Biogeochemical simulation naming protocol

All simulations from 2017 onwards have the following naming structure:



GBRg     – Model grid with g = approximate grid resolution in kilometres.

Hhhh     – Hydrodynamic model, hhh = model version.

Bbbb     – Biogeochemical model, bbb = model version.

Cccc       – Catchment model, ccc = load specification.

  • fur – Furnas relationships for wet and dry tropics rivers;
  • pre – SOURCE Catchments – Pre-Industrial catchment cover;
  • bas – SOURCE Catchments – Baseline (2012/13) catchment;
  • hyd – best available forcing (2011 – Jun 30, 2014 P2R SOURCE Catchments; Jul 1, 2014 – Oct 30, 2016 – Empirical SOURCE Catchments; Oct 30, 2016 onwards Furnas relationship].
  • q2b – SOURCE catchments (Dec 1, 2010 – Oct 30, 2018 – Empirical SOURCE Catchments; Oct 31, 2018 onwards Furnas relationship].
  • q2p –SOURCE Catchments – Pre-Industrial catchment cover –  Dec 1, 2010 – Oct 31, 2018.

Scenarios undertaken using SOURCE Catchments 2019

  • q3b – P2R SOURCE Catchments with 2019 catchment condition from Dec 1, 2010 – 30/6/2018 (used for GBR Report Card 8 published in 2019), Empirical SOURCE  with 2019 catchment condition, Jul 1, 2018 – April 30, 2019
  • q3p – P2R SOURCE Catchments with Pre-Industrial catchment condition from Dec 1, 2010 – 30/6/2018 (used for GBR Report Card 8 published in 2019), Empirical SOURCE  with Pre-Industrial catchment , Jul 1, 2018 – April 30, 2019
  • q3R – SOURCE Catchments 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.
  • q3A – SOURCE Catchments with 2019 catchment condition (q3b), with all D, C and B managed land improved to A management
  • q3B – SOURCE Catchments with 2019 catchment condition (q3b), with all D and C managed land improved to B management
  • q3C – SOURCE Catchments with 2019 catchment condition (q3b), with all D managed land improved to C management
  • q3T  – SOURCE Catchments with 2019 catchment condition (q3b), with Reef Trust Partnership load reductions

Notes: (1) P2R SOURCE Catchments involves forcing SOURCE Catchments with outputs from paddock scale modelling. The paddock scale modelling provides estimates of the hydrologic balance, including run-off and deep drainage, and the loads and concentrations of particulate and dissolved nitrogen, phosphorus, and pesticides in run-off, across a range of management practice systems or components of systems. Paddock scale model outputs also need to represent the diversity of soils and climates across the Great Barrier Reef catchments. Three paddock models, Agricultural Production Systems sIMulator (APSIM), GRASP and HowLeaky are used to generate constituent loads in sugarcane, grains, bananas and grazing. The models are based on similar soil water balance, ground cover and run-off sub-models. They are all driven by daily soil water balance sub-models, however, they vary in the level of detail, particularly in terms of representing crops and any extra processes considered (such as pesticide degradation and export); (2) The paddock scale models were improved in 2018 to better represent the suite of management actions deemed to be occurring in the reef catchments, resulting in differences between q2b and q3b beyond just the catchment cover change; (3) Empirical SOURCE  is used when the full P2R SOURCE Catchments is unavailable, and uses monthly-varying concentration generation (instead of the above paddock modelling) for each paddock with daily-calculated flows to generate daily-varying loads, and is used after June 30, 2018; (4) The SOURCE Catchments modelling framework (eWater, 2010; 2017) is used to model pollutant loads for the 35 catchments affected by land management practices in the Great Barrier Reef region. This catchment-scale water quantity and quality model uses a node link network to represent the stream. The model generates run-off and pollutant loads for each functional unit (land use, derived from the paddock scale modelling) within a subcatchment, and runoff and pollutants are transported from a sub-catchment through the stream network via nodes and links to the end of the catchment; (5) for more information see Paddock to Reef Integrated Monitoring, Modelling and Reporting.

Scenarios undertaken using SOURCE Catchments 2020

  • q4b – Baseline run with SOURCE Catchments 2020.

Dddd     – Model deployment.

  • nrt – Near Real Time (-2 days, waiting for hydrodynamic forcing);
  • fct – Forecast (+2 days);
  • hnd – Hindcast (set dates);
  • crt – catchment real time (-6 months, waiting for SOURCE Catchments);
  • ran – Reanalysis (hindcast assimilating MODIS ocean colour, implemented 2017)
  • ra2 – Reanalysis (hindcast assimilating MODIS, VIIRS ocean colour, implemented 2019).
  • ra3 – Reanalysis (hindcast assimilating OCLI onboard Sentinel-3A, implemented 2020).
  • ra4 – Reanalysis (hindcast assimilating OCLI onboard Sentinel-3A and Sentinel-3B, implemented 2021) in which a weighting was placed on individual members.

Existing configurations:

H1p85 – Hydrodynamic run for SIEF report: contained salinity errors in 2015 – grid contains only 22 rivers.

