skip to main content

Title: Multiple climate change-driven tipping points for coastal systems
Abstract As the climate evolves over the next century, the interaction of accelerating sea level rise (SLR) and storms, combined with confining development and infrastructure, will place greater stresses on physical, ecological, and human systems along the ocean-land margin. Many of these valued coastal systems could reach “tipping points,” at which hazard exposure substantially increases and threatens the present-day form, function, and viability of communities, infrastructure, and ecosystems. Determining the timing and nature of these tipping points is essential for effective climate adaptation planning. Here we present a multidisciplinary case study from Santa Barbara, California (USA), to identify potential climate change-related tipping points for various coastal systems. This study integrates numerical and statistical models of the climate, ocean water levels, beach and cliff evolution, and two soft sediment ecosystems, sandy beaches and tidal wetlands. We find that tipping points for beaches and wetlands could be reached with just 0.25 m or less of SLR (~ 2050), with > 50% subsequent habitat loss that would degrade overall biodiversity and ecosystem function. In contrast, the largest projected changes in socioeconomic exposure to flooding for five communities in this region are not anticipated until SLR exceeds 0.75 m for daily flooding and 1.5 m for storm-driven flooding (~ 2100 or more » later). These changes are less acute relative to community totals and do not qualify as tipping points given the adaptive capacity of communities. Nonetheless, the natural and human built systems are interconnected such that the loss of natural system function could negatively impact the quality of life of residents and disrupt the local economy, resulting in indirect socioeconomic impacts long before built infrastructure is directly impacted by flooding. « less
; ; ; ; ; ; ; ; ; ;
Award ID(s):
Publication Date:
Journal Name:
Scientific Reports
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract River deltas all over the world are sinking beneath sea-level rise, causing significant threats to natural and social systems. This is due to the combined effects of anthropogenic changes to sediment supply and river flow, subsidence, and sea-level rise, posing an immediate threat to the 500–1,000 million residents, many in megacities that live on deltaic coasts. The Mississippi River Deltaic Plain (MRDP) provides examples for many of the functions and feedbacks, regarding how human river management has impacted source-sink processes in coastal deltaic basins, resulting in human settlements more at risk to coastal storms. The survival of human settlement on the MRDP is arguably coupled to a shifting mass balance between a deltaic landscape occupied by either land built by the Mississippi River or water occupied by the Gulf of Mexico. We developed an approach to compare 50 % L:W isopleths (L:W is ratio of land to water) across the Atchafalaya and Terrebonne Basins to test landscape behavior over the last six decades to measure delta instability in coastal deltaic basins as a function of reduced sediment supply from river flooding. The Atchafalaya Basin, with continued sediment delivery, compared to Terrebonne Basin, with reduced river inputs, allow us tomore »test assumptions of how coastal deltaic basins respond to river management over the last 75 years by analyzing landward migration rate of 50 % L:W isopleths between 1932 and 2010. The average landward migration for Terrebonne Basin was nearly 17,000 m (17 km) compared to only 22 m in Atchafalaya Basin over the last 78 years (p\0.001), resulting in migration rates of 218 m/year (0.22 km/year) and\0.5 m/year, respectively. In addition, freshwater vegetation expanded in Atchafalaya Basin since 1949 compared to migration of intermediate and brackish marshes landward in the Terrebonne Basin. Changes in salt marsh vegetation patterns were very distinct in these two basins with gain of 25 % in the Terrebonne Basin compared to 90 % decrease in the Atchafalaya Basin since 1949. These shifts in vegetation types as L:W ratio decreases with reduced sediment input and increase in salinity also coincide with an increase in wind fetch in Terrebonne Bay. In the upper Terrebonne Bay, where the largest landward migration of the 50 % L:W ratio isopleth occurred, we estimate that the wave power has increased by 50–100 % from 1932 to 2010, as the bathymetric and topographic conditions changed, and increase in maximum storm-surge height also increased owing to the landward migration of the L:W ratio isopleth. We argue that this balance of land relative to water in this delta provides a much clearer understanding of increased flood risk from tropical cyclones rather than just estimates of areal land loss. We describe how coastal deltaic basins of the MRDP can be used as experimental landscapes to provide insights into how varying degrees of sediment delivery to coastal deltaic floodplains change flooding risks