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Inference to shape parameter of Nash model based on dynamic transport properties of channel networks

This study investigates the relations between the shape of hydrologic responses and the dynamic transport properties of channel networks within the framework of random walks on fractal networks, focusing on the shape parameter of Nash model. To this end, we evaluate the static fractal structures and...

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Detalles Bibliográficos
Autores principales: Kim, Joo-Cheol, Yoon, Yeo-Jin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640972/
https://www.ncbi.nlm.nih.gov/pubmed/36387531
http://dx.doi.org/10.1016/j.heliyon.2022.e11320
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author Kim, Joo-Cheol
Yoon, Yeo-Jin
author_facet Kim, Joo-Cheol
Yoon, Yeo-Jin
author_sort Kim, Joo-Cheol
collection PubMed
description This study investigates the relations between the shape of hydrologic responses and the dynamic transport properties of channel networks within the framework of random walks on fractal networks, focusing on the shape parameter of Nash model. To this end, we evaluate the static fractal structures and the dynamic transport properties of various channel networks and, then, validate Liu's conjecture (1992) for the shape of hydrologic responses. In the context of random walks on fractal networks, the fractal dimensions of channel networks can directly connect the static structure to the dynamic transport properties of channel networks through Horton's law of drainage composition. It is observed that the peak coordinates of hydrologic responses would have a more intimate relation to the connectivity of channel networks than the conductivity of those. The characteristic times of hydrologic responses also tend to be related to the connectivity of channel networks. Thereby, the shape of hydrologic responses would be expected directly affected by the fractal dimension of channel networks in terms of their static structure, while interpreted a combined result of the conductivity and the connectivity of channel networks in terms of their dynamic transport properties. So, the runoff hydrographs of a river basin could be considered shaped by the fractal dimensions of its channel networks following the linear hydrologic system theory.
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spelling pubmed-96409722022-11-15 Inference to shape parameter of Nash model based on dynamic transport properties of channel networks Kim, Joo-Cheol Yoon, Yeo-Jin Heliyon Research Article This study investigates the relations between the shape of hydrologic responses and the dynamic transport properties of channel networks within the framework of random walks on fractal networks, focusing on the shape parameter of Nash model. To this end, we evaluate the static fractal structures and the dynamic transport properties of various channel networks and, then, validate Liu's conjecture (1992) for the shape of hydrologic responses. In the context of random walks on fractal networks, the fractal dimensions of channel networks can directly connect the static structure to the dynamic transport properties of channel networks through Horton's law of drainage composition. It is observed that the peak coordinates of hydrologic responses would have a more intimate relation to the connectivity of channel networks than the conductivity of those. The characteristic times of hydrologic responses also tend to be related to the connectivity of channel networks. Thereby, the shape of hydrologic responses would be expected directly affected by the fractal dimension of channel networks in terms of their static structure, while interpreted a combined result of the conductivity and the connectivity of channel networks in terms of their dynamic transport properties. So, the runoff hydrographs of a river basin could be considered shaped by the fractal dimensions of its channel networks following the linear hydrologic system theory. Elsevier 2022-10-31 /pmc/articles/PMC9640972/ /pubmed/36387531 http://dx.doi.org/10.1016/j.heliyon.2022.e11320 Text en © 2022 The Author(s) https://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 Research Article
Kim, Joo-Cheol
Yoon, Yeo-Jin
Inference to shape parameter of Nash model based on dynamic transport properties of channel networks
title Inference to shape parameter of Nash model based on dynamic transport properties of channel networks
title_full Inference to shape parameter of Nash model based on dynamic transport properties of channel networks
title_fullStr Inference to shape parameter of Nash model based on dynamic transport properties of channel networks
title_full_unstemmed Inference to shape parameter of Nash model based on dynamic transport properties of channel networks
title_short Inference to shape parameter of Nash model based on dynamic transport properties of channel networks
title_sort inference to shape parameter of nash model based on dynamic transport properties of channel networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9640972/
https://www.ncbi.nlm.nih.gov/pubmed/36387531
http://dx.doi.org/10.1016/j.heliyon.2022.e11320
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