Within the hydrodynamic modelling community, it is common practice to apply different modelling systems for coastal waters and river systems. Whereas for coastal waters 3D finite difference or finite element grids are commonly used, river systems are generally modelled using 1D networks. Each of these systems is tailored towards specific applications. Three-dimensional coastal water models are designed to model the horizontal and vertical variability in coastal waters and are less well suited for representing the complex geometry and crosssectional areas of river networks. On the other hand, 1D river network models are designed to accurately represent complex river network geometries and complex structures like weirs, barrages and dams. A disadvantage, however, is that they are unable to resolve complex spatial flow variability. In real life, however, coastal oceans and rivers interact. In deltaic estuaries, both tidal intrusion of seawater into the upstream river network and river discharge into open waters play a role. This is frequently approached by modelling the systems independently, with off-line coupling of the lateral boundary forcing. This implies that the river and the coastal model run sequentially, providing lateral discharge (1D) and water level (3D) forcing to each other without the possibility of direct feedback or interaction between these processes. An additional disadvantage is that due to the time aggregation usually applied to exchanged quantities, mass conservation is difficult to ensure. In this paper, we propose an approach that couples a 3D hydrodynamic modelling system for coastal waters (Delft3D) with a 1D modelling system for river hydraulics (SOBEK) online. This implies that contrary to off-line coupling, the hydrodynamic quantities are exchanged between the 1D and 3D domains during runtime to resolve the real-time exchange and interaction between the coastal waters and river network. This allows for accurate and mass conserving modelling of complex coastal waters and river network systems, whilst the advantages of both systems are maintained and used in an optimal and computationally efficient way. The coupled 1D-3D system is used to model the flows in the Pearl River Delta (Guangdong, China), which are determined by the interaction of the upstream network of the Pearl River and the open waters of the South China Sea. The highly complex upstream river network is modelled in 1D, simulating river discharges for the dry and wet monsoon periods. The 3D coastal model simulates the flow due to the external (ocean) periodic tidal forcing, the salinity distribution for both dry and wet seasons, as well as residual water levels (sea level anomalies) originating from the South China Sea. The model is calibrated and its performance extensively assessed against field measurements, resulting in a mean root mean square (RMS) error of below 6% for water levels over the entire Pearl River Delta. The model also represents both the discharge distribution over the river network and salinity transport p...
The present paper describes the analysis and modeling of the South China Sea (SCS) temperature cycle on a seasonal scale. It investigates the possibility to model this cycle in a consistent way while not taking into account tidal forcing and associated tidal mixing and exchange. This is motivated by the possibility to significantly increase the model's computational efficiency when neglecting tides. The goal is to develop a flexible and efficient tool for seasonal scenario analysis and to generate transport boundary forcing for local models. Given the significant spatial extent of the SCS basin and the focus on seasonal time scales, synoptic remote sensing is an ideal tool in this analysis. Remote sensing is used to assess the seasonal temperature cycle to identify the relevant driving forces and is a valuable source of input data for modeling. Model simulations are performed using a three-dimensional baroclinic-reduced depth model, driven by monthly mean sea surface anomaly boundary forcing, monthly mean lateral temperature, and salinity forcing obtained from the World Ocean Atlas 2001 climatology, six hourly meteorological forcing from the European Center for Medium range Weather Forecasting ERA-40 dataset, and remotely sensed sea surface temperature (SST) data. A sensitivity analysis of model forcing and coefficients is performed. The model results are quantitatively assessed against climatological temperature profiles using a goodness-of-fit norm. In the deep regions, the model results are in good agreement with this validation data. In the shallow regions, discrepancies are found. To improve the agreement there, we apply a SST nudging method at the free water surface. This considerably improves the model's vertical temperature representation in the shallow regions. Based on the model validation against climatological in situ and SST data, we conclude that the seasonal temperature cycle for the deep SCS basin can be represented to a good degree. For shallow regions, the absence of tidal mixing and exchange has a clear impact on the model's temperature representation. This effect on the large-scale temperature cycle can be compensated to a good degree by SST nudging for diagnostic applications.
