Development of exceedance probability streamflow forecast

This paper presents a methodology for forecasting seasonal streamflow and is an extension of a previously developed categorical streamflow forecast model that used persistence (i.e., the previous season's streamflow) and El Nino-Southern Oscillation (ENSO) indicators. This newly developed methodology takes persistence, an ENSO indicator, and several Pacific/Indian Ocean sea surface temperature (SST) series as the main predictor variables. Using linear discriminant analysis, the forecast is expressed as probability of exceedance of continuous streamflow amounts. An exceedance probability forecast is continuous and is useful for the design and operation of water resource 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 other predictors, SSTs and the Southern Oscillation Index, may be more useful for 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 predictands.