Application of a Multistressor Risk Framework to the Monitoring, Assessment, and Diagnosis of River Health

River health assessment and the science to support it have evolved and expanded over recent decades so that it is now a common component of water resource management throughout the world. The broad-scale application of such assessments began as audits of the current condition and trend (i.e., how condition changed over time) using general health indicators considered to be sensitive to a broad suite of anthropogenic stressors. These broad-scale audits provide an overall evaluation of the success of environmental management in protecting river health. However, water managers are increasingly interested in assessments that not only document health, but also go further by both diagnosing the causes of degradation and identifying the priorities for mitigation measures. We outline such an approach developed by the Queensland Government in Australia and provide a case study of its application. This approach identifies multiple stressors in river health within defined assessment regions, then quantifies both the likelihood of exposure to each and the impacts (consequences) to the ecosystem condition. This is done using cause-effect conceptual models that link human pressures to stressors and stressors to ecosystem responses. Specific regional information on the likelihood and consequence is derived from literature, interrogation of available data, and expert elicitation, along with associated estimates of confidence. Risk is calculated as the product of consequence and likelihood and used to rank stressors, with those posing high and moderate risks to the ecosystem condition selected for field measurement within resourcing constraints. Metrics of stressor intensity and relevant ecosystem responses are selected according to conceptual models and their operational efficacy, then applied to a spatially balanced statistical sampling design. The resulting assessments compare and combine results of the initial risk assessment with those from field samplings to give an overall picture of river health, and importantly along with the diagnosis of the stressors responsible for the degradation. Finally, recommendations are made for management priorities to restore river health or prevent further degradation. This approach has been successfully applied to many rivers in Queensland, Australia