Pub Date : 2024-12-13DOI: 10.1038/s44304-024-00047-2
Yifan Yang, Chen Xie, Ziwu Fan, Zhonghou Xu, Bruce W. Melville, Guoqing Liu, Lei Hong
Digital twins are transforming the paradigm of water management and water hazard mitigation globally, facilitating more effective governance. However, comprehensive digitalisation at the basin scale still faces major challenges in data, modelling, policy incentives, and, most critically, widespread inequity. This article outlines a framework for building widely applicable digital-twin basins and addressing the main obstacles. Ensuring high-quality water data requires more comprehensive and well-controlled data aggregation and provision protocols. Significant improvements to the existing data infrastructure are necessary to support this effort. Most existing water models are not effectively integrated and do not include multi-physics to reflect all essential correlated physical processes at the basin scale. The current advancement in physics-informed data-driven approaches may provide a solution. Furthermore, global initiatives are critical to reducing major inequity in less developed regions, particularly the Global South, during digitalisation. It is imperative that researchers, practitioners and policymakers take decisive actions to prioritise research and allocate resources to foster transboundary collaborations towards integrated and extensive digital-twin basin systems, promoting the sustainability and resilience of global water resources.
{"title":"Digital twinning of river basins towards full-scale, sustainable and equitable water management and disaster mitigation","authors":"Yifan Yang, Chen Xie, Ziwu Fan, Zhonghou Xu, Bruce W. Melville, Guoqing Liu, Lei Hong","doi":"10.1038/s44304-024-00047-2","DOIUrl":"10.1038/s44304-024-00047-2","url":null,"abstract":"Digital twins are transforming the paradigm of water management and water hazard mitigation globally, facilitating more effective governance. However, comprehensive digitalisation at the basin scale still faces major challenges in data, modelling, policy incentives, and, most critically, widespread inequity. This article outlines a framework for building widely applicable digital-twin basins and addressing the main obstacles. Ensuring high-quality water data requires more comprehensive and well-controlled data aggregation and provision protocols. Significant improvements to the existing data infrastructure are necessary to support this effort. Most existing water models are not effectively integrated and do not include multi-physics to reflect all essential correlated physical processes at the basin scale. The current advancement in physics-informed data-driven approaches may provide a solution. Furthermore, global initiatives are critical to reducing major inequity in less developed regions, particularly the Global South, during digitalisation. It is imperative that researchers, practitioners and policymakers take decisive actions to prioritise research and allocate resources to foster transboundary collaborations towards integrated and extensive digital-twin basin systems, promoting the sustainability and resilience of global water resources.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00047-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142811345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-12DOI: 10.1038/s44304-024-00038-3
Shijie Liu, Hengxing Lan, Alexander Strom, Langping Li, Han Bao
Jiali Fault plays a key role in the dextral fault system in the southeastern Tibetan Plateau. Although it forms a striking topographic lineament the Yigong and Parlung Rivers, evidence for faulting in the Holocene has been equivocal. In this study, Holocene sediment deformation caused by the Jiali Fault was discovered in the debris flow fan near the Guxiang barrier lake. A palaeo-earthquake event that occurred between 3494 and 2865 cal B.P. was revealed, as evidenced by geological, seismic, and radiocarbon dating investigations. On the basis of a compilation of dating results, the middle segment of the Jiali Fault was proposed to belong to a Holocene active fault. This was attributed to the strong influence of the continued north eastwards compression of the Indian Plate and the clockwise rotation of the eastern Himalayan syntaxis. These findings provide new insights into the tectonic implications and earthquake activity of the southeastern Tibetan Plateau.
