High-dimensional posterior exploration of hydrologic models using multiple-try DREAM (ZS) and high-performance computing

Water Resources Research

Volumn 48, Issue 1, 2012, Pages

  Laloy, Eric ^a   Vrugt, Jasper A ^a,b  

^a University of California at Irvine   (United States)

^b UNIVERSITY OF AMSTERDAM   (Netherlands)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN INFERENCE; COMPLEX MODEL; CURRENT GENERATION; DETAILED BALANCE; DIFFERENTIAL EVOLUTION; DISTRIBUTED HYDROLOGIC MODEL; EXCELLENT PERFORMANCE; GROUND WATER RECHARGE; HIGH-DIMENSIONAL; HIGH-PERFORMANCE COMPUTING; HISTORICAL RECORDS; HYDROLOGIC MODELS; MARKOV CHAIN MONTE CARLO ALGORITHMS; MCMC APPROACH; MULTIMODAL SEARCH; OPTIMIZATION ALGORITHMS; PERFORMANCE IMPROVEMENTS; POSTERIOR DISTRIBUTIONS; POSTERIOR PROBABILITY; PREDICTIVE UNCERTAINTY; PROPOSAL DISTRIBUTION; RIVER DISCHARGE; SEARCH PROBLEM; SURFACE RUNOFFS;

BAYESIAN NETWORKS; COMPUTER SOFTWARE SELECTION AND EVALUATION; EVOLUTIONARY ALGORITHMS; GEOLOGIC MODELS; GROUNDWATER; INFERENCE ENGINES; MARKOV PROCESSES; MATHEMATICAL MODELS; PROBABILITY DENSITY FUNCTION; SOIL MOISTURE; TARGET TRACKING;

PARAMETER ESTIMATION;

BAYESIAN ANALYSIS; MARKOV CHAIN; MONTE CARLO ANALYSIS; OPTIMIZATION; PERFORMANCE ASSESSMENT; RECHARGE; RIVER DISCHARGE; RUNOFF; SOIL MOISTURE;

EID: 84856263454     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2011WR010608     Document Type: Article

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