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- W1846377860 abstract "[1] This paper dynamically combines three independent forecasts of multiple river flow volumes a season in advance for arid catchments. The case study considers five inflow locations in the upper Namoi Catchment of eastern Australia. The seasonal flows are predicted on the basis of concurrent sea surface temperature anomalies (SSTAs), which are predicted a season forward using a dynamic combination of three SSTA forecasts. The river flows are predicted using three statistical forecasting models: (1) a mixture of generalized lognormal and multinomial logit models, (2) the local regression of independent components of five inflows, and (3) the weighted nearest neighbor method, where each of these models use the forecasted SSTA along with prior lags of the flow as the main driving variables. The study demonstrates that improved SSTA forecast (due to dynamic combination) in turn improves all three flow forecasts, while the dynamic combination of the three flow forecasts results in further, although smaller, improvements." @default.
- W1846377860 created "2016-06-24" @default.
- W1846377860 creator A5011403405 @default.
- W1846377860 creator A5030713645 @default.
- W1846377860 date "2009-10-01" @default.
- W1846377860 modified "2023-09-25" @default.
- W1846377860 title "Multisite seasonal forecast of arid river flows using a dynamic model combination approach" @default.
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- W1846377860 doi "https://doi.org/10.1029/2008wr007510" @default.
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