Copula-based method for multisite monthly and daily streamflow simulation
•We proposed a method for multisite monthly and daily streamflow simulation.•The Colorado River and the upper Yangtze River were selected as case studies.•The generated data can capture the properties of the single site.•The generated data can preserve the spatial correlation at different locations....
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Veröffentlicht in: | Journal of hydrology (Amsterdam) 2015-09, Vol.528, p.369-384 |
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container_title | Journal of hydrology (Amsterdam) |
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creator | Chen, Lu Singh, Vijay P. Guo, Shenglian Zhou, Jianzhong Zhang, Junhong |
description | •We proposed a method for multisite monthly and daily streamflow simulation.•The Colorado River and the upper Yangtze River were selected as case studies.•The generated data can capture the properties of the single site.•The generated data can preserve the spatial correlation at different locations.
Multisite stochastic simulation of streamflow sequences is needed for water resources planning and management. In this study, a new copula-based method 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). Monthly or daily streamflows at multiple sites are then generated by sampling from the conditional copula. Three tributaries of Colorado River and the upper Yangtze River are selected to evaluate the proposed methodology. Results show that the generated data at both higher and lower time scales can capture the distribution properties of the single site and preserve the spatial correlation of streamflows at different locations. The main advantage of the method is that the trivairate copula can be established using three bivariate copulas and the model parameters can be easily estimated using the Kendall tau rank correlation coefficient, which makes it possible to generate daily streamflow data. The method provides a new tool for multisite stochastic simulation. |
doi_str_mv | 10.1016/j.jhydrol.2015.05.018 |
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Multisite stochastic simulation of streamflow sequences is needed for water resources planning and management. In this study, a new copula-based method 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). Monthly or daily streamflows at multiple sites are then generated by sampling from the conditional copula. Three tributaries of Colorado River and the upper Yangtze River are selected to evaluate the proposed methodology. Results show that the generated data at both higher and lower time scales can capture the distribution properties of the single site and preserve the spatial correlation of streamflows at different locations. The main advantage of the method is that the trivairate copula can be established using three bivariate copulas and the model parameters can be easily estimated using the Kendall tau rank correlation coefficient, which makes it possible to generate daily streamflow data. The method provides a new tool for multisite stochastic simulation.</description><identifier>ISSN: 0022-1694</identifier><identifier>EISSN: 1879-2707</identifier><identifier>DOI: 10.1016/j.jhydrol.2015.05.018</identifier><language>eng</language><publisher>Elsevier B.V</publisher><subject>Copula function ; Daily streamflow ; Hydrology ; Monthly streamflow ; Multisite stochastic simulation ; Preserves ; Resource management ; Sampling ; Simulation ; Stochasticity ; Water runoff</subject><ispartof>Journal of hydrology (Amsterdam), 2015-09, Vol.528, p.369-384</ispartof><rights>2015</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a398t-46ab9ba237da8d3a5bc7ded87add5bbaeec8fb1bb5923e3449cf82b8cca0428c3</citedby><cites>FETCH-LOGICAL-a398t-46ab9ba237da8d3a5bc7ded87add5bbaeec8fb1bb5923e3449cf82b8cca0428c3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jhydrol.2015.05.018$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,27924,27925,45995</link.rule.ids></links><search><creatorcontrib>Chen, Lu</creatorcontrib><creatorcontrib>Singh, Vijay P.</creatorcontrib><creatorcontrib>Guo, Shenglian</creatorcontrib><creatorcontrib>Zhou, Jianzhong</creatorcontrib><creatorcontrib>Zhang, Junhong</creatorcontrib><title>Copula-based method for multisite monthly and daily streamflow simulation</title><title>Journal of hydrology (Amsterdam)</title><description>•We proposed a method for multisite monthly and daily streamflow simulation.•The Colorado River and the upper Yangtze River were selected as case studies.•The generated data can capture the properties of the single site.•The generated data can preserve the spatial correlation at different locations.
