Hybrid model for daily runoff interval predictions based on Bayesian inference-Reference-Cited by-同舟云学术

Hybrid model for daily runoff interval predictions based on Bayesian inference

Published:2022-12-02 Issue:1 Volume:68 Page:62-75
ISSN:0262-6667
Container-title:Hydrological Sciences Journal
language:en
Short-container-title:Hydrological Sciences Journal

Author:

Xu Hanbing¹²,Song Songbai¹²,Li Jun¹²,Guo Tianli¹²

Affiliation:

1. College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, China

2. Key Laboratory of Agricultural Soil and Water Engineering in Arid and Semiarid Areas, Ministry of Education, Northwest A&F University, Yangling, China

Funder

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Water Science and Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/02626667.2022.2145201

Reference50 articles.

1. A new approach for simulating and forecasting the rainfall-runoff process within the next two months

2. Daily runoff forecasting based on data-augmented neural network model

3. Influent Forecasting for Wastewater Treatment Plants in North America

4. Prediction of contamination potential of groundwater arsenic in Cambodia, Laos, and Thailand using artificial neural network

5. Bayesian calibration of building energy models with large datasets

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