Pub Date : 2024-02-15DOI: 10.5194/nhess-24-539-2024
Laurence Hawker, J. Neal, J. Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, Pham Khanh Nam
Abstract. Flooding is an endemic global challenge with annual damages totalling billions of dollars. Impacts are felt most acutely in low- and middle-income countries, where rapid demographic change is driving increased exposure. These areas also tend to lack high-precision hazard mapping data with which to better understand or manage risk. To address this information gap a number of global flood models have been developed in recent years. However, there is substantial uncertainty over the performance of these data products. Arguably the most important component of a global flood model is the digital elevation model (DEM), which must represent the terrain without surface artifacts such as forests and buildings. Here we develop and evaluate a next generation of global hydrodynamic flood model based on the recently released FABDEM DEM. We evaluate the model and compare it to a previous version using the MERIT DEM at three study sites in the Central Highlands of Vietnam using two independent validation data sets based on a household survey and remotely sensed observations of recent flooding. The global flood model based on FABDEM consistently outperformed a model based on MERIT, and the agreement between the model and remote sensing was greater than the agreement between the two validation data sets.
摘要洪水是一个普遍存在的全球性挑战，每年造成的损失总计数十亿美元。中低收入国家受到的影响最为严重，因为这些国家人口的快速变化导致洪灾风险增加。这些地区往往也缺乏高精度的灾害测绘数据，无法更好地了解或管理风险。为了填补这一信息空白，近年来开发了一些全球洪水模型。然而，这些数据产品的性能还存在很大的不确定性。可以说，全球洪水模型最重要的组成部分是数字高程模型（DEM），它必须代表没有森林和建筑物等地表人工痕迹的地形。在此，我们以最近发布的 FABDEM DEM 为基础，开发并评估了新一代全球水动力洪水模型。我们在越南中部高原的三个研究地点，使用基于家庭调查和近期洪水遥感观测的两个独立验证数据集，对该模型进行了评估，并将其与使用 MERIT DEM 的前一版本进行了比较。基于 FABDEM 的全球洪水模型始终优于基于 MERIT 的模型，模型与遥感数据之间的一致性大于两个验证数据集之间的一致性。
{"title":"Assessing LISFLOOD-FP with the next-generation digital elevation model FABDEM using household survey and remote sensing data in the Central Highlands of Vietnam","authors":"Laurence Hawker, J. Neal, J. Savage, Thomas Kirkpatrick, Rachel Lord, Yanos Zylberberg, Andre Groeger, Truong Dang Thuy, Sean Fox, Felix Agyemang, Pham Khanh Nam","doi":"10.5194/nhess-24-539-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-539-2024","url":null,"abstract":"Abstract. Flooding is an endemic global challenge with annual damages totalling billions of dollars. Impacts are felt most acutely in low- and middle-income countries, where rapid demographic change is driving increased exposure. These areas also tend to lack high-precision hazard mapping data with which to better understand or manage risk. To address this information gap a number of global flood models have been developed in recent years. However, there is substantial uncertainty over the performance of these data products. Arguably the most important component of a global flood model is the digital elevation model (DEM), which must represent the terrain without surface artifacts such as forests and buildings. Here we develop and evaluate a next generation of global hydrodynamic flood model based on the recently released FABDEM DEM. We evaluate the model and compare it to a previous version using the MERIT DEM at three study sites in the Central Highlands of Vietnam using two independent validation data sets based on a household survey and remotely sensed observations of recent flooding. The global flood model based on FABDEM consistently outperformed a model based on MERIT, and the agreement between the model and remote sensing was greater than the agreement between the two validation data sets.\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":"24 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139836149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.5194/nhess-24-481-2024
Elke M. I. Meyer, L. Gaslikova
Abstract. Century reanalysis models offer a possibility to investigate extreme events and gain further insights into their impact through numerical experiments. This paper is a comprehensive summary of historical hazardous storm tides in the German Bight (southern North Sea) with the aim of comparing and evaluating the potential of different century reanalysis data to be used for the reconstruction of extreme water levels. The composite analysis of historical water level extremes, underlying atmospheric situations and their uncertainties may further support decision-making on coastal protection and risk assessment. The analysis is done based on the results of the regional hydrodynamic model simulations forced by atmospheric century reanalysis data, e.g. 20th Century Reanalysis Project (20CR) ensembles, ERA5 and UERRA–HARMONIE. The eight selected historical storms lead either to the highest storm tide extremes for at least one of three locations around the German Bight or to extreme storm surge events during low tide. In general, extreme storm tides could be reproduced, and some individual ensemble members are suitable for the reconstruction of respective storm tides. However, the highest observed water level in the German Bight could not be simulated with any considered forcing. The particular weather situations with corresponding storm tracks are analysed to better understand their different impact on the peak storm tides, their variability and their predictability. Storms with more northerly tracks generally show less variability in wind speed and a better agreement with the observed extreme water levels for the German Bight. The impact of two severe historical storms that peaked at low tide is investigated with shifted tides. For Husum in the eastern German Bight this results in a substantial increase in the peak water levels reaching a historical maximum.
