Prediction of sediment, particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model

Robson, Barbara J., and Dourdet, Vincent (2015) Prediction of sediment, particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model. Environmental Modelling & Software, 63. pp. 97-108.

[img] PDF (Published Version) - Published Version
Restricted to Repository staff only

View at Publisher Website: https://doi.org/10.1016/j.envsoft.2014.0...
 
7
1


Abstract

A Generalised Additive Modelling (GAM) approach is applied to prediction of both particulate and dissolved nutrient concentrations in a wet-tropical river (the Fitzroy River, Queensland, Australia). In addition to covariant terms considered in previous work (i.e. flow, discounted flow and a rising-falling limb term), we considered several new potential covariates: meteorological and hydrological variables that are routinely monitored, available in near-real time, and were considered to have potential predictive power. Of the additional terms considered, only flows from three tributaries of the Fitzroy River (namely, the Nogoa, Comet and Isaac Rivers) were found to significantly improve the model. Inclusion of one or more of these additional flow terms greatly improved results for dissolved nitrogen and dissolved phosphorus concentrations, which were not otherwise amenable to prediction. In particular, the Nogoa sub-catchment, dominated by pasture for cattle, was found to be important in determining dissolved inorganic nitrogen and phosphorus concentrations reaching the river mouth. This insight may direct further research, including future refinement of processed-based catchment models. The GAMs described here are used to provide near real-time river boundary conditions for a complex coupled hydrodynamic and biogeochemical model of the Great Barrier Reef Lagoon, and can be coupled with a forecasting hydrological model to allow integrated forecasting simulations of the catchment to coast system.

Item ID: 58044
Item Type: Article (Research - C1)
ISSN: 1873-6726
Keywords: Catchment model, Regression, Watershed, Phosphate, Empirical vs. deterministic modelling
Copyright Information: © 2014 Elsevier Ltd. All rights reserved.
Funders: eReefs, CSIRO Oceans and Atmosphere Flagship, Australian Bureau of Meteorology, Great Barrier Reef Foundation, Science Industry Endowment Fund (SIEF), BHP Billiton Mitsubishi Alliance (BMA)
Date Deposited: 17 Apr 2019 09:22
FoR Codes: 09 ENGINEERING > 0907 Environmental Engineering > 090702 Environmental Engineering Modelling @ 100%
SEO Codes: 96 ENVIRONMENT > 9605 Ecosystem Assessment and Management > 960503 Ecosystem Assessment and Management of Coastal and Estuarine Environments @ 100%
Downloads: Total: 1
More Statistics

Actions (Repository Staff Only)

Item Control Page Item Control Page