Impact of Distribution Type in Bayes Probability Flood Forecasting-Reference-Cited by-同舟云学术

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Impact of Distribution Type in Bayes Probability Flood Forecasting

Published:2017-01-21 Issue:3 Volume:31 Page:961-977
ISSN:0920-4741
Container-title:Water Resources Management
language:en
Short-container-title:Water Resour Manage

Author:

Li Wei,Zhou Jianzhong,Sun Huaiwei,Feng Kuaile,Zhang Hairong,Tayyab Muhammad

Funder

the National Natural Science Foundation of China

the State Key Program of National Natural Science of China

Fundamental Research Funds for the Central Universities, HUST

Publisher

Springer Science and Business Media LLC

Subject

Water Science and Technology,Civil and Structural Engineering

Link

http://link.springer.com/content/pdf/10.1007/s11269-016-1557-6.pdf

Reference53 articles.

1. Alemu ET, Palmer RN, Polebitski A, Meaker B (2010) Decision support system for optimizing reservoir operations using ensemble streamflow predictions. J Water Resour Plan Manag 137:72–82

2. Araghinejad S (2011) An approach for probabilistic hydrological drought forecasting. Water Resour Manag 25:191–200. doi: 10.1007/s11269-010-9694-9

3. Arsenault R, Latraverse M, Duchesne T (2016) DD. An efficient method to correct under-dispersion in ensemble streamflow prediction of inflow volumes for reservoir optimization. Water Resour Manag 30(12):4363–4380

4. Asefa T (2009) Ensemble streamflow forecast: a GLUE-based neural network Approach1. J Am Water Resour Assoc 45:1155–1163

5. Binley AM, Beven KJ, Calver A, Watts L (1991) Changing responses in hydrology: assessing the uncertainty in physically based model predictions. Water Resour Res 27:1253–1261

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