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Pub Date : 2024-02-14DOI: 10.5194/nhess-24-501-2024
Andrea Abbate, L. Mancusi, Francesco Apadula, Antonella Frigerio, M. Papini, L. Longoni
Abstract. This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.
{"title":"CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale","authors":"Andrea Abbate, L. Mancusi, Francesco Apadula, Antonella Frigerio, M. Papini, L. Longoni","doi":"10.5194/nhess-24-501-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-501-2024","url":null,"abstract":"Abstract. This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":"9 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139837357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-14DOI: 10.5194/nhess-24-481-2024
Elke M. I. Meyer, L. Gaslikova
Abstract. Century reanalysis models offer a possibility to investigate extreme events and gain further insights into their impact through numerical experiments. This paper is a comprehensive summary of historical hazardous storm tides in the German Bight (southern North Sea) with the aim of comparing and evaluating the potential of different century reanalysis data to be used for the reconstruction of extreme water levels. The composite analysis of historical water level extremes, underlying atmospheric situations and their uncertainties may further support decision-making on coastal protection and risk assessment. The analysis is done based on the results of the regional hydrodynamic model simulations forced by atmospheric century reanalysis data, e.g. 20th Century Reanalysis Project (20CR) ensembles, ERA5 and UERRA–HARMONIE. The eight selected historical storms lead either to the highest storm tide extremes for at least one of three locations around the German Bight or to extreme storm surge events during low tide. In general, extreme storm tides could be reproduced, and some individual ensemble members are suitable for the reconstruction of respective storm tides. However, the highest observed water level in the German Bight could not be simulated with any considered forcing. The particular weather situations with corresponding storm tracks are analysed to better understand their different impact on the peak storm tides, their variability and their predictability. Storms with more northerly tracks generally show less variability in wind speed and a better agreement with the observed extreme water levels for the German Bight. The impact of two severe historical storms that peaked at low tide is investigated with shifted tides. For Husum in the eastern German Bight this results in a substantial increase in the peak water levels reaching a historical maximum.
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Pub Date : 2024-02-14DOI: 10.5194/nhess-24-501-2024
Andrea Abbate, L. Mancusi, Francesco Apadula, Antonella Frigerio, M. Papini, L. Longoni
Abstract. This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.
{"title":"CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment): a new model for geo-hydrological hazard assessment at the basin scale","authors":"Andrea Abbate, L. Mancusi, Francesco Apadula, Antonella Frigerio, M. Papini, L. Longoni","doi":"10.5194/nhess-24-501-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-501-2024","url":null,"abstract":"Abstract. This work presents the new model called CRHyME (Climatic Rainfall Hydrogeological Modelling Experiment), a tool for geo-hydrological hazard evaluation. CRHyME is a physically based and spatially distributed model written in the Python language that represents an extension of the classic hydrological models working at the basin scale. CRHyME's main focus consists of simulating rainfall-induced geo-hydrological instabilities such as shallow landslides, debris flows, catchment erosion and sediment transport into a river. These phenomena are conventionally decoupled from a hydrological routine, while in CRHyME they are simultaneously and quantitatively evaluated within the same code through a multi-hazard approach. CRHyME is applied within some case studies across northern Italy. Among these, the Caldone catchment, a well-monitored basin of 27 km2 located near the city of Lecco (Lombardy), was considered for the calibration of solid-transport routine testing, as well as the spatial-scale dependence related to digital terrain resolution. CRHyME was applied across larger basins of the Valtellina (Alps) and Emilia (Apennines) areas (∼2600 km2) which have experienced severe geo-hydrological episodes triggered by heavy precipitation in the recent past. CRHyME's validation has been assessed through NSE (Nash–Sutcliffe efficiency) and RMSE (root mean square error) hydrological-error metrics, while for landslides the ROC (receiver operating characteristic) methodology was applied. CRHyME has been able to reconstruct the river discharge at the reference hydrometric stations located at the outlets of the basins to estimate the sediment yield at some hydropower reservoirs chosen as a reference and to individuate the location and the triggering conditions of shallow landslides and debris flows. The good performance of CRHyME was reached, assuring the stability of the code and a rather fast computation and maintaining the numerical conservativity of water and sediment balances. CRHyME has shown itself to be a suitable tool for the quantification of the geo-hydrological process and thus useful for civil-protection multi-hazard assessment.