Cargando…

Research on the Longitudinal Section of River Restoration Using Probabilistic Theory

Since the 1960s, many rivers have been destroyed as a consequence of the process of rapid urbanization. As accurate figures are important to repair rivers, there have been many research reports on methods to obtain the exact river slope and elevation. Until now, many research efforts have analyzed t...

Descripción completa

Detalles Bibliográficos
Autores principales: Choo, Yeon-Moon, Kim, Ji-Min, An, Ik-Tae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391294/
https://www.ncbi.nlm.nih.gov/pubmed/34441105
http://dx.doi.org/10.3390/e23080965
_version_ 1783743241219211264
author Choo, Yeon-Moon
Kim, Ji-Min
An, Ik-Tae
author_facet Choo, Yeon-Moon
Kim, Ji-Min
An, Ik-Tae
author_sort Choo, Yeon-Moon
collection PubMed
description Since the 1960s, many rivers have been destroyed as a consequence of the process of rapid urbanization. As accurate figures are important to repair rivers, there have been many research reports on methods to obtain the exact river slope and elevation. Until now, many research efforts have analyzed the river using measured river topographic factors, but when the flow velocity changes rapidly, such as during a flood, surveying is not easy; and due to cost, frequent measurements are difficult. Previous research has focused on the cross section of the river, so the information on the river longitudinal profile is insufficient. In this research, using informational entropy theory, equations are presented that can calculate the average river slope, river slope, and river longitudinal elevation for a river basin in real time. The applicability was analyzed through a comparison with the measured data of river characteristic factors obtained from the river plan. The parameters were calculated using informational entropy theory and nonlinear regression analysis using actual data, and then the longitudinal elevation entropy equation for each river and the average river slope were calculated. As a result of analyzing the applicability of the equations presented in this study by R(2) and Root Mean Square Error, all R(2) values were over 0.80, while RMSE values were analyzed to be between 0.54 and 2.79. Valid results can be obtained by calculating river characteristic factors.
format Online
Article
Text
id pubmed-8391294
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-83912942021-08-28 Research on the Longitudinal Section of River Restoration Using Probabilistic Theory Choo, Yeon-Moon Kim, Ji-Min An, Ik-Tae Entropy (Basel) Article Since the 1960s, many rivers have been destroyed as a consequence of the process of rapid urbanization. As accurate figures are important to repair rivers, there have been many research reports on methods to obtain the exact river slope and elevation. Until now, many research efforts have analyzed the river using measured river topographic factors, but when the flow velocity changes rapidly, such as during a flood, surveying is not easy; and due to cost, frequent measurements are difficult. Previous research has focused on the cross section of the river, so the information on the river longitudinal profile is insufficient. In this research, using informational entropy theory, equations are presented that can calculate the average river slope, river slope, and river longitudinal elevation for a river basin in real time. The applicability was analyzed through a comparison with the measured data of river characteristic factors obtained from the river plan. The parameters were calculated using informational entropy theory and nonlinear regression analysis using actual data, and then the longitudinal elevation entropy equation for each river and the average river slope were calculated. As a result of analyzing the applicability of the equations presented in this study by R(2) and Root Mean Square Error, all R(2) values were over 0.80, while RMSE values were analyzed to be between 0.54 and 2.79. Valid results can be obtained by calculating river characteristic factors. MDPI 2021-07-27 /pmc/articles/PMC8391294/ /pubmed/34441105 http://dx.doi.org/10.3390/e23080965 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Choo, Yeon-Moon
Kim, Ji-Min
An, Ik-Tae
Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
title Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
title_full Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
title_fullStr Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
title_full_unstemmed Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
title_short Research on the Longitudinal Section of River Restoration Using Probabilistic Theory
title_sort research on the longitudinal section of river restoration using probabilistic theory
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8391294/
https://www.ncbi.nlm.nih.gov/pubmed/34441105
http://dx.doi.org/10.3390/e23080965
work_keys_str_mv AT chooyeonmoon researchonthelongitudinalsectionofriverrestorationusingprobabilistictheory
AT kimjimin researchonthelongitudinalsectionofriverrestorationusingprobabilistictheory
AT aniktae researchonthelongitudinalsectionofriverrestorationusingprobabilistictheory