GBR4 BGC Scenario Comparison - Light intensity above seagrass

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    What do these visualisations show?

    These maps compare the estimated current state of the GBR (baseline) with pre-industrial and water quality target conditions (see eReefs BGC Scenarios for more information). The “Baseline scenario” panel shows the best estimate for light intensity above seagrass at noon for the time period from December 2010 to April 2019.

    The “Pre-industrial” panel shows the difference between the baseline scenario and pre-industrial conditions. Areas in blue correspond to locations where the pre-industrial values are estimated to be better than the current baseline (more light intensity above seagrass in the pre-industrial past). Red areas correspond to areas where the pre-industrial conditions would have been worse (lower light intensity above seagrass) than the current baseline. As this plot compares the current conditions with estimated pre-industrial conditions the difference represents the anthropogenic influence on the light intensity above seagrass on the GBR. It shows that current levels in the marine environment are lower than pre-industrial conditions along most of the coastline but specifically in the central and southern sections of the GBR.

    The “WQIP-Targets” panel shows the effects of the planned targets if they were achieved. The blue area indicates the possible increase of light intensity relative to the current baseline. Red areas correspond to a possible decrease of light intensity relative to the current baseline. The comparison between the baseline and reduced loads (WQIP-Targets) scenario shows that for most places along the coast implementing the WQIP-Target measures would be beneficial as it would increase the light intensity above seagrass, especially in the central and southern sections.

    The “% River water in sea water” panel shows the total percentage of river water in sea water. It can be used to identify significant river discharges and flood plumes which can have a big impact on the light intensity above seagrass.

    eReefs BGC Scenarios

    In 2016, Brodie et al. conducted a study utilising the eReefs 4 km coupled hydrodynamic - biogeochemical model and two GBR Dynamic SedNet catchment model scenarios to analyse the water quality in the Great Barrier Reef (GBR) (Brodie et al., 2017). The complex eReefs biogeochemical model allowed for the resolution of biogeochemical processes affecting water quality changes. The main objective was to identify specific load reduction targets for different basins within the GBR, aiming to minimize ecological impacts related to chlorophyll and suspended sediment concentrations, as well as bottom light thresholds.

    In 2020 Baird et al. built upon the previous study and expanded it by extending the time period from 2011–2014 to 2011–2018 and analysing the water quality response of a new set of catchment loads scenarios (Baird et al., 2021). These new scenario runs used the updated eReefs coupled hydrodynamic-biogeochemical model with the model configuration GBR4_H2p0_B3p1_Cq3x_Dhnd. H2p0 is the configuration of the hydrodynamic model and has been operational since 2016. B3p1 is the configuration of the biogeochemical model, described in Baird et al. (2020). Cq3x refers to one of the catchment model configurations (q3x = q3b, q3p, q3O, q3R, q3A, q3B, q3C; see Baird et al., 2021, for more information) of the 2019 report card version of the GBR Dynamic SedNet used to deliver nutrient and sediment river loads. Dhnd describes the deployment of the model, in this case being a non-assimilating hindcast (Baird et al., 2021).

    For this scenario comparison we focused on the model configurations q3b baseline, q3p pre-industrial, and q3R reduced loads (WQIP-Targets):

    q3b Baseline

    This scenario is used as the baseline representing the best estimate of the current state. It uses the Paddock to Reef Integrated Monitoring, Modelling and Reporting Program (P2R) GBR Dynamic SedNet with 2019 catchment condition from 1st of December 2010 to 30th of June 2018 (used for GBR Report Card published in 2019) and Empirical SedNet with 2019 catchment condition from 1st of July 2018 to 30th of April 2019.

    q3p Pre-Industrial

    This scenario uses a configuration to simulate pre-industrial conditions and shows the change in water quality measures from the removal of all anthropogenic loads. P2R GBR Dynamic SedNet with Pre-Industrial catchment condition from 1st of December 2010 to 30th of June 2018 (used for GBR Report Card published in 2019), Empirical SedNet with Pre-Industrial catchment from 1st of July 2018 to 30th of April 2019.

    q3R Reduced loads (WQIP-Targets)

    This scenario uses GBR Dynamic SedNet with 2019 catchment condition (q3b) with anthropogenic loads (q3b - q3p) reduced according to the percentage reductions of DIN, PN, PP and TSS specified in the Reef 2050 Water Quality Improvement Plan (WQIP) 2017–2022 as calculated in Brodie et al. (2017). Further, the reductions are adjusted to account for the cumulative reductions already achieved between 2014 and 2019 that will be reflected in the 2019 catchment condition used in q3b.

