Annual Exceedance Probability Research Articles

Climate change impacts to the coastal flood hazard in the northeastern United States

It is widely accepted that climate change will cause sea level rise and increase the coastal flood hazard in many places. However, climate change also has significant implications for hurricane climatology. While the effect of climate change on hurricane frequency is inconclusive, there is a general consensus among climate scientists that hurricane intensity will increase over the coming decades. A number of studies indicate that hurricane size and translation speed may intensify with climate change as well. Each of these properties influences storm surge generation and propagation, and thus has significant implications for the coastal flood hazard, particularly in the densely populated northeast region of the U.S. As coastal populations grow, increasing the resilience of the built environment will become an increasingly necessary priority. Local, detailed, and comprehensive flood hazard assessment is a central aspect of such efforts. In this work, we integrate global climate data, statistical-deterministic hurricane modeling, physics-based numerical storm surge modeling, and extreme value analysis methods to comprehensively assess the present day and end of century flood hazard due to hurricanes for several coastal communities along the U.S. North Atlantic coastline. We find that by the end of the century, annual exceedance probabilities of the 100-year flood may increase by factors as great as 7 due to sea level rise, and on average projected changes to tropical cyclone climatology cause these probabilities to double. For truly effective long-term resilience efforts, coastal engineers, planners, and other stakeholders must account for climate change impacts to both sea level and tropical storm climatology.

Thresholds in Road Network Functioning on US Atlantic and Gulf Barrier Islands

AbstractBarrier islands predominate the Atlantic and Gulf coastlines of the USA, where population and infrastructure growth exceed national trends. Forward‐looking models of barrier island dynamics often include feedbacks with real estate markets and management practices aimed at mitigating damage to buildings from natural hazards. However, such models thus far do not account for networks of infrastructure, such as roads, and how the functioning of infrastructure networks might influence management strategies. Understanding infrastructure networks on barrier islands is an essential step toward improved insight into the future dynamics of human‐altered barriers. Here, we examine thresholds in the functioning of 72 US Atlantic and Gulf Coast barrier islands. We use digital elevation models to assign an elevation to each intersection in each road network. From each road network we sequentially remove intersections, starting from the lowest elevation. We use the maxima of the second giant connected component to identify a specific intersection—and corresponding elevation—at which functioning of the network fails, and we match the elevation of each critical intersection to local annual exceedance probabilities for extreme high‐water levels. We find a range of failure thresholds for barrier island road network functioning, and also find that no single metric—absolute elevation, annual exceedance probability, or a quantitative metric of robustness—sufficiently ranks the susceptibility of barrier road networks to failure. Future work can incorporate thresholds for road network into forward‐looking models of barrier island dynamics that include hazard‐mitigation practices for protecting infrastructure.

Perry Bar & Witton FRMS: Forge Mill Flood Storage Area – Lessons Learnt

The Perry Barr and Witton Flood Risk Management Scheme in Birmingham protects over 1,300 properties from a 1% Annual Exceedance Probability flood event. A key component of the scheme is the Forge Mill flood storage area. Construction started in 2018 with the Preliminary Certificate signed off in spring 2022. This paper will discuss the project and share lessons learnt from the construction phase. The lessons learnt cover a variety of areas including programme considerations, use of erosion protection matting, trash screen management and use of 3D models in construction.

Future Flood Risk Exacerbated by the Dynamic Impacts of Sea Level Rise Along the Northern Gulf of Mexico

AbstractA growing concern of coastal communities is increased flood risk and non‐monetary consequences due to climate‐induced impacts such as sea level rise (SLR). Previous efforts have discussed the importance of future flood risk quantification using broad aggregations of monetary loss with “bathtub” SLR models rather than more physically based modeling approaches. Here we quantify actual impacts to coastal communities at the census block level using a dynamic, high‐resolution, bio geophysical modeling framework for four SLR scenarios for the year 2100. This framework accounts for future sea‐levels, landscape change, and urbanization to quantify the 1% and 0.2% annual exceedance probability (AEP) water levels. The computed AEP water levels were used to quantify building damage and populations of displaced people and people requiring long‐term shelter across the Northern Gulf of Mexico (NGOM) (Mississippi, Alabama, and the Florida panhandle). The increase in damaged buildings under SLR is linear, with an increase of 16,367 damaged buildings per 1 m of SLR (R2 = 0.96) for the 1% AEP flood. The rate increases to 24,981 damaged buildings per 1 m of SLR (R2 = 0.96) for the 0.2% AEP, on average. The increase in displaced people across the NGOM is 8,056 people per meter of SLR, and people requiring shelter is 300 per meter of SLR. The results in this work highlight the varying levels of risk across the NGOM and the change in risk under climate change‐induced impacts.

