Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data

Chen, Huili; Zhao, Jiaheng; Liang, Qiuhua; Maharjan, Sudan Bikash; Joshi, Srijana

doi:10.1016/j.scitotenv.2021.151289

Cited by 10 publications

(5 citation statements)

References 62 publications

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“…485 The results of this study showcase how object-based GLOF exposure and impact assessments can be carried out for multiple 490 glacial lakes across the data-scarce Himalayan region on a national scale, leveraging established techniques and methods. In doing so, this study relies on several key components, including remote sensing techniques for accurate glacial lake area delineation, Bayesian regression models for deriving lake water depth and peak discharge relationships (Veh & Walz, 2020), state-of-the-art flood modelling technology supported by parallelized high-performance computing (Zhao et al, 2022), and object-based GLOF exposure and impact evaluation using open-source data (Chen et al, 2022). Open data and images from 495 various sources are harnessed to generate input data for flood modelling and object-based exposure datasets, addressing the challenges posed by limited data availability and the inaccessibility of many glacial lakes in high-altitude regions.…”

Section: Sensitivity Analysismentioning

confidence: 99%

“…Previous studies have typically relied on census data 85 at coarse spatial resolutions or aggregated land use data that encompass various objects like properties and infrastructure, to estimate the potential socio-economic impact of GLOFs. Benefiting from the emergence of new data technologies and the resulting enhancements in data quantity and quality, a spatially explicit assessment method has been developed to identify GLOF exposure at an object level and applied to the Tsho Rolpa Lake (Chen et al, 2022). Employing a similar strategy, essential socio-economic information is collected and processed from various sources, including OpenStreetMap, Google 90…”

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confidence: 99%

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Assessing national exposure and impact to glacial lake outburst floods considering uncertainty under data sparsity

Chen,

Liang,

Zhao

et al. 2024

Preprint

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Abstract. Glacial Lake Outburst Floods (GLOFs) are widely recognized as one of the most devastating natural hazards in the Himalaya, which may catastrophic consequences including substantial loss of lives. To effectively mitigate these risks and enhance regional resilience, it is imperative to conduct an objective and holistic assessment of GLOFs hazards and their potential impacts of GLOFs over a large spatial scale. However, this is challenged by the limited availability of data and the inaccessibility to most of the glacial lakes in high-altitude areas. The data challenge is exacerbated when dealing with multiple lakes across an expansive spatial area. This study aims to exploit remote sensing techniques, well-established Bayesian regression models for estimating glacial lake conditions, cutting-edge flood modelling technology, and open data from various sources to innovate a framework for assessing the national exposure and impact of GLOFs. In the innovative framework, multi-temporal imagery is utilized with a Random Forest model to extract glacial lake water surfaces. Bayesian models, derived from previous research, are employed to estimate a plausible range of glacial lake water volumes and associated GLOF peak discharges, while accounting for the uncertainty stemming from the limited size of available data and outliers within the data. A significant amount of GLOF scenarios is subsequently generated based on this estimated plausible range of peak discharges. A GPU-based hydrodynamic model is then adopted to simulate the resulting flood hydrodynamics in different GLOF scenarios. Necessary socio-economic information is collected and processed from multiple sources including OpenStreetMap, Google Earth, local archives, and global data products to support exposure analysis. Established depth-damage curves are used to assess the GLOF damage extents to different exposures. The evaluation framework is applied to 21 glacial lakes identified potentially dangerous in the Nepal Himalaya. The results indicate that Tsho Rolpa Lake, Lower Barun Lake and Thulagi Lake bear the most serious impacts of GLOFs on buildings and roads, and influence existing hydropower facilities, while Lower Barun Lake, Tsho Rolpa Lake and Lumding Lake will experience the most impacts of GLOFs on agriculture areas. Four anonymous lakes (located at 85°37′51″ E, 28°09′44″ N; 87°44′59″ E, 27°48′57″ N; 87°56′05″ N, 27°47′26″ E; 86°55′41″ E, 27°51′00″ N) have the potential to impact more than 100 buildings, and the first three lakes may even submerge existing hydropower facilities.

