11.2
Drought monitoring and forecasting in the Apalachicola-Chatahoochee-Flint River Basin in the Southeastern United States [INVITED]

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Thursday, 27 January 2011: 3:45 PM
Drought monitoring and forecasting in the Apalachicola-Chatahoochee-Flint River Basin in the Southeastern United States [INVITED]
611 (Washington State Convention Center)
Joshua K. Roundy, Princeton University, Princeton, NJ; and J. Sheffield, E. F. Wood, K. C. Mo, and J. Dobur

Extreme hydrologic events in the form of droughts or floods are a significant source of social and economic damage in many parts of the world. Having sufficient warning of extreme events allows managers to prepare for and reduce the severity of their impacts. A hydrologic forecast system can give seasonal predictions that can be used by mangers to make better decisions; however there is still much uncertainty associated with such a system. Therefore it is important to understand the forecast skill of the system before transitioning to operational usage. Using our national hydrologic monitoring and forecast system, seasonal forecasts from the NCEP Climate Forecast System (CFS) and Climate Prediction Center (CPC) are downscaled and used to drive the Variable Infiltration Capacity (VIC) land surface hydrologic model to give hydrologic variables with lead times of up to six months. We focus on the Apalachicola-Chatahoochee-Flint (ACF) River Basin in the South Eastern United States, which has experienced a number of severe droughts in recent years and is a pilot study basin for NIDIS. The performance of the VIC model is evaluated using observational forcing and compared to observed streamflow for 21 forecast points in the ACF River Basin, some of which are affected by water management. The effectiveness of the forecast system to predict streamflow and soil moisture is evaluated from CFS hindcasts from 1982 onwards compared with observed streamflow and modeled soil moisture driven by observed atmospheric forcing. The forecast skill from the CFS and CPC are also compared with forecasts based on the Ensemble Streamflow Prediction (ESP) method, which uses initial conditions and historical forcings to generate seasonal forecasts. The skill of the system to predict drought, drought recovery and related hydrological conditions such as low-flows is assessed, along with quantified uncertainty. Potential system improvements are recommended, especially in light of the needs of the new NOAA Climate Service initiative.