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Understanding extreme storm surge events that threaten low-lying coastal communities is key to effective flood mitigation/adaptation measures. However, observational estimates are sparse and highly uncertain along most coastal regions with a lack of observational evidence about long-term underlying trends and their contribution to overall extreme sea-level changes. Here, using a spatiotemporal Bayesian hierarchical framework, we analyse US tide gauge record for 1950–2020 and find that observational estimates have underestimated likelihoods of storm surge extremes at 85% of tide gauge sites nationwide. Additionally, and contrary to prevailing beliefs, storm surge extremes show spatially coherent trends along many widespread coastal areas, providing evidence of changing coastal storm intensity in the historical monitoring period. Several hotspots exist with regionally significant storm surge trends that are comparable to trends in mean sea-level rise and its key components. Our findings challenge traditional coastal design/planning practices that rely on estimates from discrete observations and assume stationarity in surge extremes. 

Compound flooding events are a threat to many coastal regions and can have widespread socio-economic implications. However, their frequency of occurrence, underlying flood drivers, and direct link to past socio-economic losses are largely unknown despite being key to supporting risk and adaptation assessments. Here, we present an impact-based analysis of compound flooding for 203 coastal counties along the U.S. Gulf and East coasts by combining data from multiple flood drivers and socio-economic loss information from 1980 to 2018. We find that ~80% of all flood events recorded in our study area were compound rather than univariate. In addition, we show that historical compound flooding events in most counties were driven by more than two flood drivers (hydrological, meteorological, and/or oceanographic) and distinct spatial clusters exist that exhibit variability in the underlying driver of compound flood events. Furthermore, we find that in more than 80% of the counties, over 80% of recorded property and crop losses were linked to compound flooding. Nearly 80% of counties have a higher median loss from compound than univariate events. For these counties, the median property loss is over 26 times greater, and the median crop loss is over 76 times greater for compound events on average. Our analysis overcomes some of the limitations of previous compound-event studies based on pre-defined flood drivers and offers new insights into the complex relationship between hazards and associated socio-economic impacts. 

Abstract High‐tide flooding—minor, disruptive coastal inundation—is expected to become more frequent as sea levels rise. However, quantifying just how quickly high‐tide flooding rates are changing, and whether some places experience more high‐tide flooding than others, is challenging. To quantify trends in high‐tide flooding from tide‐gauge observations, flood thresholds—elevations above which flooding begins—must be specified. Past studies of high‐tide flooding in the United States have used different data sets and approaches for specifying flood thresholds, only some of which directly relate to coastal impacts, which has lead to sometimes conflicting and ambiguous results. Here we present a novel method for quantifying, with uncertainty, high‐tide flooding thresholds along the United States coast based on sparsely available impact‐based flood thresholds. We use those newly modeled thresholds to make an updated assessment of changes in high‐tide flooding across the United States over the past few decades. From 1990–2000 to 2010–2020, high‐tide flooding rates almost certainly (probability ) increased along the United States East Coast, Gulf Coast, California, and Pacific Islands, while they very likely decreased along Alaska during that time; significant changes in high‐tide flooding rates between the two decades were not detected in Oregon, Washington, and the Caribbean. Averaging spatially, we find that high‐tide flooding rates probably more than doubled nationally between 1990–2000 and 2010–2020. Our approach lays a foundation for future studies to more accurately model high‐tide flood thresholds and trends along the global coastline. 

Many climate policies adopt improving equity as a key objective. A key challenge is that policies often conceive of equity in terms of individuals but introduce strategies that focus on spatially coarse administrative areas. For example, the Justice40 Initiative in the United States requires 518 diverse federal programs to prioritize funds for “disadvantaged” census tracts. This strategy is largely untested and contrasts with the federal government’s definition of equity as the “consistent and systematic fair, just and impartial treatment of all individuals (Executive Office of the President, Federal Register, 2021).” How well does the Justice40 approach improve equity in climate adaptation outcomes acrossindividuals? We analyze this question using a case study of a municipality that faces repetitive flooding and struggles to effectively manage these risks due to limited resources and public investment. We find that the way the Federal Emergency Management Agency implements the Justice40 Initiative can be an obstacle to promoting equity in household flood-risk outcomes. For example, in this case study, ensuring the majority of benefits accrue in “Justice40 Communities” does not reduce risk for the most burdened households, does not reduce risk-burden inequality, and produces net costs. In contrast, we design simple funding rules based on household risk burden that cost-effectively target the most burdened households, reduce risk-burden inequality, and accrue large net benefits. Our findings suggest that “disadvantaged community” indicators defined at coarse spatial scales face the risk of poorly capturing many climate risks and can be ineffective for meeting equity promises about climate-related investments. 

