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This study presents an innovative tool and approach developed to facilitate the adaptive testing or monitoring of e-flow frameworks and environmental flows (e-flows) implementation using digital tools and real-time data to ensure sustainable water resource management. The project, conducted in two river basins in southern Africa, focuses on creating a user-friendly digital Application Tool, integrated with a high-resolution 3D model and modern sensors, to monitor changes in river ecosystems post eflow implementation. The methodology, grounded in the established PROBFLO e-flow frameworks for these two basins, involves an eight-step process to determine e-flows for maintaining sustainable ecosystems and the holistic testing of the socio-ecological consequences of altered flow and non-flow environmental variables. It begins with site selection, considers physico-chemical dynamics, establishes flow-ecosystem relationships, and generates flow scenarios. Utilizing Bayesian Networks (BN), the model evaluates risk or socio-ecological consequences associated with proposed e-flow requirements and any other past, present or future resource development scenario, integrating ecosystem components to ensure the holistic suitability of the determined e-flows. The risk assessment builds on to the ecological components with the including of ecosystem service allowing for the social consequences of altered flows to be evaluated using the same framework. The development of a user-friendly PROBFLO Environmental Framework Assessment (EFA) Tool enables stakeholders to test scenarios and assess risk outcomes without extensive probability or resources specialization expertise. The PROBFLO EFA Tool streamlines data analysis and BN modelling, offering an accessible platform to evaluate e-flow scenarios. While the PROBFLO EFA Tool is still undergoing refinements, its potential to empower users in making informed decisions regarding e-flow management is evident.
