Nonparametric Framework for Long‐range Streamflow Forecasting

Abstract

The extended streamflow prediction (ESP) procedure of the National Weather Service River Forecast System (NWSRFS) produces long‐range forecasts of streamflow through the use of hydrologic models and historical hydrologic data. An important element of the ESP procedure is converting hydrologic‐model output to estimates of a forecast random variable. In this paper, nonparametric statistical procedures are developed for combining hydrologic models and historical hydrologic data into long‐range streamflow forecasts. Although these procedures are developed for use within the ESP system, they should be broadly applicable to problems of long‐range streamflow forecasting. Two notable features of the procedures developed in this paper are: (1) Climate information is easily incorporated; and (2) hydrologic‐model errors can be accommodated. Results are presented for a test implementation of ESP for a basin in the southeastern United States during the severe drought period of 1988. The relative importance of climate information and soil moisture information for long‐range streamflow forecasting is compared and contrasted.