related to modeling of NNBF can be reduced through proper conceptualization of the FRM system, proper application of numerical models, improved numerical models, improved data describing NNBF response to hazards, and measurement of aspects of FRM performance across a greater range of conditions. Because NNBF initial condition (e.g., whether vegetation is growing or dormant and initial soil moisture) can affect NNBF performance, models of FRM performance should similarly be able to simulate performance under a range of likely conditions. Fragility curves (see “On the Concept of Failure” in Section 5.3.2.1) are commonly used to quantify the uncertainty in the response of structural measures in different condition states to different types of flood loading, but their application in FRM is often limited to one type of loading, and there are few examples of their application to NNBF (Jane et al. 2018; Gruhn et al. 2012). Accurate representation of fragility requires extensive modeling of a full range of possible condition states of the measure, as well as explicit characterization of all types of loading that can lead to failure (Jane et al. 2018). Because NNBF may have a larger range of possible condition states than structural measures due to natural variability, additional modeling scenarios may be required to fully represent NNBF fragility. Future work should focus on understanding the fragility of different common NNBF under different types of loadings to determine how performance varies. The dynamism of NNBF increases uncertainty of expected performance because the condition of the NNBF is not fixed and does not necessarily follow a monotonic trajectory of degradation like structural measures. As mentioned in Section 5.4, full integrated modeling of dynamic NNBF processes is not required, but the range of likely states should be described. Although NNBF are by definition dynamic, the natural variability related to the biotic components of NNBF is constrained by the habitat requirements of the biotic component and can be quantified. As mentioned previously, understanding the limiting conditions that constrain NNBF performance and modeling those boundaries can be used to determine a range of expected performance across a range of possible conditions. For example, beaches naturally vary in width and volume in response to seasonal changes and storm events. Rather than require each new project model performance for every possible beach and dune condition, Environment Agency in the United Kingdom defines several condition states for common beach-dune profiles that describe the expected performance of the system (Defra and EA 2013). A similar approach can be applied to other common NNBF types to provide more tools that can be used in project planning and monitoring. Adaptive management including routine maintenance can be used to further constrain NNBF natural variability and reduce the risk of FRM system failure to achieve performance standards. If some naturally occurring beach states are not able to deliver the required performance, then maintenance actions such as nearshore (shoreface) nourishment are taken to change the state to a condition able to provide the required performance. However, the maintenance
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