\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":"28 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139777618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-13DOI: 10.5194/nhess-24-465-2024
Sudhanshu Dixit, Srikrishnan Siva Subramanian, P. Srivastava, Ali P. Yunus, T. Martha, Sumit Sen
Abstract. Debris flows triggered by rainfall are catastrophic geohazards that occur compounded during extreme events. Few early warning systems for shallow landslides and debris flows at the territorial scale use thresholds of rainfall intensity–duration (ID). ID thresholds are mostly defined using hourly rainfall. Due to instrumental and operational challenges, current early warning systems have difficulty forecasting sub-daily time series of weather for landslides in the Himalayas. Here, we present a framework that employs a spatio-temporal numerical model preceded by the Weather Research And Forecast (WRF) Model for analysing debris flows induced by rainfall. The WRF model runs at 1.8 km × 1.8 km resolution to produce hourly rainfall. The hourly rainfall is then used as an input boundary condition in the spatio-temporal numerical model for debris flows. The debris flow model is an updated version of Van Asch et al. (2014) in which sensitivity to volumetric water content, moisture-content-dependent hydraulic conductivity, and seepage routines are introduced within the governing equations. The spatio-temporal numerical model of debris flows is first calibrated for the mass movements in the Kedarnath catchment that occurred during the 2013 North India floods. Various precipitation intensities based on the glossary of the India Meteorological Department (IMD) are set, and parametric numerical simulations are run identifying ID thresholds of debris flows. Our findings suggest that the WRF model combined with the debris flow numerical model shall be used to establish ID thresholds in territorial landslide early warning systems (Te-LEWSs).
摘要降雨引发的泥石流是灾难性的地质灾害，在极端事件中会加剧。全境范围内的浅层滑坡和泥石流预警系统很少使用降雨强度-持续时间（ID）阈值。降雨强度-持续时间（ID）阈值大多使用小时降雨量来定义。由于仪器和操作方面的挑战，目前的预警系统很难预报喜马拉雅山滑坡的亚日时间序列天气。在此，我们提出了一个框架，利用气象研究与预测模型（WRF）之前的时空数值模型来分析降雨诱发的泥石流。WRF 模型以 1.8 千米 × 1.8 千米的分辨率运行，生成每小时降雨量。然后，每小时降雨量被用作泥石流时空数值模式的输入边界条件。泥石流模型是 Van Asch 等人（2014 年）的更新版，其中在控制方程中引入了对体积含水量的敏感性、与含水量相关的水力传导性和渗流程序。泥石流时空数值模型首先针对 2013 年北印度洪水期间发生在 Kedarnath 流域的泥石流运动进行了校准。根据印度气象局（IMD）的术语表设定了各种降水强度，并进行了参数数值模拟，以确定泥石流的ID阈值。我们的研究结果表明，WRF 模型与泥石流数值模型相结合，可用于确定领土滑坡预警系统（Te-LEWS）的 ID 阈值。
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Pub Date : 2024-02-13DOI: 10.5194/nhess-24-465-2024
Sudhanshu Dixit, Srikrishnan Siva Subramanian, P. Srivastava, Ali P. Yunus, T. Martha, Sumit Sen
Abstract. Debris flows triggered by rainfall are catastrophic geohazards that occur compounded during extreme events. Few early warning systems for shallow landslides and debris flows at the territorial scale use thresholds of rainfall intensity–duration (ID). ID thresholds are mostly defined using hourly rainfall. Due to instrumental and operational challenges, current early warning systems have difficulty forecasting sub-daily time series of weather for landslides in the Himalayas. Here, we present a framework that employs a spatio-temporal numerical model preceded by the Weather Research And Forecast (WRF) Model for analysing debris flows induced by rainfall. The WRF model runs at 1.8 km × 1.8 km resolution to produce hourly rainfall. The hourly rainfall is then used as an input boundary condition in the spatio-temporal numerical model for debris flows. The debris flow model is an updated version of Van Asch et al. (2014) in which sensitivity to volumetric water content, moisture-content-dependent hydraulic conductivity, and seepage routines are introduced within the governing equations. The spatio-temporal numerical model of debris flows is first calibrated for the mass movements in the Kedarnath catchment that occurred during the 2013 North India floods. Various precipitation intensities based on the glossary of the India Meteorological Department (IMD) are set, and parametric numerical simulations are run identifying ID thresholds of debris flows. Our findings suggest that the WRF model combined with the debris flow numerical model shall be used to establish ID thresholds in territorial landslide early warning systems (Te-LEWSs).
