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As urbanization and climate change alter sediment fluxes, relative sea level, and coastal erosion around the world, management of sediment as a resource is increasingly important. Sediment is needed to enhance marsh accretion rates, raise the grade elevation of development, and build up beaches and dunes. Beneficial reuse of sediment refers to the repurposing of local sources of sediment for these applications, material typically available from dredging or sediment capture infrastructure, and represents a more sustainable approach compared to the status-quo involving transport to and from distant locations. However, in many locations, beneficial reuse remains a concept or is constrained to small-scale applications. In this paper, we draw on interviews with coastal sediment managers and regulators in Southern California to identify barriers to beneficial reuse and opportunities to overcome them. Interviewees reported numerous regulatory, technical, psychological, financial, and interorganizational barriers in their watersheds and regions. By highlighting these barriers, we aim to identify systemic changes that would make beneficial reuse a realistic and accessible option for Southern California and elsewhere. Most prominently, a more flexible regulatory framework that allows sediment management practices to adapt over time, pilot studies to understand how beneficial reuse works in various settings, and educational programs for regulators and the public could make beneficial reuse a more widespread approach.

Sea level rise (SLR), a well-documented and urgent aspect of anthropogenic global warming, threatens population and assets located in low-lying coastal regions all around the world. Common flood hazard assessment practices typically account for one driver at a time (e.g., either fluvial flooding only or ocean flooding only), whereas coastal cities vulnerable to SLR are at risk for flooding from multiple drivers (e.g., extreme coastal high tide, storm surge, and river flow). Here, we propose a bivariate flood hazard assessment approach that accounts for compound flooding from river flow and coastal water level, and we show that a univariate approach may not appropriately characterize the flood hazard if there are compounding effects. Using copulas and bivariate dependence analysis, we also quantify the increases in failure probabilities for 2030 and 2050 caused by SLR under representative concentration pathways 4.5 and 8.5. Additionally, the increase in failure probability is shown to be strongly affected by compounding effects. The proposed failure probability method offers an innovative tool for assessing compounding flood hazards in a warming climate.

Nuisance flooding corresponds to minor and frequent flood events that have significant socioeconomic and public health impacts on coastal communities. Yearly averaged local mean sea level can be used as proxy to statistically predict the impacts of sea level rise (SLR) on the frequency of nuisance floods (NFs). In this study, we use generalized linear models (GLM) and Gaussian Process (GP) models combined to (i) estimate the frequency of NF associated with the change in mean sea level, and (ii) quantify the associated uncertainties via a novel and statistically robust approach. We calibrate our models to the water level data from 18 tide gauges along the coasts of United States, and after validation, we estimate the frequency of NF associated with the SLR projections in year 2030 (under RCPs 2.6 and 8.5), along with their 90% bands, at each gauge. The historical NF-SLR data are very noisy, and show large changes in variability (heteroscedasticity) with SLR. Prior models in the literature do not properly account for the observed heteroscedasticity, and thus their projected uncertainties are highly suspect. Among the models used in this study, the Negative Binomial Distribution GLM with GP best characterizes the uncertainties associated with NF estimates; on validation data (Formula presented.) 93% of the points fall within the 90% credible limit, showing our approach to be a robust model for uncertainty quantification.

Abstract: Nuisance flooding (NF) refers to low levels of inundation that do not pose significant threats to public safety or cause major property damage, but can disrupt routine day‐to‐day activities, put added strain on infrastructure systems such as roadways and sewers, and cause minor property damage. NF has received some attention in the context of low‐lying coastal cities exposed to increasingly higher high tides, a consequence of sea level rise, which exceeds the heights of coastal topography. However, low levels of flooding are widespread and deserve greater attention. Here a simple, quantitative definition of NF is proposed based on established flood intensity thresholds for flood consequences (e.g., pedestrian safety, property damage, and health risks). Based on a wide range of literature including hydrology, transportation, public health risk, and safety impacts, we define NF based on depth >3 cm and <10 cm, regardless of the source. This definition of NF is not limited to high tide flooding but rather is inclusive of all possible flood drivers including pluvial, fluvial, and oceanic and can capture trends in NF resulting from trends in, and compounding effects of, flood drivers. Furthermore, we also distinguish between NF as a process and NF as an event, which is important for linking NF to societal impacts and developing effective policy interventions and mitigation strategies. Potential applications and implications of NF monitoring are also presented. [ABSTRACT FROM AUTHOR]