The Oktober Flut: An anomalous extreme high-water event in Annapolis, MD, USA, October 2021

Between 28 and 30 October 2021, Annapolis, Maryland, USA, experienced the third highest flood event on record, referred to as the “Oktober Flut.” Unlike many of the extreme coastal flood events that have impacted Annapolis in the past, the Oktober Flut was not associated with a tropical or post-tropical cyclone. Instead, sustained wind forcing from a series of passing extratropical storms drove anomalously high water levels. The maximum observed hourly water level during the event was 4.88 ft above mean lower low water (MLLW). This exceeded the Moderate Flood Stage, defined by the National Weather Service (NWS) as 3.3 ft (MLLW), and had an annual exceedance probability of 5.2%. In total, flood waters exceeded the NWS Minor Flood Stage (2.6 ft MLLW) for 78 non-consecutive hours over multiple tidal periods. Relative sea level rise and increasing instances of coastal nuisance flooding events, like the Oktober Flut, have the potential to impact the local economy in Annapolis, MD, and operations at the geographically adjacent U.S. Naval Academy. Coastal nuisance flooding events also challenge existing community resilience efforts and initiatives, particularly those related to preparing for natural hazards. This paper provides an overview of the meteorological factors that drove the anomalously high-water levels and coastal flooding at the U.S. Naval Academy. In addition to data analysis from fixed, long-term sensors maintained by federal partners, observations from spotdeployments in advance of the storm are also presented. The results are discussed with respect to the storm impacts on infrastructure and facility preparedness. Lessons learned are documented with the aim of informing other coastal communities on how to better assess local flood-specific action plans, based on the accuracy and timing of forecast data.

Rapid, risk‐based levee design framework for greater risk reduction at lower cost than standards‐based design

AbstractStandards‐based levee design aims to protect against events with specific probabilities, for example eliminating overtopping from a storm surge with a 1% annual exceedance probability (i.e., a “100‐year” event). This allows levee segments to be analyzed independently but ignores interior dynamics and overall risk. We present and implement a framework for calculating optimal risk‐informed design heights. Using this design paradigm and multi‐objective evolutionary algorithms, we identify levee and floodwall design heights that minimize the total system cost and expected flood losses over 50 years. With our model, decision makers may feasibly evaluate hundreds or thousands of alternative designs over a large ensemble of future states of the world. Comparing to the existing design elevations of the Larose to Golden Meadow Hurricane Protection Project in coastal Louisiana, over multiple climate change scenarios, we identify system configurations of similar cost that reduce the expected value of discounted residual risk of 26%–73% ($8–85 million). We also achieve the same residual risk at 90%–97% of the cost of the existing system (saving $19–73 million).

Recent Changes in Average Recurrence Interval Precipitation Extremes in the Mid-Atlantic United States

