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ABSTRACT: Adaptation requires planning strategies that consider the combined effect of climatic and non-climatic drivers, which are deeply uncertain. This uncertainty arises from many sources, cascades and accumulates in risk estimates. A prominent trend to incorporate this uncertainty in adaptation planning is through adaptive approaches such as the dynamic adaptive policy pathways (DAPP). We present a quantitative DAPP application for coastal erosion management to increase its utilisation in this field. We adopt an approach in which adaptation objectives and actions have continuous quantitative metrics that evolve over time as conditions change. The approach hinges on an adaptation information system that comprises hazard and impact modelling and systematic monitoring to assess changing risks and adaptation signals in the light of adaptation pathway choices. Using an elaborated case study, we force a shoreline evolution model with waves and storm surges generated by means of stochastic modelling from 2010 to 2100, considering uncertainty in extreme weather events, climate variability and mean sea-level rise. We produce a new type of adaptation pathways map showing a set of 90-year probabilistic trajectories that link changing objectives (e.g., no adaptation, limit risk increase, avoid risk increase) and nourishment placement over time. This DAPP approach could be applied to other domains of climate change adaptation bringing a new perspective in adaptive planning under deep uncertainty. ; Alexandra Toimil acknowledges the financial support from the FENIX Project funded by the Government of Cantabria. This research was also funded by the Spanish Government through the grant RISKCOADAPT (BIA2017-89401-R).

This paper applies the DIVA model to assess the risk of and adaptation to sea-level rise for the European Union in the 21st century under the A2 and B1 scenarios of the Intergovernmental Panel on Climate Change. For each scenario, impacts are estimated without and with adaptation in the form of increasing dike heights and nourishing beaches. Before 2050, the level of impacts is primarily determined by socio-economic development. In 2100 and assuming no adaptation, 780×10

Climate change impacts on coastal zones could be significant unless adaptation is undertaken. One particular macro-economic dimension of sea level rise (SLR) impacts that has received no attention so far is the potential stress of SLR impacts on public budgets. Adaptation will require increased public expenditure to protect assets at risk and could put additional stress on public budgets. We analyse the macroeconomic effects of SLR adaptation and impacts on public budgets. We include fiscal indicators in a climate change impact assessment focusing on SLR impacts and adaptation costs using a computable general equilibrium model extended with a detailed description of the public sector. Coastal protection expenditure is financed issuing government bonds, meaning that coastal adaptation places an additional burden on public budgets. SLR impacts are examined using several scenarios linked to three different Representative Concentration Pathways: 2.6, 4.5 and 8.5, and two Shared Socio-economic Pathways: SSP2 and SSP5. Future projections of direct damages of mean and extreme SLR and adaptation costs are generated by the Dynamic Interactive Vulnerability Assessment framework. Without adaptation, all world regions suffer a loss and public deficits increase respect to the reference scenario. Higher deficits imply higher government borrowing from household savings reducing available resources for private investments therefore decreasing capital accumulation and growth. Adaptation benefits result from two mechanisms: i) the avoided direct impacts, and ii) a reduced public deficit effect. This allows for an increased capital accumulation, suggesting that support to adaptation in deficit spending might trigger positive effects on public finance sustainability.

This paper assesses the potential benefits of climate change mitigation in reducing the impacts of sea-level rise over the 21st century in G-20 countries (excluding the European Union as a whole), using the Dynamic Interactive Vulnerability Assessment model. Impacts of the expected number of people flooded annually and wetland losses were assessed. To assess the benefits of mitigation, it was assumed that defences were not upgraded during the study. Globally, with a sea-level rise of 0.68m by the 2080s (with respect to 1980-1999), representing a potential future with limited climate change mitigation, and with the SRES A1 socio-economic scenario, 123 million additional people could be flooded annually and 39% of present global wetland stock could be lost. For a 0.19m rise in sea-level, associated with a substantial reduction in emissions, the number of people flooded could reduce to 13 million per year, with 21% of global wetland stock loss, unless new wetlands emerge. Collectively, non-Annex 1 G-20 countries experience a disproportionate higher number of people flooded in their nations compared with the proportion of population flooded globally. The greatest wetland losses for G-20 countries are projected for Australia, Indonesia and the USA. Thus, G-20 nations with the highest emissions or gross domestic product, frequently do not experience the greatest impacts, despite some of these nations being potentially more able to pay for adaptation.

