An Approach Using a 1D Hydraulic Model, Landsat Imaging and Generalized Likelihood Uncertainty Estimation for an Approximation of Flood Discharge
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jung, Younghun | - |
dc.contributor.author | Merwade, Venkatesh | - |
dc.contributor.author | Yeo, Kyudong | - |
dc.contributor.author | Shin, Yongchul | - |
dc.contributor.author | Lee, Seung Oh | - |
dc.date.accessioned | 2021-11-11T03:43:12Z | - |
dc.date.available | 2021-11-11T03:43:12Z | - |
dc.date.created | 2021-11-10 | - |
dc.date.issued | 2013-12 | - |
dc.identifier.issn | 2073-4441 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/16989 | - |
dc.description.abstract | Collection and investigation of flood information are essential to understand the nature of floods, but this has proved difficult in data-poor environments, or in developing or under-developed countries due to economic and technological limitations. The development of remote sensing data, GIS, and modeling techniques have, therefore, proved to be useful tools in the analysis of the nature of floods. Accordingly, this study attempts to estimate a flood discharge using the generalized likelihood uncertainty estimation (GLUE) methodology and a 1D hydraulic model, with remote sensing data and topographic data, under the assumed condition that there is no gauge station in the Missouri river, Nebraska, and Wabash River, Indiana, in the United States. The results show that the use of Landsat leads to a better discharge approximation on a large-scale reach than on a small-scale. Discharge approximation using the GLUE depended on the selection of likelihood measures. Consideration of physical conditions in study reaches could, therefore, contribute to an appropriate selection of informal likely measurements. The river discharge assessed by using Landsat image and the GLUE Methodology could be useful in supplementing flood information for flood risk management at a planning level in ungauged basins. However, it should be noted that this approach to the real-time application might be difficult due to the GLUE procedure. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | MDPI AG | - |
dc.subject | UNGAUGED MESOSCALE CATCHMENTS | - |
dc.subject | REMOTE-SENSING OBSERVATIONS | - |
dc.subject | INUNDATION MODELS | - |
dc.subject | GLUE METHODOLOGY | - |
dc.subject | SATELLITE-OBSERVATIONS | - |
dc.subject | CONTINUOUS SIMULATION | - |
dc.subject | WATER STAGES | - |
dc.subject | PREDICTIONS | - |
dc.subject | CALIBRATION | - |
dc.subject | RIVER | - |
dc.title | An Approach Using a 1D Hydraulic Model, Landsat Imaging and Generalized Likelihood Uncertainty Estimation for an Approximation of Flood Discharge | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Seung Oh | - |
dc.identifier.doi | 10.3390/w5041598 | - |
dc.identifier.scopusid | 2-s2.0-84888809299 | - |
dc.identifier.wosid | 000330518400009 | - |
dc.identifier.bibliographicCitation | WATER, v.5, no.4, pp.1598 - 1621 | - |
dc.relation.isPartOf | WATER | - |
dc.citation.title | WATER | - |
dc.citation.volume | 5 | - |
dc.citation.number | 4 | - |
dc.citation.startPage | 1598 | - |
dc.citation.endPage | 1621 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalResearchArea | Water Resources | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.relation.journalWebOfScienceCategory | Water Resources | - |
dc.subject.keywordPlus | UNGAUGED MESOSCALE CATCHMENTS | - |
dc.subject.keywordPlus | REMOTE-SENSING OBSERVATIONS | - |
dc.subject.keywordPlus | INUNDATION MODELS | - |
dc.subject.keywordPlus | GLUE METHODOLOGY | - |
dc.subject.keywordPlus | SATELLITE-OBSERVATIONS | - |
dc.subject.keywordPlus | CONTINUOUS SIMULATION | - |
dc.subject.keywordPlus | WATER STAGES | - |
dc.subject.keywordPlus | PREDICTIONS | - |
dc.subject.keywordPlus | CALIBRATION | - |
dc.subject.keywordPlus | RIVER | - |
dc.subject.keywordAuthor | discharge approximation | - |
dc.subject.keywordAuthor | GLUE | - |
dc.subject.keywordAuthor | Landsat | - |
dc.subject.keywordAuthor | likelihood measure | - |
dc.subject.keywordAuthor | data-poor environment | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
94, Wausan-ro, Mapo-gu, Seoul, 04066, Korea02-320-1314
COPYRIGHT 2020 HONGIK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.