AbstractIncreases in the frequency of extreme rainfall occurrence have emerged as one of the more consistent climate trends in recent decades, particularly in the eastern United States. Such changes challenge the veracity of the conventional assumption of stationarity that has been applied in the published extreme rainfall analyses that are the foundation for engineering design assessments and resiliency planning. Using partial-duration series with varying record lengths, temporal changes in daily and hourly rainfall extremes corresponding to average annual recurrence probabilities ranging from 50% (i.e., the 2-yr storm) to 1% (i.e., the 100-yr storm) are evaluated. From 2000 through 2019, extreme rainfall amounts across a range of durations and recurrence probabilities have increased at 75% of the long-term precipitation observation stations in the mid-Atlantic region. At approximately one-quarter of the stations, increases in extreme rainfall have exceeded 5% from 2000 through 2019, with some stations experiencing increases in excess of 10% for both daily and hourly durations. At over 40% of the stations, the rainfall extremes based on the 1950–99 partial-duration series show a significant (p> 0.90) change in the 100-yr ARI relative to the 1950–2019 period. Collectively, the results indicate that, given recent trends in extreme rainfall, routine updates of extreme rainfall analyses are warranted on 20-yr intervals.Significance StatementEngineering design standards for drainage systems, dams, and other infrastructure rely on analyses of precipitation extremes. Often such structures are designed on the basis of the probability of exceeding a specified rainfall rate in a given year. The frequency of extreme rainfall events has increased in the mid-Atlantic region of the United States in recent decades, leading us to evaluate how these changes have affected these exceedance probabilities. From 2000 through 2019, there has been a consistent increase of generally 2.5%–5.0% in design rainfall amounts. The increase is similar across a range of rainfall durations from 1 h to 20 days and also annual exceedance probabilities ranging from 50% to 1% (i.e., from the “2-yr storm” to the “100-yr storm”). The work highlights the need to routinely update the climatological extreme-value analyses used in engineering design, with the results suggesting that a 20-yr cycle might be an appropriate update frequency.

Enhanced flood hazard assessment beyond decadal climate cycles based on centennial historical data (Duero basin, Spain)

Abstract. Current climate modelling frameworks present significant uncertainties when it comes to quantifying flood quantiles in the context of climate change, calling for new information and strategies in hazard assessments. Here, state-of-the-art methods on hydraulic and statistical modelling are applied to historical and contemporaneous flood records to evaluate flood hazards beyond natural climate cycles. A comprehensive flood record of the Duero River in Zamora (Spain) was compiled from documentary sources, early water-level readings and continuous gauge records spanning the last 500 years. Documentary evidence of flood events includes minute books (municipal and ecclesiastic), narrative descriptions, epigraphic marks, newspapers and technical reports. We identified 69 flood events over the period 1250 to 1871, of which 15 were classified as catastrophic floods, 16 as extraordinary floods and 38 as ordinary floods. Subsequently, a two-dimensional hydraulic model was implemented to relate flood stages (flood marks and inundated areas) to discharges. The historical flood records show the largest floods over the last 500 years occurred in 1860 (3450 m3 s−1), 1597 (3200 m3 s−1) and 1739 (2700 m3 s−1). Moreover, at least 24 floods exceeded the perception threshold of 1900 m3 s−1 during the period (1500–1871). Annual maximum flood records were completed with gauged water-level readings (pre-instrumental dataset, PRE: 1872–1919) and systematic gauge records (systematic dataset, SYS: 1920–2018). The flood frequency analyses were based on (1) the expected moments algorithm (EMA) and (2) the maximum likelihood estimator (MLE) method, using five datasets with different temporal frameworks (historic dataset, HISTO: 1511–2018; PRE–SYS: 1872–2018; full systematic record, ALLSYS: 1920–2018; SYS1: 1920–1969; and SYS2: 1970–2018). The most consistent results were obtained using the HISTO dataset, even for high quantiles (0.001 % annual exceedance probability, AEP). PRE–SYS was robust for the 1 % AEP flood with increasing uncertainty in the 0.2 % AEP or 500-year flood, and ALLSYS results were uncertain in the 1 % and 0.2 % AEP floods. Since the 1970s, the frequency of extraordinary floods (>1900 m3 s−1) declined, although floods on the range of the historical perception threshold occurred in 2001 (2075 m3 s−1) and 2013 (1654 m3 s−1). Even if the future remains uncertain, this bottom-up approach addresses flood hazards under climate variability, providing real and certain flood discharges. Our results can provide a guide on low-regret adaptation decisions and improve public perception of extreme flooding.