Climate change may affect ocean-driven coastal flooding regimes by both raising the mean sea level (msl) and altering ocean-atmosphere interactions. For reliable projections of coastal flood risk, information provided by different climate models must be considered in addition to associated uncertainties. In this paper, we propose a framework to project future coastal water levels and quantify the resulting flooding hazard to infrastructure. We use Bayesian Model Averaging to generate a weighted ensemble of storm surge predictions from eight climate models for two coastal counties in California. The resulting ensembles combined with msl projections, and predicted astronomical tides are then used to quantify changes in the likelihood of road flooding under representative concentration pathways 4.5 and 8.5 in the near-future (1998-2063) and mid-future (2018-2083). The results show that road flooding rates will be significantly higher in the near-future and mid-future compared to the recent past (1950-2015) if adaptation measures are not implemented. [ABSTRACT FROM AUTHOR]

The cumulative cost of frequent events (e.g., nuisance floods) over time may exceed the costs of the extreme but infrequent events for which societies typically prepare. Here we analyze the likelihood of exceedances above mean higher high water and the corresponding property value exposure for minor, major, and extreme coastal floods. Our results suggest that, in response to sea level rise, nuisance flooding (NF) could generate property value exposure comparable to, or larger than, extreme events. Determining whether (and when) low cost, nuisance incidents aggregate into high cost impacts and deciding when to invest in preventive measures are among the most difficult decisions for policymakers. It would be unfortunate if efforts to protect societies from extreme events (e.g., 0.01 annual probability) left them exposed to a cumulative hazard with enormous costs. We propose a Cumulative Hazard Index ( CHI) as a tool for framing the future cumulative impact of low cost incidents relative to infrequent extreme events. CHI suggests that in New York, NY, Washington, DC, Miami, FL, San Francisco, CA, and Seattle, WA, a careful consideration of socioeconomic impacts of NF for prioritization is crucial for sustainable coastal flood risk management. [ABSTRACT FROM AUTHOR]

Schubert, J.E.; Gallien, T.W.; Majd, M.S., and Sanders, B.F., 2015. Terrestrial laser scanning of anthropogenic beach berm erosion and overtopping. Anthropogenic berms are widely deployed to manage coastal flooding. The dynamic erosion of scraped berms exposed to waves and a rising tide in southern California was monitored with a terrestrial laser scanner (TLS) on three occasions in February and March of 2012. An improved characterization of initial berm geometry and the dynamics of berm erosion was pursued to accurately predict the onset and impact of coastal flooding associated with berm erosion and overtopping. TLS is shown to yield a digital terrain model (DTM) with a vertical accuracy of ca. 3 cm, indicating it is an excellent source of data for initializing mechanistic and/or empirical models that could be used to predict the onset and rate of wave overtopping. Minimum scan point spacings required to achieve this level of accuracy are investigated and reported. Additionally, a dimensionless water level representing the fractional submergence of the berm is identified as a good predictor of cumulative berm erosion under the test conditions. [ABSTRACT FROM AUTHOR]

Coastal flood risk in California is concentrated around urbanized embayments that are protected by infrastructure, such as levees, pumps, and flood walls, which pose a challenge to accurate flood prediction. A capability to predict coastal urban flooding at the parcel-scale (individual home or street) from high ocean levels (extreme high tides) is shown here by coupling a regional ocean forecasting system to an embayment-scale hydrodynamic model that incorporates detailed information about flood defenses. A unique flooding data set affords the rare opportunity to validate model predictions and allows us to identify model data that are essential for accurate forecasting. In particular, results show that flood defense height data are critical, and here, that information is supplied by a Real Time Kinematic Global Positioning System (RTK-GPS) survey, which yields ca. 1-cm, vertical root mean-squared error accuracy. Bathymetry surveys and aerial Light Detection and Ranging (LIDAR) data characterizing the embayment also prove essential. Moreover, hydrodynamic modeling of flood inundation is shown to significantly improve on planar surface models, which overestimate inundation, particularly when manipulated to account for run-up in a simplistic way. This is attributed to the transient nature of overtopping flows and motivates the need for dynamic, spatially-distributed overtopping models that are tailored to the urban environment. [ABSTRACT FROM AUTHOR]

