Challenges in Assessing Socio-Economic Impacts of SLR Nassos Vafeidis with contributions from G. Kaiser, B. Neumann and J. Hinkel

Outline SLR and Impacts Metrics/methods for assessing SLR s-e impacts Methodological, scale- and data-related issues: Population, Elevation, GDP Ideas & future needs EEA Meeting, Copenhagen 31.05.2018

(Source: Nicholls and Cazenave, 2010) Global Mean SLR Sea Level Rise SRES Scenarios 2000 to 2100 Vermeer and Rahmstorf (2009) Rahmstorf (2007) Source: IPCC 2001. Climate Change 2001: Synthesis Report. Contribution of Working Groups I, II and III to the Third Assessment Report of the Intergovernmental Panel on Climate Change [Watson,R.T et al. (eds.)]. Cambridge University Press, Cambridge, UK. p 74. Grinsted et al. (2009) (Source: Nicholls and Cazenave, 2010) EEA Meeting, Copenhagen 31.05.2018

Main Biophysical Effects Coastal Impacts The main biophysical effects of relative sea level rise Displacement of costal lowlands and wetlands Coastal erosion at Happisburgh, UK in 2009 (2) Mangroves, Thailand Increased coastal erosion Increased flooding (frequency and depth) SLR Coastal flooding, New York (1) Saltwater intrusion (in surface- and groundwaters) Others Rio de la Plata, Argentina (3) (1) http://www.erh.noaa.gov/okx/images/coastal.jpg (2) www.happisburgh.org.uk/press/edp060209.html (3) http://veimages.gsfc.nasa.gov/4874/Argentina.A2003026.1730.250m.jpg EEA Meeting, Copenhagen 31.05.2018

Area Exposure – Global Scale Areas below 10m of elevation EEA Meeting, Copenhagen 31.05.2018

Assessing Socio-Economic Impacts Population and Area Exposure: Global to Regional Scales Area: First-order assessment using elevation data No protection/adaptation is considered: Worst-case impacts Population density / counts (global datasets), combined with information on elevation Nightlights, ORL EEA Meeting, Copenhagen 31.05.2018

Assessing socio-economic Impacts DIVA Results People flooded under the A2 scenario without adaptation in 2100 People per country flooded & forced to migrate due to erosion under the A2 scenario, w/o adaptation, in 2100 Hinkel et al., 2010 EEA Meeting, Copenhagen 31.05.2018

Areas below 10m of elevation Area Exposure Areas below 10m of elevation EEA Meeting, Copenhagen 31.05.2018

Hydrological Connectivity Hydrological connectivity not considered Hydrologically connected areas EEA Meeting, Copenhagen 31.05.2018

Input Data Estimates of area and population exposure depend heavily on the datasets that are employed for the analyses Differences up to 150% in area estimates, around 10% for population for low elevations Differences become smaller with higher elevations Lichter et al., In Press EEA Meeting, Copenhagen 31.05.2018

Resolution of DEMs Aster orig (30m), MFC orig/ corrected (1m), SRTM orig, corr (90m) EEA Meeting, Copenhagen 31.05.2018

Surface Models vs Corrected Models DSM – Digital Surface Model DEM – Digital Elevation Model (corrected) EEA Meeting, Copenhagen 31.05.2018

Elevation Data Tendency to use high-resolution datasets These, do not always provide the best information Combine datasets, depending on the case study? EEA Meeting, Copenhagen 31.05.2018

Inundation Modelling Local Scale EEA Meeting, Copenhagen 31.05.2018

Inundation Modelling Local Scale Changes in water flux and inundated area. Large differences, depending on parameterisation Detailed inundation models offer a high degree of precision but are subject to severe limitations regarding their use at regional and global scales Flux EEA Meeting, Copenhagen 31.05.2018

Population Data Ambient population Time is important at night... ...and by day Ambient population Time is important Distribution of population (http://www.joelertola.com/grfx/index.html) EEA Meeting, Copenhagen 31.05.2018

Scenarios: night, day, season People exposure Improved population distribution using Land use classification Census data Information schools, hotels, hospitals, etc., survey Methods for distributing people: Dasymetric mapping Distribution of the people according to land use classes Scenarios: night, day, season EEA Meeting, Copenhagen 31.05.2018

Economic Impacts Damage costs under A2 in 2100, w/o adaptation DIVA Results Damage costs under A2 in 2100, w/o adaptation Adaptation cost in 2100, under A2 Hinkel et al., 2010 EEA Meeting, Copenhagen 31.05.2018

Economic Impacts DIVA Results Annual damage cost per country per year in 2100 w/o adaptation (left) and with adaptation: Rahmstorf BAU scenario Absolute (left) and annual adaptation cost in 2100 Countries are ranked as to their values under the Rahmstorf BAU scenario Hinkel et al., accepted EEA Meeting, Copenhagen 31.05.2018

GDP Data GDP density: Difficult to process globally Resolution still coarse compared to global population& elevation data (http://gecon.yale.edu/large-pixeled-contour-globe) EEA Meeting, Copenhagen 31.05.2018

Conclusions Scale and methods of analysis and use of data are inter- related issues A great deal of effort and resources are required for improving global and regional datasets Data should be employed with caution Methods exist for improving existing data and should be applied whenever possible EEA Meeting, Copenhagen 31.05.2018

Thank you for your attention Nassos Vafeidis “Coastal Risks and Sea-Level Rise” Research Group, Institute of Geography, Future Ocean Excellence Cluster, Christian-Albrechts University Kiel, Germany vafeidis@geographie.uni-kiel.de http://www.crslr.uni-kiel.de EEA Meeting, Copenhagen 31.05.2018