Journal article
Development of a Maximum Entropy-Archimedean Copula-Based Bayesian Network Method for Streamflow Frequency Analysis—A Case Study of the Kaidu River Basin, China
Abstract
Frequency analysis of streamflow is critical for water-resources system planning, water conservancy projects and the mitigation of hydrological extremes events. In this study, a maximum entropy-Archimedean copula-based Bayesian network (MECBN) method has been proposed for frequency analysis of monthly streamflow in the Kaidu River Basin, which integrates the maximum entropy-Archimedean copula (MEAC) and Bayesian network methods into a general …
Authors
Kong X; Zeng X; Chen C; Fan Y; Huang G; Li Y; Wang C
Journal
Water, Vol. 11, No. 1,
Publisher
MDPI
DOI
10.3390/w11010042
ISSN
2073-4441