Climate-Based Estimation of Hydrologic Inflow into Lake Okeechobee, Florida
Publication: Journal of Water Resources Planning and Management
Volume 131, Issue 5
Abstract
This paper presents a comparative evaluation of methods for climate-based estimation of the net inflow rate into Lake Okeechobee, Fla. The estimated net inflow rate is used by the South Florida Water Management District (SFWMD) to support the management and operations of the Lake Okeechobee hydrologic system. The first method evaluated in this paper (Croley) uses rainfall outlooks provided by the National Oceanic and Atmospheric Administration’s Climate Prediction Center (CPC) to calculate a weighed average of historical inflow values for each month. The second method evaluated in this paper (SFWMD Empirical) uses a linear regression on statistics of historical data to predict the net inflow rate. These two methods were developed and have been used operationally by the SFWMD since 2000. Three new methods are presented and comparatively evaluated to gauge their ability in estimating net inflow rates. The first two of these methods are based on CPC issued forecasts in decile probability density format. The remaining method is based on a subsampling technique for “peer” wet∕dry years in the historical record and is found to yield better results in a retrospective analysis. For extreme climatic events on the historical record, CPC rainfall outlooks are found not to yield a large enough shift in probabilities for forecasts to match observed net inflow rates; this is especially noticeable during El Niño Southern Oscillation events. Recommendations are made for potential improvements to climate-based net inflow rate estimation methods, particularly in regard to their ability to reproduce observed results for net inflow into Lake Okeechobee in the presence of an extreme climatic event, as well as over an extended climatological period.
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Acknowledgment
This work is funded by the National Oceanic and Atmospheric Administration (NOAA), Office of Global Programs Research Integrated Science Assessments.
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© 2005 ASCE.
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Received: Apr 26, 2004
Accepted: Feb 3, 2005
Published online: Sep 1, 2005
Published in print: Sep 2005
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