Multisite stochastic simulation of streamflow sequences is needed for water resources planning and management. In this study, a new copula-based method 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). Monthly or daily streamflows at multiple sites are then generated by sampling from the conditional copula. Three tributaries of Colorado River and the upper Yangtze River are selected to evaluate the proposed methodology. Results show that the generated data at both higher and lower time scales can capture the distribution properties of the single site and preserve the spatial correlation of streamflows at different locations. The main advantage of the method is that the trivairate copula can be established using three bivariate copulas and the model parameters can be easily estimated using the Kendall tau rank correlation coefficient, which makes it possible to generate daily streamflow data. The method provides a new tool for multisite stochastic simulation.</description><subject>Copula function</subject><subject>Daily streamflow</subject><subject>Hydrology</subject><subject>Monthly streamflow</subject><subject>Multisite stochastic simulation</subject><subject>Preserves</subject><subject>Resource management</subject><subject>Sampling</subject><subject>Simulation</subject><subject>Stochasticity</subject><subject>Water runoff</subject><issn>0022-1694</issn><issn>1879-2707</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkM1LAzEQxYMoWKt_grBHL1vztbvZk0jxo1DwoucwSWZpyu6mJqnS_94t9a7Dg5nDew_mR8gtowtGWX2_XWw3BxdDv-CUVQs6iakzMmOqaUve0OaczCjlvGR1Ky_JVUpbOo0QckZWy7Db91AaSOiKAfMmuKILsRj2ffbJZyyGMOZNfyhgdIUDP10pR4Sh68N3kfxkhOzDeE0uOugT3vzuOfl4fnpfvpbrt5fV8nFdgmhVLmUNpjXAReNAOQGVsY1DpxpwrjIGEK3qDDOmarlAIWVrO8WNshao5MqKObk79e5i-NxjynrwyWLfw4hhnzRrGkWlVJz_wypr1dZiYjEn1clqY0gpYqd30Q8QD5pRfaSst_qXsj5S1nQSU1Pu4ZTD6eUvj1En63G06HxEm7UL_o-GH_8JitY</recordid><startdate>201509</startdate><enddate>201509</enddate><creator>Chen, Lu</creator><creator>Singh, Vijay P.</creator><creator>Guo, Shenglian</creator><creator>Zhou, Jianzhong</creator><creator>Zhang, Junhong</creator><general>Elsevier B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7QH</scope><scope>7ST</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>8FD</scope><scope>FR3</scope><scope>KR7</scope></search><sort><creationdate>201509</creationdate><title>Copula-based method for multisite monthly and daily streamflow simulation</title><author>Chen, Lu ; Singh, Vijay P. ; Guo, Shenglian ; Zhou, Jianzhong ; Zhang, Junhong</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a398t-46ab9ba237da8d3a5bc7ded87add5bbaeec8fb1bb5923e3449cf82b8cca0428c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Copula function</topic><topic>Daily streamflow</topic><topic>Hydrology</topic><topic>Monthly streamflow</topic><topic>Multisite stochastic simulation</topic><topic>Preserves</topic><topic>Resource management</topic><topic>Sampling</topic><topic>Simulation</topic><topic>Stochasticity</topic><topic>Water runoff</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Lu</creatorcontrib><creatorcontrib>Singh, Vijay P.</creatorcontrib><creatorcontrib>Guo, Shenglian</creatorcontrib><creatorcontrib>Zhou, Jianzhong</creatorcontrib><creatorcontrib>Zhang, Junhong</creatorcontrib><collection>CrossRef</collection><collection>Aqualine</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Civil Engineering Abstracts</collection><jtitle>Journal of hydrology (Amsterdam)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Lu</au><au>Singh, Vijay P.</au><au>Guo, Shenglian</au><au>Zhou, Jianzhong</au><au>Zhang, Junhong</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Copula-based method for multisite monthly and daily streamflow simulation</atitle><jtitle>Journal of hydrology (Amsterdam)</jtitle><date>2015-09</date><risdate>2015</risdate><volume>528</volume><spage>369</spage><epage>384</epage><pages>369-384</pages><issn>0022-1694</issn><eissn>1879-2707</eissn><abstract>•We proposed a method for multisite monthly and daily streamflow simulation.•The Colorado River and the upper Yangtze River were selected as case studies.•The generated data can capture the properties of the single site.•The generated data can preserve the spatial correlation at different locations.
Multisite stochastic simulation of streamflow sequences is needed for water resources planning and management. In this study, a new copula-based method 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). Monthly or daily streamflows at multiple sites are then generated by sampling from the conditional copula. Three tributaries of Colorado River and the upper Yangtze River are selected to evaluate the proposed methodology. Results show that the generated data at both higher and lower time scales can capture the distribution properties of the single site and preserve the spatial correlation of streamflows at different locations. The main advantage of the method is that the trivairate copula can be established using three bivariate copulas and the model parameters can be easily estimated using the Kendall tau rank correlation coefficient, which makes it possible to generate daily streamflow data. The method provides a new tool for multisite stochastic simulation.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.jhydrol.2015.05.018</doi><tpages>16</tpages></addata></record> |
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subjects | Copula function Daily streamflow Hydrology Monthly streamflow Multisite stochastic simulation Preserves Resource management Sampling Simulation Stochasticity Water runoff |
title | Copula-based method for multisite monthly and daily streamflow simulation |
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