Long Lead-Time Streamflow Forecasting of the North Platte River Incorporating Oceanic-Atmospheric Climate Variability

Document Type

Article

Publication Date

4-30-2009

Publication Title

Journal of Hydrology

Volume

368

Issue

1-4

First page number:

131

Last page number:

142

Abstract

An evaluation of the influence of oceanic–atmospheric climate variability on streamflow in the upper North Platte River basin is presented. Through the application of Singular Value Decomposition (SVD) statistical methods, sea surface temperatures (SSTs), 500 mbar geopotential height (Z500) values and North Platte streamflow were evaluated over a historical period from 1948 to 2006. This resulted in the identification of new regions of highly correlated SSTs and Z500 that may not be represented by existing index regions (Niño 3.4 — defined El Nino Southern Oscillation region, PDO – Pacific Decadal Oscillation, and AMO – Atlantic Multidecadal Oscillation). A long lead-time approach was utilized such that a three month lead-time (seasonal average of monthly SSTs or Z500 for October, November, and December) as well as a six month lead-time (seasonal average of monthly SSTs or Z500 for July, August, and September) of previous year variability were used as predictors for the following year spring streamflow (seasonal monthly average of April, May, June, and July). Temporal expansion series from SVD were utilized as predictors in a non-parametric model to develop continuous exceedance probability forecasts. The results displayed good skill using SSTs for the six month lead-time forecast and excellent skill using Z500 values for the three month lead-time forecast. The improved skill found over basic climatology forecasts will be useful to water managers when trying to predict and manage expected streamflow volumes several months in advance.

Keywords

500 mbar geopotential height; Exceedance probability; North Platte River basin; Oceanic–atmospheric climate variability; Sea surface temperatures; Singular value decomposition; Streamflow forecast

Disciplines

Climate | Environmental Sciences | Fresh Water Studies

Language

English

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