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The book presents recent studies covering the aspects of challenges in predictive modelling and applications. Advanced numerical techniques for accurate and efficient real-time prediction and optimal management in coastal and hydraulic engineering are explored. For example, adaptive unstructured meshes are introduced to capture the important dynamics that operate over a range of length scales. Deep learning techniques enable rapid and accurate modelling simulations and pave the way towards both real-time forecasting and overall optimisation control over time, thus improving profitability and managing risk. The use of data assimilation techniques incorporates information from experiments and observations to reduce uncertainties in predictions and improve predictive accuracy. Targeted observation approaches can be used for identifying when, where, and what types of observations would provide the greatest improvement to specific model forecasts at a future time. Such targeted observations are important as they will allow the most effective use of available monitoring resources. The combination of deep learning and data assimilation enables a rapid and accurate response in emergencies. The technologies discussed here can be also used to determine the sensitivity of outputs to various operational conditions in engineering and management, thus providing reliable information to both the public and policy-makers
Research & information: general --- numerical modelling --- unstructured meshes --- finite volume --- North Sea --- salinity --- deep learning --- martinez boundary salinity generator --- Sacramento–San Joaquin Delta --- residence time --- exposure time --- transport time scale --- hyper-tidal estuary --- singular value decomposition --- data assimilation --- ocean models --- observation strategies --- ocean forecasting systems --- ocean Double Gyre --- 4D-Var --- ROMS --- MEOF --- initial ensemble --- ensemble spread --- LETKF --- n/a --- Sacramento-San Joaquin Delta
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The book presents recent studies covering the aspects of challenges in predictive modelling and applications. Advanced numerical techniques for accurate and efficient real-time prediction and optimal management in coastal and hydraulic engineering are explored. For example, adaptive unstructured meshes are introduced to capture the important dynamics that operate over a range of length scales. Deep learning techniques enable rapid and accurate modelling simulations and pave the way towards both real-time forecasting and overall optimisation control over time, thus improving profitability and managing risk. The use of data assimilation techniques incorporates information from experiments and observations to reduce uncertainties in predictions and improve predictive accuracy. Targeted observation approaches can be used for identifying when, where, and what types of observations would provide the greatest improvement to specific model forecasts at a future time. Such targeted observations are important as they will allow the most effective use of available monitoring resources. The combination of deep learning and data assimilation enables a rapid and accurate response in emergencies. The technologies discussed here can be also used to determine the sensitivity of outputs to various operational conditions in engineering and management, thus providing reliable information to both the public and policy-makers
numerical modelling --- unstructured meshes --- finite volume --- North Sea --- salinity --- deep learning --- martinez boundary salinity generator --- Sacramento–San Joaquin Delta --- residence time --- exposure time --- transport time scale --- hyper-tidal estuary --- singular value decomposition --- data assimilation --- ocean models --- observation strategies --- ocean forecasting systems --- ocean Double Gyre --- 4D-Var --- ROMS --- MEOF --- initial ensemble --- ensemble spread --- LETKF --- n/a --- Sacramento-San Joaquin Delta
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The book presents recent studies covering the aspects of challenges in predictive modelling and applications. Advanced numerical techniques for accurate and efficient real-time prediction and optimal management in coastal and hydraulic engineering are explored. For example, adaptive unstructured meshes are introduced to capture the important dynamics that operate over a range of length scales. Deep learning techniques enable rapid and accurate modelling simulations and pave the way towards both real-time forecasting and overall optimisation control over time, thus improving profitability and managing risk. The use of data assimilation techniques incorporates information from experiments and observations to reduce uncertainties in predictions and improve predictive accuracy. Targeted observation approaches can be used for identifying when, where, and what types of observations would provide the greatest improvement to specific model forecasts at a future time. Such targeted observations are important as they will allow the most effective use of available monitoring resources. The combination of deep learning and data assimilation enables a rapid and accurate response in emergencies. The technologies discussed here can be also used to determine the sensitivity of outputs to various operational conditions in engineering and management, thus providing reliable information to both the public and policy-makers
Research & information: general --- numerical modelling --- unstructured meshes --- finite volume --- North Sea --- salinity --- deep learning --- martinez boundary salinity generator --- Sacramento-San Joaquin Delta --- residence time --- exposure time --- transport time scale --- hyper-tidal estuary --- singular value decomposition --- data assimilation --- ocean models --- observation strategies --- ocean forecasting systems --- ocean Double Gyre --- 4D-Var --- ROMS --- MEOF --- initial ensemble --- ensemble spread --- LETKF
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Geophysical, environmental, and urban fluid flows (i.e., flows developing in oceans, seas, estuaries, rivers, aquifers, reservoirs, etc.) exhibit a wide range of reactive and transport processes. Therefore, identifying key phenomena, understanding their relative importance, and establishing causal relationships between them is no trivial task. Analysis of primitive variables (e.g., velocity components, pressure, temperature, concentration) is not always conducive to the most fruitful interpretations. Examining auxiliary variables introduced for diagnostic purposes is an option worth considering. In this respect, tracer and timescale methods are proving to be very effective. Such methods can help address questions such as, "where does a fluid-born dissolved or particulate substance come from and where will it go?" or, "how fast are the transport and reaction phenomena controlling the appearance and disappearance such substances?" These issues have been dealt with since the 19th century, essentially by means of ad hoc approaches. However, over the past three decades, methods resting on solid theoretical foundations have been developed, which permit the evaluation of tracer concentrations and diagnostic timescales (age, residence/exposure time, etc.) across space and time and using numerical models and field data. This book comprises research and review articles, introducing state-of-the-art diagnostic theories and their applications to domains ranging from shallow human-made reservoirs to lakes, river networks, marine domains, and subsurface flows
