Development of catchment water quality models within a realtime status and forecast system for the Great Barrier Reef

Abstract

Realtime information on sediment and nutrients generated and transported from catchments is essential to inform management decisions aimed to improve the ecosystem health of the Great Barrier Reef (GBR). A water quality modelling methodology is developed to provide accurate and reliable estimates of sediments, dissolved and particulate nutrients, i.e., Nitrogen and Phosphorus for historical simulations, realtime status and forecasts. A water quality model is built for seven key water quality constituents at ten locations in eight GBR catchments using a non-linear multivariate regression technique. Covariates used in the multivariate regression models were derived from either streamflow, baseflow, or time-based cyclical processes. The performance of models varied by site location and constituent and out of 67 models developed here, 27 models have NSE values > 0.5 and 57 models have NSE values > 0.3. These 67 hourly models have been used to generate historical simulations and forecasts of concentration and load.