A probabilistic drought forecasting framework: A combined dynamical and statistical approach

Journal of Hydrology

Volumn 548, Issue , 2017, Pages 291-304

  Yan, Hongxiang ^a   Moradkhani, Hamid ^b   Zarekarizi, Mahkameh ^b  

^a PACIFIC NORTHWEST NATIONAL LABORATORY   (United States)

^b PORTLAND STATE UNIVERSITY   (United States)

Author keywords

Data assimilation; Initial condition uncertainty; Particle Markov chain Monte Carlo; Probabilistic drought forecasting

Indexed keywords

MARKOV CHAINS; MONTE CARLO METHODS; WEATHER FORECASTING;

DATA ASSIMILATION; FORECASTING MODELING; INITIAL CONDITION UNCERTAINTIES; LAND SURFACE MODELING; MONTE CARLO ENSEMBLE; PARTICLE MARKOV CHAIN MONTE CARLO; STATISTICAL APPROACH; STATISTICAL MODELING;

DROUGHT;

DATA ASSIMILATION; DROUGHT; FORECASTING METHOD; HYDROLOGICAL MODELING; LAND SURFACE; MARKOV CHAIN; PROBABILITY; STATISTICAL ANALYSIS; UNCERTAINTY ANALYSIS;

COLUMBIA BASIN; PACIFIC NORTHWEST; UNITED STATES;

EID: 85015396043     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2017.03.004     Document Type: Article

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