Investigation of the national weather service soil moisture accounting models for flood prediction in the northeast floods of january 1996

摘要

Extensive flooding occurred throughout the northeastern United States duringudJanuary of 1996. The flood event cost the lives of 33 people and over a billion dollars inudflood damage. Following the `Blizzard of `96 ", a warm front moved into the Mid-Atlantic region bringing extensive rainfall and causing significant melting and flooding toudoccur. Flood forecasting is a vital part of the National Weather Service (NWS)udhydrologic responsibilities. Currently, the NWS River Forecast Centers use either theudAntecedent Precipitation Index (API) or the Sacramento Soil -Moisture AccountingudModel (SAC-SMA). This study evaluates the API and SAC -SMA models for theirudeffectiveness in flood forecasting during this rain -on -snow event. The SAC -SMA, inudconjunction with the SNOW-17 model, is calibrated for five basins in the Mid -Atlanticudregion using the Shuffled Complex Evolution (SCE-UA) automatic algorithm developedudat the University of Arizona. Nash-Sutcliffe forecasting efficiencies (Ef) for theudcalibration period range from 0.79 to 0.87, with verification values from 0.42 to 0.95.udFlood simulations were performed on the five basins using the API and calibrated SAC-SMA model. The SAC-SMA model does a better job of estimating observed flooduddischarge on three of the five study basins, while two of the basins experience floodudsimulation problems with both models. Study results indicate the SAC-SMA has theudpotential for better flood forecasting during complex rain-on-snow events such as duringudthe January 1996 floods in the Northeast.