Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models

Lahars at Changbaishan region are understudied despite being a major hazard due to its extensive river systems and large crater lake. Previous studies modelled the lahar hazard at Changbaishan under various scenarios, mostly using LaharZ due to the lack of field data. With new field data available,...

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Main Author: Chow, Jun Rui
Other Authors: Susanna Jenkins
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/156312
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author Chow, Jun Rui
author2 Susanna Jenkins
author_facet Susanna Jenkins
Chow, Jun Rui
author_sort Chow, Jun Rui
collection NTU
description Lahars at Changbaishan region are understudied despite being a major hazard due to its extensive river systems and large crater lake. Previous studies modelled the lahar hazard at Changbaishan under various scenarios, mostly using LaharZ due to the lack of field data. With new field data available, this study benchmarks LaharZ, Titan2D and LaharFlow by reconstructing the Millennium Eruption (ME) lahars before applying them for lahar hazard assessment at Changbaishan using model inputs informed by LaharDB, a new global lahar database. LaharDB builds upon an earlier unpublished database, and was reviewed to address various issues to improve its reliability and updated with recent data, before using it to constrain and infer model inputs. To reconstruct the ME lahars, model inputs were incrementally tested to determine the best-fit between model outputs and field extent. LaharZ best reconstructs the ME lahars; LaharFlow has the poorest reconstruction. The models provide insights into various aspects of lahars that are useful for land-use planning. For hazard assessment, scenarios defined by input volume, triggering mechanism and source location were modelled. The resulting runouts for crater lake, ice melt and rainfall scenarios are 2 – 65, 12 – 74 and 1 – 17 km respectively; the inundation areas are 1 – 683, 3 – 1137 and 0.5 – 17 km^2 respectively. The overall cropland, population, road, tree cover and built-up exposures are 0 – 22 km^2, 0 – 26,000 people, 0 – 588 km, 0.3 – 715 km^2 and 0 – 8 km^2 respectively. Careful land-use and hazard planning are important for minimising future lahar hazard and exposure.
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spelling ntu-10356/1563122023-02-28T16:46:53Z Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models Chow, Jun Rui Susanna Jenkins Asian School of the Environment susanna.jenkins@ntu.edu.sg Science::Geology::Volcanoes and earthquakes Science::Mathematics::Applied mathematics::Simulation and modeling Social sciences::Geography::Natural disasters Lahars at Changbaishan region are understudied despite being a major hazard due to its extensive river systems and large crater lake. Previous studies modelled the lahar hazard at Changbaishan under various scenarios, mostly using LaharZ due to the lack of field data. With new field data available, this study benchmarks LaharZ, Titan2D and LaharFlow by reconstructing the Millennium Eruption (ME) lahars before applying them for lahar hazard assessment at Changbaishan using model inputs informed by LaharDB, a new global lahar database. LaharDB builds upon an earlier unpublished database, and was reviewed to address various issues to improve its reliability and updated with recent data, before using it to constrain and infer model inputs. To reconstruct the ME lahars, model inputs were incrementally tested to determine the best-fit between model outputs and field extent. LaharZ best reconstructs the ME lahars; LaharFlow has the poorest reconstruction. The models provide insights into various aspects of lahars that are useful for land-use planning. For hazard assessment, scenarios defined by input volume, triggering mechanism and source location were modelled. The resulting runouts for crater lake, ice melt and rainfall scenarios are 2 – 65, 12 – 74 and 1 – 17 km respectively; the inundation areas are 1 – 683, 3 – 1137 and 0.5 – 17 km^2 respectively. The overall cropland, population, road, tree cover and built-up exposures are 0 – 22 km^2, 0 – 26,000 people, 0 – 588 km, 0.3 – 715 km^2 and 0 – 8 km^2 respectively. Careful land-use and hazard planning are important for minimising future lahar hazard and exposure. Bachelor of Science in Environmental Earth Systems Science 2022-04-12T08:03:35Z 2022-04-12T08:03:35Z 2022 Final Year Project (FYP) Chow, J. R. (2022). Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156312 https://hdl.handle.net/10356/156312 en application/pdf Nanyang Technological University
spellingShingle Science::Geology::Volcanoes and earthquakes
Science::Mathematics::Applied mathematics::Simulation and modeling
Social sciences::Geography::Natural disasters
Chow, Jun Rui
Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models
title Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models
title_full Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models
title_fullStr Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models
title_full_unstemmed Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models
title_short Reconstructing and assessing the lahar hazard at Changbaishan: insights from open-access numerical models
title_sort reconstructing and assessing the lahar hazard at changbaishan insights from open access numerical models
topic Science::Geology::Volcanoes and earthquakes
Science::Mathematics::Applied mathematics::Simulation and modeling
Social sciences::Geography::Natural disasters
url https://hdl.handle.net/10356/156312
work_keys_str_mv AT chowjunrui reconstructingandassessingthelaharhazardatchangbaishaninsightsfromopenaccessnumericalmodels