Astronomical high tides and meteorological storm surges present a combined flood hazard to communities and infrastructure. There is a need to incorporate the impact of tide-surge interaction and the spatial and temporal variability of the combined flood hazard in flood risk assessments, especially in hyper-tidal estuaries where the consequences of tide and storm surge concurrence can be catastrophic. Delft3D-FLOW is used to assess up-estuary variability in extreme water levels for a range of historical events of different severity within the Severn Estuary, southwest England as an example. The influence of the following on flood hazard is investigated: (i) event severity, (ii) timing of the peak of a storm surge relative to tidal high water and (iii) the temporal distribution of the storm surge component (here in termed the surge skewness). Results show when modelling a local area event severity is most important control on flood hazard. Tide-surge concurrence increases flood hazard throughout the estuary. Positive surge skewness can result in a greater variability of extreme water levels and residual surge component, the effects of which are magnified up-estuary by estuarine geometry to exacerbate flood hazard. The concepts and methodology shown here can be applied to other estuaries worldwide.

Storm surge is often the greatest threat to life and critical infrastructures during hurricanes and violent storms. Millions of people living in low-lying coastal zones and critical infrastructure within this zone rely on accurate storm surge forecast for disaster prevention and flood hazard mitigation. However, variability in residual sea level up-estuary, defined here as observed sea level minus predicted tide, can enhance total water levels; variability in the surge thus needs to be captured accurately to reduce uncertainty in site specific hazard assessment. Delft3D-FLOW is used to investigate surge variability, and the influence of storm surge timing on barotropic tide-surge propagation in a tide-dominant estuary using the Severn Estuary, south-west England, as an example. Model results show maximum surge elevation increases exponentially up-estuary and, for a range of surge timings consistently occurs on the flood tide. In the Severn Estuary, over a distance of 40 km from the most upstream tide gauge at Oldbury, the maximum surge elevation increases by 255%. Up-estuary locations experience short duration, high magnitude surge elevations and greater variability due to shallow-water effects and channel convergence. The results show that surge predictions from forecasting systems at tide gauge locations could under-predict the magnitude and duration of surge contribution to up-estuary water levels. Due to the large tidal range and dynamic nature of hyper-tidal estuaries, local forecasting systems should consider changes in surge elevation and shape with distance up-estuary from nearby tide gauge sites to minimize uncertainties in flood hazard assessment.

Coastal flood warning and design of coastal protection schemes rely on accurate estimations of water level and waves during hurricanes and violent storms. These estimations frequently use numerical models, which, for computational reasons, neglect the interaction between the hydrodynamic and wave fields. Here, we show that neglecting such interactions, or local effects of atmospheric forcing, causes large uncertainties, which could have financial and operational consequences because flood warnings are potentially missed or protection schemes underdesigned. Using the Severn Estuary, SW England, we show that exclusion of locally generated winds underestimates high water significant wave height by up to 90.1%, high water level by 1.5%, and hazard proxy (water level + 1/2 significant wave height) by 9.1%. The uncertainty in water level and waves is quantified using a system to model tide-surge-wave conditions, Delft3D-FLOW-WAVE in a series of eight model simulations for four historic storm events.Plain Language Summary Coastal zones worldwide are subject to combined effects of astronomical tides, meteorological storms surges, waves, and wind during storms and hurricanes, which can lead to flooding, property damage, and casualties. Coastal communities and critical infrastructure rely on accurate water level and wave forecasts to mitigate these combined hazards. Forecasts utilize hydrodynamic numerical models, which need to accurately represent these hazards and how they interact with, and feedback to, each other. This study uses a model, Delft3D-FLOW-WAVE, to calculate how tides and waves from four historic storm events combine to contribute to water level, wave height, and hazard proxy (water level + 1/2 wave height) in the Severn Estuary, southwest England. Additional simulations are run to show how local winds can further contribute to the hazard. Results show that including locally generating winds in simulations of water level, wave height, and hazard proxy is most important for accurate representation of physical processes that contribute to coastal hazards. Excluding locally generated winds from numerical model predictions could mean that flood alerts, warnings, and evacuation orders are missed, or coastal protection schemes are underdesigned, potentially leading to more flooding.

