Report on the Acceleration of Coastal Flood Risk and its Implications for Sustainable Development

Executive Summary

A comprehensive national study of New Zealand’s coastal communities reveals that the combined effects of global sea-level rise (SLR) and local vertical land motion (VLM) will significantly accelerate the timing and increase the magnitude of financial losses from coastal flooding over the next century. This analysis, which quantifies building-level financial risk, underscores the critical need to integrate localized geological data into climate adaptation strategies. The findings directly impact the achievement of several Sustainable Development Goals (SDGs), particularly SDG 11 (Sustainable Cities and Communities) and SDG 13 (Climate Action), by providing essential data for resilient infrastructure planning (SDG 9) and protecting vulnerable populations from climate-induced economic shocks (SDG 1).

Introduction and Alignment with Sustainable Development Goals

The increasing frequency and intensity of extreme sea-level (ESL) events, driven by climate change, pose a significant threat to global coastal populations. This report details a study conducted in New Zealand to assess the financial impact of episodic coastal flooding on buildings, considering both global SLR and local VLM. The research provides critical insights for developing robust adaptation strategies that align with the United Nations Sustainable Development Goals.

Core SDG Linkages:

• SDG 11 (Sustainable Cities and Communities): The study directly supports Target 11.5 by quantifying economic losses from disasters and Target 11.b by providing data to implement integrated policies for inclusion, resource efficiency, and disaster risk reduction.
• SDG 13 (Climate Action): By projecting future flood risks under different climate scenarios (SSPs), this work directly contributes to Target 13.1, which aims to strengthen resilience and adaptive capacity to climate-related hazards.
• SDG 9 (Industry, Innovation, and Infrastructure): The findings highlight vulnerabilities in existing infrastructure (buildings) and inform the need for developing quality, reliable, and resilient infrastructure as per Target 9.1.
• SDG 1 (No Poverty): Understanding and mitigating the financial risks of coastal flooding is crucial for preventing climate-induced poverty traps, aligning with the goal of eradicating poverty in all its forms.

Key Findings: A National and Sub-National Analysis

The study estimated financial losses for buildings over a 100-year period using a detailed risk model. The analysis compared scenarios with SLR alone against scenarios that also included local VLM, revealing significant disparities in risk profiles.

1. National-Level Impact of Vertical Land Motion

At a national scale, VLM exacerbates the financial risks posed by SLR.

1. Increased Financial Losses: The inclusion of VLM in projections increases the estimated national financial losses from 100-year coastal flood events by up to 15% by the year 2100 compared to projections based on SLR alone.
2. Accelerated Risk Timeline: VLM effectively brings forward the expected end-of-century financial losses by 10 to 12 years. This acceleration challenges existing timelines for adaptation and investment, impacting progress towards SDG 13.
3. Average Annualised Loss (AAL): Downward land motion (subsidence) increases the national AAL, causing the AAL projected for 2100 under SLR alone to occur 11-15 years earlier.

2. Sub-National Disparities and Localized Risk

The most significant findings emerge at the regional and territorial levels, where VLM dramatically alters local risk landscapes. This highlights the importance of localized data for achieving SDG 11’s goal of safe and resilient communities.

• Downward Land Motion (Subsidence):
  • In regions with significant subsidence (e.g., Wellington, Hawke’s Bay), annual losses could occur up to 25 years earlier than predicted by SLR-only models.
  • In Lower Hutt City, subsidence is projected to more than double the rate of AAL increase between 2080 and 2100, making it a critical hotspot for risk mitigation.
• Upward Land Motion (Uplift):
  • In regions experiencing uplift (e.g., Bay of Plenty), the onset of annual losses could be delayed by up to 19 years.
  • In Tauranga City, uplift extends the timeline for reaching the GMSLR-estimated AAL at 2100 by as much as 19 years, providing a longer window for adaptation planning.

Implications for Policy and Sustainable Development

The study’s findings have profound implications for policy, planning, and investment aimed at achieving sustainable development in coastal areas.

Recommendations for Action:

1. Integrate VLM into Risk Assessments: National and local authorities must incorporate high-resolution VLM data into all coastal hazard and risk assessments to avoid underestimating risk and misallocating resources. This is fundamental for evidence-based policymaking under SDG 11 and SDG 13.
2. Prioritize High-Risk Zones: The identification of areas with rapid subsidence allows for the prioritization of adaptation investments, such as resilient infrastructure (SDG 9), nature-based solutions, and managed retreat strategies.
3. Update Policy and Planning Guidance: Coastal policy statements and land-use planning regulations must be updated to reflect the accelerated risk timelines presented by VLM. This ensures that new developments are not placed in areas of escalating risk.
4. Asset-Level Risk Information: Providing risk information at the individual building level is critical for homeowners, insurers, and mortgage lenders to manage financial risk, contributing to economic stability and poverty prevention (SDG 1).

Conclusion

This research demonstrates unequivocally that vertical land motion is a critical, non-uniform factor that significantly influences the timing and severity of coastal flood risk. Overlooking VLM leads to a dangerously optimistic view of future risks. For New Zealand, and for coastal nations globally, incorporating local geological dynamics into climate change adaptation is not merely a technical improvement but a fundamental necessity for building truly sustainable and resilient communities. Achieving the targets set out in the Sustainable Development Goals, particularly those related to climate action (SDG 13) and sustainable cities (SDG 11), depends on a clear and accurate understanding of these localized, compounding risks.

