Theme: Hydrological Prediction
This Theme pursues the OzEWEX aim to improve and provide hydrological predictions over time scales of hours to decades. Activities include testing existing and develop improved methods of hydrological prediction at a wide range of time scales. Of particular interest are streamflow forecasts at daily, seasonal and decadal time scales. Scientific topics of interest include forecast initialisation, using meteorological forecasts and predictions, and determining prediction skill.
Forecast initialisation refers to the initialisation of hydrological models. This can involve assimilation of hydrometric and hydrological remote sensing data and deal with data latency and lead time, for example by combining historic data and short-term forecasts to ‘now-cast’ recent conditions. This also relates to inundation modelling, where near-real time remote sensing information can be used to constrain hydrodynamic models, which in turn can be run in forecast mode.
Using weather forecasts and climate predictions involves mechanisms for researchers to access weather forecasts and climate predictions, research to evaluate the skill of alternative forecast and prediction sources, and the development of ensemble, downscaling and bias-correction procedures for hydrological application. Anticipated activities could facilitate near-real time research access to forecasts from the BoM’s numerical weather prediction and seasonal prediction systems, and original or post-processed climate predictions produced in support of the Intergovernmental Panel on Climate Change’s 5th Assessment Report (e.g., the COordinated Regional climate Downscaling Experiment, CORDEX).
Several techniques and approaches to hydrological forecast exist, and include simple as well as complex that may use meteorological forecasts, hydrological models, multi-variate statistical techniques, ensemble methods or a combination of these. There is a need to measure and compare their respective skill. This will require the design of benchmarking experiments and infrastructure to test improvements. Performance needs to consider accuracy as well as reliability in the forecasts, and consider unavoidable operational constraints. The BoM is a key stakeholder as the organisation responsible for operational forecasting.
This Theme encourages the design and execution of hind-cast experiments to compare the skill of alternative statistical and/or dynamic prediction techniques. This can build on the hind-cast and verification experiments that have occurred in WIRADA and the BoM Extended Hydrological Prediction section, and likely involve the same or a similar set of experiment catchments.
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