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Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation

The dataset contains reservoir characteristic parameters, streamflow series of reservoirs in the upper Yangtze River, the standard operating rules (SORs) and the seasonal top of buffer pools (seasonal TBPs) for these reservoirs, which were provided by the Yangtze River Commission. Moreover, annual h...

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Detalles Bibliográficos
Autores principales: He, Shaokun, Guo, Shenglian, Chen, Kebing, Deng, Lele, Liao, Zhen, Xiong, Feng, Yin, Jiabo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736769/
https://www.ncbi.nlm.nih.gov/pubmed/31516958
http://dx.doi.org/10.1016/j.dib.2019.104440
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author He, Shaokun
Guo, Shenglian
Chen, Kebing
Deng, Lele
Liao, Zhen
Xiong, Feng
Yin, Jiabo
author_facet He, Shaokun
Guo, Shenglian
Chen, Kebing
Deng, Lele
Liao, Zhen
Xiong, Feng
Yin, Jiabo
author_sort He, Shaokun
collection PubMed
description The dataset contains reservoir characteristic parameters, streamflow series of reservoirs in the upper Yangtze River, the standard operating rules (SORs) and the seasonal top of buffer pools (seasonal TBPs) for these reservoirs, which were provided by the Yangtze River Commission. Moreover, annual hydropower of these reservoirs is tested to evaluate operation performance. These research materials are related to the research article in Advances in Water Resources, entitled ‘Optimal impoundment operation for cascade reservoirs coupling parallel dynamic programming with importance sampling and successive approximation’ (He et al., 2019). The dataset could be used to derive optimal operating rules to explore the potential benefits of water resources via our proposed algorithm (importance sampling – parallel dynamic programming, IS-PDP) in different runoff scenarios. It can also be further applied for water resources management and other potential users.
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spelling pubmed-67367692019-09-12 Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation He, Shaokun Guo, Shenglian Chen, Kebing Deng, Lele Liao, Zhen Xiong, Feng Yin, Jiabo Data Brief Environmental Science The dataset contains reservoir characteristic parameters, streamflow series of reservoirs in the upper Yangtze River, the standard operating rules (SORs) and the seasonal top of buffer pools (seasonal TBPs) for these reservoirs, which were provided by the Yangtze River Commission. Moreover, annual hydropower of these reservoirs is tested to evaluate operation performance. These research materials are related to the research article in Advances in Water Resources, entitled ‘Optimal impoundment operation for cascade reservoirs coupling parallel dynamic programming with importance sampling and successive approximation’ (He et al., 2019). The dataset could be used to derive optimal operating rules to explore the potential benefits of water resources via our proposed algorithm (importance sampling – parallel dynamic programming, IS-PDP) in different runoff scenarios. It can also be further applied for water resources management and other potential users. Elsevier 2019-08-28 /pmc/articles/PMC6736769/ /pubmed/31516958 http://dx.doi.org/10.1016/j.dib.2019.104440 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Environmental Science
He, Shaokun
Guo, Shenglian
Chen, Kebing
Deng, Lele
Liao, Zhen
Xiong, Feng
Yin, Jiabo
Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
title Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
title_full Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
title_fullStr Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
title_full_unstemmed Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
title_short Dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
title_sort dataset for reservoir impoundment operation coupling parallel dynamic programming with importance sampling and successive approximation
topic Environmental Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6736769/
https://www.ncbi.nlm.nih.gov/pubmed/31516958
http://dx.doi.org/10.1016/j.dib.2019.104440
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