摘要降雨引发的泥石流是灾难性的地质灾害，在极端事件中会加剧。全境范围内的浅层滑坡和泥石流预警系统很少使用降雨强度-持续时间（ID）阈值。降雨强度-持续时间（ID）阈值大多使用小时降雨量来定义。由于仪器和操作方面的挑战，目前的预警系统很难预报喜马拉雅山滑坡的亚日时间序列天气。在此，我们提出了一个框架，利用气象研究与预测模型（WRF）之前的时空数值模型来分析降雨诱发的泥石流。WRF 模型以 1.8 千米 × 1.8 千米的分辨率运行，生成每小时降雨量。然后，每小时降雨量被用作泥石流时空数值模式的输入边界条件。泥石流模型是 Van Asch 等人（2014 年）的更新版，其中在控制方程中引入了对体积含水量的敏感性、与含水量相关的水力传导性和渗流程序。泥石流时空数值模型首先针对 2013 年北印度洪水期间发生在 Kedarnath 流域的泥石流运动进行了校准。根据印度气象局（IMD）的术语表设定了各种降水强度，并进行了参数数值模拟，以确定泥石流的ID阈值。我们的研究结果表明，WRF 模型与泥石流数值模型相结合，可用于确定领土滑坡预警系统（Te-LEWS）的 ID 阈值。
{"title":"Numerical-model-derived intensity–duration thresholds for early warning of rainfall-induced debris flows in a Himalayan catchment","authors":"Sudhanshu Dixit, Srikrishnan Siva Subramanian, P. Srivastava, Ali P. Yunus, T. Martha, Sumit Sen","doi":"10.5194/nhess-24-465-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-465-2024","url":null,"abstract":"Abstract. Debris flows triggered by rainfall are catastrophic geohazards that occur compounded during extreme events. Few early warning systems for shallow landslides and debris flows at the territorial scale use thresholds of rainfall intensity–duration (ID). ID thresholds are mostly defined using hourly rainfall. Due to instrumental and operational challenges, current early warning systems have difficulty forecasting sub-daily time series of weather for landslides in the Himalayas. Here, we present a framework that employs a spatio-temporal numerical model preceded by the Weather Research And Forecast (WRF) Model for analysing debris flows induced by rainfall. The WRF model runs at 1.8 km × 1.8 km resolution to produce hourly rainfall. The hourly rainfall is then used as an input boundary condition in the spatio-temporal numerical model for debris flows. The debris flow model is an updated version of Van Asch et al. (2014) in which sensitivity to volumetric water content, moisture-content-dependent hydraulic conductivity, and seepage routines are introduced within the governing equations. The spatio-temporal numerical model of debris flows is first calibrated for the mass movements in the Kedarnath catchment that occurred during the 2013 North India floods. Various precipitation intensities based on the glossary of the India Meteorological Department (IMD) are set, and parametric numerical simulations are run identifying ID thresholds of debris flows. Our findings suggest that the WRF model combined with the debris flow numerical model shall be used to establish ID thresholds in territorial landslide early warning systems (Te-LEWSs).\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":"107 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139781099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-09DOI: 10.5194/nhess-24-445-2024
Jonas Mortelmans, A. Felsberg, Gabriëlle J. M. De Lannoy, S. Veraverbeke, Robert D. Field, Niels Andela, Michel Bechtold
Abstract. The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.
{"title":"Improving the fire weather index system for peatlands using peat-specific hydrological input data","authors":"Jonas Mortelmans, A. Felsberg, Gabriëlle J. M. De Lannoy, S. Veraverbeke, Robert D. Field, Niels Andela, Michel Bechtold","doi":"10.5194/nhess-24-445-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-445-2024","url":null,"abstract":"Abstract. The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":"63 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139849593","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-09DOI: 10.5194/nhess-24-445-2024
Jonas Mortelmans, A. Felsberg, Gabriëlle J. M. De Lannoy, S. Veraverbeke, Robert D. Field, Niels Andela, Michel Bechtold
Abstract. The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.
