In a significant stride for water resource management and disaster risk reduction, researchers at the UK Centre for Ecology & Hydrology (UKCEH) have developed a novel approach to seasonal hydrological forecasting. The study, led by W. Chan and published in the journal ‘Hydrology and Earth System Sciences’ (which translates to ‘Hydrology and Earth System Sciences’), introduces the Historic Weather Analogues (HWA) method, a promising advancement in predicting river flows and groundwater levels across the UK.
The UK Hydrological Outlook (UKHO) has long relied on the Ensemble Streamflow Prediction (ESP) method for seasonal forecasts. However, the HWA method offers a fresh perspective by leveraging high-resolution historical weather data to find analogue months that match atmospheric circulation patterns forecasted by dynamical weather models. This approach allows for more accurate and reliable predictions, particularly in the winter months.
“Our study demonstrates that the HWA method can significantly improve river flow forecasts, especially during winter,” said W. Chan, lead author of the study. “This enhanced predictability is crucial for water resource planning and disaster risk reduction, providing valuable insights for industries dependent on water, including the energy sector.”
The research involved a hindcast experiment using the GR6J hydrological model across 314 UK catchments. The results were promising, showing that the HWA method outperformed the standard ESP method in winter, making skilful forecasts possible across the entire UK, whereas the ESP method was previously only reliable in southeast England.
The improvements were most notable in upland, fast-responding catchments with limited storage, where river flow variability is closely tied to climate variability. The HWA method’s ability to derive high-resolution meteorological inputs suitable for catchment hydrological modelling contributed to this success.
However, the skill was not uniform across all seasons. While there were moderate improvements in spring forecasts in northern England and northeast Scotland, autumn forecasts saw little change. Summer flow predictability remained limited to southeast England, with some catchments even showing reduced skill compared to the ESP method.
“This study highlights the potential of the HWA method to leverage both climate information from dynamical weather forecasting models and the influence of initial hydrological conditions,” Chan explained. “It provides a robust framework for future improvements in hydrological forecasting.”
The energy sector, which relies heavily on water for cooling and generation processes, stands to benefit significantly from these advancements. Accurate seasonal forecasts can aid in better planning and management of water resources, ensuring a stable supply for energy production and reducing the risk of water-related disruptions.
As the field of hydrological forecasting continues to evolve, this research underscores the importance of continuous innovation and rigorous testing. The HWA method represents a significant step forward, offering a more reliable and comprehensive approach to seasonal hydrological forecasting. With further refinement and application, it could become an invaluable tool for water resource management and disaster risk reduction, ultimately contributing to a more sustainable and resilient future.