residence time --- Three Gorges Reservoir --- tributary bay --- density current --- water level regulation --- marina --- water renewal --- transport timescales --- return-flow --- macro-tidal --- wind influence --- floating structures --- San Francisco Estuary --- Sacramento–San Joaquin Delta --- water age --- transport time scales --- hydrodynamic model --- tidal hydrodynamics --- stable isotopes --- reactive tracers --- tailor-made tracer design --- hydrogeological tracer test --- kinetics --- partitioning --- Mahakam Delta --- age --- exposure time --- return coefficient --- CART --- source water fingerprinting --- floodplain --- turbulence --- ADCP measurement --- wave bias --- Reynolds stress --- transport process --- passive tracers --- terrestrial dissolved substances --- Pearl River Estuary --- shallow lake --- meteorological influence --- sub-basins --- Delft3D --- partial differential equations --- boundary conditions --- geophysical and environmental fluid flows --- reactive transport --- interpretation methods --- diagnostic timescales --- age distribution function --- radionuclide --- tracer --- data collection --- antimony 125 (125Sb) --- tritium (3H) --- dispersion --- modeling --- English Channel --- North Sea --- Biscay Bay --- timescale --- transport --- hydrodynamic --- ecological --- biogeochemical --- coastal --- estuary --- flushing time --- shallow reservoir --- numerical modeling --- Lagrangian transport modelling --- coupled wave–ocean models --- ocean drifters --- wave-induced processes --- model skills --- n/a --- Sacramento-San Joaquin Delta --- coupled wave-ocean models
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In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean–atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean–atmosphere, land–atmosphere, and soil–vegetation data assimilation.
land data assimilation system --- land data assimilation --- rainfall-runoff simulation --- 4D-Var data assimilation --- total water storage --- accuracy --- ocean–atmosphere assimilation --- precipitation --- Earth system models --- numerical weather prediction --- fluorescence --- GRACE --- MCA analysis --- weakly coupled data assimilation --- GPM IMERG --- atmospheric models --- rainfall correction --- remote sensing --- microwave remote sensing --- SMAP --- land surface modeling --- bending angle --- floods soil moisture --- vegetation --- GPSRO --- WRF --- merged CMORPH --- land surface model --- temperature --- 4D-Var --- data assimilation --- data-driven methods --- GSI --- radio occultation data --- rainfall --- soil moisture --- sea level anomaly --- total cloud cover --- land surface models --- Mediterranean basin --- interpolation --- sea surface height --- drought --- TRMM 3B42 --- analog data assimilation --- ocean models
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Geophysical, environmental, and urban fluid flows (i.e., flows developing in oceans, seas, estuaries, rivers, aquifers, reservoirs, etc.) exhibit a wide range of reactive and transport processes. Therefore, identifying key phenomena, understanding their relative importance, and establishing causal relationships between them is no trivial task. Analysis of primitive variables (e.g., velocity components, pressure, temperature, concentration) is not always conducive to the most fruitful interpretations. Examining auxiliary variables introduced for diagnostic purposes is an option worth considering. In this respect, tracer and timescale methods are proving to be very effective. Such methods can help address questions such as, "where does a fluid-born dissolved or particulate substance come from and where will it go?" or, "how fast are the transport and reaction phenomena controlling the appearance and disappearance such substances?" These issues have been dealt with since the 19th century, essentially by means of ad hoc approaches. However, over the past three decades, methods resting on solid theoretical foundations have been developed, which permit the evaluation of tracer concentrations and diagnostic timescales (age, residence/exposure time, etc.) across space and time and using numerical models and field data. This book comprises research and review articles, introducing state-of-the-art diagnostic theories and their applications to domains ranging from shallow human-made reservoirs to lakes, river networks, marine domains, and subsurface flows
Research & information: general --- Biology, life sciences --- residence time --- Three Gorges Reservoir --- tributary bay --- density current --- water level regulation --- marina --- water renewal --- transport timescales --- return-flow --- macro-tidal --- wind influence --- floating structures --- San Francisco Estuary --- Sacramento-San Joaquin Delta --- water age --- transport time scales --- hydrodynamic model --- tidal hydrodynamics --- stable isotopes --- reactive tracers --- tailor-made tracer design --- hydrogeological tracer test --- kinetics --- partitioning --- Mahakam Delta --- age --- exposure time --- return coefficient --- CART --- source water fingerprinting --- floodplain --- turbulence --- ADCP measurement --- wave bias --- Reynolds stress --- transport process --- passive tracers --- terrestrial dissolved substances --- Pearl River Estuary --- shallow lake --- meteorological influence --- sub-basins --- Delft3D --- partial differential equations --- boundary conditions --- geophysical and environmental fluid flows --- reactive transport --- interpretation methods --- diagnostic timescales --- age distribution function --- radionuclide --- tracer --- data collection --- antimony 125 (125Sb) --- tritium (3H) --- dispersion --- modeling --- English Channel --- North Sea --- Biscay Bay --- timescale --- transport --- hydrodynamic --- ecological --- biogeochemical --- coastal --- estuary --- flushing time --- shallow reservoir --- numerical modeling --- Lagrangian transport modelling --- coupled wave-ocean models --- ocean drifters --- wave-induced processes --- model skills
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