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Dynamic adaptive policy pathways (DAPP) is emerging as a 'fit-for-purpose' method for climate-change adaptation planning to address widening future uncertainty and long planning timeframes. A key component of DAPP is to monitor indicators of change such as flooding and storm events, which can trigger timely adaptive actions (change pathway/behavior) ahead of thresholds. Signals and triggers are needed to support DAPP-the signal provides early warning of the emergence of the trigger (decision-point), and the trigger initiates the process to change pathway before a harmful adaptation-threshold is reached. We demonstrate a new approach to designing signals and triggers using the case of increased flooding as sea level continues to rise. The flooding frequency is framed in terms of probable timing of several events reaching a specific height threshold within a set monitoring period. This framing is well suited to adaptive planning for different hazards, because it allows the period over which threshold exceedances are monitored to be specified, and thus allows action before adaptation-thresholds are reached, while accounting for the potential range of timing and providing a probability of premature warning, or of triggering adaptation too late. For our New Zealand sea level case study, we expect early signals to be observed in 10 year monitoring periods beginning 2021. Some urgency is therefore required to begin the assessment, planning and community engagement required to develop adaptive plans and associated signals and triggers for monitoring. Worldwide, greater urgency is required at tide-dominated sites than those adapted to large storm-surges. Triggers can be designed with confidence that a change in behavior pathway (e.g. relocating communities) will be triggered before an adaptation-threshold occurs. However, it is difficult to avoid the potential for premature adaptation. Therefore, political, social, economic, or cultural signals are also needed to complement the signals and triggers based on coastal-hazard considerations alone.

Flooding in coastal areas is a major global hazard, made worse during compound flood events, which occur when multiple flood-drivers, such as tide, sea surge, and fluvial and pluvial flooding, coincide. We use 12 sea-level, 2065 rainfall, and 81 river-flow records to assess the dependence of (1) extreme skew-surge and extreme rainfall (pluvial/surface runoff) and (2) extreme skew-surge and extreme river-flow (fluvial discharge) in New Zealand. We found that (1) skew-surge and rainfall and (2) skew-surge and river-flow are significantly, but not strongly, correlated in NZ. When spatially averaged to within 30 km of sea-level gauge location, the correlation was generally significant and positive, but weak with Kendall’s rank correlation coefficient τ < 0.3. We identify the weather types driving regional patterns of dependence. Trough weather types were the dominant driver of individual and coincident extreme events. Blocking weather types were associated with the highest extreme skew-surge and rainfall events along the northeast coast of the North Island and, consequently, were associated with a high proportion of coincident skew-surge/rainfall and skew-surge/river-flow events there. These findings have important implications for flood management, emergency response, and the insurance sector because impacts and losses may be correlated in space. Our findings add to a growing understanding of compound flooding worldwide for different geographical and meteorological settings. The positive dependence observed suggests that more attention to compound event probabilities is warranted when undertaking localized coastal-flood modelling.

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.

Sea level anomaly extremes impact tropical Pacific Ocean islands, often with too little warning to mitigate risks. With El Niño, such as the strong 2015/16 event, comes weaker trade winds and mean sea level drops exceeding 30 cm in the western Pacific that expose shallow-water ecosystems at low tides. Nearly opposite climate conditions accompany La Niña events, which cause sea level high stands (10–20 cm) and result in more frequent tide- and storm-related inundations that threaten coastlines. In the past, these effects have been exacerbated by decadal sea level variability, as well as continuing global sea level rise. Climate models, which are increasingly better able to simulate past and future evolutions of phenomena responsible for these extremes (i.e., El Niño–Southern Oscillation, Pacific decadal oscillation, and greenhouse warming), are also able to describe, or even directly simulate, associated sea level fluctuations. By compiling monthly sea level anomaly predictions from multiple statistical and dynamical (coupled ocean–atmosphere) models, which are typically skillful out to at least six months in the tropical Pacific, improved future outlooks are achieved. From this multimodel ensemble comes forecasts that are less prone to individual model errors and also uncertainty measurements achieved by comparing retrospective forecasts with the observed sea level. This framework delivers online a new real-time forecasting product of monthly mean sea level anomalies and will provide to the Pacific island community information that can be used to reduce impacts associated with sea level extremes.

