A regional scale ecological risk framework for environmental flow evaluations

Abstract. Recent developments in Environmental Flow (E-flow) frameworks advocate holistic, regional scale, probabilistic E-flow assessments that consider flow and non-flow drivers of change in socio-ecological context as best practice. Regional Scale ecological risk assessments of multiple sources, stressors and diverse ecosystems that address multiple social and ecological endpoints, have been undertaken internationally at different spatial scales using the relative-risk model since the mid 1990's. With the recent incorporation of Bayesian belief networks into the relative-risk model, a robust regional scale ecological risk assessment approach is available that can contribute to achieving the best practice recommendations of E-flow frameworks. PROBFLO is a regional scale, holistic E-flow assessment method that incorporates the relative-risk model and Bayesian belief networks (BN-RRM) into a transparent probabilistic modelling tool that addresses uncertainty explicitly. PROBFLO has been developed to holistically evaluate the socio-ecological consequences of historical, current and future altered flows in the context of non-flow drivers and generate E-flow requirements on regional scales spatial scales. The approach has been implemented in two regional scale case studies in Africa where its flexibility and functionality has been demonstrated. In both case studies the evidence based outcomes facilitated informed environmental management decision making, in the context of social and ecological aspirations. This paper presents the PROBFLO approach as applied to the Senqu River catchment in Lesotho and further developments and application in the Mara River catchment in Kenya and Tanzania. The ten BN-RRM procedural steps incorporated in PROBFLO are demonstrated with examples from both case studies. Outcomes allowed stakeholders to consider sustainable social and ecological E-flow trade-offs between social and ecological endpoints. PROBFLO can be incorporated into adaptive management processes and contribute to the sustainable management of the use and protection of water resources.