Pub Date : 2022-12-10DOI: 10.3390/geohazards3040027
Marco Márquez, C. Paredes, M. Llorente
The eruption of Cumbre Vieja (also known as Tajogaite volcano, 19 September–13 December 2021, Spain) is an example of successful emergency management. The lessons learnt are yet to be fully disclosed as is whether the response can be further improved. The latter may include tools to predict lava flow inundation rheological characteristics, amongst other issues related to volcanic eruptions (i.e., ash fall and gas emission). The aim of this study was to explore if a scientific open-source, readily available, lava-flow-modelling code (VolcFlow) would suffice for lava emplacement forecasting, focusing on the first seven days of the eruption. We only the open data that were released during the crisis and previously available data sets. The rheology of the lava, as well as the emission rate, are of utmost relevance when modelling lava flow, and these data were not readily available. Satellite lava extent analysis allowed us to preliminarily estimate its velocity, the average flow emitted, and flow viscosity. These estimates were numerically adjusted by maximising the Jaccard morphometric index and comparing the area flooded by the lava for a simulated seven-day advance with the real advance of the lava in the same timescale. The manual search for the solution to this optimization problem achieved morphometric matches of 85% and 60%. We obtained an estimated discharge rate of about 140 m3/s of lava flow during the first 24 h of the eruption. We found the emission rate then asymptotically decreased to 60 m3/s. Viscosity varied from 8 × 106 Pa s, or a yield strength of 42 × 103 Pa, in the first hours, to 4 × 107 Pa s and 35 × 103 Pa, respectively, during the remainder of the seven days. The simulations of the lava emplacement up to 27 September showed an acceptable distribution of lava thickness compared with the observations and an excellent geometrical fit. The calculations of the calibrated model required less time than the simulated time span; hence, flow modelling can be used for emergency management. However, both speed and accuracy can be improved with some extra developments and guidance on the data to be collected. Moreover, the available time for management, once the model is ready, quasi-linearly increases as the forecasting time is extended. This suggests that a predictive response during an emergency with similar characteristics is achievable, provided that an adequate rheological description of the lava is available.
Cumbre Vieja火山(也称为Tajogaite火山，2021年9月19日至12月13日，西班牙)的喷发是成功应急管理的一个例子。吸取的教训尚未充分披露，是否可以进一步改进应对措施也是如此。后者可能包括预测熔岩流淹没流变特性的工具，以及与火山爆发有关的其他问题(即灰烬落下和气体排放)。这项研究的目的是探索一个科学的、开源的、随时可用的熔岩流建模代码(VolcFlow)是否足以进行熔岩就位预测，重点是火山喷发的前七天。我们只使用危机期间发布的公开数据和之前可用的数据集。熔岩的流变性，以及排放率，在模拟熔岩流时是最重要的，而这些数据并不容易获得。卫星熔岩范围分析使我们能够初步估计其速度、平均流出流量和流动粘度。通过将Jaccard形态测量指数最大化，并将模拟的7天内熔岩淹没的区域与同一时间尺度下熔岩的实际推进进行比较，对这些估计进行了数值调整。手动搜索这个优化问题的解决方案实现了85%和60%的形态匹配。我们估计在火山爆发的前24小时，熔岩流的流量约为140 m3/s。我们发现排放率逐渐下降到60 m3/s。在7天的剩余时间里，粘度从最初的8 × 106 Pa s(即42 × 103 Pa)变化到4 × 107 Pa s和35 × 103 Pa。对9月27日以前熔岩就位的模拟表明，与观测结果相比，熔岩厚度的分布是可以接受的，而且几何上非常吻合。校正后的模型计算所需的时间比模拟时间短;因此，流模型可用于应急管理。但是，速度和准确性都可以通过一些额外的开发和收集数据的指导来提高。而且，一旦模型准备好，管理的可用时间随着预测时间的延长而准线性增加。这表明，只要对熔岩有充分的流变描述，在紧急情况下具有类似特征的预测反应是可以实现的。
{"title":"Attempt to Model Lava Flow Faster Than Real Time: An Example of La Palma Using VolcFlow","authors":"Marco Márquez, C. Paredes, M. Llorente","doi":"10.3390/geohazards3040027","DOIUrl":"https://doi.org/10.3390/geohazards3040027","url":null,"abstract":"The eruption of Cumbre Vieja (also known as Tajogaite volcano, 19 September–13 December 2021, Spain) is an example of successful emergency management. The lessons learnt are yet to be fully disclosed as is whether the response can be further improved. The latter may include tools to predict lava flow inundation rheological characteristics, amongst other issues related to volcanic eruptions (i.e., ash fall and gas emission). The aim of this study was to explore if a scientific open-source, readily available, lava-flow-modelling code (VolcFlow) would suffice for lava emplacement forecasting, focusing on the first seven days of the eruption. We only the open data that were released during the crisis and previously available data sets. The rheology of the lava, as well as the emission rate, are of utmost relevance when modelling lava flow, and these data were not readily available. Satellite lava extent analysis allowed us to preliminarily estimate its velocity, the average flow emitted, and flow viscosity. These estimates were numerically adjusted by maximising the Jaccard morphometric index and comparing the area flooded by the lava for a simulated seven-day advance with the real advance of the lava in the same timescale. The manual search for the solution to this optimization problem achieved morphometric matches of 85% and 60%. We obtained an estimated discharge rate of about 140 m3/s of lava flow during the first 24 h of the eruption. We found the emission rate then asymptotically decreased to 60 m3/s. Viscosity varied from 8 × 106 Pa s, or a yield strength of 42 × 103 Pa, in the first hours, to 4 × 107 Pa s and 35 × 103 Pa, respectively, during the remainder of the seven days. The simulations of the lava emplacement up to 27 September showed an acceptable distribution of lava thickness compared with the observations and an excellent geometrical fit. The calculations of the calibrated model required less time than the simulated time span; hence, flow modelling can be used for emergency management. However, both speed and accuracy can be improved with some extra developments and guidance on the data to be collected. Moreover, the available time for management, once the model is ready, quasi-linearly increases as the forecasting time is extended. This suggests that a predictive response during an emergency with similar characteristics is achievable, provided that an adequate rheological description of the lava is available.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"156 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2022-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76549658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-29DOI: 10.1080/17499518.2022.2149815