{"title":"Improving the fire weather index system for peatlands using peat-specific hydrological input data","authors":"Jonas Mortelmans, A. Felsberg, Gabriëlle J. M. De Lannoy, S. Veraverbeke, Robert D. Field, Niels Andela, Michel Bechtold","doi":"10.5194/nhess-24-445-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-445-2024","url":null,"abstract":"Abstract. The Canadian Fire Weather Index (FWI) system, even though originally developed and calibrated for an upland Jack pine forest, is used globally to estimate fire danger for any fire environment. However, for some environments, such as peatlands, the applicability of the FWI in its current form, is often questioned. In this study, we replaced the original moisture codes of the FWI with hydrological estimates resulting from the assimilation of satellite-based L-band passive microwave observations into a peatland-specific land surface model. In a conservative approach that maintains the integrity of the original FWI structure, the distributions of the hydrological estimates were first matched to those of the corresponding original moisture codes before replacement. The resulting adapted FWI, hereafter called FWIpeat, was evaluated using satellite-based information on fire presence over boreal peatlands from 2010 through 2018. Adapting the FWI with model- and satellite-based hydrological information was found to be beneficial in estimating fire danger, especially when replacing the deeper moisture codes of the FWI. For late-season fires, further adaptations of the fine fuel moisture code show even more improvement due to the fact that late-season fires are more hydrologically driven. The proposed FWIpeat should enable improved monitoring of fire risk in boreal peatlands.\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":" 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139789493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-08DOI: 10.5194/nhess-24-429-2024
Rimali Mitra, Hajime Naruse, Tomoya Abe
Abstract. The 2011 Tohoku-oki tsunami inundated the Joban coastal area in the Odaka region of the city of Minamisoma, up to 2818 m from the shoreline. In this study, the flow characteristics of the tsunami were reconstructed from deposits using the DNN (deep neural network) inverse model, suggesting that the tsunami inundation occurred in the Froude supercritical condition. The DNN inverse model effectively estimated the tsunami flow parameters in the Odaka region, including the maximum inundation distance, flow velocity, maximum flow depth, and sediment concentration. Despite having a few topographical anthropogenic undulations that caused the inundation height to fluctuate greatly, the reconstructed maximum flow depth and flow velocity were reasonable and close to the values reported in the field observations. The reconstructed data around the Odaka region were characterized by an extremely high velocity (12.1 m s−1). This study suggests that the large fluctuation in flow depths on the Joban Coast compared with the stable flow depths in the Sendai Plain can be explained by the inundation in the supercritical flow condition.
摘要2011 年的东北海啸淹没了南相马市大高地区的常磐沿海地区，距离海岸线长达 2818 米。在这项研究中，利用 DNN（深度神经网络）反模型从沉积物中重建了海啸的流动特征，表明海啸淹没发生在 Froude 超临界条件下。DNN 反演模型有效地估算了小田中地区的海啸流参数，包括最大淹没距离、流速、最大流深和沉积物浓度。尽管有一些地形人为起伏导致淹没高度波动较大，但重建的最大水流深度和水流速度是合理的，与实地观测报告的数值接近。小田中地区周围重建数据的特点是流速极高（12.1 m s-1）。这项研究表明，与仙台平原稳定的水流深度相比，常磐海岸的水流深度波动较大，这可以用超临界水流条件下的淹没来解释。
{"title":"Understanding flow characteristics from tsunami deposits at Odaka, Joban Coast, using a deep neural network (DNN) inverse model","authors":"Rimali Mitra, Hajime Naruse, Tomoya Abe","doi":"10.5194/nhess-24-429-2024","DOIUrl":"https://doi.org/10.5194/nhess-24-429-2024","url":null,"abstract":"Abstract. The 2011 Tohoku-oki tsunami inundated the Joban coastal area in the Odaka region of the city of Minamisoma, up to 2818 m from the shoreline. In this study, the flow characteristics of the tsunami were reconstructed from deposits using the DNN (deep neural network) inverse model, suggesting that the tsunami inundation occurred in the Froude supercritical condition. The DNN inverse model effectively estimated the tsunami flow parameters in the Odaka region, including the maximum inundation distance, flow velocity, maximum flow depth, and sediment concentration. Despite having a few topographical anthropogenic undulations that caused the inundation height to fluctuate greatly, the reconstructed maximum flow depth and flow velocity were reasonable and close to the values reported in the field observations. The reconstructed data around the Odaka region were characterized by an extremely high velocity (12.1 m s−1). This study suggests that the large fluctuation in flow depths on the Joban Coast compared with the stable flow depths in the Sendai Plain can be explained by the inundation in the supercritical flow condition.\u0000","PeriodicalId":508073,"journal":{"name":"Natural Hazards and Earth System Sciences","volume":" 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139791008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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