of a sinking delta using landward migrations of 50 % L:W isopleths. The nonlinear response of migrating L:W isopleths as wind fetch increases is a critical feedback effect that should influence human river-management decisions in deltaic coast. Changes in land area alone do not capture how corresponding landscape degradation and increased water area can lead to exponential increase in flood risk to human populations in low-lying coastal regions. Reduced land formation in coastal deltaic basins (measured by changes in the land:water ratio) can contribute significantly to increasing flood risks by removing the negative feedback of wetlands on wave and storm-surge that occur during extreme weather events. Increased flood risks will promote population migration as human risks associated with living in a deltaic landscape increase, as land is submerged and coastal inundation threats rise. These system linkages in dynamic deltaic coasts define a balance of river management and human settlement dependent on a certain level of land area within coastal deltaic basins (L).« less
  2. Coastal wetlands are globally important stores of carbon (C). However, accelerated sea-level rise (SLR), increased saltwater intrusion, and modified freshwater discharge can contribute to the collapse of peat marshes, converting coastal peatlands into open water. Applying results from multiple experiments from sawgrass (Cladium jamaicense)-dominated freshwater and brackish water marshes in the Florida Coastal Everglades, we developed a system-level mechanistic peat elevation model (EvPEM). We applied the model to simulate net ecosystem C balance (NECB) and peat elevation in response to elevated salinity under inundation and drought exposure. Using a mass C balance approach, we estimated net gain in C and corresponding export of aquatic fluxes ( ) in the freshwater marsh under ambient conditions (NECB = 1119 ± 229 gC m−2 year−1; FAQ = 317 ± 186 gC m−2 year−1). In contrast, the brackish water marsh exhibited substantial peat loss and aquatic C export with ambient (NECB = −366 ± 15 gC m−2 year−1; FAQ = 311 ± 30 gC m−2 year−1) and elevated salinity (NECB = −594 ± 94 gC m−2 year−1; FAQ = 729 ± 142 gC m−2 year−1) under extended exposed conditions. Further, mass balance suggests a considerable decline in soil C and corresponding elevation loss with elevated salinity and seasonal dry-down. Applying EvPEM, we developed critical marsh net primarymore »productivity (NPP) thresholds as a function of salinity to simulate accumulating, steady-state, and collapsing peat elevations. The optimization showed that ~150–1070 gC m−2 year−1 NPP could support a stable peat elevation (elevation change ≈ SLR), with the corresponding salinity ranging from 1 to 20 ppt under increasing inundation levels. The C budgeting and modeling illustrate the impacts of saltwater intrusion, inundation, and seasonal dry-down and reduce uncertainties in understanding the fate of coastal peat wetlands with SLR and freshwater restoration. The modeling results provide management targets for hydrologic restoration based on the ecological conditions needed to reduce the vulnerability of the Everglades' peat marshes to collapse. The approach can be extended to other coastal peatlands to quantify C loss and improve understanding of the influence of the biological controls on wetland C storage changes for coastal management.« less
  3. Abstract

    Flood exposure is increasing in coastal communities due to rising sea levels. Understanding the effects of sea level rise (SLR) on frequency and consequences of coastal flooding and subsequent social and economic impacts is of utmost importance for policymakers to implement effective adaptation strategies. Effective strategies may consider impacts from cumulative losses from minor flooding as well as acute losses from major events. In the present study, a statistically coherent Mixture Normal‐Generalized Pareto Distribution model was developed, which reconciles the probabilistic characteristics of the upper tail as well as the bulk of the sea level data. The nonstationary sea level condition was incorporated in the mixture model using Quantile Regression method to characterize variable Generalized Pareto Distribution thresholds as a function of SLR. The performance validity of the mixture model was corroborated for 68 tidal stations along the Contiguous United States (CONUS) coast with long‐term observed data. The method was subsequently employed to assess existing and future coastal minor and major flood frequencies. The results indicate that the frequency of minor and major flooding will increase along all CONUS coastal regions in response to SLR. By the end of the century, under the “Intermediate” SLR scenario, major flooding ismore »anticipated to occur with return period less than a year throughout the coastal CONUS. However, these changes vary geographically and temporally. The mixture model was reconciled with the property exposure curve to characterize how SLR might influence Average Annual Exposure to coastal flooding in 20 major CONUS coastal cities.

