LONG‐RANGE STREAMFLOW FORCASTING USING NONPARAMETRIC REGRESSION

Research output: Contribution to journalArticle

17 Scopus citations

Abstract

ABSTRACT: A class of nonparametric procedures is developed for producing long‐range streamflow forecasts. The forecasting procedures, which are based solely on daily streamflow data, utilize nonparametric regression to relate a forecast variable to a covariate variable. The forecast variable is a function of future streamflow and can take a wide variety of forms. The covariate variable is a function of antecedent streamflow. The forecasting procedures are quite flexible, both in terms of the duration of the forecast period and the types of forecast variables that can be considered. The procedures are used to develop long‐term (1–4 months) forecasts of minimum daily flow of the Potomac River at Washington, D.C. This forecast information is an integral component of water management activities for the Washington, D.C. metropolitan area.

Original languageEnglish (US)
Pages (from-to)39-46
Number of pages8
JournalJAWRA Journal of the American Water Resources Association
Volume27
Issue number1
DOIs
StatePublished - Jan 1 1991

All Science Journal Classification (ASJC) codes

  • Ecology
  • Water Science and Technology
  • Earth-Surface Processes

Fingerprint Dive into the research topics of 'LONG‐RANGE STREAMFLOW FORCASTING USING NONPARAMETRIC REGRESSION'. Together they form a unique fingerprint.

  • Cite this