Applying Principles of Uncertainty within Coastal Hazard Assessments to Better Support Coastal Adaptation

Abstract

Abstract: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.

Developing signals to trigger adaptation to sea-level rise

“…Rising sea level is already causing more frequent flooding along many coasts globally [1][2][3], and in future will greatly increase the frequency and consequences of flooding [1,4], and cause saltwater intrusion into groundwater and rivers, geomorphological adjustment of the coastline, rising groundwater levels and vegetation change [5]. Expected sea-level rise (SLR) of 0.5-2.0 m could displace 72-187 million people globally [6].…”

“…Expected sea-level rise (SLR) of 0.5-2.0 m could displace 72-187 million people globally [6]. Exposed communities must adapt to these consequences, but planning is complicated by deep uncertainty in the height and timing of storm-tides and SLR, which drive flooding [3,7,8]. We address a key supporting mechanism for implementing adaptation actions, by showing how early signals (warnings) and triggers (decision-points) can be designed to initiate adaptive action before coastal flooding reaches an adaptation-threshold beyond which undue harm occurs and costs of adaptation increase.…”

“…Adaptation-thresholds also relate to the coping capacity of people as service levels change and losses and harm occurs (figure 1). Adaptation-thresholds are often framed in terms of extreme events [18] that cause social disruption [14], but can be identified through community engagement [14,18,22] and/or detailed modelling and risk assessments [3,15,18] ahead of such events.…”

Coastal Sea Levels, Impacts and Adaptation

“…Le Cozannet et al [23] assess the translation of SLR information for efficient adaptation, while Stephens et al [24] offer a framework for uncertainty identification and management and show, by practical example, how flexibility in decision-making for adaptation to future hazards can be supported by maps of the degree of hazard exposure.…”

“…Stephens et al [24] explore the matter of uncertainty management for decision-making, with respect to coastal hazards and adaptation, addressing that near-term decisions need to build in flexibility, both in order to reduce exposure and to enable changes to actions, or pathways that can accommodate higher sea levels over longer timeframes. They outline a logical framework, starting from the land use situation, through the level of uncertainty, hazard scenarios in question, and complexity of the hazard modelling, to the decision (accept, adapt, or avoid).…”