Geng-Fu He, Pin Zhang, Z. Yin, Yin‐Fu Jin, Yi Yang
ABSTRACT Conventional phenomenological elasto-viscoplastic models include numerous parameters that need to be calibrated by case-specific experiments. Data-driven modelling has recently emerged and provided an alternative to constitutive modelling. This study proposes a modelling framework based on multi-fidelity data to model the rate-dependent behaviour of soft clays. In this framework, low-fidelity (LF) data generated by an elasto-viscoplastic model and high-fidelity (HF) data from experimental tests are necessary. Stress–strain-strain rate correlations behind LF and HF data can be captured by long short-term memory and feedforward neural networks, respectively, such that final predictions can be given by a multi-fidelity residual neural network (MR-NN). Such a framework with the same LF data is applied in Hong Kong marine deposits and Merville clay to investigate its feasibility and generalisation ability. In addition, the effect of LF data on the performance of MR-NN is discussed to verify the robustness of the framework. All results demonstrate that rate-dependent undrained shear strength and pore-water pressure can be accurately modelled through the framework, showing adaptive non-linear modelling capability, less demand for experimental data, and superior robustness. These characteristics indicate a considerable potential in modelling the rate-dependent behaviour of clays.
{"title":"Multi-fidelity data-driven modelling of rate-dependent behaviour of soft clays","authors":"Geng-Fu He, Pin Zhang, Z. Yin, Yin‐Fu Jin, Yi Yang","doi":"10.1080/17499518.2022.2149815","DOIUrl":"https://doi.org/10.1080/17499518.2022.2149815","url":null,"abstract":"ABSTRACT Conventional phenomenological elasto-viscoplastic models include numerous parameters that need to be calibrated by case-specific experiments. Data-driven modelling has recently emerged and provided an alternative to constitutive modelling. This study proposes a modelling framework based on multi-fidelity data to model the rate-dependent behaviour of soft clays. In this framework, low-fidelity (LF) data generated by an elasto-viscoplastic model and high-fidelity (HF) data from experimental tests are necessary. Stress–strain-strain rate correlations behind LF and HF data can be captured by long short-term memory and feedforward neural networks, respectively, such that final predictions can be given by a multi-fidelity residual neural network (MR-NN). Such a framework with the same LF data is applied in Hong Kong marine deposits and Merville clay to investigate its feasibility and generalisation ability. In addition, the effect of LF data on the performance of MR-NN is discussed to verify the robustness of the framework. All results demonstrate that rate-dependent undrained shear strength and pore-water pressure can be accurately modelled through the framework, showing adaptive non-linear modelling capability, less demand for experimental data, and superior robustness. These characteristics indicate a considerable potential in modelling the rate-dependent behaviour of clays.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"17 1","pages":"64 - 76"},"PeriodicalIF":4.8,"publicationDate":"2022-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42909693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-26DOI: 10.3390/geohazards3040026
Anna Małka
This paper presents the results of landslide prediction modelling for young glacial areas performed using statistical methods. The area in question is urbanized and therefore mass wasting activity is a matter of interest to both the local community and the authorities. The analysis was based on the 2011 ‘Register of landslides and areas prone to mass movements with a scale of 1:10,000 for the city of Gdansk’ and the 2012 incomplete ‘Register of landslides and areas prone to mass movements with a scale of 1:10,000 for the city of Gdynia’. The research took into account geological, geomorphological, hydrological, hydrogeological, and anthropogenic conditions. The landslide susceptibility map was created using the statistical landslide index. The calculated indices were used to create a map of Gdansk’s landslide susceptibility. In Gdansk, 84.50% of the total diagnosed landslide area belongs to the high susceptibility class, 14.25% to the moderate susceptibility class, and only 1.25% to the low or very low susceptibility class. After extrapolation, the data was also used to create a susceptibility map for the remaining parts of the Tri-City area, Sopot and Gdynia. The difficulty of extrapolating landslide data for neighboring urban areas was indicated. In Gdansk, which had been covered by geological mapping, the best modelling results were obtained with a large number of causal factors. In Gdynia and Sopot, for which the statistical landslide index value was extrapolated from Gdansk, the best results were obtained when selected causal factors were considered. In Sopot and Gdynia, 81.6% of the landslide area belongs to the high susceptibility class, 15.1% to the moderate class, and 3.3% to the low susceptibility class. These results emphasize a different role of some causal factor classes in the occurrence of landslides in neighboring urban areas. The resultant maps show the areas in which mass wasting is the most probable in the future.