<p>The impact of extreme weather events on coastal areas around the world is set to increase in the future, both through sea level rise, climate change (increasing storm intensity, rainfall and droughts) and continued development and investment in hazard-prone deltaic and coastal environments. Given the changing natural and socio-economic environment, accurate predictions of current and future risk are becoming increasingly important world-wide to mitigate risks. Recent advances in computational power (e.g., cloud-computing) and data availability (e.g., growth of satellite-derived products) are enabling, for the first time, the development of global scale flood risk models for application in areas where local models are less well developed or prohibitively expensive, or for applications where a synoptic global coverage is important. Despite the increasing granularity of these global models and datasets however, they often still lack the resolution and accuracy to be &#8220;locally relevant&#8221;, especially where inundation and impact assessments are considered. While a solution to this problem is to downscale global models and datasets to the local scale, setting up local models is hampered by inconsistency between underlying datasets, and the required manual effort to generate downscaled integrated risk models inhibits their global application. To address these issues, we are developing a generalized risk assessment framework, called GHIRAF (Globally-applicable High-resolution Integrated Risk Assessment Framework), which couples data and models to quickly provide locally-actionable information on impact of historic, current- and future world-wide extreme weather events (e.g., storms, extreme rainfall, drought). The framework is designed to support world-wide efforts to reduce and mitigate risks associated with extreme weather events by aiding prevention (scenario-testing, design) and preparation (Early Warning) for extreme events, as well as support response (targeted relief efforts) and recovery (build-back-better) efforts. In this work we discuss application of the framework to study hurricane impacts on the eastern coast of the USA, as well as in data-poor, small island state environments.</p>
<p>The European Blue Growth perspective suggests a larger share in global economic production<br>and food security appointed to the marine and coastal zone and an increase of marine and coastal<br>infrastructures &#160; and &#160; operations. &#160; However, &#160; this &#160; growth &#160; must &#160; be &#160; aligned &#160; with &#160; increasing<br>environmental constraints as well as complying and restoring regulations and frameworks. The<br>compliance of growth and sustainability requires the adoption of economically and ecologically<br>efficient behaviours, based on a wider incorporation of available information and knowledge from<br>the industry and citizens alike. Marine and coastal managers must make decisions to maintain<br>the social, economic, and ecological health of marine and coastal areas while operating, planning<br>and managing their activities at sea.<br>The European funded FORCOAST project represents a step forward in this direction by bringing<br>the coastal water quality and met-ocean information closer to the target sectors: wild fisheries,<br>oyster &#160; grounds &#160; restoration, &#160; and &#160; bivalve &#160; mariculture. &#160; FORCOAST &#160; will &#160; develop, &#160; test &#160; and<br>demonstrate, in operational mode, novel Copernicus-based downstream information services that<br>will &#160;incorporate &#160;and &#160;combine &#160;Copernicus &#160;Marine &#160;Environment &#160;Monitoring &#160;Service &#160;(CMEMS),<br>Copernicus Land &#160;Monitoring Service (CLMS) and &#160;Climate Change Monitoring Service &#160;(CMS),<br>local monitoring data and advanced modelling in the service.<br>FORCOAST will provide consistent high-resolution data products for coastal applications, based<br>on a standardized data processing scheme. The services of FORCOAST will provide managerial<br>tools (e.g decision support, user warnings, on-demand case study) built upon those products and<br>implemented through cloud-processing infrastructures.<br>FORCOAST will develop and provide those services in eight pilot service uptake sites covering<br>five &#160;different &#160;regional &#160;waters &#160;(North &#160;Sea, &#160;Baltic &#160;Sea, &#160;Mediterranean &#160;Sea, &#160;Black &#160;Sea and &#160;the<br>coastal Atlantic Ocean). Each of those pilots gathers marine information producers (eg. models),<br>providers (dissemination) and user (operating SMEs), to ensure inter-sectoral consistency.<br>The outcome of FORCOAST is a novel commercial service that will provide Copernicus-based<br>downstream &#160;information &#160;coastal &#160;services &#160;to &#160;a &#160;variety &#160;of &#160;stakeholders, &#160;which &#160;will &#160;result &#160;in &#160;an<br>operation, planning and management improvement of different marine activities in the sectors of<br>wild fisheries and aquaculture, having an economic and societal positive effect on the involved<br>parties.</p><p><br>*This &#160;project &#160;has &#160;received &#160;funding &#160;from &#160;the &#160;European &#160;Union&#8217;s &#160;Horizon &#160;2020 &#160;research &#160;and &#160;innovation<br>programme under grant agreement No 870465</p>
<p>Sea related activities are set to increase and the growth in food production from sea enhancing global food security is already a reality. However, this growth must be aligned with increasing environmental constraints as well as complying and restoring regulations and frameworks. This requires the adoption of improved and efficient behaviors based on wider incorporation of available information and knowledge from the industry and citizens alike. Marine and coastal managers must make decisions to maintain the social, economic, and ecological health of marine and coastal areas in coastal and nearshore areas and to operate, plan and manage their activities at sea. The European funded FORCAST project represents a step forward in this direction by bringing the coastal water quality and met-ocean information closer to the target sectors: wild fisheries, oystergrounds restoration, and bivalve mariculture. FORCOAST will develop, test and demonstrate, in operational mode, novel Copernicus-based downstream information services that will incorporate and combine Copernicus Marine Environment Monitoring Service (CMEMS), Copernicus Land Monitoring Service (CLMS) and Climate Change Monitoring Service (CMS), local monitoring data and advanced modelling in the service. FORCOAST will provide consistent high resolution data products for coastal applications, based on a standardized data processing scheme. Furthermore, FORCOAST will make use DIAS which will help to develop the data access and cloud processing service. FORCOAST will provide those services in eight pilot service uptake sites covering five different regional waters (North Sea, Baltic Sea, Mediterranean Sea, Black Sea and the coastal Atlantic Ocean). The outcome of FORCAST is a novel commercial service that will provide Copernicus-based downstream information coastal services to a variety of stakeholders, which will result in an operation, planning and management improvement of different marine activities in the sectors of wild fisheries and aquaculture, having an economic and societal positive effect on the involved parties.</p><p>*This project has received funding from the European Union&#8217;s Horizon 2020 research and innovation programme under grant agreement No 870465</p>
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