Tropical-cyclone impacts can have devastating effects on the population, infrastructure, and natural habitats. However, predicting these impacts is difficult due to the inherent uncertainties in the storm track and intensity. In addition, due to computational constraints, both the relevant ocean physics and the uncertainties in meteorological forcing are only partly accounted for. This paper presents a new method, called the Tropical Cyclone Forecasting Framework (TC-FF), to probabilistically forecast compound flooding induced by tropical cyclones, considering uncertainties in track, forward speed, and wind speed and/or intensity. The open-source method accounts for all major relevant physical drivers, including tide, surge, and rainfall, and considers TC uncertainties through Gaussian error distributions and autoregressive techniques. The tool creates temporally and spatially varying wind fields to force a computationally efficient compound-flood model, allowing for the computation of probabilistic wind and flood hazard maps for any oceanic basin in the world as it does not require detailed information on the distribution of historical errors. A comparison of TC-FF and JTWC operational ensembles, both based on DeMaria et al. (2009), revealed minor differences of <10 %, suggesting that TC-FF can be employed as an alternative, for example, in data-scarce environments. The method was applied to Cyclone Idai in Mozambique. The underlying physical model showed reliable skill in terms of tidal propagation, reproducing the storm surge generation during landfall and flooding near the city of Beira (success index of 0.59). The method was successfully applied to forecasting the impact of Idai with different lead times. The case study analyzed needed at least 200 ensemble members to get reliable water levels and flood results 3 d before landfall (<1 % flood probability error and <20 cm sampling errors). Results showed the sensitivity of forecasting, especially with increasing lead times, highlighting the importance of accounting for cyclone variability in decision-making and risk management.@en

Rip currents are one of the most dangerous coastal hazards for swimmers. In order to minimize the risk, a coastal operational-process based-model system can be utilized in order to provide forecast of nearshore waves and currents that may endanger beach goers. In this paper, an operational model for rip current prediction by utilizing nearshore bathymetry obtained from video image technique is demonstrated. For the nearshore scale model, XBeach1 is used with which tidal currents, wave induced currents (including the effect of the wave groups) can be simulated simultaneously. Up-to-date bathymetry will be obtained using video images technique, cBathy2. The system will be tested for the Egmond aan Zee beach, located in the northern part of the Dutch coastline. This paper will test the applicability of bathymetry obtained from video technique to be used as input for the numerical modelling system by comparing simulation results using surveyed bathymetry and model results using video bathymetry. Result s show that the video technique is able to produce bathymetry converging towards the ground truth observations. This bathymetry validation will be followed by an example of operational forecasting type of simulation on predicting rip currents. Rip currents flow fields simulated over measured and modeled bathymetries are compared in order to assess the performance of the proposed forecast system.@en

People living behind coastal dunes depend on the strength and resilience of dunes for their safety. Forecasts of hydrodynamic conditions and morphological change on a timescale of several days can provide essential information to protect lives and property. In order for forecasts to protect they need be relevant, accurate, provide lead time, and information on confidence. Here we show how confident one can be in morphological predictions of several days ahead. The question is answered by assessing the forecast skill as a function of lead time. The study site in the town of Egmond, the Netherlands, where people depend on the dunes for their safety, is used because it is such a rich data source, with a history of forecasts, tide gauges and bathymetry measurements collected by video cameras. Even though the forecasts are on a local scale, the methods are generally applicable. It is shown that the intertidal beach volume change can be predicted up to three days ahead.

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Knowledge of the actual condition of hydrodynamics in the nearshore and coastal area is essential for coastal monitoring activities. To this end, a coastal operational model system can serve as a tool in providing recent and up-to-date, state-of-the-art hydrodynamics along the coast. In this paper, we apply CoSMoS (Coastal Storm Modeling System), a generic operational wave and tide-surge modelling system applied here to predict waves and water levels along the Dutch coast. The CoSMoS application is not limited to storm impact prediction on the Dutch coast, but can also be applied to other coastal hazards such as rip currents and coastal flooding, in other environments. In this paper, we present the set-up of the CoSMoS system and a validation of the wave and surge model, with deep-water wave buoy data and tidal gauge measurements as ground truth validation material. The evaluation is presented as monthly error measures between computed parameters and observed ones. Hindcast results over the whole year of 2009 show that the simulated wave parameters and surge elevation from the CoSMoS are in good agreement with data, with average root mean square (rms) error over the year of 0.14 m for the surge elevation and 0.24 m for the significant wave height. It is noted that there is a tendency of the wave model to underestimate the height of northerly waves with lower frequencies (swell). Additionally, when a wave separation algorithm is applied on the overall spectrum, results show consistent underestimation of the swell component by the model, which for the Dutch coast will mainly come from the north, where the North Sea is open to the Atlantic Ocean. In the proposed model system, the swell boundary can have a significant effect on the simulated wave results, suggesting room for improvement for the swell boundary conditions to the north and the swell propagation within the Dutch Continental Shelf Model. Finally, we show that in forecast mode, CoSMoS can provide reasonably good wave and surge prediction.

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This paper demonstrates the potential use of nearshore bathymetry estimated from video data in a coastal operational model for the Dutch Coast, which provides daily forecast of waves, water levels and (rip) currents. Two video techniques to obtain beach bathymetry from video data- Beach Wizard and CBathy are validated against jet ski surveyed bathymetry. Both methods show good agreement with surveyed data, and bathymetric features of the beach are adequately produced. To assess the applicability of video-derived bathymetry for the purpose of rip current predictions, a model is built for Egmond aan Zee in The Netherlands, in which rip current predictions based on video-derived bathymetry are compared with those based on the jetski survey. Results show that predicted maximum mean offshore-directed (rip) velocities are in good agreement when using surveyed bathymetry (reference model) and video-derived bathymetry. Finally, to address the rip current forecasting skill, this local model is forced by wave boundary conditions obtained from a larger-scale wave prediction model, in addition to the bathymetry from video. Results show that useful information can still be obtained regarding the rip currents' flow where maximum offshore-directed velocities obtained from the predictive model resemble adequately rip currents pattern in the reference model. This paper will discuss each component of the model system and the validation result on hindcasting and forecasting rip currents.@en