H2p0 – No known forcing problems. 70 rivers included as boundaries, but only 22 have flows and loads. Fixed a rainfall forcing issue.

B1p0 – This is the original biogeochemical model. The simulations for the SIEF report in Jan 2016, and which have been referred to previously as v926, used this version.

B1p9 – More accurate optical calculations; Normanby – particulate and dissolved loads corrected; Sediment tracer “Dust” added; Oxygen mass conservation part of diagnostics.

B2p0 – Added deep seagrass species, seagrass mortality enhanced by bottom shear stress and nutrient uptake by seagrass leaves; spectral light forcing benthic microalgae; carbon chemistry calculations in sediment and using time-varying atmospheric pCO2; distinguish carbonate and non-carbonate fine sediments; in-line calculation of simulated satellite products; VIIRS satellite comparison; implement ecological processes on boundary cells; dynamic porosity in ecological process calculations; calculation of turbidity using optical model.

B2p1 – Added new coral bleaching processes.

B3p0 – Changes from B2p0:

  • Optical properties of carbonate minerals (absoprtion, scattering and backscattering coefficients) introduced from Lucinda Jetty data set.
  • Spectrally-resolved phytoplankton backscattering.
  • Coral bleaching added using new process (coral_spectral_grow_bleach_epi.c) and new variables (Coral N, P, I reserves, xanthophyll photosynthetic and heat dissipating pigments, oxidised, reduced and inhibited reaction centres, reactive oxygen species), parameter values (ROS_threshold, ) and diagnostics (Rubisco activity, bleaching rate).
  • Coral heterotrophic feeding fixed: reserves from grazed phytoplankton now returned to water column.
  • New diagnostic variables included in optical model: simulated fluorescence, simulated turbidity, simulated normalised fluorescence line height, simulated Secchi depth, downwelling light on z-interfaces, SWR_bot_abs (the PAR weighted bottom absorption calculated by the model), OC4Me – chlorophyll algorithm for MERIS and Sentinel.
  • Optical code now has options of spectral absorption coefficients calculated through HPLC analysis, or via Gaussian approximations (previous version).
  • Separated coral growth and mortality (in coral_spectral_grow_*_epi.c) from dissolution / calcification processes (coral_spectral_carb_epi.c). Added argument to coral_spectral_carb_epi.c to apply Eyre relationship.
  • New process light_spectral_sed.c considers spectrally-resolved microphytobenthos light absorption.
  • Mass balance for oxygen includes nitrate, with stoichiometry changed for photosynthesis / respiration.
  • Seagrass growth: Small fix in partitioning of nitrate / ammonium uptake in seagrass from roots – > put new version in seagrass_spectral_grow_epi.c
  • Quadratic term for seagrass mortality added to seagrass_spectral_mortality_proto_epi.c, but zero value for all but deep seagrass.
  • Remineralisation rate of phosphorus has a separate parameter to that of C and N, requiring 2 new parameters  (r_RD_NtoP, r_DOM_NtoP)
  • New output file (ecology_setup.txt) generated (containing process list implement including options, parameter values and what was previously in spectral.txt) for improved simulation quality assurance.
  • Re-calculation of diagnostic optical properties in postcalc so they are calculated at the output time.
  • Code now Open Source, available at:, with headers improved for readability.
  • EFI now defined based on minerals present – resulting definition output into eco_setup.txt.
  • Code supports outputting solar zenith angle as either a 3D tracer (“Zenith”) or 2D epibenthic variable (“Zenith2D”).
  • New Trichodesmium processes with code updated and bug in density call fix. New process called trichodesmium_spectral_grow_wc.c
  • Introduced new sediment-water diagnostic variable.
  • Rationalisation of grid description for 2D tracers in netcdf output files.

Significant simulations:

GBR4_H1p85_B1p0_Cbas_Dhnd – The simulation run for the 2016 SIEF report that was the first publicly-available long run of the full coupled hydrodynamic – biogeochemical model (formally known as gbr926).

GBR4_H2p0_B2p0_Chyd_Dhnd – Second publicly release simulation (released mid 2017) being used for GBRF resilience and NESP TWQ Hub projects.

GBR4_H2p0_B2p0_Cpre_Dhnd – Identical to GBR4_H2p0_B2p0_Chyd_Dhnd except with Pre-Industrial loads.

GBR4_H2p0_B1p9_Chyd_Dran – First application of BGC data assimilation that is being used for GBR Report Card 7.

GBR4_H2p0_B3p0_Cq2b_Dhnd – Third publicly released simulation  (released Feb 7, 2019) available on NCI and RECOM.

GBR4_H2p0_B3p0_Cq2p_Dhnd – Identical to  GBR4_H2p0_B3p0_Cq2b_Dhnd except with Pre-Industrial loads.

GBR4_H2p0_B3p0_Cq2b_Dra2 – 2nd application of BGC data assimilation that was used for GBR Report Card 8.

GBR4_H2p0_B3p2_Cq3b_Dra3 – 3rd application of BGC data assimilation that was used for GBR Report Card 9.

GBR4_H2p0_B3p3_Cq4b_Dra4 – 4th application of BGC data assimilation that was  used for GBR Report Card 10.