Utilization of the Bayesian Method to Improve Hydrological Drought Prediction Accuracy
Author:
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
http://link.springer.com/article/10.1007/s11269-017-1682-x/fulltext.html
Reference26 articles.
1. Coelho CAS, Pezzulli S, Balmaseda M, Doblas-Reyes FJ, Stephenson DB (2004) Forecast calibration and combination: a simple Bayesian approach for ENSO. J Clim 17:1504–1516
2. Fang L, Qing-Cun Z, Chao-Fan L (2009) A Bayesian scheme for probabilistic multi-model ensemble prediction of summer rainfall over the Yangtze River valley. Atmos Oceanic Sci Lett 2:314–319
3. Gelman A (2003) A Bayesian formulation of exploratory data analysis and goodness-of-fit testing. Int Stat Rev 71:369–382
4. Gobena AK, Gan TY (2010) Incorporation of seasonal climate forecasts in the ensemble streamflow prediction system. J Hydrol 385:336–352
5. Hosking JRM, Wallis JR (1993) Some statistics useful in regional frequency analysis. Water Resour Res 29:271–281
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