Development of exceedance probability streamflow forecast

This paper presents a methodology for forecasting seasonal streamflow and i s an extension of a previously developed categorical streamflow forecast mo del that used persistence (i.e., the previous season's streamflow) and El N ino-Southern Oscillation (ENSO) indicators. This newly developed methodolog y takes persistence, an ENSO indicator, and several Pacific/Indian Ocean se a surface temperature (SST) series as the main predictor variables. Using l inear discriminant analysis, the forecast is expressed as probability of ex ceedance of continuous streamflow amounts. An exceedance probability foreca st is continuous and is useful for the design and operation of water resour ce systems, which require a high degree of system reliability. Application of the forecast model to five Australian catchments shows that persistence is the most important predictor of streamflow for the next season. The othe r predictors, SSTs and the Southern Oscillation Index, may be more useful f or forecasts with Ion-er lead times when the degree of persistence is less noticeable. Finally, it is noteworthy that this generic approach to making an exceedance probability forecast can be used on any predictors and predic tands.