AbstractCurrent practice using probabilistic methods applied for designing hydraulic structures generally assume that extreme events are stationary. However, many studies in the past decades have ...shown that hydrological records exhibit some type of nonstationarity such as trends and shifts. Human intervention in river basins (e.g., urbanization), the effect of low-frequency climatic variability (e.g., Pacific Decadal Oscillation), and climate change due to increased greenhouse gasses in the atmosphere have been suggested to be the leading causes of changes in the hydrologic cycle of river basins in addition to changes in the magnitude and frequency of extreme floods and extreme sea levels. To tackle nonstationarity in hydrologic extremes, several approaches have been proposed in the literature such as frequency analysis, in which the parameters of a given model vary in accordance with time. The aim of this paper is to show that some basic concepts and methods used in designing flood-related hydraulic structures assuming a stationary world can be extended into a nonstationary framework. In particular, the concepts of return period and risk are formulated by extending the geometric distribution to allow for changing exceeding probabilities over time. Building on previous developments suggested in the statistical and climate change literature, the writers present a simple and unified framework to estimate the return period and risk for nonstationary hydrologic events along with examples and applications so that it can be accessible to a broad audience in the field. The applications demonstrate that the return period and risk estimates for nonstationary situations can be quite different than those corresponding to stationary conditions. They also suggest that the nonstationary analysis can be helpful in making an appropriate assessment of the risk of a hydraulic structure during the planned project-life.
AbstractEstimating design quantiles for extreme floods in river basins under nonstationary conditions is an emerging field. Nonstationarities could arise from a variety of human and natural factors ...such as urbanization and climate change. Concepts of return period, design quantile (return level), and risk have already been developed for situations in which increasing or decreasing trends and abrupt shifts in extreme events are present. Because of limited data records, sampling variability, model errors, and the errors in projections into the future, significant uncertainties in the estimates of design floods of future projects will arise. To address the issue of uncertainty resulting from limited sample size of the observations, three methods have been developed for computing confidence intervals for the design quantile corresponding to a desired return period under a nonstationary framework, including (a) delta, (b) bootstrap, and (c) profile likelihood methods. These methods have been developed assuming a generalized extreme value distribution with nonstationary parameters. The applicability and comparison of the proposed methods for determining the confidence interval of quantiles have been demonstrated by using the annual flood maxima of the Assunpink Creek in New Jersey. The delta method, with numerically derived local derivatives, and the approximate bootstrap can be computationally efficient. The profile likelihood method, which is known to be more accurate, is quite burdensome computationally but provides more realistic asymmetric confidence intervals.
The cooccurrence of coastal and riverine flooding leads to compound events with substantial impacts on people and property in low‐lying coastal areas. Climate change could increase the level of ...compound flood hazard through higher extreme sea levels and river flows. Here, a bivariate flood hazard assessment method is proposed to estimate compound coastal‐riverine frequency under current and future climate conditions. A copula‐based approach is used to estimate the joint return period (JRP) of compound floods by incorporating sea‐level rise (SLR) and changes in peak river flows into the marginal distributions of flood drivers. Specifically, the changes in JRP of compound major coastal‐riverine flooding defined based on simultaneous exceedances above major coastal and riverine thresholds, are explored by midcentury. Subsequently, the increase in the probability of occurrence of at least one compound major coastal‐riverine flooding for a given period of time is quantified. The proposed compound flood hazard assessment is conducted at 26 paired tidal‐riverine stations along the Contiguous United States coast with long‐term data and defined flood thresholds. We show that the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal‐riverine flood probability under current conditions. However, future SLR scenarios show the highest frequency amplification along the southeast Atlantic coast. The impact of changes in peak river flows is found to be considerably less than that of SLR. Climate change impacts, especially SLR, may lead to more frequent compound events, which cannot be ignored for future adaptation responses in estuary regions.
Plain Language Summary
Compound coastal and inland flooding poses serious threats to many coastal cities around the world. Climate change could increase the level of compound flood hazard through sea level rise (SLR) and higher extreme precipitation and river flows. An example of recent compound flooding in the US is the cooccurrence of heavy precipitation and storm surge from Hurricane Harvey, which caused huge flooding along the Gulf coast of Texas. We propose a compound flood hazard assessment method to project compound coastal‐riverine flood frequency under climate change. Coastal and riverine flood impact thresholds are used to define compound major coastal‐riverine flooding. The application of the method along the Contiguous United States coast shows that SLR is the most prominent factor in increasing the frequency of future major compound flood events and the impact of changes in peak river flows is negligible in most of the locations. Under current climate conditions, the northeast Atlantic and the western part of the Gulf coasts are experiencing the highest compound major coastal‐riverine flood probability. However, future SLR scenarios show emerging high compound major flooding probability along the southeast Atlantic coast.