Sea-level rise will cause erosion of land, deeper and increasingly frequent flooding and will eventually permanently inundate low-elevation land, forcing the adaptation of seaside communities to avoid or reduce risk. To inform adaptation planning, we quantified the effects of incremental relative sea-level rise (RSLR) on exposed land area, number and replacement value of buildings within Tauranga Harbour, New Zealand. The assessment compared three coastal hazards: flooding, permanent inundation and erosion. Increasingly frequent coastal flooding will be the dominant trigger for adaptation in Tauranga. In the absence of adaptation, coastal flooding, recurring at least once every 5 years on average, will overtake erosion as the dominant coastal hazard after about 0.15–0.2 m RSLR, which is likely to occur between the years 2038–2062 in New Zealand and will rapidly escalate in frequency and consequence thereafter. Coastal erosion will remain the dominant hazard for the relatively-few properties on high-elevation coastal cliffs. It will take 0.8 m more RSLR for permanent inundation to reach similar impact thresholds to coastal flooding, in terms of the number and value of buildings exposed. For buildings currently within the mapped 1% annual exceedance probability (AEP) zone, the flooding frequency will transition to 20% AEP within 2–3 decades depending on the RSLR rate, requiring prior adaptive action. We also compared the performance of simple static-planar versus complex dynamic models for assessing coastal flooding exposure. Use of the static-planar model could result in sea level thresholds being reached 15–45 years earlier than planned for in this case. This is compelling evidence to use dynamic models to support adaptation planning.

Knowledge of coastal hydrogeology and hazards as groundwater responds to sea‐level rise (SLR) can be improved through installation of shallow groundwater monitoring piezometers and continuous observations. Interpolation of site data enables mapping of the present‐day state of groundwater elevation, depth to groundwater (DTW), their temporal statistical variation, and differing spatial responses to tides and rainfall. Future DTW and its variability can be projected under increments of SLR, with assumptions and caveats, to show where and when episodic and/or permanent inundation can be expected. This methodology is outlined in a case study of Dunedin, New Zealand, which enabled comparison of rising groundwater's contribution to pluvial flooding and groundwater emergence with coastal inundation. Changes in relative land exposure with SLR shows evolution in flood hazard from current pluvial‐dominated events, into “flooding from below” and groundwater emergence, in advance of any overland coastal inundation. Dunedin exemplifies how groundwater transfers effects of SLR surprisingly far inland, but the lowest‐lying or shoreline‐proximal suburbs are not necessarily the most vulnerable. Unlike coastal inundation, rising groundwater is unconstrained by protective topography and presents as a creeping hazard, or contributor to hazards such as pluvial flooding, which can be widespread, occurring already and difficult to defend against. The empirical models contain assumptions and uncertainties important to the veracity of results and application. While conservative (“risk averse”) and a compromise from computationally expensive numerical solutions, their value is in providing the spatial and temporal precision needed for multi‐source hazard assessment and holistic adaptive planning. Plain Language Summary Groundwater is largely unseen and hence poorly understood. Near the coast, shallow groundwater is influenced by sea level. Understanding how it will respond to sea‐level rise is important for predicting hazard to coastal land. By installing monitoring devices and tracking water level changes over time, valuable information can be gathered on the local relationship between groundwater and the ocean. A case‐study from Dunedin, New Zealand, shows how groundwater and effects of tides and rainfall can be mapped. These present‐day observations are then used to model future shallowing of groundwater as sea levels rise. Initially this decreases land's ability to absorb rain, then starts flooding from below and causing a range of possible problems while still below ground, before eventually emerging as springs and flooding areas above the land surface. Groundwater‐related flood risks extend far inland and depend on the slope of both groundwater and land, not just proximity to the coast. The scientific approach proposed here enables insight into local groundwater dynamics and associated hazards, that differ from direct inundation overland from the sea. The models do contain important assumptions and come with uncertainties, but the approach provides information critical for planning and managing multiple hazards in coastal regions. Key Points Shallow groundwater is a poorly understood hazard that will convey the effects of sea‐level rise far inland Empirical data and geospatial models of groundwater rise can enable multi‐hazard forecasts of episodic and permanent flooding Subsurface storage depletion, emergent groundwater and coastal inundation are variable potential factors in flood hazard over time

