Search

Australian and Queensland Government's Reef 2050 Water Quality Improvement Plan has set targets for improving the water quality entering the Great Barrier Reef lagoon. Given the large public investment and the deficit of data linking on-farm land management to changes in environmental outcomes, there is a need for a robust and efficient methods of quantifying links between land management and water quality. This paper explores a pragmatic approach to making this link using available data. We demonstrate that a simple parameterisation process is suitable for estimating hydrology and water quality across a wide range of land uses and management practices in agricultural landscapes. However, a manually calibrated model may still require the analysis of parameters to reduce error variances and evaluate uncertainties. Confidence in estimating hydrology and water quality in descending order is: runoff, sediment, nitrogen, phosphorous, and pesticide losses, reflecting the availability of data and inherent error propagation. • A pragmatic modelling by Howleaky is suitable to link management to water quality. • A manually calibrated model may still require a reduction in error variances. • Data availability and inherent error propagation determined confidence in modelling. [ABSTRACT FROM AUTHOR]

The Great Barrier Reef is a UNESCO World Heritage Area that has been assessed as having a very poor outlook and needing urgent intervention. The eReefs hydrodynamic-biogeochemical models are used to complement monitoring, facilitate data interpretation and support policy decisions. Management and policy for the Great Barrier Reef are politically contentious, so a high standard of model evaluation is required. We report the application of a recently-developed four-level "CSPS" (Concept/State/Process/System) model evaluation framework to the eReefs biogeochemical model. The framework considers: Level 0, conceptual evaluation; Level 1, simulated state variables; Level 2, process rates; and Level 3, system-level patterns and emergent properties. This paper is the first complete application of this model assessment framework. It highlights both strengths and weaknesses of the eReefs biogeochemical model that might not have been apparent from a traditional model evaluation. The framework can be applied to evaluation of any complex, process-based numerical model. • In politically-contentious contexts, models require a high standard of assessment. • We demonstrate the four-level (Concept/State/Process/System) assessment framework. • The performance of the eReefs marine models is assessed. • The approach highlights strengths and weaknesses of the models. • Emergent properties are particularly useful to enhance model assessment. [ABSTRACT FROM AUTHOR]

Estimating the impact of environmental processes on vertical reef development in geological time is a very challenging task. pyReef-Core is a deterministic carbonate stratigraphic forward model designed to simulate the key biological and environmental processes that determine vertical reef accretion and assemblage changes in fossil reef drill cores. We present a Bayesian framework called Bayesreef for the estimation and uncertainty quantification of parameters in pyReef-Core that represent environmental conditions affecting the growth of coral assemblages in geological timescales. Weencounter multimodal posterior distributions and investigate the challenges of sampling using Markov chain Monte-Carlo (MCMC) methods, which includes parallel tempering MCMC. We use a synthetic reef-core to investigate fundamental issues and then apply the methodology to a selected reef-core from the Great Barrier Reef in Australia. The results show that Bayesreef accurately estimates and provides uncertainty quantification of the selected parameters that represent environment and ecological conditions in pyReef-Core. Bayesreef provides insights into the complex posterior distributions of the parameters in pyReef-Core , which provides the groundwork for future research in this area. • Estimating the impact of environmental processes on vertical reef development in geological time is a very challenging task. • pyReef-Core is a deterministic carbonate stratigraphic forward model designed to simulate the key biological and environmental processes. • This paper presents Bayesreef for the estimation and uncertainty quantification of parameters in pyReef-Core. • The results show that Bayesreef accurately estimates and provides uncertainty quantification for parameters in pyReef-Core. • Bayesreef provides insights in of pyReef-Core and establishes the groundwork for future research. [ABSTRACT FROM AUTHOR]