Assessing Hydrologic Uncertainty Processor Performance for Flood Forecasting in a Semiurban Watershed-Reference-Cited by-同舟云学术

Assessing Hydrologic Uncertainty Processor Performance for Flood Forecasting in a Semiurban Watershed

Published:2019-09 Issue:9 Volume:24 Page:05019025
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Han Shasha¹,Coulibaly Paulin²,Biondi Daniela³

Affiliation:

1. Ph.D. Candidate, Dept. of Civil Engineering, McMaster Univ., 1280 Main St. West, Hamilton, ON, Canada L8S 4L7 (corresponding author).

2. Professor, Jointly in School of Geography and Earth Sciences, Dept. of Civil Engineering, McMaster Univ., 1280 Main St. West, Hamilton, ON, Canada L8S 4L7.

3. Associate Professor, Dept. of Informatics, Modelling, Electronics and Systems Engineering, Univ. of Calabria, Via Pietro Bucci, Arcavacata Rende, Cosenza 87036, Italy.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0001828

Reference62 articles.

1. Grey neural networks for river stage forecasting with uncertainty

2. Choice between competitive pairs of frequency models for use in hydrology: a review and some new results

3. A Bayesian approach for real-time flood forecasting

4. Performance assessment of a Bayesian Forecasting System (BFS) for real-time flood forecasting

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