嘉里断裂在青藏高原东南部的右旋断裂体系中起着关键作用。虽然它形成了引人注目的一公河和帕龙河地形，但全新世断裂的证据一直模棱两可。本研究在谷乡堰塞湖附近的泥石流扇中发现了由嘉里断裂引起的全新世沉积变形。通过地质、地震和放射性碳测年，揭示了发生在3494 ~ 2865 cal B.P.之间的古地震事件。综合各测年资料，认为嘉里断裂中段属于全新世活动断裂。这归因于印度板块持续的北东挤压和喜马拉雅东部辐合的顺时针旋转的强烈影响。这些发现为青藏高原东南部的构造意义和地震活动提供了新的见解。
{"title":"Spatial segmentation of Jiali Fault’s Holocene activity in the southeastern Tibetan Plateau","authors":"Shijie Liu, Hengxing Lan, Alexander Strom, Langping Li, Han Bao","doi":"10.1038/s44304-024-00038-3","DOIUrl":"10.1038/s44304-024-00038-3","url":null,"abstract":"Jiali Fault plays a key role in the dextral fault system in the southeastern Tibetan Plateau. Although it forms a striking topographic lineament the Yigong and Parlung Rivers, evidence for faulting in the Holocene has been equivocal. In this study, Holocene sediment deformation caused by the Jiali Fault was discovered in the debris flow fan near the Guxiang barrier lake. A palaeo-earthquake event that occurred between 3494 and 2865 cal B.P. was revealed, as evidenced by geological, seismic, and radiocarbon dating investigations. On the basis of a compilation of dating results, the middle segment of the Jiali Fault was proposed to belong to a Holocene active fault. This was attributed to the strong influence of the continued north eastwards compression of the Indian Plate and the clockwise rotation of the eastern Himalayan syntaxis. These findings provide new insights into the tectonic implications and earthquake activity of the southeastern Tibetan Plateau.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2024-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00038-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142811371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-09DOI: 10.1038/s44304-024-00044-5
V. K. Krishnapriya, A. Rajaneesh, K. S. Sajinkumar, Thomas Oommen, Ali P. Yunus, Nikhil Nedumpallile Vasu, R. B. Binoj Kumar, S. Adarsh
The long run-out debris flows caused by oversaturated soil systems during the aggravated monsoon period in the Western Ghats raise questions about the hill community’s future. Here, we report the catastrophic long run-out Wayanad debris flow that occurred on 30th July 2024, which resulted in 231 fatalities and 128 people missing, and caused widespread destruction to infrastructure. This involved a maximum flow height of 10.66 m and maximum flow velocity of 18.7 m/s, simulated using RApid Mass Movement Simulation.
{"title":"A rapid run-out assessment methodology for the 2024 Wayanad debris flow","authors":"V. K. Krishnapriya, A. Rajaneesh, K. S. Sajinkumar, Thomas Oommen, Ali P. Yunus, Nikhil Nedumpallile Vasu, R. B. Binoj Kumar, S. Adarsh","doi":"10.1038/s44304-024-00044-5","DOIUrl":"10.1038/s44304-024-00044-5","url":null,"abstract":"The long run-out debris flows caused by oversaturated soil systems during the aggravated monsoon period in the Western Ghats raise questions about the hill community’s future. Here, we report the catastrophic long run-out Wayanad debris flow that occurred on 30th July 2024, which resulted in 231 fatalities and 128 people missing, and caused widespread destruction to infrastructure. This involved a maximum flow height of 10.66 m and maximum flow velocity of 18.7 m/s, simulated using RApid Mass Movement Simulation.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00044-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142790467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Machine learning (ML) models can simulate flood risk by identifying critical non-linear relationships between flood damage locations and flood risk factors (FRFs). To explore it, Tampa Bay, Florida, is selected as a test site. The study’s goal is to simulate flood risk and identify dominant FRFs using historical flood damage data as target variable, with 16 FRFs as predictor variables. Five different ML models such as decision tree (DT), support vector machine (SVM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and random forest (RF) were adopted. RF classifies 2.42% of Tampa Bay as very high risk and 2.54% as high risk, while XGBoost classifies 3.85% as very high risk and 1.11% as high risk. Moreover, the communities reside at low altitudes and near the waterbodies, with dense man-made infrastructure, are at high flood risk. This study introduces a comprehensive framework for flood risk assessment and helps policymakers mitigate flood risk.
{"title":"Simulating flood risk in Tampa Bay using a machine learning driven approach","authors":"Hemal Dey, Md Munjurul Haque, Wanyun Shao, Matthew VanDyke, Feng Hao","doi":"10.1038/s44304-024-00045-4","DOIUrl":"10.1038/s44304-024-00045-4","url":null,"abstract":"Machine learning (ML) models can simulate flood risk by identifying critical non-linear relationships between flood damage locations and flood risk factors (FRFs). To explore it, Tampa Bay, Florida, is selected as a test site. The study’s goal is to simulate flood risk and identify dominant FRFs using historical flood damage data as target variable, with 16 FRFs as predictor variables. Five different ML models such as decision tree (DT), support vector machine (SVM), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), and random forest (RF) were adopted. RF classifies 2.42% of Tampa Bay as very high risk and 2.54% as high risk, while XGBoost classifies 3.85% as very high risk and 1.11% as high risk. Moreover, the communities reside at low altitudes and near the waterbodies, with dense man-made infrastructure, are at high flood risk. This study introduces a comprehensive framework for flood risk assessment and helps policymakers mitigate flood risk.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00045-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142778629","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-05DOI: 10.1038/s44304-024-00040-9
Kristen M. Joyse, Michael L. Stein, Benjamin P. Horton, Robert E. Kopp
Estimates of extreme sea-level return periods guide flood hazard mitigation. Return period estimates calculated from tide gauge records, which are relatively short (typically less than 100 years), can fail to capture the rarest and most potentially impactful extreme events. Here, we employ a two-dimensional Poisson point process model to fuse water-level data from tide gauges with data from multi-century geologic records of extreme overwash events. Experiments with synthetic data show that including geologic data reduces the uncertainty of 1% and 0.1% average annual chance water levels by about half, relative to using tide gauge data alone. Similar uncertainty reductions occur with two case studies of geologic data (Mattapoisett Marsh, Massachusetts and Cheesequake, New Jersey) and their neighboring tide gauges (Woods Hole, Massachusetts and the Battery, New York). The analysis also reveals non-stationarity at Cheesequake and The Battery, arising from either climatic changes or changes in the fidelity of the geological record, with substantially higher 1–10% average annual chance water levels since 1900 compared to prior centuries.