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Section: Sensitivity Analysismentioning

confidence: 99%

mentioning

confidence: 99%

Assessing national exposure and impact to glacial lake outburst floods considering uncertainty under data sparsity

Chen,

Liang,

Zhao

et al. 2024

Preprint

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“…HiPIMS solves the above governing equations using a Godunov-type finite volume numerical scheme, making it suitable for simulating different types of shallow flow hydrodynamics, including the high-transient flash flooding processes induced by dam breaks or intense rainfall. HiPIMS is also implemented on multiple graphics processing units (GPUs) to achieve high-performance 220 computing and has been intensively tested for modelling catchment-scale overland flow and flooding processes as well as other types of flood hydrodynamics (Ming et al, 2022;Chen et al, 2022). HiPIMS is therefore suited for predicting the transient and complex flow hydrodynamics across different flow regimes in the debris flow triggering area, as required by this work.…”

Section: Hydrodynamic Modelingmentioning

confidence: 99%

A coupled hydrological and hydrodynamic modelling approach for estimating rainfall thresholds of debris-flow occurrence

Wei,

Shang,

Liang

et al. 2023

Preprint

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Abstract. Rainfall-induced hydrological processes and surface water flow hydrodynamics may play a key role in initiating debris flows. In this study, a new framework based on an integrated hydrological and hydrodynamic model is proposed to estimate the Intensity-Duration (I-D) rainfall thresholds that trigger debris flows. In the new framework, intensity-duration-frequency (IDF) analysis is carried out to generate design rainfall to drive the integrated models to calculate grid-based hydrodynamic indices (i.e. unit-width discharge). The hydrodynamic indices are subsequently compared with hydrodynamic thresholds to indicate the occurrence of debris flows and derive rainfall thresholds through the introduction of a zone threshold. The capability of the new framework in predicting the occurrence of debris flows is verified and confirmed by application to a small catchment in Zhejiang Province, China, where observed hydrological data are available. Compared with the traditional statistical approaches to derive Intensity-Duration (I-D) thresholds, the current physically-based framework can effectively take into account the hydrological processes controlled by meteorological conditions and spatial topographic properties, making it more suitable for application in ungauged catchments where historical debris flow data is lacking.

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“…There are also studies on the Learning from Floods (LFF) model to compare flood resilience in two environments [ 114 ]. In addition to traditional models, some scholars also predict flood risk based on high-performance [ 115 , 116 ] and large-scale flood models [ 52 ], in order to propose development strategies for urban flood resilience.…”

Section: Systematic Analysismentioning

confidence: 99%

Review of Urban Flood Resilience: Insights from Scientometric and Systematic Analysis

Gao

Wang

Yang

2022

IJERPH

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In recent decades, climate change is exacerbating meteorological disasters around the world, causing more serious urban flood disaster losses. Many solutions in related research have been proposed to enhance urban adaptation to climate change, including urban flooding simulations, risk reduction and urban flood-resistance capacity. In this paper we provide a thorough review of urban flood-resilience using scientometric and systematic analysis. Using Cite Space and VOS viewer, we conducted a scientometric analysis to quantitively analyze related papers from the Web of Science Core Collection from 1999 to 2021 with urban flood resilience as the keyword. We systematically summarize the relationship of urban flood resilience, including co-citation analysis of keywords, authors, research institutions, countries, and research trends. The scientometric results show that four stages can be distinguished to indicate the evolution of different keywords in urban flood management from 1999, and urban flood resilience has become a research hotspot with a significant increase globally since 2015. The research methods and progress of urban flood resilience in these four related fields are systematically analyzed, including climate change, urban planning, urban system adaptation and urban flood-simulation models. Climate change has been of high interest in urban flood-resilience research. Urban planning and the adaptation of urban systems differ in terms of human involvement and local policies, while more dynamic factors need to be jointly described. Models are mostly evaluated with indicators, and comprehensive resilience studies based on traditional models are needed for multi-level and higher performance models. Consequently, more studies about urban flood resilience based on local policies and dynamics within global urban areas combined with fine simulation are needed in the future, improving the concept of resilience as applied to urban flood-risk-management and assessment.

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Assessing the potential impact of glacial lake outburst floods on individual objects using a high-performance hydrodynamic model and open-source data

Cited by 10 publications

References 62 publications

Assessing national exposure and impact to glacial lake outburst floods considering uncertainty under data sparsity

Assessing national exposure and impact to glacial lake outburst floods considering uncertainty under data sparsity

A coupled hydrological and hydrodynamic modelling approach for estimating rainfall thresholds of debris-flow occurrence

Review of Urban Flood Resilience: Insights from Scientometric and Systematic Analysis

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