WAFARi: A new modelling system for Seasonal Streamflow Forecasting service of the Bureau of Meteorology, Australia

MODSIM 2011 - 19th International Congress on Modelling and Simulation - Sustaining Our Future: Understanding and Living with Uncertainty

Volumn , Issue , 2011, Pages 2374-2380

  Shin, D ^a   Schepen, A ^a   Peatey, T ^a   Zhou, S ^a   MacDonald, A ^a   Chia, T ^a   Perkins, J ^a   Plummer, N ^a  

^a BUREAU OF METEOROLOGY   (Australia)

Author keywords

Bureau of Meteorology; Forecast; Model; Streamflow; System

Indexed keywords

AUSTRALIA; FORECAST; GRAPHICAL TOOLS; INTERMEDIATE MODEL; JOINT PROBABILITY; PROBABILISTIC FORECASTS; RELIABLE DELIVERY; RESOURCE INFORMATION; SCRIPTING ENVIRONMENT; SINGLE LOCATION; STREAMFLOW FORECAST; STREAMFLOW FORECASTING; SYSTEM; WATER ACT; WATER AVAILABILITY; WATER STORAGE;

BEHAVIORAL RESEARCH; INFORMATION MANAGEMENT; METEOROLOGY; MODELS; PARALLEL ARCHITECTURES; STREAM FLOW; UNCERTAINTY ANALYSIS; WATER RESOURCES;

FORECASTING;

EID: 84858824360     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (8)

1. Hunter, J. D. (2007). Matplotlib: A 2D graphics environment. Computing in Science & Engineering, 9:90-95.
2. Oliphant, T. E. (2007). Python for scientific computing. Computing in Science & Engineering, 9:10-20.
3. Ousterhout, J. K. (1998). Scripting: higher level programming for the 21st century. IEEE Computer, 3:23-30.
4. Plummer, N., Tuteja, N.K., Wang, Q.J., Wang, E., Robertson, D., Zhou, S., (2009) A Seasonal Water Availability Prediction Service: Opportunities and Challenges. 18th World IMACS / MODSIM Congress, Cairns, 13-17.
5. Pérez, F. and B. E. Granger (2007). IPython: A system for interactive scientific computing. Computing in Science & Engineering, 9:21-29.
6. Pérez, F., B. E. Granger, and J. D. Hunter (2011). Python: An ecosystem for scientific computing. Computing in Science & Engineering, 13:13-21.
7. Wang, Q. J., D. E. Robertson, and F. H. S. Chiew (2009). A Bayesian joint probability modeling approach for seasonal forecasting of streamflows at multiple sites, Water Resources Research, 45, W05407, doi:10.1029/2008WR007355.
8. Wang, Q. J. and D. E. Robertson (2011). Multisite probabilistic forecasting of seasonal flows for streams with zero value occurrences. Water Resources Research, 47, W02546, doi:10.1029/2010WR009333.