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The hydrodynamic flows in the Singapore regional waters (SRW) are the result of a complex mix of tide, seasonal and meteorological effects. The study of non-tidal effects or sea level anomalies (SLA) in this region has shown that it is possible to model some of these anomalies. The present study addresses the non-tidal barotropic water levels and currents in the Singapore region in detail. This analysis includes a multi-scale approach, and addresses amongst others hydrodynamic model grid resolution and the importance of resolving non-linear tide–surge interaction. The results show that the water level and current anomalies phenomena in a complex region like SRW can be effectively modelled using an approach combining non-tidal barotropic and multi-scale numerical modelling. A detailed investigation of the levels of non-linear tide–surge interaction is carried out by simulating SLA events in the Singapore regional waters during North-East (positive SLA) and South-West (negative SLA) monsoons based on ECMWF numerical weather forcing conditions. The results of combining both approaches suggest that the finer grid resolution improves the accuracy of water level and current anomalies simulations. Furthermore, the results also indicate that for the simulations of non-tidal barotropic flows in this area, non-linear tide–surge interaction is important and should be taken into account. Finally, the behaviour of the non-tidal barotropic flow in the region and its changes with tidal variation in the shallow region of the Singapore Strait is now much better understood. Therefore, for reliable operational forecast of sea level, the inclusion of non-linear tide–surge interaction should be required in numerical models to reproduce both tides and surges with improved accuracy in this region. [ABSTRACT FROM AUTHOR]

Hydrodynamic models are commonly used for predicting water levels and currents in the deep ocean, ocean margins and shelf seas. Their accuracy is typically limited by factors, such as the complexity of the coastal geometry and bathymetry, plus the uncertainty in the flow forcing (deep ocean tide, winds and pressure). In Southeast Asian waters with its strongly hydrodynamic characteristics, the lack of detailed marine observations (bathymetry and tides) for model validation is an additional factor limiting flow representation. This paper deals with the application of ensemble Kalman filter (EnKF)-based data assimilation with the purpose of improving the deterministic model forecast. The efficacy of the EnKF is analysed via a twin experiment conducted with the 2D barotropic Singapore regional model. The results show that the applied data assimilation can improve the forecasts significantly in this complex flow regime. [ABSTRACT FROM AUTHOR]

An overview of Composite Modelling (CM) is presented, as elaborated in the EU/HYDRALAB joint research project Composite Modelling of the Interactions Between Beaches and Structures. An introduction and a review of the main literature on CM in the hydraulic community are given. In Section 3, the case studies of CM of the seven partners participating in this project are discussed. The focus is on the methodologies used and their impact on the modelling approach, rather than the results of the experiments per se. A further section presents reflections on key elements in CM, as they emerged in the various case studies. The related subject of Good Modelling Practice is summarized in Section 5. Then guidelines are given on how to decide if CM may be beneficial, and how to set up a CM experiment. It is concluded that CM in the hydraulic community is still in its infancy but involves challenging research with significant potential. [ABSTRACT FROM AUTHOR]

Abstract: This paper describes the generic data assimilation software tool DATools. DATools can be used as standalone or within Delft-FEWS. DATools is completely configurable via XML configuration. DATools is built up of three components: a Filter, a Stochastic Modeler, and a Stochastic Observer. Configuration of all these three parts is explained in detail. At the moment two data assimilation filters are available within DATools: (1) ensemble Kalman Filter and (2) the residual resampling filter. Results of a twin experiment with both filters with DATtools show similar results as a previous study performed with custom implementations. It is also shown that DATools can function inside Delft-FEWS software used for operational flood forecasting. Applying EnKF to a 1D hydrodynamic SOBEK-RE model of the river Rhine within the operational system FEWS-NL Rhine and Meuse improves the forecasts at the Lobith gaugin station and downstream of Lobith. DATools has been coupled with the HBV-96, SOBEK, and REW models and will be coupled to MODFLOW, Delft-3D, and the geotechnical model MSetlle in the near future. Uncertainty analysis with this tool is also possible and calibration will be added later this year. [Copyright &y& Elsevier]