Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers
During extreme floods caused by climate change, reliable flow discharge data are essential for successful reservoir operation to mitigate downstream flood damage. Generally, the flow discharge is computed using the rating curve (RC) established from the relationship between the flow rate and water s...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IOP Publishing
2024-01-01
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| Series: | Environmental Research Communications |
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| Online Access: | https://doi.org/10.1088/2515-7620/ad277c |
| _version_ | 1797302128984719360 |
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| author | Hansol Kang Yeonsu Kim Hyunuk An Jisun Byun Joonwoo Noh |
| author_facet | Hansol Kang Yeonsu Kim Hyunuk An Jisun Byun Joonwoo Noh |
| author_sort | Hansol Kang |
| collection | DOAJ |
| description | During extreme floods caused by climate change, reliable flow discharge data are essential for successful reservoir operation to mitigate downstream flood damage. Generally, the flow discharge is computed using the rating curve (RC) established from the relationship between the flow rate and water stage level. Determining the parameters of rating curves is subject to uncertainties related to the difficulties and limitations of flow monitoring in covering a wide range of flow variations. Especially at river confluences, the uncertainties are pronounced when floods occur owing to several factors such as roughness change, backwaters, and levee overflow. The Seomjin River Basin in Korea suffered from flood inundation that occurred at the tributary confluence during an extreme flood in 2020. To identify a reliable flow rate of the main stream and tributary, this study proposes an indirect flow assessment scheme using a 1D hydrodynamic simulation model to find the best simulated water level in an iterative manner based on Monte Carlo (MC) simulations. With a large amount of discharge data generated from random-number combinations, it is possible to obtain the best results automatically by specifying the reliability limitation considering the uncertainty of the predetermined RC parameters associated with the roughness coefficient. Nash Sutcliffe Efficiency (NSE) was incorporated to evaluate the reproduced water level to meet the threshold specified for NSE ≥ 0.75. The simulated flowrates computed from the revised RC and roughness coefficients revealed an error range of 8%–36.6% compared with the design flood. The approach proposed in this study is applicable for determining the valid parameters necessary to create a revised RC at an existing water level gauge station, where the uncertainties of the RC are pronounced, particularly in the vicinity of the channel confluence. |
| first_indexed | 2024-03-07T23:32:19Z |
| format | Article |
| id | doaj.art-28e5889add6e4a54bbc35f043e24460f |
| institution | Directory Open Access Journal |
| issn | 2515-7620 |
| language | English |
| last_indexed | 2024-03-07T23:32:19Z |
| publishDate | 2024-01-01 |
| publisher | IOP Publishing |
| record_format | Article |
| series | Environmental Research Communications |
| spelling | doaj.art-28e5889add6e4a54bbc35f043e24460f2024-02-20T11:47:38ZengIOP PublishingEnvironmental Research Communications2515-76202024-01-016202501210.1088/2515-7620/ad277cEstimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two riversHansol Kang0https://orcid.org/0000-0001-9023-0456Yeonsu Kim1https://orcid.org/0000-0003-0893-672XHyunuk An2https://orcid.org/0000-0002-4566-5159Jisun Byun3Joonwoo Noh4Department of Agricultural and Rural Engineering, Chungnam National University , Daejeon 34134, Republic of KoreaK-Water Research Institute, Daejeon 34045, Republic of KoreaDepartment of Agricultural and Rural Engineering, Chungnam National University , Daejeon 34134, Republic of KoreaK-Water Research Institute, Daejeon 34045, Republic of KoreaK-Water Research Institute, Daejeon 34045, Republic of KoreaDuring extreme floods caused by climate change, reliable flow discharge data are essential for successful reservoir operation to mitigate downstream flood damage. Generally, the flow discharge is computed using the rating curve (RC) established from the relationship between the flow rate and water stage level. Determining the parameters of rating curves is subject to uncertainties related to the difficulties and limitations of flow monitoring in covering a wide range of flow variations. Especially at river confluences, the uncertainties are pronounced when floods occur owing to several factors such as roughness change, backwaters, and levee overflow. The Seomjin River Basin in Korea suffered from flood inundation that occurred at the tributary confluence during an extreme flood in 2020. To identify a reliable flow rate of the main stream and tributary, this study proposes an indirect flow assessment scheme using a 1D hydrodynamic simulation model to find the best simulated water level in an iterative manner based on Monte Carlo (MC) simulations. With a large amount of discharge data generated from random-number combinations, it is possible to obtain the best results automatically by specifying the reliability limitation considering the uncertainty of the predetermined RC parameters associated with the roughness coefficient. Nash Sutcliffe Efficiency (NSE) was incorporated to evaluate the reproduced water level to meet the threshold specified for NSE ≥ 0.75. The simulated flowrates computed from the revised RC and roughness coefficients revealed an error range of 8%–36.6% compared with the design flood. The approach proposed in this study is applicable for determining the valid parameters necessary to create a revised RC at an existing water level gauge station, where the uncertainties of the RC are pronounced, particularly in the vicinity of the channel confluence.https://doi.org/10.1088/2515-7620/ad277crating curveMonte Carlo simulationhydraulic modeldischarge uncertainty |
| spellingShingle | Hansol Kang Yeonsu Kim Hyunuk An Jisun Byun Joonwoo Noh Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers Environmental Research Communications rating curve Monte Carlo simulation hydraulic model discharge uncertainty |
| title | Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers |
| title_full | Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers |
| title_fullStr | Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers |
| title_full_unstemmed | Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers |
| title_short | Estimation of river discharge using Monte Carlo simulations and a 1D hydraulic model based on the artificial multi-segmented rating curves at the confluence of two rivers |
| title_sort | estimation of river discharge using monte carlo simulations and a 1d hydraulic model based on the artificial multi segmented rating curves at the confluence of two rivers |
| topic | rating curve Monte Carlo simulation hydraulic model discharge uncertainty |
| url | https://doi.org/10.1088/2515-7620/ad277c |
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