Improving statistical forecasts of seasonal streamflows using hydrological model output
Statistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditi...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2013-02-01
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| Series: | Hydrology and Earth System Sciences |
| Online Access: | http://www.hydrol-earth-syst-sci.net/17/579/2013/hess-17-579-2013.pdf |
| _version_ | 1811326039320690688 |
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| author | D. E. Robertson P. Pokhrel Q. J. Wang |
| author_facet | D. E. Robertson P. Pokhrel Q. J. Wang |
| author_sort | D. E. Robertson |
| collection | DOAJ |
| description | Statistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditions are surrogates for the true source of predictability and can potentially have limitations. This study investigates a hybrid seasonal forecasting system that uses the simulations from a dynamic hydrological model as a predictor to represent the initial catchment condition in a statistical seasonal forecasting method. We compare the skill and reliability of forecasts made using the hybrid forecasting approach to those made using the existing operational practice of the Australian Bureau of Meteorology for 21 catchments in eastern Australia. We investigate the reasons for differences. In general, the hybrid forecasting system produces forecasts that are more skilful than the existing operational practice and as reliable. The greatest increases in forecast skill tend to be (1) when the catchment is wetting up but antecedent streamflows have not responded to antecedent rainfall, (2) when the catchment is drying and the dominant source of antecedent streamflow is in transition between surface runoff and base flow, and (3) when the initial catchment condition is near saturation intermittently throughout the historical record. |
| first_indexed | 2024-04-13T14:43:33Z |
| format | Article |
| id | doaj.art-aa5804ab0677462a9917e9f6b06ffd5a |
| institution | Directory Open Access Journal |
| issn | 1027-5606 1607-7938 |
| language | English |
| last_indexed | 2024-04-13T14:43:33Z |
| publishDate | 2013-02-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Hydrology and Earth System Sciences |
| spelling | doaj.art-aa5804ab0677462a9917e9f6b06ffd5a2022-12-22T02:42:50ZengCopernicus PublicationsHydrology and Earth System Sciences1027-56061607-79382013-02-0117257959310.5194/hess-17-579-2013Improving statistical forecasts of seasonal streamflows using hydrological model outputD. E. RobertsonP. PokhrelQ. J. WangStatistical methods traditionally applied for seasonal streamflow forecasting use predictors that represent the initial catchment condition and future climate influences on future streamflows. Observations of antecedent streamflows or rainfall commonly used to represent the initial catchment conditions are surrogates for the true source of predictability and can potentially have limitations. This study investigates a hybrid seasonal forecasting system that uses the simulations from a dynamic hydrological model as a predictor to represent the initial catchment condition in a statistical seasonal forecasting method. We compare the skill and reliability of forecasts made using the hybrid forecasting approach to those made using the existing operational practice of the Australian Bureau of Meteorology for 21 catchments in eastern Australia. We investigate the reasons for differences. In general, the hybrid forecasting system produces forecasts that are more skilful than the existing operational practice and as reliable. The greatest increases in forecast skill tend to be (1) when the catchment is wetting up but antecedent streamflows have not responded to antecedent rainfall, (2) when the catchment is drying and the dominant source of antecedent streamflow is in transition between surface runoff and base flow, and (3) when the initial catchment condition is near saturation intermittently throughout the historical record.http://www.hydrol-earth-syst-sci.net/17/579/2013/hess-17-579-2013.pdf |
| spellingShingle | D. E. Robertson P. Pokhrel Q. J. Wang Improving statistical forecasts of seasonal streamflows using hydrological model output Hydrology and Earth System Sciences |
| title | Improving statistical forecasts of seasonal streamflows using hydrological model output |
| title_full | Improving statistical forecasts of seasonal streamflows using hydrological model output |
| title_fullStr | Improving statistical forecasts of seasonal streamflows using hydrological model output |
| title_full_unstemmed | Improving statistical forecasts of seasonal streamflows using hydrological model output |
| title_short | Improving statistical forecasts of seasonal streamflows using hydrological model output |
| title_sort | improving statistical forecasts of seasonal streamflows using hydrological model output |
| url | http://www.hydrol-earth-syst-sci.net/17/579/2013/hess-17-579-2013.pdf |
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