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Estuaries are potentially exposed to compound flooding where weather-driven extreme sea levels can occur synchronously with extreme fluvial discharge to amplify the hazard. The likelihood of compound flooding is difficult to determine due to multiple interacting physical processes operating at sub-daily scales, and poor observation records within estuaries with which to determine potential future probabilistic scenarios. We hypothesize that fluvial extremes can occur within the peak of the surge in small/steep catchments because of rapid runoff times, whilst the length-scale in larger/flatter catchments will result in fluvial and marine extremes being out-of-phase. Data (15 min river flow and hourly sea level) spanning 40 years were analyzed to assesses the behaviour and timings of fluvial and sea level extremes in two contrasting estuaries: Humber and Dyfi (United Kingdom). Compound events were common in the Dyfi, a small/steep catchment on Britain’s west coast with fast fluvial response times. Almost half of the 937 skew-surge events (95th-percentile) occurred within a few hours of an extreme fluvial peak, suggesting that flood risk is sensitive to the storm timing relative to high tide—especially since flows persisted above the 95th-percentile typically for less than 12 h. Compound events were more frequent during autumn/winter than spring/summer. For the Humber, a larger/flatter catchment on the east coast with slower fluvial response times, extreme fluvial and skew-surge peaks were less frequent (half as many as the Dyfi) and compound events were less common (15% of events co-occurred). Although flows in the Humber persisted above the 95th-percentile for typically between one and 4 days, hence overlapping several high tides and possibly other surges. Analysis of 56 flooding events across both estuaries revealed: 1) flooding is more common in the Dyfi than Humber; 2) Dyfi flooding is driven by 99th-percentile flows lasting hours and co-occurring with a 95th percentile skew-surge; 3) Humber flooding was driven by 95th-percentile flows lasting days, or surge-driven—but rarely co-occurring. Our results suggest that compound flooding studies require at least hourly data (previous analyses have often used daily-means), especially for smaller systems and considering the potential intensification of rainfall patterns into the future.

Compound estuarine flooding is driven by extreme sea-levels and river discharge occurring concurrently, or in close succession, and threatens low-lying coastal regions worldwide. We hypothesise that these drivers of flooding rarely occur independently and co-operate at sub-daily timescales. This research aimed to identify regions and individual estuaries within Britain susceptible to storm-driven compound events, using 27 tide gauges linked to 126 river gauges covering a 30-year record. Five methods were evaluated, based on daily mean, daily maximum, and instantaneous 15-min discharge data to identify extremes in the river records, with corresponding skew surges identified within a ‘storm window’ based on average hydrograph duration. The durations, relative timings, and overlap of these extreme events were also calculated. Dependence between extreme skew surge and river discharge in Britain displayed a clear east–west split, with gauges on the west coast showing stronger correlations up to 0.33. Interpreting dependence based on correlation alone can be misleading and should be considered alongside number of historic extreme events. The analyses identified 46 gauges, notably the Rivers Lune and Orchy, where there has been the greatest chance and most occurrences of river-sea extremes coinciding, and where these events readily overlapped one another. Our results were sensitive to the analysis method used. Most notably, daily mean discharge underestimated peaks in the record and did not accurately capture likelihood of compound events in 68% of estuaries. This has implications for future flood risk in Britain, whereby studies should capture sub-daily timescale and concurrent sea-fluvial climatology to support long-term flood management plans.

Climate-change-induced hazards are negatively affecting the small islands across Indonesia. Sabang Island is one of the most vulnerable small islands due to the rising sea levels and increasing coastal inundation which threaten the low-lying coastal areas with and without coastal defences. However, there is still a lack of studies concerning the long-term trends in climatic variables and, consequently, sea level changes in the region. Accordingly, the current study attempts to comprehensively assess sea level changes and coastal inundation through satellite-derived datasets and model-based products around Sabang Island, Indonesia. The findings of the study show that the temperature (both minimum and maximum) and rainfall of the island are increasing by ~0.01 °C and ~11.5 mm per year, respectively. The trends of temperature and rainfall are closely associated with vegetative growth; an upward trend in the dense forest is noticed through the enhanced vegetation index (EVI). The trend analysis of satellite altimeter datasets shows that the sea level is increasing at a rate of 6.6 mm/year. The DEM-based modelling shows that sea level rise poses the greatest threat to coastal habitations and has significantly increased in recent years, accentuated by urbanisation. The GIS-based model results predict that about half of the coastal settlements (2.5 sq km) will be submerged completely within the next 30 years, provided the same sea level rise continues. The risk of coastal inundation is particularly severe in Sabang, the largest town on the island. The results allow regional, sub-regional, and local comparisons that can assess variations in climate change, sea level rise, coastal inundation, and associated vulnerabilities.

Combination of uncertainties in water level and wave height predictions for extreme storms can result in unacceptable levels of error, rendering flood hazard assessment frameworks less useful. A 2D inundation model, LISFLOOD-FP, was used to quantify sensitivity of flooding to uncertainty in coastal hazard conditions and method used to force the coastal boundary of the model. It is shown that flood inundation is more sensitive to small changes in coastal hazard conditions due to the setup of the regional model, than the approach used to apply these conditions as boundary forcing. Once the threshold for flooding is exceeded, a few centimetres increase in combined water level and wave height increases both the inundation and consequent damage costs. Improved quantification of uncertainty in inundation assessments can aid long-term coastal flood hazard mitigation and adaptation strategies, to increase confidence in knowledge of how coastlines will respond to future changes in sea-level.