The Dynamic Interactive Vulnerability Assessment Wetland Change Model (DIVA_WCM) comprises a dataset of contemporary global coastal wetland stocks (estimated at 756 × 10^3 km^2 (in 2011)), mapped to a one-dimensional global database, and a model of the macro-scale controls on wetland response to sea-level rise. Three key drivers of wetland response to sea-level rise are considered: 1) rate of sea-level rise relative to tidal range; 2) lateral accommodation space; and 3) sediment supply. The model is tuned by expert knowledge, parameterised with quantitative data where possible, and validated against mapping associated with two large-scale mangrove and saltmarsh vulnerability studies. It is applied across 12,148 coastal segments (mean length 85 km) to the year 2100. The model provides better-informed macro-scale projections of likely patterns of future coastal wetland losses across a range of sea-level rise scenarios and varying assumptions about the construction of coastal dikes to prevent sea flooding (as dikes limit lateral accommodation space and cause coastal squeeze). With 50 cm of sea-level rise by 2100, the model predicts a loss of 46–59% of global coastal wetland stocks. A global coastal wetland loss of 78% is estimated under high sea-level rise (110 cm by 2100) accompanied by maximum dike construction. The primary driver for high vulnerability of coastal wetlands to sea-level rise is coastal squeeze, a consequence of long-term coastal protection strategies. Under low sea-level rise (29 cm by 2100) losses do not exceed ca. 50% of the total stock, even for the same adverse dike construction assumptions. The model results confirm that the widespread paradigm that wetlands subject to a micro-tidal regime are likely to be more vulnerable to loss than macro-tidal environments. Countering these potential losses will require both climate mitigation (a global response) to minimise sea-level rise and maximisation of accommodation space and sediment supply (a regional response) on low-lying coasts. ; The authors gratefully acknowledge funding from the European Union under contract number EVK2-2000-22024. They thank all their partners in the DINAS-COAST project Dynamic and Interactive Assessment of National, Regional and Global Vulnerability of Coastal Zones to Climate Change and Sea-level rise. We are grateful to staff at UNEP-WCMC for generous access to evolving databases on global coastal wetland extent: Jon Hutton, Hannah Thomas, Jan-Willem van Bochove, Simon Blyth and Chris McOwen. Current wetland databases held at WCMC build upon the pioneering efforts of Mark Spalding and Carmen Lacambra. ; This is the author accepted manuscript. The final version is available from Elsevier via http://dx.doi.org/10.1016/j.gloplacha.2015.12.018

China experiences frequent coastal flooding, with nearly US$ 77 billion of direct economic losses and over 7,000 fatalities reported from 1989 to 2014. Flood damages are likely to grow due to climate change induced sea-level rise and increasing exposure if no further adaptation measures are taken. This paper quantifies potential damage and adaptation costs of coastal flooding in China over the 21st Century, including the effects of sea-level rise. It develops and utilises a new, detailed coastal database of China developed within the Dynamic Interactive Vulnerability Assessment (DIVA) model framework. The refined database provides a more realistic spatial representation of coasts, with more than 2,700 coastal segments, covering 28,966 km of coastline. Over 50% of China's coast is artificial, representing defended coast and/or claimed land. Coastal flood damage and adaptation costs for China are assessed for different Representative Concentration Pathway (RCP) and Shared Socio-economic Pathways (SSP) combinations representing climate change and socio-economic change and two adaptation strategies: no upgrade of currently existing defences and maintaining current protection levels. By 2100, 0.7-20.0 million people may be flooded/yr and US$ 67-3,308 billion damages/yr are projected without upgrade to defences. In contrast, maintaining the current protection level would reduce those numbers to 0.2-0.4 million people flooded/yr and US$ 22-60 billion/yr flood costs by 2100, with a protection investment costs of US$ 8-17 billion/yr. In 2100, maintaining current protection levels, dikes costs are two orders of magnitude smaller than flood costs across all scenarios, even without accounting for indirect damages. This research improves on earlier national assessments of China by generating a wider range of projections, based on improved datasets. The information delivered in this study will help governments, policy-makers, insurance companies and local communities in China understand risks and design appropriate strategies to adapt to increasing coastal flood risk in an uncertain world.