Key Points
A bivariate flood hazard assessment method is proposed to estimate compound coastal‐riverine frequency under climate change impacts
Future sea level rise scenarios show emerging high compound major flooding probability along the southeast Atlantic coast
The impact of changes in peak river flows is found to be significantly less than the impacts of sea level rise
Probabilities of coastal extreme water levels (EWLs) are increasing as sea levels rise. Using a time‐dependent statistical model on tide gauge data along U.S. and Pacific Basin coastlines, we show ...that EWL probability distributions also shift on an annual basis from climate forcing and long‐period tidal cycles. In some regions, combined variability (>15 cm) can be as large or larger than the amount of sea level rise (SLR) experienced over the past 30 years and projected over the next 30 years. Considering SLR and variability by 2050 at a location like La Jolla, California suggests a moderate‐level (damaging) flood today with a 50‐year return level (2% annual chance) would occur about 3–4 times a year during an El Nino nearing the peak of the nodal tide cycle. If interannual variability is overlooked, SLR related impacts could be more severe than anticipated based solely upon decadal‐scale projections.
Plain Language Summary
Coastal communities are flooding more often due to sea level rise (SLR), but some years are worse than others. We use a statistical model to show how the probabilities of coastal high waters, often referred to as extreme water levels—a combination of above average tides and storm surge—have shifted higher or lower every year with SLR and from changes in the tides and climatic (persistent weather and ocean) patterns. There are many U.S. and Pacific coastal regions where year‐to‐year variability is 15 cm or more, which is as large as the last 30 years of SLR and this pattern is projected to continue over the next 30 years. Considering additional SLR over the next 30 years could help compensate for year‐to‐year variability.
Key Points
Probability distributions of coastal extreme water levels shift higher and lower with tide cycles, climatic patterns and sea level rise (SLR)
Annual shifts of >15 cm from variability along Pacific coasts exceed SLR over the last 30 years and projected over the next 30 years
Annual‐scale variability envelopes are envisioned to assist in decadal‐scale SLR and flood frequency assessments
South Asian countries have been experiencing frequent drought incidents recently, and due to this reason, many scientific studies have been carried out to explore drought in South Asia. In this ...context, we review scientific studies related to drought in South Asia. The study initially identifies the importance of drought-related studies and discusses drought types for South Asian regions. The representative examples of drought events, severity, frequency, and duration in South Asian countries are identified. The Standardized Precipitation Index (SPI) was mostly adopted in South Asian countries to quantify and monitor droughts. Nevertheless, the absence of drought quantification studies in Bhutan and the Maldives is of great concern. Future studies to generate a combined drought severity map for the South Asian region are required. Moreover, the drought prediction and projection in the regions is rarely studied. Furthermore, the teleconnection between drought and large-scale atmospheric circulations in the South Asia has not been discussed in detail in most of the scientific literature. Therefore, as a take-home message, there is an urgent need for scientific studies related to drought quantification for some regions in South Asia, prediction and projection of drought for an individual country (or as a region), and drought teleconnection to atmospheric circulation.
In order to increase the flood resilience of cities (i.e., the ability to cope with flood hazards), it is also crucial to make critical infrastructure functions resilient, since these are essential ...for urban society. Cities are complex systems with many actors of different disciplines and many interdependent critical infrastructure networks and functions. Common flood risk analysis techniques provide useful information but are not sufficient to obtain a complete overview of the effects of flooding and potential measures to increase flood resilience related to critical infrastructure networks. Therefore, a more comprehensive approach is needed which helps accessing knowledge of actors in a structured way. Fort Lauderdale, Florida, United States has suffered from flood impacts, especially from disruptions in critical infrastructure. This paper shows how shared insight among different sectors and stakeholders into critical infrastructure resilience and potential resilience-enhancing measures was obtained using input from these actors. It also provides a first quantitative indication of resilience, indicated by the potential disruption due to floods and the effect of measures on resilience. The paper contributes to the existing literature on resilience specifically by considering the duration of disruption, the inclusion of critical infrastructure disruption in flood impact analysis, and the step from resilience quantification to measures.
