Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas

Water Resources Research

Volumn 47, Issue 12, 2011, Pages

  Frey, M P ^a,b   Stamm, C ^a   Schneider, M K ^c   Reichert, P ^a,b  

^a SWISS FEDERAL INSTITUTE OF AQUATIC SCIENCE AND TECHNOLOGY   (Switzerland)

^b ETH ZURICH   (Switzerland)

^c AGROSCOPE RECKENHOLZ TÄNIKON RESEARCH STATION ART   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

AGRICULTURAL CATCHMENTS; AUTOREGRESSIVE ERROR MODEL; BAYESIAN INFERENCE; BAYESIAN UPDATING; DISTRIBUTED EFFECTS; DISTRIBUTED HYDROLOGICAL MODEL; HYDROLOGICAL DATA; HYDROLOGICAL MODELS; INPUT DATAS; INTEGRATED DATA; ITERATIVE PROCEDURES; LEARNING PROCESS; LOCAL DATA; LOCAL MEASUREMENT; LOWER BOUNDARY; MARGINAL DISTRIBUTION; MODEL MODIFICATION; MODEL PARAMETERS; MODEL TESTING; PERCOLATION RATES; PRIOR KNOWLEDGE; PRIOR PARAMETER DISTRIBUTION; RESIDUAL ANALYSIS; SOIL HYDRAULIC PARAMETERS; SOURCE AREA; SPATIAL DATA; SPATIAL PREDICTION; SWITZERLAND;

AGRICULTURAL RUNOFF; BAYESIAN NETWORKS; CATCHMENTS; CLIMATE MODELS; FORECASTING; HERBICIDES; INFERENCE ENGINES; SOLVENTS; SPATIAL DISTRIBUTION; STATISTICAL TESTS; UNCERTAINTY ANALYSIS; WEED CONTROL;

DATA REDUCTION;

AGRICULTURAL PRACTICE; BAYESIAN ANALYSIS; CATCHMENT; DATA SET; DISCHARGE; ERROR ANALYSIS; HERBICIDE; HYDROLOGICAL MODELING; MEASUREMENT METHOD; POLLUTION EFFECT; RUNOFF; SOIL WATER; UNCERTAINTY ANALYSIS;

SWITZERLAND;

EID: 84855397565     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2010WR009993     Document Type: Article

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