Seismic risk assessments for real estate portfolios: Impact of engineering investigation on quality of seismic risk studies

Seismic risk evaluation studies for real estate portfolios conducted by technical professionals (often Civil and Structural Engineers) have become increasingly desirable and common in financial decisions. In this article, we develop a series of risk measures and ratings based on common outcomes from probabilistic portfolio seismic risk assessments. We first define two portfolio risk metrics: Portfolio Expected Loss (PELα) and Portfolio Upper Loss (PULα), where “α” is the annual exceedance probability, or the corresponding return period (“1/α”). PULα/PELα ratio characterizes the uncertainty in estimated portfolio risks which results from the uncertainty in seismic performance of the individual assets. Three uncertainty levels are defined, namely, low, medium, and high, based on the PULα/PELα. We then develop an asset risk metric, called Tail Contribution Index (TCIα), that characterizes the contribution of individual assets to the portfolio losses that fall within the high-consequence “tail” of the portfolio loss distribution. To describe the overall engineering efforts of a portfolio seismic risk study, we develop a portfolio risk metric, called Portfolio Level of Investigation (PLIα), that characterizes the effective level of engineering investigation. Three investigation levels are defined: low ( desktop), medium ( semi-engineered), and high ( engineered), based on the PLIα. Finally, based on the combination of uncertainty level and investigation level, we develop a rating scheme by which the quality (Qα) of a portfolio seismic risk study is characterized. Five quality levels are defined: very poor, poor, fair, good, and very good. These risk indices and ratings can help stakeholders and technical professionals better diagnose and communicate portfolio seismic risks, scope adequate studies, effectively utilize valuable resources, and base financial decisions on risk assessment results that have the desired reliability.

On estimating long period wind speed return levels from annual maxima

The uniform risk engineering practices that are increasingly being adopted for structural design require estimates of the extreme wind loads with very low annual probabilities of exceedance, corresponding to return periods of up to 3000-years in some cases. These estimates are necessarily based on observational wind data that typically spans only a few decades. The estimates are therefore affected by both large sampling uncertainty and, potentially, non-negligible biases. Design practices that aim to meet mandated structural reliability criteria take the sampling uncertainty of long period wind speed or wind pressure estimates into account, but reliability could be compromised if estimates are also biased. In many circumstances, estimates are obtained by fitting an extreme value distribution to annual maximum wind speed observed over a few decades. A key assumption implicit in doing so is that wind speed annual maxima are max-stable. Departures from max-stability can exacerbate the uncertainty of long-period return level estimates by inducing systematic estimation bias as well. Observational records, however, are generally too short to assess max-stability. We therefore use wind speed data from a large (50-member) ensemble of CanRCM4 historical simulations over North America to assess whether wind speed annual maxima are max-stable. While results are generally reassuring at the continental scale, disquieting evidence of a lack of max-stability is often found in the central and southern parts of the continent. Results show that when annual maximum wind speeds are not max-stable, long period return level extreme wind speeds tend to be underestimated, which would compromise reliability if used to design infrastructure such as tall buildings and towers.

Intense rainfall and debris flows in the Lomond Hills, Fife, 11–12 August 2020

ABSTRACT Over the night of 11–12th August 2020, unusually intense convective rainfall triggered several debris flows along the Lomond Hills escarpment. Rainfall intensities locally exceeded an estimated 0.33% annual exceedance probability. Each debris flow had a different magnitude and physical character depending on the availability of water and sediment and the effectiveness of the vegetation buffer, such that similar-looking micro-catchments responded in different ways. The largest debris flow far exceeded the others in magnitude, extending over 1 km with a descent of 246 m and an estimated volume of c. 1500–3000 m3, causing damage to a forestry road. Debris was entrained from a gullied relict talus, including fallen trees and incision of Lateglacial glaciofluvial sand. Deposit sedimentology and morphology demonstrate an initial debris-flow surge probably happened early in the storm coinciding with the greatest runoff generation, followed by later fluvial incision and sediment reworking. This appears to be the largest such event in the Lomond Hills for more than 90 years and may be characteristic of the landscape response to projected increases in convective rainfall intensities in twenty-first century summers.

