Development of the GeoCRP for Smart River Management in the Smart City(I)

Bonhyun Koo; Seunguk Oh; Jaseob Koo; Kyucheoul Shim

doi:doi:10.11648/j.wros.20211005.17

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Development of the GeoCRP for Smart River Management in the Smart City(I)

Bonhyun Koo, Seunguk Oh, Jaseob Koo, Kyucheoul Shim

Published in Journal of Water Resources and Ocean Science (Volume 10, Issue 5)

Received: 7 October 2021 Accepted: 25 October 2021 Published: 30 October 2021

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Abstract

In this study, we developed the Geo City River Platform (GeoCRP), which regularly collects data on the web and provides the analyzed information by performing flood analysis based on the collected information in order to effectively perform smart city river management. GeoCRP was analyzed and tested in the Eco Delta City (EDC) area. In this platform, a watershed runoff analysis model, a river flow analysis model and an urban runoff analysis model were applied for flood analysis in EDC. GeoCRP can obtain more reliable results by taking a step-by-step approach to urban overflow that may occur in smart cities through the applied model. In addition, since all analysis processes such as data collection, input data generation and result data storage are automatically performed on the web, analysis can be performed, and results can be viewed if an environment that can access the web is established without special equipment or tools. The displayed analysis result is provided visually so that the user can intuitively confirm the information, so it is easy to understand the analysis results. Through this, smart city managers can effectively manage rivers, and it is expected that educational institutions will be able to use it as educational material on urban runoff.

Published in	Journal of Water Resources and Ocean Science (Volume 10, Issue 5)
DOI	10.11648/j.wros.20211005.17
Page(s)	145-155
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

Watershed Runoff, River Flow Runoff, Urban Runoff, Flood Analysis

References

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[2]	Federal Emergency Management Agency (FEMA) and Harris County Flood Control District (HCFCD) (2002). Off the charts T. S. allison public report. Harris County Flood Control District, TX, U.S.
[3]	Evans, E. P., and Von Lany, P. H. (1983). "A mathematical model of overbank spilling and urban flooding, Paper No. G5." International Conference on the Hydraulic Aspects of Floods & Flood Control, London, U.K., pp. 241-255.
[4]	Tate, E., and Maidment, D. (1999). Flood plain mapping using HEC-RAS and ArcView GIS. Center for Research in Water Resources, The University of Texas, Austin, T. X., U.S.
[5]	Syme, W. J., and Paudyal, G. G. (1994). "Bangladesh flood management model." Proceedings Second International Conference on River Flood Hydraulics, York, U.K., pp. 167-176.
[6]	National Weather Service (NWS) (1997). Automated local flood warning systems handbook weather service hydrology handbook No. 2. U.S. Department of Commerce, National Oceanic and Atmospheric Administra-tion, National Weather Service, Office of Hydrology: Silver Spring, M. D., U.S.
[7]	Lee, H. L., Lee, J. W., and Kim, D. G., (1999). "Flood forecasting system and mapping using GIS." Journal of Civil and Environmental Engineering Research, Vol. 1999, No. 3, pp. 365-368.
[8]	Bae, D.-H., Jeong, C., and Yoon, S.-s. (2008). "Development of flood prediction model using hydrologic observations in Cheonggye stream." Journal of The Korean Society of Civil Engineers, Vol. 28, No. 6B, pp. 683-690.
[9]	Yoo, H.-H., Kim, W.-S., and Kim, S.-S. (2006). "Inundating disaster assessment in coastal areas using urban flood model." Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 24, No. 3, pp. 299-309.
[10]	Sathish Kumar, D.; Arya, D. S.; Vojinovic, Z. Modeling of urban growth dynamics and its impact on surface runoff characteristics. Comput. Environ. Urban 2013, 41, 124–135.
[11]	Shin, H.-S., Jeon, S.-U., and Seo, B.-C. (2000). "Flood influence analysis on SUYOUNG River based on HEC-HMS/HEC-RAS." Journal of Korea Water Resources Association, Vol. 33, pp. 281-287.
[12]	Shin, Hyunsuk, Park, Yong-Woon, and Hong, Ilpyo, (2007), “The Study on the Development of Flood Prediction and Warning System at Ungaged Coastal Urban Area - On-Cheon Stream in Busan -” Journal of Korea Water Resources Association, vol. 40, no. 6, pp. 447–458.
[13]	Sin, Hyeon-Seok, Jeon, Seong-U, and Seo, Bong-Cheol, (2000), "Flood Influence Analysis on SUYOUNG River Based on HEC-HMS/HEC-RAS." Journal of Korea Water Resources Association, vol. 33, pp. 281-287.
[14]	Ministry of Land, Infrastructure and Transport (MOLIT) (2012). West Nakdong basic river plan (changed) report. Busan Regional Construction and Management Office.
[15]	Ministry of Land, Infrastructure and Transport (MOLIT) (2013). Nakdong basic river plan (changed) report. Busan Regional Construction and Management Office.

