An Intelligent Analytics System for Real-Time Catchment Regulation and Water Management

Regulation procedures and water management that incorporate projected hydrological changes with related uncertainties become extremely important in order to prevent degradation of water ecosystems. Ensuring real time water management and optimization becomes mandatory for resolving the constraints of water supply/demand and to comply with biodiversity requirements. We focus our research on water optimization and catchment regulation and present our solution that has been developed as part of the Innovate UK Radical project. 1 In our study, we use the Usk reservoir in South Wales with rich biodiversity and nationally significant fishery to optimize catchment flow and to conserve water with real-time catchment management information to support the decision makers. Our developed solution uses artificial intelligence techniques to deliver real-time decision support for water management and catchment regulation with reflection to biodiversity protection and reservation. We present an intelligent analytics system that uses real-time data from river stations enabling informed decisions and a more dynamic approach for managing water resources. The system utilizes a neuronal network engine to support river level prediction based on which a dependency modeling is developed for assessing the probability of risk in the Usk reservoir.