Preprints
https://doi.org/10.5194/egusphere-2022-198
https://doi.org/10.5194/egusphere-2022-198
06 May 2022
 | 06 May 2022

DSCIM-Coastal v1.0: An Open-Source Modeling Platform for Global Impacts of Sea Level Rise

Nicholas Depsky, Ian Bolliger, Daniel Allen, Jun Ho Choi, Michael Delgado, Michael Greenstone, Ali Hamidi, Trevor Houser, Robert E. Kopp, and Solomon Hsiang

Abstract. Global sea level rise (SLR) may impose substantial economic costs to coastal communities worldwide, but characterizing its global impact remains challenging because SLR costs depend heavily on natural characteristics and human investments at each location—including topography, the spatial distribution of assets, and local adaptation decisions. To date, several impact models have been developed to estimate global costs of SLR, yet the limited availability of open-source and modular platforms that easily ingest up-to-date socioeconomic and physical data sources limits the ability of existing systems to transparently incorporate new insights. In this paper, we present a modular open-source platform designed to address this need, providing end-to-end transparency from global input data to a scalable least-cost optimization framework that estimates adaptation and net SLR costs for nearly 10,000 global coastline segments and administrative regions. Our approach accounts both for uncertainty in the magnitude of global SLR and spatial variability in local relative sea level rise. Using this platform, we evaluate costs across 110 possible socioeconomic and SLR trajectories in the 21st century. We find annual global SLR costs of $180 billion to $200 billion in 2100 assuming optimal adaptation, moderate emissions (RCP 4.5) and middle-of-the-road (SSP 2) socioeconomic trajectories. Under the highest SLR scenarios modeled, this value ranges from $400 billion to $520 billion. We make this platform publicly available in an effort to spur research collaboration and support decision-making, with segment level physical and socioeconomic input characteristics provided at https://doi.org/10.5281/zenodo.6449231, source code for this dataset at https://doi.org/10.5281/zenodo.6456115, the modeling framework at https://doi.org/10.5281/zenodo.6453099, and model results at https://doi.org/10.5281/zenodo.6014086.

Nicholas Depsky et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-198', Goneri Le Cozannet, 05 Jun 2022
    • AC2: 'Reply on RC1', Ian Bolliger, 30 Apr 2023
  • RC2: 'Comment on egusphere-2022-198', Anonymous Referee #2, 27 Sep 2022
  • AC1: 'Author Comments - Response to Reviewers', Nicholas Depsky, 29 Oct 2022

Nicholas Depsky et al.

Nicholas Depsky et al.

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Short summary
This work presents a novel, open-source modelling platform and associated input dataset of physical and socioeconomic coastal characteristics for over 9,000 discrete segments of global coastlines for evaluating future sea-level rise (SLR) impacts. We performed an initial evaluation of estimated future costs under 110 different future scenarios of SLR and socioeconomic growth trajectories and estimate global annual costs from SLR to range from roughly $200–500 billion by the year 2100.