Journal article
Reliable long-range ensemble streamflow forecasts: Combining calibrated climate forecasts with a conceptual runoff model and a staged error model
JC Bennett, QJ Wang, M Li, DE Robertson, A Schepen
Water Resources Research | AMER GEOPHYSICAL UNION | Published : 2016
DOI: 10.1002/2016WR019193
Abstract
We present a new streamflow forecasting system called forecast guided stochastic scenarios (FoGSS). FoGSS makes use of ensemble seasonal precipitation forecasts from a coupled ocean-atmosphere general circulation model (CGCM). The CGCM forecasts are post-processed with the method of calibration, bridging and merging (CBaM) to produce ensemble precipitation forecasts over river catchments. CBaM corrects biases and removes noise from the CGCM forecasts, and produces highly reliable ensemble precipitation forecasts. The post-processed CGCM forecasts are used to force the Wapaba monthly rainfall-runoff model. Uncertainty in the hydrological modeling is accounted for with a three-stage error mode..
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Funding Acknowledgements
This research has been supported by the Water Information Research and Development Alliance (WIRADA) between the Bureau of Meteorology and CSIRO Land & Water. Thanks to Senlin Zhou, Julien Lerat, Paul Feikema and Daehyok Shin (all Bureau of Meteorology) for supplying data and for fruitful discussions on the development of FoGSS. Thanks to Kelvin Michael (University of Tasmania) and Luis Neumann (CSIRO) for comments on an earlier draft of this manuscript. Catchment maps in Figure 1 are generated using data from the Bureau of Meteorology Geofabric (http://www.bom.gov.au/water/geofabric/). The streamflow and climate data used in this study are listed in the references or are available from the CSIRO data access portal http://data.csiro.au/dap/. We thank Prof Andrew Western, Dr Massimiliano Zappa and two anonymous reviewers for thorough and constructive reviews of our manuscript.