Assessment and significance of the frequency domain for trends in annual peak streamflow

AbstractRisk management of nonstationary floods depends on an understanding of trends over a range of flood frequencies representing small (frequent) to large (infrequent) floods. Quantile regression is applied to the annual peak streamflow distributions at 2683 sites in the contiguous United States to test for trends in the 10th quantile (floods with a 0.9 annual exceedance probability), the 50th quantile (median annual flood), and 90th quantile (floods with a 0.1 annual exceedance probability). Trends are most common (36% of sites) for the median annual flood (50th quantile) and often coherent with trends in both frequent small floods (10th quantile) and infrequent large floods (90th quantile). Changes in the at‐site variance of annual peak streamflow, indicated by convergence (decreasing variance) or divergence (increasing variance) of the 10th and 90th quantiles over time, are primarily in response to reservoir operation or urban development rather than climate. An analysis of synthetic series generated from nonstationary distributions demonstrates that quantile regression and standard trend tests used in flood frequency analysis have limited power and high rates of false negatives (>70%) when a test has a significance of p = 0.05. Quantile regression and tests with lower significance complement standard trend testing to inform flood risk management.

Future Changes in Built Environment Risk to Coastal Flooding, Permanent Inundation and Coastal Erosion Hazards

Sea-level rise will cause erosion of land, deeper and increasingly frequent flooding and will eventually permanently inundate low-elevation land, forcing the adaptation of seaside communities to avoid or reduce risk. To inform adaptation planning, we quantified the effects of incremental relative sea-level rise (RSLR) on exposed land area, number and replacement value of buildings within Tauranga Harbour, New Zealand. The assessment compared three coastal hazards: flooding, permanent inundation and erosion. Increasingly frequent coastal flooding will be the dominant trigger for adaptation in Tauranga. In the absence of adaptation, coastal flooding, recurring at least once every 5 years on average, will overtake erosion as the dominant coastal hazard after about 0.15–0.2 m RSLR, which is likely to occur between the years 2038–2062 in New Zealand and will rapidly escalate in frequency and consequence thereafter. Coastal erosion will remain the dominant hazard for the relatively-few properties on high-elevation coastal cliffs. It will take 0.8 m more RSLR for permanent inundation to reach similar impact thresholds to coastal flooding, in terms of the number and value of buildings exposed. For buildings currently within the mapped 1% annual exceedance probability (AEP) zone, the flooding frequency will transition to 20% AEP within 2–3 decades depending on the RSLR rate, requiring prior adaptive action. We also compared the performance of simple static-planar versus complex dynamic models for assessing coastal flooding exposure. Use of the static-planar model could result in sea level thresholds being reached 15–45 years earlier than planned for in this case. This is compelling evidence to use dynamic models to support adaptation planning.

Impacts on catastrophe risk assessments from multi-segment and multi-fault ruptures in the UCERF3 model

The Uniform California Earthquake Rupture Forecast Version 3 (UCERF3) relaxes fault segmentation, allowing multi-segment and multi-fault ruptures through fault-to-fault “jumps,” with lengths up to ∼1200 km along the San Andreas Fault. Local faults are also highly interconnected, including ruptures on the order of hundreds of kilometers. These prescribed long ruptures did not exist in older models. Longer ruptures produce larger aggregate loss estimates for geographically dispersed assets (portfolios) due to the wider areas that are affected by strong ground shaking. In this study, we model probabilistic earthquake losses of a hypothetical state-wide building portfolio in California. We develop risk deaggregation methods to identify multi-segment and multi-fault ruptures that contribute significantly to high portfolio-wide risks. Three risk measures that are commonly used in risk management decisions are examined: Average Annual Loss (AAL), Return Period Loss (RPLα), and Tail Conditional Expectation (TCEα), for an annual exceedance probability “α,” or corresponding return period “1/α.” Our results show that while the super long ruptures (>500 km) contribute modestly (∼7%) to the portfolio AAL estimate, they contribute more significantly to portfolio catastrophe risk estimates. Specifically, at a 250 year return period, these long ruptures contribute about 26% and 32% to RPL250 and TCE250 estimates, respectively. At a 500-year return period, the corresponding contributions reach about 35% and 39%. Ruptures that connect complex fault systems are also found to be highly influential to estimated portfolio risks. At a 500-year return period, a mere six rupture groups contribute nearly 70% to the RPL500 estimate. Due to the importance of the UCERF3 model to many risk management and public policy decisions, a critical examination of the limit and uncertainty of fault connectivity and rupture lengths of future earthquakes, as well as their impacts on catastrophe risk assessments, is warranted in future model updates.