    « less
  4. It is generally acknowledged that interdependent critical infrastructure in coastal urban areas is constantly threatened by storm-induced flooding. Due to changing climate effects, such as sea level rise (SLR), the occurrence of catastrophic events will be more frequent and may trigger an increased likelihood of severe hazards. Planning a protective measure or mitigation strategy is a complex problem given the constraints that it must fit within a prescribed and limited fiscal budget and be beneficial to the community it protects both socially and economically. This article proposes a methodology for optimizing protective measures and mitigation strategies for interdependent infrastructures subjected to storm-induced flooding and climate change impacts such as SLR. Optimality is defined in this methodology as a maximum reduction in overall expected losses within a prescribed budget (compared to the expected losses in the case of doing nothing for protection/mitigation). Protective measures can include seawalls, barriers, artificial dunes, restoration of wetlands, raising individual buildings, sealing parts of the infrastructure, strategic retreat, insurance, and many more. The optimal protective strategy can be a combination of several protective measures implemented over space and time. The optimization process starts with parameterizing the protective measures. Storm-induced flooding and SLR, and their corresponding consequences,more »are estimated using a GIS-based subdivision-redistribution methodology (GISSR) developed by the authors for finding a rough solution in the first brute-force iterations of the optimization loop. A storm surge computational model called GeoClaw is subsequently used to simulate ensembles of synthetic storms in order to fine-tune and achieve the optimal solution. Damage loss, including economic impacts, is quantified based on calculated flood estimates. The suitability of the potential optimal solution is examined and assessed with input from stakeholders' interviews. It should be mentioned that the results and conclusions provided in this work depend on the assumptions made about future sea level rise (SLR). The authors acknowledge that there are other, more severe predictions for sea level rise (SLR), than the one used in this paper.« less
  5. Low-lying coastal cities across the world are vulnerable to the combined impact of rainfall and storm tide. However, existing approaches lack the ability to model the combined effect of these flood mechanisms, especially under climate change and sea level rise (SLR). Thus, to increase flood resilience of coastal cities, modeling techniques to improve the understanding and prediction of the combined effect of these flood hazards are critical. To address this need, this study presents a modeling system for assessing the combined flood impact on coastal cities under selected future climate scenarios that leverages ocean modeling with land surface modeling capable of resolving urban drainage infrastructure within the city. The modeling approach is demonstrated in quantifying the impact of possible future climate scenarios on transportation infrastructure within Norfolk, Virginia, USA. A series of combined storm events are modeled for current (2020) and projected future (2070) climate scenarios. The results show that pluvial flooding causes a larger interruption to the transportation network compared to tidal flooding under current climate conditions. By 2070, however, tidal flooding will be the dominant flooding mechanism with even nuisance flooding expected to happen daily due to SLR. In 2070, nuisance flooding is expected to cause a 4.6%more »total link close time (TLC), which is more than two times that of a 50-year storm surge (1.8% TLC) in 2020. The coupled flood model was compared with a widely used but physically simplistic bathtub method to assess the difference resulting from the more complex modeling presented in this study. The results show that the bathtub method overestimated the flooded area near the shoreline by 9.5% and 3.1% for a 10-year storm surge event in 2020 and 2070, respectively, but underestimated the flooded area in the inland region by 9.0% and 4.0% for the same events. The findings demonstrate the benefit of sophisticated modeling methods compared to more simplistic bathtub approaches, in climate adaptive planning and policy in coastal communities.« less