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SUWANNEE RIVER LONG RANGE STREAMFLOW FORECASTS BASED ON SEASONAL CLIMATE PREDICTORS 1
Author(s) -
Tootle Glenn A.,
Piechota Thomas C.
Publication year - 2004
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.2004.tb01047.x
Subject(s) - streamflow , environmental science , climatology , multivariate enso index , flood forecasting , flood myth , range (aeronautics) , spring (device) , hydrology (agriculture) , el niño southern oscillation , drainage basin , geography , la niña , geology , mechanical engineering , materials science , cartography , archaeology , geotechnical engineering , engineering , composite material
ABSTRACT: A study of the influence of climate variability on streamflow in the southeastern United States is presented. Using a methodology previously applied to watersheds in Australia and the United States, a long range streamflow forecast (0 to 9 months in advance) is developed. Persistence (i.e., the previous season's streamflow) and climate predictors of the previous season are used to forecast the following season's (winter and spring) streamflow of the Suwannee River located in northern Florida. The winter and spring streamflow is historically the most likely to have severe flood events due to large scale cyclonic (frontal) storms. Results of the analysis indicated that a strong El Nino‐Southern Oscillation (ENSO) signal exists at various lead times to the winter and spring streamflow of the Suwannee River. These results are based on the high correlation values of two commonly used measurements of ENSO strength, the Multivariate ENSO Index (MEI) and Sea Surface Temperature Range 1. Using the relationships developed between climate and streamflow, a continuous exceedance probability forecast was developed for two Suwannee River stations. The forecast system provided an improved forecast for ENSO years. The ability to predict above normal (flood) or below normal (drought) years can provide communities the necessary lead time to protect life, property, sensitive wetlands, and endangered and threatened species.