Search for: All records

Abstract. To improve our understanding of the influence of tropicalcyclones (TCs) on coastal flooding, the relationships between storm surgeand TC characteristics are analyzed for 12 sites along the east coast of theUnited States. This analysis offers a unique perspective by first examiningthe relationship between the characteristics of TCs and their resultingstorm surge and then determining the probabilities of storm surge associatedwith TCs based on exceeding certain TC characteristic thresholds. Usingobservational data, the statistical dependencies of storm surge on TCs areexamined for these characteristics: TC proximity, intensity, path angle, andpropagation speed, by applying both exponential and linear fits to the data.At each tide gauge along the east coast of the United States, storm surge isinfluenced differently by these TC characteristics, with some locations morestrongly influenced by TC intensity and others by TC proximity. Thecorrelation for individual and combined TC characteristics increases whenconditional sorting is applied to isolate strong TCs close to a location.The probabilities of TCs generating surge exceeding specific return levels(RLs) are then analyzed for TCs passing within 500 km of a tide gauge, wherebetween 6 % and 28 % of TCs were found to cause surge exceeding the1-year RL. If only the closest and strongest TCs are considered, thepercentage of TCs thatmore »generate surge exceeding the 1-year RL is between 30 % and 70 % at sites north of Sewell's Point, VA, and over 65 % atalmost all sites south of Charleston, SC. When examining storm surgeproduced by TCs, single-variable regression provides a good fit, whilemulti-variable regression improves the fit, particularly when focusing on TCproximity and intensity, which are, probabilistically, the two mostinfluential TC characteristics on storm surge.« less

Abstract Recent advances in machine learning have enabled Neural Network (NN) inference directly on constrained embedded devices. This local approach enhances the privacy of user data, as the inputs to the NN inference are not shared with third-party cloud providers over a communication network. At the same time, however, performing local NN inference on embedded devices opens up the possibility of Power Analysis attacks, which have recently been shown to be effective in recovering NN parameters, as well as their activations and structure. Knowledge of these NN characteristics constitutes a privacy threat, as it enables highly effective Membership Inference and Model Inversion attacks, which can recover information about the sensitive data that the NN model was trained on. In this paper we address the problem of securing sensitive NN inference parameters against Power Analysis attacks. Our approach employs masking , a countermeasure well-studied in the context of cryptographic algorithms. We design a set of gadgets , i.e., masked operations, tailored to NN inference. We prove our proposed gadgets secure against power attacks and show, both formally and experimentally, that they are composable, resulting in secure NN inference. We further propose optimizations that exploit intrinsic characteristics of NN inference to reducemore »the masking’s runtime and randomness requirements. We empirically evaluate the performance of our constructions, showing them to incur a slowdown by a factor of about 2–5.« less

Populated coastal areas worldwide have a legacy of numerous solid waste disposal sites. At the same time, mean sea level is rising and likely to accelerate, increasing flooding and/or erosion. There is therefore concern that landfill sites located at and near the coast pose a growing risk to the environment from the potential release of liquid and solid waste materials. This paper aims to assess our present understanding of this issue as well as research and practice needs by synthesizing the available evidence across a set of developed country cases, comprising England, France, Germany, the Netherlands, and the United States (Florida). Common insights gained here include: (1) a lack of data and limited appreciation of waste release from coastal landfill as a potential problem; (2) recognition of the scale and diversity of coastal landfill waste within a range of generic settings (or situations); and (3) a lack of robust protocols that allow the impact of different categories of waste release to the coast to be assessed in a consistent and evidence-based manner, most particularly for solid waste. Hence, a need for greater understanding of the following issues is identified: (1) the amount, character and impact of waste that could bemore »released from landfill sites; (2) the acceptability and regulation of waste eroding from coastal landfills; (3) present and future erosion rates at landfill sites suggesting the need for more monitoring and relevant predictive tools; (4) the full range of possible management methods for dealing with waste release from landfills and the science to support them; and (5) relevant long-term funding mechanisms to address this issue. The main focus and experience of current management practice has been protection/retention, or removal of landfills, with limited consideration of other feasible solutions and how they might be facilitated. Approaches to assess and address solid waste release to the marine/coastal environment represent a particular gap. Lastly, as solid waste will persist indefinitely and sea levels will rise for many centuries, the long timescale of this issue needs wider appreciation and should be included in coastal and waste policy.« less

Abstract. The interaction between storm surge and concurrent precipitation is poorly understood in many coastal regions. This paper investigates the potential compound effects from these two flooding drivers along the coast of China for the first time by using the most comprehensive records of storm surge and precipitation. Statistically significant dependence between flooding drivers exists at the majority of locations that are analysed, but the strength of the correlation varies spatially and temporally and depending on how extreme events are defined. In general, we find higher dependence at the south-eastern tide gauges (TGs) (latitude < 30∘ N) compared to the northern TGs. Seasonal variations in the dependence are also evident. Overall there are more sites with significant dependence in the tropical cyclone (TC) season, especially in the summer. Accounting for past sea level rise further increases the dependence between flooding drivers, and future sea level rise will hence likely lead to an increase in the frequency of compound events. We also find notable differences in the meteorological patterns associated with events where both drivers are extreme versus events where only one driver is extreme. Events with both extreme drivers at south-eastern TG sites are caused by low-pressure systems with similar characteristics across locations, including high precipitable watermore »content (PWC) and strong winds that generate high storm surge. Based on historical disaster damages records of Hong Kong, events with both extreme drivers account for the vast majority of damages and casualties, compared to univariate flooding events, where only one flooding driver occurred. Given the large coastal population and low capacity of drainage systems in many Chinese urban coastal areas, these findings highlight the necessity to incorporate compound flooding and its potential changes in a warming climate into risk assessments, urban planning, and the design of coastal infrastructure and flood defences.« less