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APA Style

Bonhyun Koo, Seunguk Oh, Jaseob Koo, Kyucheoul Shim. (2021). Development of the GeoCRP for Smart River Management in the Smart City(I). Journal of Water Resources and Ocean Science, 10(5), 145-155. https://doi.org/10.11648/j.wros.20211005.17

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ACS Style

Bonhyun Koo; Seunguk Oh; Jaseob Koo; Kyucheoul Shim. Development of the GeoCRP for Smart River Management in the Smart City(I). J. Water Resour. Ocean Sci. 2021, 10(5), 145-155. doi: 10.11648/j.wros.20211005.17

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AMA Style

Bonhyun Koo, Seunguk Oh, Jaseob Koo, Kyucheoul Shim. Development of the GeoCRP for Smart River Management in the Smart City(I). J Water Resour Ocean Sci. 2021;10(5):145-155. doi: 10.11648/j.wros.20211005.17

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@article{10.11648/j.wros.20211005.17,
  author = {Bonhyun Koo and Seunguk Oh and Jaseob Koo and Kyucheoul Shim},
  title = {Development of the GeoCRP for Smart River Management in the Smart City(I)},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {10},
  number = {5},
  pages = {145-155},
  doi = {10.11648/j.wros.20211005.17},
  url = {https://doi.org/10.11648/j.wros.20211005.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20211005.17},
  abstract = {In this study, we developed the Geo City River Platform (GeoCRP), which regularly collects data on the web and provides the analyzed information by performing flood analysis based on the collected information in order to effectively perform smart city river management. GeoCRP was analyzed and tested in the Eco Delta City (EDC) area. In this platform, a watershed runoff analysis model, a river flow analysis model and an urban runoff analysis model were applied for flood analysis in EDC. GeoCRP can obtain more reliable results by taking a step-by-step approach to urban overflow that may occur in smart cities through the applied model. In addition, since all analysis processes such as data collection, input data generation and result data storage are automatically performed on the web, analysis can be performed, and results can be viewed if an environment that can access the web is established without special equipment or tools. The displayed analysis result is provided visually so that the user can intuitively confirm the information, so it is easy to understand the analysis results. Through this, smart city managers can effectively manage rivers, and it is expected that educational institutions will be able to use it as educational material on urban runoff.},
 year = {2021}
}

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TY  - JOUR
T1  - Development of the GeoCRP for Smart River Management in the Smart City(I)
AU  - Bonhyun Koo
AU  - Seunguk Oh
AU  - Jaseob Koo
AU  - Kyucheoul Shim
Y1  - 2021/10/30
PY  - 2021
N1  - https://doi.org/10.11648/j.wros.20211005.17
DO  - 10.11648/j.wros.20211005.17
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 145
EP  - 155
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20211005.17
AB  - In this study, we developed the Geo City River Platform (GeoCRP), which regularly collects data on the web and provides the analyzed information by performing flood analysis based on the collected information in order to effectively perform smart city river management. GeoCRP was analyzed and tested in the Eco Delta City (EDC) area. In this platform, a watershed runoff analysis model, a river flow analysis model and an urban runoff analysis model were applied for flood analysis in EDC. GeoCRP can obtain more reliable results by taking a step-by-step approach to urban overflow that may occur in smart cities through the applied model. In addition, since all analysis processes such as data collection, input data generation and result data storage are automatically performed on the web, analysis can be performed, and results can be viewed if an environment that can access the web is established without special equipment or tools. The displayed analysis result is provided visually so that the user can intuitively confirm the information, so it is easy to understand the analysis results. Through this, smart city managers can effectively manage rivers, and it is expected that educational institutions will be able to use it as educational material on urban runoff.
VL  - 10
IS  - 5
ER  -

