Improving streamflow forecast lead time using oceanic-atmospheric oscillations for Kaidu River basin, Xinjiang, China

Journal of Hydrologic Engineering

Volumn 18, Issue 8, 2013, Pages 1031-1040

  Kalra, Ajay ^a,b   Li, Lanhai ^c   Li, Xuemei ^c   Ahmad, Sajjad ^b  

^a DESERT RESEARCH INSTITUTE   (United States)

^b UNIVERSITY OF NEVADA   (United States)

^c XINJIANG INSTITUTE OF ECOLOGY AND GEOGRAPHY   (China)

Author keywords

Climate variability; Forecast; Kaidu River; Least square support vector machine (LSSVM); Oscillations; Streamflow; Xinjiang

Indexed keywords

ATLANTIC MULTIDECADAL OSCILLATIONS; CLIMATE VARIABILITY; FEEDFORWARD BACKPROPAGATION; LEAST-SQUARE SUPPORT VECTOR MACHINE (LSSVM); NORTH ATLANTIC OSCILLATIONS; OSCILLATIONS; WATER RESOURCES PLANNING AND MANAGEMENTS; XINJIANG;

ATMOSPHERIC PRESSURE; CLIMATOLOGY; FORECASTING; GLOBAL WARMING; INFORMATION MANAGEMENT; LINEAR REGRESSION; NEURAL NETWORKS; SUPPORT VECTOR MACHINES; WATER MANAGEMENT; WATER SUPPLY; WATERSHEDS;

STREAM FLOW;

AIR-SEA INTERACTION; ANNUAL VARIATION; ARTIFICIAL NEURAL NETWORK; ATMOSPHERE-OCEAN COUPLING; BACK PROPAGATION; DECADAL VARIATION; EL NINO-SOUTHERN OSCILLATION; FORECASTING METHOD; LEAST SQUARES METHOD; MULTIPLE REGRESSION; NORTH ATLANTIC OSCILLATION; PACIFIC DECADAL OSCILLATION; STREAMFLOW; WATER RESOURCE;

CHINA; KAIDU BASIN; XINJIANG UYGUR;

EID: 84881328588     PISSN: 10840699     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)HE.1943-5584.0000707     Document Type: Article

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