An evaluation of statistical, NMME and hybrid models for drought prediction in China-Reference-Cited by-同舟云学术

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An evaluation of statistical, NMME and hybrid models for drought prediction in China

Published:2018-11 Issue: Volume:566 Page:235-249
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Xu Lei,Chen Nengcheng^ORCID,Zhang Xiang,Chen Zeqiang

Funder

Union Foundation of Ministry of Education of the People’s Republic of China

Creative Research Groups of Natural Science Foundation of Hubei Province of China

Fundamental Research Funds for the Central Universities

National Nature Science Foundation of China

Nature Science Foundation of Hubei Province

China Meteorological Administration Drought Research Fund

China Postdoctoral Science Foundation

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference87 articles.

1. Extended contingency table: performance metrics for satellite observations and climate model simulations;AghaKouchak;Water Resour. Res.,2013

2. A baseline probabilistic drought forecasting framework using standardized soil moisture index: application to the 2012 United States drought;AghaKouchak;Hydrol. Earth Syst. Sci.,2014

3. A multivariate approach for persistence-based drought prediction: application to the 2010–2011 East Africa drought;AghaKouchak;J. Hydrol.,2015

4. Daily reservoir inflow forecasting using multiscale deep feature learning with hybrid models;Bai;J. Hydrol.,2016

5. Deterministic skill of ENSO predictions from the North American Multimodel Ensemble;Barnston;Clim. Dyn.,2016

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