Extreme Ground Snow Loads in Europe from 1951 to 2100

Lightweight roofs are extremely sensitive to extreme snow loads, as confirmed by recently occurring failures all over Europe. Obviously, the problem is further emphasized in warmer climatic areas, where low design values are generally foreseen for snow loads. Like other climatic actions, representative values of snow loads provided in structural codes are usually derived by means of suitable elaborations of extreme statistics, assuming climate stationarity over time. As climate change impacts are becoming more and more evident over time, that hypothesis is becoming controversial, so that suitable adaptation strategies aiming to define climate resilient design loads need to be implemented. In the paper, past and future trends of ground snow load in Europe are assessed for the period 1950–2100, starting from high-resolution climate simulations, recently issued by the CORDEX program. Maps of representative values of snow loads adopted for structural design, associated with an annual probability of exceedance p = 2%, are elaborated for Europe. Referring to the historical period, the obtained maps are critically compared with the current European maps based on observations. Factors of change maps, referred to subsequent time windows are presented considering RCP4.5 and RCP8.5 emission trajectories, corresponding to medium and maximum greenhouse gas concentration scenarios. Factors of change are thus evaluated considering suitably selected weather stations in Switzerland and Germany, for which high quality point measurements, sufficiently extended over time are available. Focusing on the investigated weather stations, the study demonstrates that climate models can appropriately reproduce historical trends and that a decrease of characteristic values of the snow loads is expected over time. However, it must be remarked that, if on one hand the mean value of the annual maxima tends to reduce, on the other hand, its standard deviation tends to increase, locally leading to an increase of the extreme values, which should be duly considered in the evaluation of structural reliability over time.

Preliminary Forecasting of Rainfall-Induced Shallow Landslides in the Wildfire Burned Areas of Western Greece

A new methodology for shallow landslide forecasting in wildfire burned areas is proposed by estimating the annual probability of rainfall threshold exceedance. For this purpose, extensive geological fieldwork was carried out in 122 landslides, which have been periodically activated in Western Greece, after the devastating wildfires that occurred in August 2007 and burned large areas in several parts of Western Greece. In addition, daily rainfall data covering more than 40 years has been collected and statistically processed to estimate the exceedance probability of the rainfall threshold above which these landslides are activated. The objectives of this study are to quantify the magnitude and duration of rainfall above which landslides in burned areas are activated, as well as to introduce a novel methodology on rainfall-induced landslide forecasting. It has been concluded that rainfall-induced landslide annual exceedance probability in the burned areas is higher when cumulative rainfall duration ranges from 6 to 9 days with local differences due to the prevailing geological conditions and landscape characteristics. The proposed methodology can be used as a basis for landslide forecasting in wildfire-affected areas, especially when triggered by rainfall, and can be further developed as a tool for preliminary landslide hazard assessment.

An Empirical Method for Estimating Source Vicinity Ground-Motion Levels on Hard Bedrock and Annual Exceedance Probabilities for Inland Crustal Earthquakes with Sources Difficult to Identify in Advance

ABSTRACT The locations and scales of the seismic sources of inland crustal earthquakes without surface fault traces (Mw≲6.5 in Japan) are difficult to identify in advance, even by conducting detailed surveys, and in such a case, it seems rational to uniformly evaluate ground-motion levels in the regions with similar seismogenic conditions. For such earthquakes, we first developed a technique to estimate ground-motion levels in a specific area by calculating the response spectra corresponding to nonexceedance probabilities (NEPs) based on probability density functions derived using strong-motion records. These records were used in the analysis after adjustments to the condition of being and on hard bedrock (VS≈2000–3000 m/s) in the source vicinity. Next, we developed an empirical method to estimate the correspondence between the NEP spectrum levels and their annual exceedance probabilities (AEPs) by considering annual occurrence frequencies for the target event group. Moreover, we showed an example that applied our approach to all over Japan, where a large number of downhole records on stiff baserock (VS≈700–3000 m/s) have been obtained by the KiK-net, a dense nationwide network of vertical array stations (pairs of surface and downhole recordings). In the example, we demonstrated that the empirical AEP spectral levels using our method are consistent with AEP response spectra, that is, uniform hazard spectra, derived from the probabilistic seismic hazard analysis using the kinematic fault rupture modeling method in a previous study.

