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Titlebook: Copulas and Its Application in Hydrology and Water Resources; Lu Chen,Shenglian Guo Book 2019 Springer Nature Singapore Pte Ltd. 2019 Copu

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書目名稱Copulas and Its Application in Hydrology and Water Resources
編輯Lu Chen,Shenglian Guo
視頻videohttp://file.papertrans.cn/239/238186/238186.mp4
概述Shares the latest studies on the concept and methods of copulas for multivariate hydrological analysis.Enriches readers’ understanding of determining the input for artificial neural networks for flood
叢書名稱Springer Water
圖書封面Titlebook: Copulas and Its Application in Hydrology and Water Resources;  Lu Chen,Shenglian Guo Book 2019 Springer Nature Singapore Pte Ltd. 2019 Copu
描述This book presents an overview of copula theory and its application in hydrology, and provides valuable insights, useful methods and practical applications for multivariate hydrological analysis using copulas. In addition, it extends the traditional bivariate model to trivariate or multivariate models. The specific applications covered include the study of flood frequency analysis, drought frequency analysis, dependence analysis, flood coincidence risk analysis and statistical simulation using copulas. The book offers a valuable guide for researchers, scientists and engineers working in hydrology and water resources, and will also benefit graduate or doctoral students with a basic grasp of copula functions who want to learn about the latest research developments in the field.
出版日期Book 2019
關(guān)鍵詞Copula theory; Application in hydrology and water resources; Hydrological frequency analysis; Risk anal
版次1
doihttps://doi.org/10.1007/978-981-13-0574-0
isbn_softcover978-981-13-4454-1
isbn_ebook978-981-13-0574-0Series ISSN 2364-6934 Series E-ISSN 2364-8198
issn_series 2364-6934
copyrightSpringer Nature Singapore Pte Ltd. 2019
The information of publication is updating

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Copula-Based Method for Multisite Monthly and Daily Streamflow Simulation,d is proposed for generating long-term multisite monthly and daily streamflow data. A multivariate copula, which is established based on bivariate copulas and conditional probability distributions, is employed to describe temporal dependences (single site) and spatial dependences (between sites). Mo
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Uncertainty Analysis of Hydrologic Forecasts Based on Copulas,ion. The results show that the copula-based HUP is comparable to the meta-Gaussian HUP regarding the posterior median forecasts. Besides, the probabilistic forecasts produced by the copula-based HUP have slightly higher reliability and lower resolution, as compared to those of the meta-Gaussian HUP.
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Correlations Among Rivers Using Copula Entropy, concept of total correlation, computed by the copula entropy method, is applied to measuring the dependence. This method only needs to calculate the copula entropy instead of the marginal or joint entropy, which estimates the total correlation more directly and avoids the accumulation of systematic
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