In coastal regions, compound flooding can arise from a combination of different drivers, such as storm surges, high tides, excess river discharge, and rainfall. Compound flood potential is often assessed by quantifying the dependence and joint probabilities of flood drivers using multivariate models. However, most of these studies assume that all extreme events originate from a single population. This assumption may not be valid for regions where flooding can arise from different generation processes, e.g., tropical cyclones (TCs) and extratropical cyclones (ETCs). Here we present a flexible copula-based statistical framework to assess compound flood potential from multiple flood drivers while explicitly accounting for different storm types. The proposed framework is applied to Gloucester City, New Jersey, and St. Petersburg, Florida, as case studies. Our results highlight the importance of characterizing the contributions from TCs and non-TCs separately to avoid potential underestimation of the compound flood potential. In both study regions, TCs modulate the tails of the joint distributions (events with higher return periods), while non-TC events have a strong effect on events with low to moderate joint return periods. We show that relying solely on TCs may be inadequate when estimating compound flood risk in coastal catchments that are also exposed to other storm types. We also assess the impact of non-classified storms that are not linked to either TCs or ETCs in the region (such as locally generated convective rainfall events and remotely forced storm surges). The presented study utilizes historical data and analyzes two populations, but the framework is flexible and can be extended to account for additional storm types (e.g., storms with certain tracks or other characteristics) or can be used with model output data including hindcasts or future projections. 

Abstract. Compound flooding, where the combination or successive occurrence of two or more flood drivers leads to a greater impact, can exacerbate the adverse consequences of flooding, particularly in coastal/estuarine regions. This paper reviews the practices and trends in coastal/estuarine compound flood research and synthesizes regional to global findings. Systematic review is employed to construct a literature database of 271 studies relevant to compound flooding in a coastal/estuarine context. This review explores the types of compound flood events, their mechanistic processes, and synthesizes terminology throughout the literature. Considered in the review are six flood drivers (fluvial, pluvial, coastal, groundwater, damming/dam failure, and tsunami) and five precursor events and environmental conditions (soil moisture, snow, temp/heat, fire, and drought). Furthermore, this review summarizes research methodology and study applications trends, and considers the influences of climate change and urban environments. Finally, this review highlights knowledge gaps in compound flood research and discusses the implications on future practices. Our five recommendations for compound flood research are: 1) adopt consistent terminology and approaches; 2) expand the geographic coverage of research; 3) pursue more inter-comparison projects; 4) develop modelling frameworks that better couple dynamic Earth systems; and 5) design urban and coastal infrastructure with compounding in mind. 

Abstract. In coastal regions, compound flooding can arise from a combination of different drivers such as storm surges, high tides, excess river discharge, and rainfall. Compound flood potential is often assessed by quantifying the dependence and joint probabilities of the flood drivers using multivariate models. However, most of these studies assume that all extreme events originate from a single population. This assumption may not be valid for regions where flooding can arise from different generation processes, e.g., tropical cyclones (TCs) and extratropical cyclones (ETCs). Here we present a flexible copula-based statistical framework to assess compound flood potential from multiple flood drivers while explicitly accounting for different storm types. The proposed framework is applied to Gloucester City, New Jersey, and St. Petersburg, Florida as case studies. Our results highlight the importance of characterizing the contributions from TCs and non-TCs separately to avoid potential underestimation of the compound flood potential. In both study regions, TCs modulate the tails of the joint distributions (events with higher return periods) while non-TC events have a strong effect on events with low to moderate joint return periods. We show that relying solely on TCs may be inadequate when estimating compound flood risk in coastal catchments that are also exposed to other storm types. We also assess the impact of non-classified storms that are neither linked to TCs or ETCs in the region (such as locally generated convective rainfall events and remotely forced storm surges). The presented study utilizes historical data and analyzes two populations, but the framework is flexible and can be extended to account for additional storm types (e.g., storms with certain tracks or other characteristics) or can be used with model output data including hindcasts or future projections.