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Author Information

Bonhyun Koo

Institute of Smart Disaster Management, JBT Corporation, Seoul, Korea
Seunguk Oh

Institute of Smart Disaster Management, JBT Corporation, Seoul, Korea
Jaseob Koo

Institute of Smart Disaster Management, JBT Corporation, Seoul, Korea
Kyucheoul Shim

Institute of Smart Disaster Management, JBT Corporation, Seoul, Korea

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Plain Text BibTeX RIS

APA Style

Bonhyun Koo, Seunguk Oh, Jaseob Koo, Kyucheoul Shim. (2021). Development of the GeoCRP for Smart River Management in the Smart City(I). Journal of Water Resources and Ocean Science, 10(5), 145-155. https://doi.org/10.11648/j.wros.20211005.17

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ACS Style

Bonhyun Koo; Seunguk Oh; Jaseob Koo; Kyucheoul Shim. Development of the GeoCRP for Smart River Management in the Smart City(I). J. Water Resour. Ocean Sci. 2021, 10(5), 145-155. doi: 10.11648/j.wros.20211005.17

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AMA Style

Bonhyun Koo, Seunguk Oh, Jaseob Koo, Kyucheoul Shim. Development of the GeoCRP for Smart River Management in the Smart City(I). J Water Resour Ocean Sci. 2021;10(5):145-155. doi: 10.11648/j.wros.20211005.17

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@article{10.11648/j.wros.20211005.17,
  author = {Bonhyun Koo and Seunguk Oh and Jaseob Koo and Kyucheoul Shim},
  title = {Development of the GeoCRP for Smart River Management in the Smart City(I)},
  journal = {Journal of Water Resources and Ocean Science},
  volume = {10},
  number = {5},
  pages = {145-155},
  doi = {10.11648/j.wros.20211005.17},
  url = {https://doi.org/10.11648/j.wros.20211005.17},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.wros.20211005.17},
  abstract = {In this study, we developed the Geo City River Platform (GeoCRP), which regularly collects data on the web and provides the analyzed information by performing flood analysis based on the collected information in order to effectively perform smart city river management. GeoCRP was analyzed and tested in the Eco Delta City (EDC) area. In this platform, a watershed runoff analysis model, a river flow analysis model and an urban runoff analysis model were applied for flood analysis in EDC. GeoCRP can obtain more reliable results by taking a step-by-step approach to urban overflow that may occur in smart cities through the applied model. In addition, since all analysis processes such as data collection, input data generation and result data storage are automatically performed on the web, analysis can be performed, and results can be viewed if an environment that can access the web is established without special equipment or tools. The displayed analysis result is provided visually so that the user can intuitively confirm the information, so it is easy to understand the analysis results. Through this, smart city managers can effectively manage rivers, and it is expected that educational institutions will be able to use it as educational material on urban runoff.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Development of the GeoCRP for Smart River Management in the Smart City(I)
AU  - Bonhyun Koo
AU  - Seunguk Oh
AU  - Jaseob Koo
AU  - Kyucheoul Shim
Y1  - 2021/10/30
PY  - 2021
N1  - https://doi.org/10.11648/j.wros.20211005.17
DO  - 10.11648/j.wros.20211005.17
T2  - Journal of Water Resources and Ocean Science
JF  - Journal of Water Resources and Ocean Science
JO  - Journal of Water Resources and Ocean Science
SP  - 145
EP  - 155
PB  - Science Publishing Group
SN  - 2328-7993
UR  - https://doi.org/10.11648/j.wros.20211005.17
AB  - In this study, we developed the Geo City River Platform (GeoCRP), which regularly collects data on the web and provides the analyzed information by performing flood analysis based on the collected information in order to effectively perform smart city river management. GeoCRP was analyzed and tested in the Eco Delta City (EDC) area. In this platform, a watershed runoff analysis model, a river flow analysis model and an urban runoff analysis model were applied for flood analysis in EDC. GeoCRP can obtain more reliable results by taking a step-by-step approach to urban overflow that may occur in smart cities through the applied model. In addition, since all analysis processes such as data collection, input data generation and result data storage are automatically performed on the web, analysis can be performed, and results can be viewed if an environment that can access the web is established without special equipment or tools. The displayed analysis result is provided visually so that the user can intuitively confirm the information, so it is easy to understand the analysis results. Through this, smart city managers can effectively manage rivers, and it is expected that educational institutions will be able to use it as educational material on urban runoff.
VL  - 10
IS  - 5
ER  -

Copy | Download