked by reported container throughput (Lloyd's List, 2021). Dataset includes Seaport, Country, Region, Reclaimed area (km^2) [smoothed with a Savitzky-Golay filter], ranked list of seaports by expansion extent, and TEU (millions) handled in 2020, and Lloyd's List rank in 2020 (Lloyd's List, 2021). 'Sengupta_Lazarus_2023_ports_excluded.csv' - contains list of 34 ports excluded from thus analysis because they are either not on an open coastline (e.g. estuarine, riverine) or expanded less than 1 km^2 seaward between 1990-2020. 'RECLAIM_port_trajectories_v11.ipynb' - Jupyter notebook for data wrangling and plotting figures presented in Sengupta & Lazarus (2023). (Note that this notebook does not produce the map-based figures presented in that work.) The method for calculating reclaimed area over time in Google Earth Engine (GEE) is described in Sengupta et al. (2023), and the GEE code is available here: https://github.com/dhritirajsen/Seaport_reclamation These data and code are also available here: https://github.com/edlazarus/Seaports 
Type Of Material Database/Collection of data 
Year Produced 2023 
Provided To Others? Yes  
URL https://zenodo.org/record/8399137
 
Description "Of beaches and bulldozers" - public lecture for Head Tide Pub summer salon (Alna, Maine, USA) - August 2024 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Presented an evening "summer salon" lecture at a local pub gathering of ~40 people in Alna, Maine (USA). I presented work conceptually related to this award, which sparked discussion and questions afterward.
Year(s) Of Engagement Activity 2024
 
Description invited EuroCoast Zoominar presentation [online] (17 May 2024) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Professional Practitioners
Results and Impact Presented invited talk - "'Emergency landscaping' - morphodynamic interventions in coastal hazards" - for the EuroCoast Zoominar [online] (17 May 2024), on work conceptually related to this award; ~40 people in virtual attendance. Material sparked questions and discussion afterward, including preliminary plans to pursue follow-up funding with specific international colleagues.
Year(s) Of Engagement Activity 2024