Miami-Dade County is vulnerable to flash, pluvial, fluvial, coastal and groundwater flooding due to its low-elevation karst morphology. Despite considerable advances in understanding the impact of ...compound flooding events by considering major flood drivers (precipitation, river discharge, and coastal surge), little is known regarding the severity of groundwater hazards in this region. This study links a multivariate statistical analysis with a coupled physically-based 2D hydraulic model to estimate the flood hazard in the Arch Creek Basin located in North Miami. A bivariate copula analysis was used to capture the joint probability of key flood drivers with predefined water table thresholds to set-up the flood modeling conditions. Results demonstrate the high vulnerability to extreme precipitation events compared to coastal surge in the study area. Similarly, groundwater flooding is relevant in shallow water table environments, as it influences the severity of flood hazards in terms of flood inundation depth, extent, and damage to the built environment. This research demonstrates that groundwater flooding is a latent risk that should be incorporated in flood hazard mapping in regions susceptible to high water tables and sea level rise.
In this study, we used a comprehensive set of statistical metrics to investigate the historical trends in averages and extremes of rainfall and temperature in Sri Lanka. The data consist of 55 years ...(1961–2015) of daily rainfall, maximum temperature (Tmax), and minimum temperature (Tmin) records from 20 stations scattered throughout Sri Lanka. The linear trends were analyzed using the nonparametric Mann–Kendall test and Sen–Theil regression. The prewhitening method was first used to remove autocorrelation from the time series, and the modified seasonal Mann–Kendall test was then applied for the seasonal data. The results show that, during May, 15% of the stations showed a significant decrease in wet days, which may be due to the delayed southwest monsoon (SWM) to Sri Lanka. A remarkable increase in the annual average temperature of Tmin and Tmax was observed as 70% and 55% of the stations, respectively. For the entire period, 80% of the stations demonstrated statistically significant increases of Tmin during June and July. The daily temperature range (DTR) exhibited a widespread increase at the stations located within the southwestern coast region of Sri Lanka. Although changes in global climate, teleconnections, and local deforestation in recent decades at least partially influence the trends observed in Sri Lanka, a formal trend attribution study should be conducted.
A regional frequency analysis (RFA) of tide gauge (TG) data fit with a Generalized Pareto Distribution (GPD) is used to estimate contemporary extreme sea level (ESL) probabilities and the risk of a ...damaging flood along Pacific Basin coastlines. Methods to localize and spatially granulate the regional ESL (sub-annual to 500-yr) probabilities and their uncertainties are presented to help planners of often-remote Pacific Basin communities assess (ocean) flood risk of various threshold severities under current and future sea levels. Downscaling methods include use of local TG observations of various record lengths (e.g., 1-19+ years), and if no in-situ data exist, tide range information. Low-probability RFA ESLs localized at TG locations are higher than other recent assessments and generally more precise (narrower confidence intervals). This is due to increased rare-event sampling as measured by numerous TGs regionally. For example, the 100-yr ESLs (1% annual chance event) are 0.15 m and 0.25 higher (median at-site difference) than a single-TG based analysis that is closely aligned to those supporting recent Intergovernmental Panel on Climate Change (IPCC) assessments and a third-generation global tide and surge model, respectively. Height thresholds for damaging flood levels along Pacific Basin coastlines are proposed. These floods vary between about 0.6-1.2 m or more above the average highest tide and are associated with warning levels of the U.S. National Oceanic and Atmospheric Administration (NOAA). The risk of a damaging flood assessed by the RFA ESL probabilities under contemporary sea levels have about a (median) 20 to 25-yr return interval (4-5% annual chance) for TG locations along Pacific coastlines. Considering localized sea level rise projections of the IPCC associated with a global rise of about 0.5 m by 2100 under a reduced emissions scenario, damaging floods are projected to occur annually by 2055 and >10 times/year by 2100 at the majority of TG locations.
Water resource management in South Florida faces nearly intractable problems, in part due to weather and climate variability. Rising sea level and coastal storm surge are two phenomena with ...significant impacts on natural systems, fresh water supplies and flood drainage capability. However, decision support information regarding management of water resources in response to storm surge is not well developed. In an effort to address this need we analyze long term tidal records from Key West, Pensacola and Mayport Florida to extract surge distributions, to which we apply a nonlinear eustatic sea level rise model to project storm surge return levels and periods. Examination of climate connections reveals a statistically significant dependence between surge distributions and the Atlantic Multidecadal Oscillation (AMO). Based on a recent probabilistic model for AMO phase changes, we develop AMO-dependent surge distributions. These AMO-dependent surge projections are used to examine the flood control response of a coastal water management structure as an example of how climate dependent water resource forcings can be used in the formulation of decision support tools.
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