A Multi-Site Streamflow Forecast Framework: Application to the Upper Colorado River Basin

The multi-site streamflow forecast framework is a simple and parsimonious method for incorporating large-scale climate information into basin scale streamflow forecasts. The method is parsimonious because predictors need only be developed at one index gage, which is the sum of the seasonal flows at many spatial locations. In an application to the Upper Colorado River Basin (UCRB), multi-model ensemble (MME) forecasts were made of the seasonal (April-July) flows at the index gage. A K nearest-neighbor (KNN) nonparametric disaggregation technique is implemented which provides seasonal forecasts at four spatial locations and in turn monthly forecasts for the peak flow season (April-July). The predictions made in a retroactive forecast mode were comparable to the Colorado Basin River Forecast Center (CBRFC) predictions which are made using the Ensemble Streamflow Prediction (ESP) model. The earliest forecast of the ESP model is January 1 because of its heavy reliance on snowpack information. The multi-site framework provides skillful predictions as early as November 1 by its inclusion of large scale climate information such as geopotential height, zonal winds, meridional winds and sea surface temperature. It is possible that the ESP model and the multi-site framework could be combined in a Bayesian context that could incorporate professional judgment.