Existing needs to manage flood risk in the United States are underserved by available flood hazard information. This contributes to an alarming escalation of flood impacts amounting to hundreds of billions of dollars per year and countless disrupted lives and affected communities. Making information about flood hazards useful for the range of decisions that dictate the consequences of flooding poses many challenges. Here, we describe collaborative flood modeling, whereby researchers and end‐users at two coastal sites co‐develop fine‐resolution flood hazard models and maps responsive to decision‐making needs. We find, first of all, that resident perception and awareness of flooding are enhanced more by fine‐resolution depth contour maps than Federal Emergency Management Agency (FEMA) flood hazard classification maps and that viewing fine‐resolution depth contour maps helps to minimize differences in flood perception across subgroups within the community, generating a shared understanding. We also find that collaborative flood modeling supports the engagement of a wide range of end‐users in contemplating the risks of flooding and provides strong evidence that the co‐produced knowledge can be readily adopted and applied for Flood Risk Management (FRM). Overall, collaborative flood modeling advances FRM by providing multiple points of entry for diverse groups of end‐users to contemplate the spatial extent, intensity, timing, chance, and consequences of flooding, thus enabling the web of decision‐making related to flooding to be better informed with the best available science. This transdisciplinary approach emphasizes vulnerability reduction and is complementary to FEMA Flood Insurance Rate Maps used for flood insurance administration. Plain Language Summary: This work demonstrates a new process for communities to build flood resilience: collaborative flood modeling. Development of fine‐resolution flood models by scientists and engineers serves as a focal point for community stakeholders to build useful knowledge and tools to address flooding. A key issue shown here is that fine‐resolution flood visualizations help diverse community stakeholders build a more shared awareness about flooding, which creates conditions favorable to improved flood management. Key Points: Resident perception and awareness of flooding are enhanced more by fine‐resolution depth contour maps than FEMA mapsViewing fine‐resolution flood maps helps to minimize differences in flood perception across subgroups of a communityCollaborative flood modeling is a transdisciplinary process to coproduce actionable flood information and knowledge [ABSTRACT FROM AUTHOR]

Highlights • Introduce sediment-related tidal asymmetry proxy based on skewness method. • Oceanic tides control peak current asymmetry and inter-tidal flats determine slack water asymmetry. • SLR reduces both peak current asymmetry and slack water asymmetry, suggesting a negative feedback mechanism. Abstract Tidal asymmetry in estuaries and lagoons (tidal basins) controls residual sediment transport, and quantifying tidal asymmetry is important for understanding the factors contributing to long-term morphological changes. Asymmetry in peak flood and ebb currents (Peak Current Asymmetry – PCA) controls residual transport of coarse sediment, and asymmetry in slack water duration preceding flood and ebb currents (Slack Water Asymmetry – SWA) controls residual transport of fine sediment. PCA and SWA are analyzed herein for Newport Bay, a tidal embayment in southern California, based on the skewness of tidal currents predicted for several stations by a hydrodynamic model. Use of skewness for tidal asymmetry is relatively new and offers several advantages over a traditional harmonic method including the ability to resolve variability over a wide range of time scales. Newport Bay is externally forced by mixed oceanic tides that are shown to be ebb dominant because of shorter falling tide than rising tide. Both PCA and SWA indicate ebb dominance that favors export of coarse and fine sediments, respectively, to the coastal ocean. However, we show that the ebb dominance of SWA is derived from the basin geometry and not the external forcing, while ebb dominance of PCA is linked to the external forcing and the basin geometry. We also show that tidal flats in Newport Bay play an important role in maintaining ebb dominated transport of both coarse and fine sediments. Loss of tidal flats could weaken PCA and reverse SWA to become flood dominant. Specifically, we show that sea level rise > 0.8 m that inundates tidal flats will begin to weaken ebb dominant PCA and SWA and that sea level rise > 1.0 m will reverse SWA to become flood dominant. This feedback mechanism is likely to be important for predicting long-term evolution of tidal basins under accelerating sea level rise. [ABSTRACT FROM AUTHOR]