Forecasting scheme for swan coastal river streamflow using combined model of IOHLN and Niño4
The study aims to investigate the possible relationship between Niño 4 and Indian Ocean high longitude (IOHLN) with the Swan coastal river flow by constructing a regression model which predict streamflow patterns and which enables to obtain long time lead to forecasting, in a period when there was n...
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Veröffentlicht in: | Asia-Pacific journal of atmospheric sciences 2014-02, Vol.50 (2), p.211-219 |
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description | The study aims to investigate the possible relationship between Niño 4 and Indian Ocean high longitude (IOHLN) with the Swan coastal river flow by constructing a regression model which predict streamflow patterns and which enables to obtain long time lead to forecasting, in a period when there was not much rainfall. Many streamflow forecast models use rainfall and runoff relationship, which is dependent on basin response time and hence cannot provide large forecasting lead time. For water resource management, this lead time of predictability is not capable for a long period of drying trend. Significant findings of this study suggest that Niño 4 and Indian Ocean high pressure longitude (IOHLN) can be used for forecasting of flow in Swan river. In this study not only qualitative forecast of Swan coastal river is presented based on the conditional probability, but also a quantitative forecast is done by combining Niño.4 and IOHLN indices using multiple regression, which shows enhancement over other climate indicators when used alone. The Conditional probability model correctly predict 7 years category of flow out of 8 years flow. |
doi_str_mv | 10.1007/s13143-014-0009-6 |
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Many streamflow forecast models use rainfall and runoff relationship, which is dependent on basin response time and hence cannot provide large forecasting lead time. For water resource management, this lead time of predictability is not capable for a long period of drying trend. Significant findings of this study suggest that Niño 4 and Indian Ocean high pressure longitude (IOHLN) can be used for forecasting of flow in Swan river. In this study not only qualitative forecast of Swan coastal river is presented based on the conditional probability, but also a quantitative forecast is done by combining Niño.4 and IOHLN indices using multiple regression, which shows enhancement over other climate indicators when used alone. 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Many streamflow forecast models use rainfall and runoff relationship, which is dependent on basin response time and hence cannot provide large forecasting lead time. For water resource management, this lead time of predictability is not capable for a long period of drying trend. Significant findings of this study suggest that Niño 4 and Indian Ocean high pressure longitude (IOHLN) can be used for forecasting of flow in Swan river. In this study not only qualitative forecast of Swan coastal river is presented based on the conditional probability, but also a quantitative forecast is done by combining Niño.4 and IOHLN indices using multiple regression, which shows enhancement over other climate indicators when used alone. 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Many streamflow forecast models use rainfall and runoff relationship, which is dependent on basin response time and hence cannot provide large forecasting lead time. For water resource management, this lead time of predictability is not capable for a long period of drying trend. Significant findings of this study suggest that Niño 4 and Indian Ocean high pressure longitude (IOHLN) can be used for forecasting of flow in Swan river. In this study not only qualitative forecast of Swan coastal river is presented based on the conditional probability, but also a quantitative forecast is done by combining Niño.4 and IOHLN indices using multiple regression, which shows enhancement over other climate indicators when used alone. The Conditional probability model correctly predict 7 years category of flow out of 8 years flow.</abstract><cop>Heidelberg</cop><pub>Korean Meteorological Society</pub><doi>10.1007/s13143-014-0009-6</doi><tpages>9</tpages></addata></record> |
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subjects | Atmospheric Sciences Climatology Earth and Environmental Science Earth Sciences Freshwater Geophysics/Geodesy |
title | Forecasting scheme for swan coastal river streamflow using combined model of IOHLN and Niño4 |
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