Coastal flooding is a major global hazard, yet few studies have examined the spatial and temporal characteristics of extreme sea level and associated coastal flooding. Here we analyse sea-level records around the coast of New Zealand (NZ) to quantify extreme storm-tide and skew-surge frequency and magnitude. We identify the relative magnitude of sea-level components contributing to 85 extreme sea level and 135 extreme skew-surge events recorded in NZ since 1900. We then examine the spatial and temporal clustering of these extreme storm-tide and skew-surge events and identify typical storm tracks and weather types associated with the spatial clusters of extreme events. We find that most extreme storm tides were driven by moderate skew surges combined with high perigean spring tides. The spring–neap tidal cycle, coupled with a moderate surge climatology, prevents successive extreme storm-tide events from happening within 4–10 d of each other, and generally there are at least 10 d between extreme storm-tide events. This is similar to findings from the UK (Haigh et al., 2016), despite NZ having smaller tides. Extreme events more commonly impacted the east coast of the North Island of NZ during blocking weather types, and the South Island and west coast of the North Island during trough weather types. The seasonal distribution of both extreme storm-tide and skew-surge events closely follows the seasonal pattern of mean sea-level anomaly (MSLA) – MSLA was positive in 92 % of all extreme storm-tide events and in 88 % of all extreme skew-surge events. The strong influence of low-amplitude (−0.06 to 0.28 m) MSLA on the timing of extreme events shows that mean sea-level rise (SLR) of similarly small height will drive rapid increases in the frequency of presently rare extreme sea levels. These findings have important implications for flood management, emergency response and the insurance sector, because impacts and losses may be correlated in space and time.

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.

Tide-surge interaction (TSI) is a critical factor in assessing flooding in shallow coastal systems, particularly in estuaries and harbours. Non-linear interactions between tides and surges can occur due to the water depth and bed friction. Global investigations have been conducted to examine TSI, but its occurrence and impact on water levels in Aotearoa New Zealand (NZ) have not been extensively studied. Water level observations from 36 tide gauges across the diverse coast of NZ were analysed to determine the occurrence and location of TSI. Statistical analysis and numerical modelling were conducted on data from both inside and outside estuaries, focusing on one estuary (Manukau Harbour) to determine the impact of TSI and estuarine morphology on the co-occurrence rate of extreme events. TSI was found to occur at most sites in NZ and primarily affects the timing of the largest surges relative to high tide. There were no regional patterns associated with the tide, non-tidal residual, or skew-surge regimes. The strongest TSI occurred in inner estuarine locations and was correlated with the intertidal area. The magnitude of the TSI varied depending on the method used, ranging from -16 cm to +27 cm. Co-occurrence rates of extreme water levels outside and inside the same estuary varied from 20% to 84%, with TSI modulating the rate by affecting tidal amplification. The results highlight the importance of investing in a more extensive tide gauge network to provide longer observations in highly populated estuarine coastlines. The incorporation of TSI in flooding hazard projections would benefit from more accurate and detailed observations, particularly in estuaries with high morphological complexity. TSI occurs in most sites along the coast of NZ and has a significant impact on water levels in inner estuarine locations. TSI modulates the co-occurrence rate of extreme water levels in estuaries of NZ by affecting tidal amplification. Therefore, further investment in the tide gauge network is needed to provide more accurate observations to incorporate TSI in flooding hazard projections.

A technique to produce high-water alerts from coinciding high astronomical tide and high mean sea level anomaly is demonstrated for the Pacific Islands region. Low-lying coastal margins are vulnerable to episodic inundation that often coincides with times of higher-than-normal high tides. Prior knowledge of the dates of the highest tides can assist with efforts to minimize the impacts of increased exposure to inundation. It is shown that the climate-driven mean sea level anomaly is an important component of total sea level elevation in the Pacific Islands region, which should be accounted for in medium-term (1–7 months) sea level forecasts. An empirical technique is applied to develop a mean sea level–adjusted high-water alert calendar that accounts for both sea level components and provides a practical tool to assist with coastal inundation hazard planning and management.