Which SDGs are addressed or connected to the issues highlighted in the article?

Explanation

The article on coastal flood risk in New Zealand due to sea-level rise and vertical land motion directly addresses several Sustainable Development Goals. The analysis focuses on the socio-economic impacts of climate change on human settlements and infrastructure, aligning with the core principles of the following SDGs:

• SDG 11: Sustainable Cities and Communities: The study is centered on the vulnerability of “coastal communities” and “major coastal cities” to flooding. It assesses financial losses for “building objects” and discusses the exposure of urban areas, which is a key concern of SDG 11. The article states, “Populations residing in major coastal cities could experience annual financial losses of approximately US$52 billion by 2050.”
• SDG 13: Climate Action: The entire article is framed around the impacts of climate change. It analyzes future flood risks based on “global sea level rise (SLR) driven by climate change” and different “Shared Socio-economic Pathway (SSP) scenarios.” The core purpose is to provide data for “local adaptation strategies to mitigate socio-economic consequences under changing climate conditions,” which is central to SDG 13.
• SDG 9: Industry, Innovation and Infrastructure: The research quantifies the risk to critical infrastructure, specifically “buildings” and “infrastructure network components.” It discusses the need for mitigation interventions such as “levees, seawalls, flood gates.” This focus on assessing the vulnerability of existing infrastructure and informing the development of resilient alternatives is directly related to SDG 9.

What specific targets under those SDGs can be identified based on the article’s content?

Explanation

Based on the specific issues discussed, the following targets are directly relevant:

1. Target 11.5: “By 2030, significantly reduce the number of deaths and the number of people affected and substantially decrease the direct economic losses…caused by disasters, including water-related disasters…”
   • The article’s primary objective is to estimate “building financial losses for extreme sea level-driven flooding.” It provides detailed projections of “direct economic loss from coastal flooding,” such as the finding that “total potential losses to 100-year ARI flooding at present-day… are estimated at NZD$1.3 billion.” This directly contributes to understanding and mitigating the economic losses mentioned in Target 11.5.
2. Target 11.b: “By 2020, substantially increase the number of cities and human settlements adopting and implementing integrated policies and plans towards… adaptation to climate change, resilience to disasters…”
   • The study provides data that serves as a foundation for such policies. It notes that the analysis provides “important metrics for coastal hazard management as stipulated in the New Zealand Coastal Policy Statement,” demonstrating how scientific risk assessment can be integrated into national policies for disaster resilience, aligning with the goal of Target 11.b.
3. Target 13.1: “Strengthen resilience and adaptive capacity to climate-related hazards and natural disasters in all countries.”
   • The research is a direct effort to strengthen resilience by improving the understanding of climate-related hazards. The conclusion states that the findings “highlight the importance of including VLM in coastal flood risk assessments to inform risk mitigation location and timing under changing RSLs.” This information is crucial for enhancing the adaptive capacity of coastal communities.
4. Target 9.1: “Develop quality, reliable, sustainable and resilient infrastructure…to support economic development and human well-being…”
   • The article assesses the vulnerability of existing infrastructure (buildings) and the protective structures designed to defend them, such as levees. By calculating the “average annualised loss (AAL)” and identifying how “downward land motion will accelerate decreasing design levels for structures,” the study provides the necessary evidence to guide investment in more resilient infrastructure capable of withstanding future climate impacts.

Are there any indicators mentioned or implied in the article that can be used to measure progress towards the identified targets?

Explanation

The article mentions and calculates several quantitative metrics that can serve as direct or proxy indicators for the identified targets:

1. For Target 11.5 (Indicator 11.5.2: Direct economic loss…):
   • Directly Mentioned Indicator: The article is replete with calculations of direct economic loss. It estimates “financial losses” in New Zealand Dollars (NZD), “average annualised loss (AAL),” and “expected annual damage (EAD).” For example, it projects that “episodic flooding by the end of this century could cause national annual losses between NZD$0.9 billion… and NZD$1.5 billion.” These figures are a direct application of Indicator 11.5.2.
2. For Target 11.b (Indicator 11.b.1: …national disaster risk reduction strategies…):
   • Implied Indicator: The article refers to the “New Zealand Coastal Policy Statement,” which represents a national strategy for disaster risk reduction. The study’s role in providing “important metrics for coastal hazard management as stipulated” in this policy implies the implementation and refinement of such strategies, which is the focus of Indicator 11.b.1.
3. For Target 13.1 (Indicator 13.1.2: …national adaptation plans…):
   • Implied Indicator: The study’s entire purpose is to provide a scientific basis for adaptation. The “nationwide RSL projection database” and the analysis of “spatiotemporal shifts in expected losses” are tools designed to inform and improve national and local adaptation plans. The use of such risk assessments to “inform risk mitigation location and timing” is a measure of a country’s increasing ability to adapt.
4. For Target 9.1:
   • Implied Indicator: While there isn’t a single official indicator that fits perfectly, the article’s metrics on “building replacement value” and “financial losses from building structure damage” serve as an inverse indicator of infrastructure resilience. A high or increasing financial loss projection indicates low resilience. Therefore, tracking the “projected financial loss to buildings and infrastructure due to coastal flooding” can measure the resilience gap and the need for investment in line with Target 9.1.

Table of SDGs, Targets, and Indicators

Source: nature.com