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You are here : eLibrary : IAHR World Congress Proceedings : 34th Congress - Brisbane (2011) : THEME 3: Water and Carbon: Climate Change Impact : Using water balance model output to represent initial catchment conditions in statistical forecastin...
Using water balance model output to represent initial catchment conditions in statistical forecasting of seasonal streamflows
Author : D.E. Robertson1, Q.J. Wang1, T.C. Pagano1 and H.A.P. Hapuarachchi1
Statistical seasonal streamflow forecasting methods commonly use antecedent streamflows as predictors to represent initial catchment conditions. However, antecedent streamflows do not necessarily capture the full dynamics of catchment processes. This paper investigates the use of water balance model output as an alternative representation of the initial catchment conditions. The Bayesian joint probability modelling approach is used to produce seasonal forecasts using two sets of predictors representing initial catchment conditions: predictors selected from a pool of candidates comprising antecedent streamflow and rainfall totals, and simulations made using a monthly water balance model. In general, using water balance model output as predictors results in more skilful streamflow forecasts, with the greatest differences being in seasons where the dominant source of streamflows transitions between surface runoff and base flow. The use of water balance model output as predictors also has the advantage of reducing artificial skill due to predictor selection.
File Size : 228,166 bytes
File Type : Adobe Acrobat Document
Chapter : IAHR World Congress Proceedings
Category : 34th Congress - Brisbane (2011)
Article : THEME 3: Water and Carbon: Climate Change Impact
Date Published : 01/07/2011
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