Articles | Volume 20, issue 10
https://doi.org/10.5194/hess-20-4117-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Special issue:
https://doi.org/10.5194/hess-20-4117-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Optimising seasonal streamflow forecast lead time for operational decision making in Australia
Andrew Schepen
CORRESPONDING AUTHOR
CSIRO Land and Water, 4102 Dutton Park, Australia
Tongtiegang Zhao
CSIRO Land and Water, 3168 Clayton, Australia
Q. J. Wang
CSIRO Land and Water, 3168 Clayton, Australia
Senlin Zhou
Bureau of Meteorology, 3001 Melbourne, Australia
Paul Feikema
Bureau of Meteorology, 3001 Melbourne, Australia
Viewed
Total article views: 2,723 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 09 May 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,551 | 1,068 | 104 | 2,723 | 109 | 117 |
- HTML: 1,551
- PDF: 1,068
- XML: 104
- Total: 2,723
- BibTeX: 109
- EndNote: 117
Total article views: 2,085 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 10 Oct 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
1,242 | 757 | 86 | 2,085 | 89 | 98 |
- HTML: 1,242
- PDF: 757
- XML: 86
- Total: 2,085
- BibTeX: 89
- EndNote: 98
Total article views: 638 (including HTML, PDF, and XML)
Cumulative views and downloads
(calculated since 09 May 2016)
HTML | XML | Total | BibTeX | EndNote | |
---|---|---|---|---|---|
309 | 311 | 18 | 638 | 20 | 19 |
- HTML: 309
- PDF: 311
- XML: 18
- Total: 638
- BibTeX: 20
- EndNote: 19
Cited
15 citations as recorded by crossref.
- A multi-model integration method for monthly streamflow prediction: modified stacking ensemble strategy Y. Li et al. 10.2166/hydro.2019.066
- Skilful seasonal forecasts of streamflow over Europe? L. Arnal et al. 10.5194/hess-22-2057-2018
- Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods S. Charles et al. 10.5194/hess-22-3533-2018
- Seasonal hydroclimatic ensemble forecasts anticipate nutrient and suspended sediment loads using a dynamical-statistical approach S. Sharma et al. 10.1088/1748-9326/ab2c26
- A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments A. Schepen et al. 10.5194/hess-22-1615-2018
- Process-based forecasts of lake water temperature and dissolved oxygen outperform null models, with variability over time and depth W. Woelmer et al. 10.1016/j.ecoinf.2024.102825
- The Application of Adaptive Operation Decision Technology and Optimization Algorithm Model of Smart Supply Chain Oriented to the Internet of Things Q. Chen 10.1080/03772063.2021.1973594
- Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden M. Girons Lopez et al. 10.5194/hess-25-1189-2021
- Monthly Reservoir Inflow Forecasting for Dry Period Using Teleconnection Indices: A Statistical Ensemble Approach D. Lee et al. 10.3390/app10103470
- Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. 10.5194/hess-22-3601-2018
- Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. 10.3390/w16101438
- The development and evaluation of a hydrological seasonal forecast system prototype for predicting spring flood volumes in Swedish rivers K. Foster et al. 10.5194/hess-22-2953-2018
- Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge K. Wheeler et al. 10.1016/j.agrformet.2023.109810
- Seasonal discharge forecasting for the Upper Danube I. Martin Santos et al. 10.1016/j.ejrh.2021.100905
- A Medium and Long-Term Runoff Forecast Method Based on Massive Meteorological Data and Machine Learning Algorithms Y. Li et al. 10.3390/w13091308
15 citations as recorded by crossref.
- A multi-model integration method for monthly streamflow prediction: modified stacking ensemble strategy Y. Li et al. 10.2166/hydro.2019.066
- Skilful seasonal forecasts of streamflow over Europe? L. Arnal et al. 10.5194/hess-22-2057-2018
- Seasonal streamflow forecasting in the upper Indus Basin of Pakistan: an assessment of methods S. Charles et al. 10.5194/hess-22-3533-2018
- Seasonal hydroclimatic ensemble forecasts anticipate nutrient and suspended sediment loads using a dynamical-statistical approach S. Sharma et al. 10.1088/1748-9326/ab2c26
- A Bayesian modelling method for post-processing daily sub-seasonal to seasonal rainfall forecasts from global climate models and evaluation for 12 Australian catchments A. Schepen et al. 10.5194/hess-22-1615-2018
- Process-based forecasts of lake water temperature and dissolved oxygen outperform null models, with variability over time and depth W. Woelmer et al. 10.1016/j.ecoinf.2024.102825
- The Application of Adaptive Operation Decision Technology and Optimization Algorithm Model of Smart Supply Chain Oriented to the Internet of Things Q. Chen 10.1080/03772063.2021.1973594
- Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden M. Girons Lopez et al. 10.5194/hess-25-1189-2021
- Monthly Reservoir Inflow Forecasting for Dry Period Using Teleconnection Indices: A Statistical Ensemble Approach D. Lee et al. 10.3390/app10103470
- Seasonal streamflow forecasts in the Ahlergaarde catchment, Denmark: the effect of preprocessing and post-processing on skill and statistical consistency D. Lucatero et al. 10.5194/hess-22-3601-2018
- Performance Evaluation of a National Seven-Day Ensemble Streamflow Forecast Service for Australia M. Bari et al. 10.3390/w16101438
- The development and evaluation of a hydrological seasonal forecast system prototype for predicting spring flood volumes in Swedish rivers K. Foster et al. 10.5194/hess-22-2953-2018
- Predicting spring phenology in deciduous broadleaf forests: NEON phenology forecasting community challenge K. Wheeler et al. 10.1016/j.agrformet.2023.109810
- Seasonal discharge forecasting for the Upper Danube I. Martin Santos et al. 10.1016/j.ejrh.2021.100905
- A Medium and Long-Term Runoff Forecast Method Based on Massive Meteorological Data and Machine Learning Algorithms Y. Li et al. 10.3390/w13091308
Saved (preprint)
Latest update: 26 Dec 2024
Short summary
Australian seasonal streamflow forecasts are issued by the Bureau of Meteorology with up to two weeks' delay. Timelier forecast release will enhance forecast value and enable sub-seasonal forecasting. The bureau's forecasting approach is modified to allow timelier forecast release, and changes in reliability and skill are quantified. The results are combined with insights into the forecast production process to recommend a more flexible forecasting system to better meet the needs of users.
Australian seasonal streamflow forecasts are issued by the Bureau of Meteorology with up to two...
Special issue