    Model variables

    Light intensity above seagrass (EpiPAR_sg)

    The variable EpiPAR_sg represents the light intensity above seagrass measured in daily light integral (mol photons per square meter per day). Please note that the eReefs BGC model is using a 4km resolution and is developed for large-scale predictions.

    Light intensity above seagrass pre-industrial minus baseline (EpiPAR_sg_pre-base)

    This variable represents the difference of daily light intensity above seagrass in mol photons per square meter between the pre-industrial scenario and the baseline scenario. This highlights the anthropogenic impact.

    EpiPAR_sg_pre-base = pre-industrial (q3p) EpiPAR_sg - baseline (q3b) EpiPAR_sg

    Light intensity above seagrass reduced loads (WQIP-Targets) minus baseline (EpiPAR_sg_reduced-base)

    This variable represents the difference of daily light intensity above seagrass in mol photons per square meter between the reduced loads (WQIP-Targets) scenario and the baseline scenario. This highlights the alignment of the current state with the targets.

    EpiPAR_sg_reduced-base = reduced loads (q3R) EpiPAR_sg - baseline (q3b) EpiPAR_sg

    Aggregation of all rivers (all_rivers)

    The GBR4 river tracer model output represents the river water concentration in sea water for the major rivers along the Queensland coastline flowing into the Great Barrier Reef Marine Park. The “all_rivers” product aggregates the output for each river into one variable to represent the total concentration of river water in the sea water.

    In the model, tracers are released at the mouth into the surface flow of each river. These tracers move with the ocean currents, becoming more dilute as they spread out and mix with the ocean water, allowing the concentration of river water to be tracked over time. These tracers show the fraction of the water, at any given location, associated with each river.

    The lowest threshold of river water concentration (1%) shown in the visualisation was chosen to align with the visible extent of flood plumes as seen in satellite imagery. At this concentration we can expect organisms on the sea floor to see raised nutrient levels, some fine sediment and a significant reduction in light.

    See Flood plume extents for major rivers on GBR based on modelled river tracers for more information.

    References

    Brodie, J., Baird, M., Mongin, M., Skerratt, J., Robillot, C., Waterhouse, J., 2017. Pollutant target setting for the Great Barrier Reef: using the eReefs framework. In: Syme, G., Hatton MacDonald, D., Fulton, B., Piantadosi, J. (Eds.), MODSIM2017, 22nd International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2017, pp. 1913–1919.

    Mark E. Baird, Mathieu Mongin, Jennifer Skerratt, Nugzar Margvelashvili, Sharon Tickell, Andrew D.L. Steven, Cedric Robillot, Robin Ellis, David Waters, Paulina Kaniewska, Jon Brodie, 2021. Impact of catchment-derived nutrients and sediments on marine water quality on the Great Barrier Reef: An application of the eReefs marine modelling system. https://doi.org/10.1016/j.marpolbul.2021.112297

    M.E. Baird, K.A. Wild-Allen, J. Parslow, M. Mongin, B. Robson, J. Skerratt, F. Rizwi, M. Soja-Woźnaik, E. Jones, M. Herzfeld, N. Margvelashvili, J. Andrewartha, C. Langlais, M.P. Adams, N. Cherukuru, M. Gustafsson, S. Hadley, P.J. Ralph, U. Rosebrock, T. Schroeder, L. Laiolo, D. Harrison, A.D.L. Steven CSIRO Environmental Modelling Suite (EMS): scientific description of the optical and biogeochemical models (vB3p0) Geosci. Model Dev., 13 (2020), pp. 4503-4553

    Source data

    The videos/images on this page are based on the 4km eReefs BioGeoChemical model (v3.1) (GBR4_H2p0_B3p1_Cq3b_Dhnd, GBR4_H2p0_B3p1_Cq3p_Dhnd, GBR4_H2p0_B3p1_Cq3R_Dhnd) run with SOURCE Catchments using Baseline, Pre-Industrial, and reduced loads (WQIP-Targets) catchment conditions. Detailed information about the model can be found in the paper: CSIRO Environmental Modelling Suite (EMS): Scientific description of the optical and biogeochemical models (vB3p0).

    The raw model data is available from the NCI THREDDS server (daily, in curvilinear NetCDF format):

    Aggregate data is available from the AIMS eAtlas THREDDS server (daily, monthly, yearly, in regular rectangular grid NetCDF format):

    Data span

    These results are based on a fixed time period (Dec 2010 - Apr 2019) hind-cast analysis developed for comparing changes in land practices. The river run off used to drive the BGC model were provided by the SOURCE Catchments modelling.