{"title":"Multi-century geological data thins the tail of observationally based extreme sea level return period curves","authors":"Kristen M. Joyse, Michael L. Stein, Benjamin P. Horton, Robert E. Kopp","doi":"10.1038/s44304-024-00040-9","DOIUrl":"10.1038/s44304-024-00040-9","url":null,"abstract":"Estimates of extreme sea-level return periods guide flood hazard mitigation. Return period estimates calculated from tide gauge records, which are relatively short (typically less than 100 years), can fail to capture the rarest and most potentially impactful extreme events. Here, we employ a two-dimensional Poisson point process model to fuse water-level data from tide gauges with data from multi-century geologic records of extreme overwash events. Experiments with synthetic data show that including geologic data reduces the uncertainty of 1% and 0.1% average annual chance water levels by about half, relative to using tide gauge data alone. Similar uncertainty reductions occur with two case studies of geologic data (Mattapoisett Marsh, Massachusetts and Cheesequake, New Jersey) and their neighboring tide gauges (Woods Hole, Massachusetts and the Battery, New York). The analysis also reveals non-stationarity at Cheesequake and The Battery, arising from either climatic changes or changes in the fidelity of the geological record, with substantially higher 1–10% average annual chance water levels since 1900 compared to prior centuries.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00040-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142778660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1038/s44304-024-00035-6
Carolyn Kousky, Xuesong You
To protect households and communities from growing losses due to natural disasters and stabilize climate-stressed insurance markets, investments in cost-effective risk reduction must be expanded. Using a unique survey of survivors of one of four U.S. landfalling hurricanes, we investigate the decision to invest in mitigation measures during rebuilding. We find that insurers play a key role in this process by providing both information and financial incentives.
{"title":"The role of insurers in driving post-hurricane risk reduction investments","authors":"Carolyn Kousky, Xuesong You","doi":"10.1038/s44304-024-00035-6","DOIUrl":"10.1038/s44304-024-00035-6","url":null,"abstract":"To protect households and communities from growing losses due to natural disasters and stabilize climate-stressed insurance markets, investments in cost-effective risk reduction must be expanded. Using a unique survey of survivors of one of four U.S. landfalling hurricanes, we investigate the decision to invest in mitigation measures during rebuilding. We find that insurers play a key role in this process by providing both information and financial incentives.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00035-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1038/s44304-024-00039-2
Constance Ting Chua, Takuro Otake, Tanghua Li, An-Chi Cheng, Qiang Qiu, Linlin Li, Anawat Suppasri, Fumihiko Imamura, Adam D. Switzer
Seaports are vulnerable to extreme sea level events. Beyond physical damage, any port inoperability affects trade flows in and out of the affected port and disrupts shipping routes connected to it, which then propagates throughout the port network. Here, we propose an approach to assessing tsunami risk to ports and the global port network. We leverage on the topological properties of the global liner shipping network and centrality measures to quantify the potential impacts of a Manila Trench earthquake-tsunami under both present and future sea levels. We find that a Manila Trench tsunami could potentially damage up to 11 ports at present-day conditions and 15 ports under rising sea levels. Port closure could exceed 200 days and cause greater disruption to shipping routes than historical tsunami events. We also find that sea level rise is likely to result in uneven changes in tsunami heights spatially and hence, uneven impacts on the global port network.