Assessing compound flooding potential with multivariate statistical models in a complex estuarine system under data constraints

AbstractCompound flooding may result from the interaction of two or more contributing processes, which may not be extreme themselves, but in combination lead to extreme impacts. Here, we use statistical methods to assess compounding effects from storm surge and multiple riverine discharges in Sabine Lake, TX. We employ several trivariate statistical models, including vine‐copulas and a conditional extreme value model, to examine the sensitivity of results to the choice of data pre‐processing steps, statistical model setup, and outliers. We define a response function that represents water levels resulting from the interaction between discharge and surge processes inside Sabine Lake and explore how it is affected by including or ignoring dependencies between the contributing flooding drivers. Our results show that accounting for dependencies leads to water levels that are up to 30 cm higher for a 2% annual exceedance probability (AEP) event and up to 35 cm higher for a 1% AEP event, compared to assuming independence. We also find notable variations in the results across different sampling schemes, multivariate model configurations, and sensitivity to outlier removal. Under data constraints, this highlights the need for testing various statistical modelling approaches, while the choice of an optimal approach remains subjective.

Viability assessment of algal wastewater treatment projects under outdoor conditions based on algal productivity and nutrient removal rate

In this work, a viability study of algal wastewater treatment projects under outdoor conditions is proposed. The viability analysis of solar plant projects based on annual exceedance probability, which is the probability that a certain energy value will be exceeded, is applied. The two outputs used (algal productivity and ammonium uptake rate) are obtained from literature models under different scenarios. The first scenario studies algal productivity of the microalgae Chlorella vulgaris cultivation in an open pond system. The second scenario considers the ammonium uptake rate of the microalgae Scenedesmus sp. Cultivation in a flat-plate photobioreactor. Both scenarios are set out under outdoor conditions in two stations with different climates.The work also aims at including in the viability study an analysis of the intermittency of productivity/ammonium uptake rate to take into account intra-annual variability. The study of variability is usually limited to the estimation of statistics during each season. The methodology proposed, based on exceedance probabilities of variation, evaluates discontinuities in the production and/or nutrient removal processes.Finally, the work aims at evaluating the effects of storage on the discontinuities that can compromise project viability defining the Risk Factor Improvement Index. This index assesses the degree of improvement in viability due to discontinuity in productivity and ammonium removal processes provided by storage. According to this index, improvements of up to 31% for the productivity and up to 20% for the ammonium uptake rate can be reached. By including storage, the discontinuity effect and thus the intermittency analysis may be disregarded.

Modeling nearshore dynamics of extreme storms in complex environments of Connecticut

Flood hazard planning requires the accurate estimation of total water elevation due to predicted tide, surge, and wave runup to design flood protection structures and improve coastal risk planning for severe storms. The beach geomorphology and nearshore hydrodynamic conditions impact the conclusive flood inundation mapping in complex environments. The conventional approaches of flood modeling are limited due to either i) simple static estimates, ii) the application of a coupled circulation and phase-averaged wave models in coarse resolution, iii) failing to calibrate and validate with in-situ data, or iv) not considering sea-level rise projections in mapping the flood extent. We used a fully nonlinear Boussinesq wave model (FUNWAVE-TVD) on the nearshore area with a high-resolution grid to determine total water elevation on the shores. The model adopted the boundary conditions from coupled circulation and wave model of the Long Island Sound (Liu et al., 2020).We applied the model to Branford, Norwalk, and New Haven, CT to represent the complex topo-bathymetric features and the structural interference in shallow water wave dynamics. We compared the model results with the FEMA base flood elevation, the North Atlantic Coast Comprehensive Study (NACCS), and (Liu et al., 2020)’s Long Island Sound FVCOM-SWAVE model. The FUNWAVE-TVD model is found to model wave processes more accurately in shallow water regions compared to the empirical equation application of FEMA and coupled circulation-phase averaged model application of NACCS and FVCOM-SWAVE. We also examined local sea-level rise predictions of storms with 1% and 10% annual exceedance probability by the year 2050 in Connecticut and found that the flood extent of these two storms showed little to no difference. We suggest the planning approaches should consider the increase in the frequency of the storms in the predicted inundation zones due to sea-level rise.