Prediction of sediment, particulate nutrient and dissolved nutrient concentrations in a dry tropical river to provide input to a mechanistic coastal water quality model. (January 2015)

• Record Type: Journal Article
• Authors: Robson, Barbara J.; Dourdet, Vincent
• Is Part Of: Environmental modelling & software. Volume 63(2015:Jan.)
• Page Start: 97
• Page End: 108
• Publication Date: 2015-01
• Subjects: Catchment model -- Regression -- Watershed -- Phosphate -- Empirical vs. deterministic modelling; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2014.08.009
• Languages: English
• ISSNs: 1364-8152

Abstract

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. Graphical abstract: Despite the absence of any obvious direct relationship between flow and dissolved nutrient concentrations (in this case dissolved organic nitrogen, DON) concentrations in the Fitzroy River (left), a Generalised Additive Model is able to predict dissolved nutrient concentrations as a function of flow in the Fitzroy River and one of its tributaries (right). Highlights: A GAM is applied to predict dissolved and particulate nutrient concentrations. A thorough performance evaluation was conducted. Tributary flows were required to successfully predict dissolved nutrients. The Nogoa catchment is an important source of dissolved phosphorus in the Fitzroy. The models will provide input to a mechanistic receiving waters model.