Mid- and long-term runoff predictions by an improved phase-space reconstruction model-Reference-Cited by-同舟云学术

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Mid- and long-term runoff predictions by an improved phase-space reconstruction model

Published:2016-07 Issue: Volume:148 Page:560-573
ISSN:0013-9351
Container-title:Environmental Research
language:en
Short-container-title:Environmental Research

Author:

Hong Mei,Wang Dong,Wang Yuankun,Zeng Xiankui,Ge Shanshan,Yan Hengqian,Singh Vijay P.

Funder

Chinese National Natural Science Fund

Chinese National Natural Science Fund for young scholars

Chinese National Natural Science Fund of Jiangsu Province

Program for New Century Excellent Talents in University

China Doctoral Program of Higher Education

Qing Lan Project

Nanjing University

Publisher

Elsevier BV

Subject

General Environmental Science,Biochemistry

Reference80 articles.

1. A multi-model approach for long-term runoff modeling using rainfall forecasts;Alexandre G.;Expert Syst. Appl.,2012

2. Rainfall–runoff modelling using artificial neural networks technique: a Blue Nile catchment case study;Antar;Hydrol. Process.,2011

3. Neural networks for real time catchment flow modeling and prediction;Aquil;Water Resources Manag.,2007

4. The effect of climate change on hydrological regime in Europe: a continental perspective;Arnell;Global Environ. Change,1999

5. The future of distributed models: model calibration and uncertainty prediction;Beven;Hydrol. Processes,1992

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