{"title":"An approach to assessing tsunami risk to the global port network under rising sea levels","authors":"Constance Ting Chua, Takuro Otake, Tanghua Li, An-Chi Cheng, Qiang Qiu, Linlin Li, Anawat Suppasri, Fumihiko Imamura, Adam D. Switzer","doi":"10.1038/s44304-024-00039-2","DOIUrl":"10.1038/s44304-024-00039-2","url":null,"abstract":"Seaports are vulnerable to extreme sea level events. Beyond physical damage, any port inoperability affects trade flows in and out of the affected port and disrupts shipping routes connected to it, which then propagates throughout the port network. Here, we propose an approach to assessing tsunami risk to ports and the global port network. We leverage on the topological properties of the global liner shipping network and centrality measures to quantify the potential impacts of a Manila Trench earthquake-tsunami under both present and future sea levels. We find that a Manila Trench tsunami could potentially damage up to 11 ports at present-day conditions and 15 ports under rising sea levels. Port closure could exceed 200 days and cause greater disruption to shipping routes than historical tsunami events. We also find that sea level rise is likely to result in uneven changes in tsunami heights spatially and hence, uneven impacts on the global port network.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-13"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00039-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-04DOI: 10.1038/s44304-024-00037-4
Yilong Li, Zhenguo Zhang, Xiaofei Chen
Earthquakes remain unpredictable and pose significant challenges to disaster preparedness. This study develops a rapid assessment framework for earthquake disaster losses based on physical simulations, demonstrated through analysis of the 2021 Ms 6.4 Yangbi earthquake. A finite fault source based on observed data is employed on a GPU-accelerated 3D strong ground motion simulation platform. The computational process considers the effects of 3D heterogeneous velocity structure and terrain. Subsequently, this data is incorporated into a mathematical model for earthquake disaster loss assessment derived from historical statistics, evaluating emergency response levels, fatalities, and economic losses. The inclusion of teleseismic data into this framework underscores its extensive applicability for rapid loss assessments, even in regions lacking local seismic data. Through comparisons with station observation waveforms and government-reported loss, the validity and practicality of the framework were substantiated. It plays a vital role in assisting emergency decisions, optimizing resource allocation, and further mitigating losses.
{"title":"Developing a rapid assessment framework for China earthquake disaster losses: insights from physical simulations of the Yangbi earthquake","authors":"Yilong Li, Zhenguo Zhang, Xiaofei Chen","doi":"10.1038/s44304-024-00037-4","DOIUrl":"10.1038/s44304-024-00037-4","url":null,"abstract":"Earthquakes remain unpredictable and pose significant challenges to disaster preparedness. This study develops a rapid assessment framework for earthquake disaster losses based on physical simulations, demonstrated through analysis of the 2021 Ms 6.4 Yangbi earthquake. A finite fault source based on observed data is employed on a GPU-accelerated 3D strong ground motion simulation platform. The computational process considers the effects of 3D heterogeneous velocity structure and terrain. Subsequently, this data is incorporated into a mathematical model for earthquake disaster loss assessment derived from historical statistics, evaluating emergency response levels, fatalities, and economic losses. The inclusion of teleseismic data into this framework underscores its extensive applicability for rapid loss assessments, even in regions lacking local seismic data. Through comparisons with station observation waveforms and government-reported loss, the validity and practicality of the framework were substantiated. It plays a vital role in assisting emergency decisions, optimizing resource allocation, and further mitigating losses.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00037-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142762979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-12-02DOI: 10.1038/s44304-024-00043-6
Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, Renata Libonati
{"title":"Author Correction: Compound dry-hot-fire events connecting Central and Southeastern South America: an unapparent and deadly ripple effect","authors":"Djacinto Monteiro dos Santos, Aline M. de Oliveira, Ediclê S. F. Duarte, Julia A. Rodrigues, Lucas S. Menezes, Ronaldo Albuquerque, Fabio de O. Roque, Leonardo F. Peres, Judith J. Hoelzemann, Renata Libonati","doi":"10.1038/s44304-024-00043-6","DOIUrl":"10.1038/s44304-024-00043-6","url":null,"abstract":"","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00043-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142758120","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-11-22DOI: 10.1038/s44304-024-00034-7
Thomas J. Jones, Harry Nyce Jr., Yannick Le Moigne, Glyn Williams-Jones, Deanna Nyce
Indigenous peoples are widely affected by natural hazards and their history and knowledge can directly inform on past events and mitigation strategies. Here we show how effective co-creation of resources and bi-lateral knowledge exchange between natural hazard researchers and local Indigenous communities provides an effective, equitable, and sustainable way to conduct research.
{"title":"Rethinking natural hazards research and engagement to include co-creation with Indigenous communities","authors":"Thomas J. Jones, Harry Nyce Jr., Yannick Le Moigne, Glyn Williams-Jones, Deanna Nyce","doi":"10.1038/s44304-024-00034-7","DOIUrl":"10.1038/s44304-024-00034-7","url":null,"abstract":"Indigenous peoples are widely affected by natural hazards and their history and knowledge can directly inform on past events and mitigation strategies. Here we show how effective co-creation of resources and bi-lateral knowledge exchange between natural hazard researchers and local Indigenous communities provides an effective, equitable, and sustainable way to conduct research.","PeriodicalId":501712,"journal":{"name":"npj Natural Hazards","volume":" ","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44304-024-00034-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142679961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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