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Flood quantiles in a changing climate: Seasonal forecasts and causal relations
 

Summary: Flood quantiles in a changing climate:
Seasonal forecasts and causal relations
A. Sankarasubramanian and Upmanu Lall1
International Research Institute for Climate Prediction, Lamont-Doherty Earth Observatory, Columbia University, Palisades,
New York, USA
Received 17 July 2002; revised 16 December 2002; accepted 4 March 2003; published 21 May 2003.
[1] Recognizing that the frequency distribution of annual maximum floods at a given
location may change over time in response to interannual and longer climate fluctuations,
we compare two approaches for the estimation of flood quantiles conditional on selected
``climate indices'' that carry the signal of structured low-frequency climate variation,
and influence the atmospheric mechanisms that modify local precipitation and flood
potential. A parametric quantile regression approach and a semiparametric local
likelihood approach are compared using synthetic data sets and for data from a
streamflow gauging station in the western United States. Their relative utility in different
settings for seasonal flood risk forecasting as well as for the assessment of long-term
variation in flood potential is discussed. INDEX TERMS: 1821 Hydrology: Floods; 1833
Hydrology: Hydroclimatology; 4522 Oceanography: Physical: El Nin~o; KEYWORDS: teleconnection, seasonal
flood forecasting, local likelihood, quantile regression
Citation: Sankarasubramanian, A., and U. Lall, Flood quantiles in a changing climate: Seasonal forecasts and causal relations,
Water Resour. Res., 39(5), 1134, doi:10.1029/2002WR001593, 2003.

  

Source: Arumugam, Sankar - Department of Civil, Construction, and Environmental Engineering, North Carolina State University

 

Collections: Environmental Sciences and Ecology; Engineering