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<p>Ensuring the resilience and security of water supply will be one of the most significant future challenges facing water utilities worldwide given potential impacts of climate change and population growth. The development of new water resource options is costly, hence the need to develop techniques to maximize the potential and resilience of current water resource assets without compromising environmental regulations. The availability of real-time meteorological and hydrological data combined with real-time forecasting techniques provide a potential to increase water abstraction volumes without compromising environmental regulations and reduce operational costs. This paper presents an approach for managing surface water abstraction utilizing real-time flow forecasting techniques, coupled with a water resource model and Genetic Algorithm optimization. To evaluate this approach, a retrospective analysis of a historical period 2017/2018 is conducted, comparing historic water abstractions, reservoir water level data, flows downstream abstraction point and energy costs at a case study abstraction site within a catchment in the UK with corresponding simulations based on forecasted flows. Simulation results show that on average 25 Ml/day of additional water could have been abstracted using the forecasting led scheme, without compromising environmental regulations. The results show that rapid declines in reservoir levels during low flow periods can be avoided and energy costs can be significantly reduced (by approximately £ 0.35M / annum) using the proposed approach. This study demonstrates the benefits of utilizing real-time flow forecasting and flexible water pumping schedules to maximize the value of existing surface water resources, in some cases this may reduce the need for significant investment to increase the resilience of supply. Further work will seek to extend the approach to enable optimization of pumping and water release operations in multi reservoir systems.</p>