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Abstract: This paper describes sequential assimilation of data into a three-dimensional coastal ocean model using fast and cheap statistical surrogates of the model (emulators). The model simulates resuspension and deposition of fine sediments in a macro-tidal environment of the Fitzroy Estuary and Keppel Bay, North-East Australian coast. The assimilation algorithm was applied first to synthetic observations produced by a twin model run, and then with real data obtained from satellite observation. The latter are derived from remote sensing algorithms customised to the study region. The main objective of simulations was to test the data assimilation scheme using synthetic observations and identify potential issues and challenges when assimilating real data sets. The assimilation algorithm proved capable of substantially reducing a prior uncertainty of the model for both the scenario with the synthetic observations and the scenario with the satellite data. Significant remaining error in western Keppel Bay after assimilating satellite data is diagnostic of an underlying error in the system conceptualisation – in other words, it indicates that the primary source of error is not in the parameter values specified, but in the model structure, in the interpretation of satellite data or in the other input data. The results of our study show the utility of the developed technique for the data assimilation into the three-dimensional sediment transport model of the Fitzroy estuary and Keppel Bay. More research is required to understand the capacity of this technique to generalise to other models and regions. [Copyright &y& Elsevier]

A one-dimensional vertical model of sediment and dissolved material transport in a coupled, vertically resolved benthic-pelagic system has been developed. An apparently unique feature of the model is that the governing equations are first formulated in a time-varying Eulerian frame and then solved numerically, which provides a consistent approach for incorporating resuspension/deposition, swelling/consolidation, and biodiffusion processes within a single modelling framework. Numerical experiments were carried out with varying grids to test diffusive properties of the model. A stretched numerical grid that maintains high vertical resolution of the top sediments and constrains numerical diffusion in deep layers is an integral part of the model. The developed model provides a test bed for testing scientific hypothesis pertaining to coastal sediment transport. The model can also be used to support biogeochemical studies in a coupled benthic-pelagic system. [Copyright &y& Elsevier]

Abstract The dynamics of nutrients, phytoplankton, zooplankton and water clarity of the iconic Great Barrier Reef World Heritage Area (GBRWHA) are influenced by seasonal variation in coastal and oceanic conditions, and anthropogenic inputs. We use the 3-dimensional coupled catchment-hydrodynamic-sediment-wave-optical-biogeochemical eReefs model to hindcast nutrient and planktonic responses to changes in seasonal and annual variability over a six-year period (2011–2016). In this paper we present a comparison of the eReefs model conducted against a range of in situ observations that included 24 water quality moorings, 2 nutrient sampling programs (with a total of 18 stations) and time-series of taxon-specific plankton abundance. At 14 near-coastal stations the simulated chlorophyll a (Chl a), when compared with chlorophyll extractions from water samples, had an average root mean square (RMS) error of 0.30 mg m−3 and a Willmott index of 0.59. For the same sites, simulated turbidity, when compared with turbidity sensors, had a Willmott index of 0.58 and simulated nitrate + nitrite had a Willmott index of 0.41 when compared with tri-annual water samples. Comparison with a spatially-resolved statistical model of zooplankton based on >900 observations in the region showed similarities in the relationship and spatial distribution of simulated and observed biomass, where both show zooplankton biomass is greatest inshore, biomass is highest around shallow reef areas and in the southern and central GBRWHA, and greater in summer than winter. Additionally, we investigate planktonic and nutrient responses to climatic variation. The first two years of the simulation coincided with La Niña events that drive greater than average winds, rainfall and river discharge. Throughout all years, simulated Chl a increases from north to south and from outer to inner coastal regions. Dissolved inorganic nitrogen, primary production and phytoplankton biomass were higher during La Niña in inshore and mid-shelf waters, while offshore regions were similar in all years from 2011 to 2016. Simulated Secchi depth was deeper offshore and decreased from offshore to inner coastal regions and from north to south. The eReefs simulation contributes to the understanding at a high spatial and temporal resolution of where and how nutrients and plankton originate and interact within the Great Barrier Reef. Highlights • Use of a 3D-catchment-hydrodynamic-sediment-wave-optical-biogeochemical model • Model encompasses the 2300 km long Great Barrier Reef from coast to Coral Sea. • Comparison of observations with simulated plankton & nutrients • Observations include remote sensing, moorings and water samples. • Simulated nutrients and plankton show realistic seasonal and interannual variation. [ABSTRACT FROM AUTHOR]