• Energy Research

Climate change and relative sea-level rise (RSLR) will increasingly expose coastal cities to coastal flooding, erosion, pluvial and fluvial flooding, episodic storm-tide flooding and eventually, permanent inundation. Tools are needed to support adaptive management approaches that allow society to adapt incrementally by making decisions now without creating path dependency and compromising decision-making options in the future. We developed an agent-based model that integrates climate-related physical hazard drivers and socio-economic drivers. We used it to explore how adaptive actions might be sequentially triggered within a low-elevation coastal city in New Zealand, in response to various climate change and socio-economic scenarios. We found that different adaptive actions are triggered at about the same RSLR level regardless of shared socio-economic pathway/representative concentration pathway scenario. The timing of actions within each pathway is dictated mainly by the rate of RSLR and the timing and severity of storm events. For the representative study site, the model suggests that the limits for soft and hard protection will occur around 30 cm RSLR, fully-pumped water systems are viable to around 35 cm RSLR and infrastructure upgrades and policy mechanisms are feasible until between 40 cm and 75 cm RSLR. After 75 cm RSLR, active retreat is the only remaining adaptation pathway.

Coastal flooding from extreme sea levels will increase in frequency and magnitude as global climate change forces sea-level rise (SLR). Extreme sea-level events, rare in the recent past (i.e., once per century), are projected to occur at least once per year by 2050 along many of the world’s coastlines. Information showing where and how built-environment exposure increases with SLR, enables timely adaptation before damaging thresholds are reached. This study presents a first national-scale assessment of New Zealand’s built-environment exposure to future coastal flooding. We use an analytical risk model framework, “RiskScape”, to enumerate land, buildings and infrastructure exposed to a present and future 100-year extreme sea-level flood event (ESL100). We used high-resolution topographic data to assess incremental exposure to 0.1 m SLR increases. This approach detects variable rates in the potential magnitude and timing of future flood exposure in response to SLR over decadal scales. National built-land and asset exposure to ESL100 flooding doubles with less than 1 m SLR, indicating low-lying areas are likely to experience rapid exposure increases from modest increases in SLR expected within the next few decades. This highlights an urgent need for national and regional actions to anticipate and adaptively plan to reduce future socio-economic impacts arising from flood exposure to extreme sea-levels and SLR.

Coastal hazards result from erosion of the shore, or flooding of low-elevation land when storm surges combine with high tides and/or large waves. Future sea-level rise will greatly increase the frequency and depth of coastal flooding and will exacerbate erosion and raise groundwater levels, forcing vulnerable communities to adapt. Communities, local councils and infrastructure operators will need to decide when and how to adapt. The process of decision making using adaptive pathways approaches, is now being applied internationally to plan for adaptation over time by anticipating tipping points in the future when planning objectives are no longer being met. This process requires risk and uncertainty considerations to be transparent in the scenarios used in adaptive planning. We outline a framework for uncertainty identification and management within coastal hazard assessments. The framework provides a logical flow from the land use situation, to the related level of uncertainty as determined by the situation, to which hazard scenarios to model, to the complexity level of hazard modeling required, and to the possible decision type. Traditionally, coastal flood hazard maps show inundated areas only. We present enhanced maps of flooding depth and frequency which clearly show the degree of hazard exposure, where that exposure occurs, and how the exposure changes with sea-level rise, to better inform adaptive planning processes. The new uncertainty framework and mapping techniques can better inform identification of trigger points for adaptation pathways planning and their expected time range, compared to traditional coastal flooding hazard assessments.

Episodic inundation from extreme sea-levels (ESLs) will have increasing social and economic impacts in response to relative sea level rise (RSLR). Despite the improved global understanding of ESL frequencies and magnitudes, detailed nationwide inundation maps are unavailable for many countries. This study quantifies New Zealand’s land area exposure to inundation from ESLs and RSLR by: (i) calculating ESL heights for nine annual recurrence intervals (ARI) between 2 and 1,000-years, (ii) converted into space-varying water surface grids, (iii) developing a composite topographical dataset comprised of Airborne Light Detection and Ranging (LIDAR) and bias corrected Shuttle Radar Topography Mission (SRTM), (iv) modifying topographical data to represent mitigation structures, and (v) executing a scalable static model to map land inundation areas for 0.1 m RSLR increments. This modular approach supports continuous integration of new models and data at resolutions appropriate for quantifying inundation hazard and risk trends. In response to 0.1 m–0.4 m RSLR expected in the New Zealand region from 2040 to 2070 under SSP5-8.5 global mean sea level rise scenarios, a rapid cumulative inundation area increase is observed for 10 and 100-year ESL ARIs at national and regional levels. The RSLR time independent maps developed here supports future investigations of ESL inundation hazards and risks for any prescribed RSLR heights or timeframes.