Suwannee River Long Range Streamflow Forecasts Based on Seasonal Climate Predictors
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.
Climate; Climatology; El Nino-Southern Oscillation; Floods; Sea surface temperatures; Statistical analysis; Streamflow; Streamflow—Forecasting; Streamflow forecasts; Water; Water temperature; Watersheds
Civil and Environmental Engineering | Climate | Environmental Engineering | Environmental Health and Protection | Environmental Monitoring | Environmental Sciences | Oceanography | Oceanography and Atmospheric Sciences and Meteorology | Water Resource Management
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Tootle, G. A.,
Piechota, T. C.
Suwannee River Long Range Streamflow Forecasts Based on Seasonal Climate Predictors.
Journal of the American Water Resources Association, 40(2),