Abstract. Flooding is of particular concern in low-lying coastal zones that are prone to flooding impacts from multiple drivers, such as oceanographic (storm surge and wave), fluvial (excessive river discharge), and/or pluvial (surface runoff). In this study, we analyse, for the first time, the compound flooding potential along the contiguous United States (CONUS) coastline from all flooding drivers, using observations and reanalysis data sets. We assess the overall dependence from observations by using Kendall's rank correlation coefficient (τ) and tail (extremal) dependence (χ). Geographically, we find the highest dependence between different drivers at locations in the Gulf of Mexico, southeastern, and southwestern coasts. Regarding different driver combinations, the highest dependence exists between surge–waves, followed by surge–precipitation, surge–discharge, waves–precipitation, and waves–discharge. We also perform a seasonal dependence analysis (tropical vs. extra-tropical season), where we find higher dependence between drivers during the tropical season along the Gulf and parts of the East Coast and stronger dependence during the extra-tropical season on the West Coast. Finally, we compare the dependence structure of different combinations of flooding drivers, using observations and reanalysis data, and use the Kullback–Leibler (KL) divergence to assess significance in the differences of the tail dependence structure. We find, for example, that models underestimate the tailmore »dependence between surge–discharge on the East and West coasts and overestimate tail dependence between surge–precipitation on the East Coast, while they underestimate it on the West Coast. The comprehensive analysis presented here provides new insights on where the compound flooding potential is relatively higher, which variable combinations are most likely to lead to compounding effects, duringwhich time of the year (tropical versus extra-tropical season) compoundflooding is more likely to occur, and how well reanalysis data capture thedependence structure between the different flooding drivers.« less

Nuisance flooding (NF) is defined as minor, nondestructive flooding that causes substantial, accumulating socioeconomic impacts to coastal communities. While sea-level rise is the main driver for the observed increase in NF events in the United States, we show here that secular changes in tides also contribute. An analysis of 40 tidal gauge records from U.S. coasts finds that, at 18 locations, NF increased due to tidal amplification, while decreases in tidal range suppressed NF at 11 locations. Estuaries show the largest changes in NF attributable to tide changes, and these can often be traced to anthropogenic alterations. Limited long-term measurements from estuaries suggest that the effects of evolving tides are more widespread than the locations considered here. The total number of NF days caused by tidal changes has increased at an exponential rate since 1950, adding ~27% to the total number of NF events observed in 2019 across locations with tidal amplification.

Gated storm surge barriers are being studied by the United States Army Corps of Engineers (USACE) for coastal storm risk management for the New York City metropolitan area. Surge barrier gates are only closed when storm tides exceeding a specific “trigger” water level might occur in a storm. Gate closure frequency and duration both strongly influence the physical and environmental effects on enclosed estuaries. In this paper, we use historical observations to represent future storm tide hazard, and we superimpose local relative sea-level rise (SLR) to study the potential future changes to closure frequency and duration. We account for the effects of forecast uncertainty on closures, using a relationship between past storm surge and forecast uncertainty from an operational ensemble forecast system. A concern during a storm surge is that closed gates will trap river streamflow and could cause a new problem with trapped river water flooding. Similarly, we evaluate this possibility using historical data to represent river flood hazard, complemented by hydrodynamic model simulations to capture how waters rise when a hypothetical barrier is closed. The results show that SLR causes an exponential increase of the gate closure frequency, a lengthening of the closure duration, and a rising probabilitymore »of trapped river water flooding. The USACE has proposed to prevent these SLR-driven increases by periodically raising the trigger water level (e.g., to match a prescribed storm return period). However, this alternative management approach for dealing with SLR requires waterfront seawalls to be raised at a high, and ongoing, additional future expense. For seawalls, costs and benefits will likely need to be weighed on a neighborhood-by-neighborhood basis, and in some cases retreat or other non-structural options may be preferable.« less

Abstract Extreme sea levels (ESLs) due to typhoon-induced storm surge threaten the societal security of densely populated coastal China. Uncertainty in extreme value analysis (EVA) for ESL estimation has large implications for coastal communities’ adaptation to natural hazards. Here we evaluate uncertainties in ESL estimation and relevant driving factors based on hourly observations from 13 tide gauge stations and a complementary dataset derived from a hydrodynamic model. Results indicate significant uncertainties in ESL estimations stemming from using different EVA methods, which then propagate to the inundation assessment. Amplification factors due to sea-level rise (SLR) are highly sensitive to local relative SLR and the shape of the exceedance probability curve, which in turn depends on the selected EVA method. The hydrodynamic model hindcast indicates that high ESLs mainly occurred in eastern coastal China due to typhoon-induced storm surge. Larger uncertainties in the modelled ESLs are found for the coasts of the Yangtze River Delta, and particularly in the river mouth region. Future research and adaptation planning should prioritize these regions given expected future rising sea level, compound flood events, and human-induced factors (e.g. subsidence). This study provides theoretical and practical references for adaptation to ESL-related hazards along coastal China, with implicationsmore »for coastal regions worldwide.« less