{"title":"GIS-Based Landslide Susceptibility Modelling in Urbanized Areas: A Case Study of the Tri-City Area of Poland","authors":"Anna Małka","doi":"10.3390/geohazards3040026","DOIUrl":"https://doi.org/10.3390/geohazards3040026","url":null,"abstract":"This paper presents the results of landslide prediction modelling for young glacial areas performed using statistical methods. The area in question is urbanized and therefore mass wasting activity is a matter of interest to both the local community and the authorities. The analysis was based on the 2011 ‘Register of landslides and areas prone to mass movements with a scale of 1:10,000 for the city of Gdansk’ and the 2012 incomplete ‘Register of landslides and areas prone to mass movements with a scale of 1:10,000 for the city of Gdynia’. The research took into account geological, geomorphological, hydrological, hydrogeological, and anthropogenic conditions. The landslide susceptibility map was created using the statistical landslide index. The calculated indices were used to create a map of Gdansk’s landslide susceptibility. In Gdansk, 84.50% of the total diagnosed landslide area belongs to the high susceptibility class, 14.25% to the moderate susceptibility class, and only 1.25% to the low or very low susceptibility class. After extrapolation, the data was also used to create a susceptibility map for the remaining parts of the Tri-City area, Sopot and Gdynia. The difficulty of extrapolating landslide data for neighboring urban areas was indicated. In Gdansk, which had been covered by geological mapping, the best modelling results were obtained with a large number of causal factors. In Gdynia and Sopot, for which the statistical landslide index value was extrapolated from Gdansk, the best results were obtained when selected causal factors were considered. In Sopot and Gdynia, 81.6% of the landslide area belongs to the high susceptibility class, 15.1% to the moderate class, and 3.3% to the low susceptibility class. These results emphasize a different role of some causal factor classes in the occurrence of landslides in neighboring urban areas. The resultant maps show the areas in which mass wasting is the most probable in the future.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"19 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74931010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-23DOI: 10.1080/17499518.2022.2138918
Lizhou Wu, J. Zhou, H. Zhang, S. R. Wang, Tengyu Ma, H. Yan, S. H. Li
{"title":"Time series analysis and gated recurrent neural network model for predicting landslide displacements","authors":"Lizhou Wu, J. Zhou, H. Zhang, S. R. Wang, Tengyu Ma, H. Yan, S. H. Li","doi":"10.1080/17499518.2022.2138918","DOIUrl":"https://doi.org/10.1080/17499518.2022.2138918","url":null,"abstract":"","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"1 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2022-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41765360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-17DOI: 10.1080/17499518.2022.2132263
J. Zhang, Hongli Yao, Zi-peng Wang, Yaning Xue, Lu-lu Zhang
ABSTRACT The inverse velocity (INV) method is widely used for predicting the slope failure time. When applying the INV method, the inverse velocity can be assumed to be a linear and non-linear function of time, respectively, which are called linear and non-linear INV methods in this paper, respectively. Very few guidance is available in the literatures on the use of the two types of INV methods. In this paper, the performances of the linear and non-linear INV methods are assessed using a landslide database with 55 case histories. It is found that, two types of pitfalls may be encountered when applying the non-linear INV method, i.e. the saddle point and the ill-conditioned Hessian matrix. For the landslides examined in this paper, the linear INV method is free from the two pitfalls. When these pitfalls are encountered, the failure time predicted based on the non-linear INV methods may be significantly different from the actual slope failure time. For the landslides examined in this paper, the linear INV method is not only more stable, but also more accurate than the non-linear INV method. It is suggested that the linear INV method should be preferred over the non-linear INV method in future applications.
{"title":"On prediction of slope failure time with the inverse velocity method","authors":"J. Zhang, Hongli Yao, Zi-peng Wang, Yaning Xue, Lu-lu Zhang","doi":"10.1080/17499518.2022.2132263","DOIUrl":"https://doi.org/10.1080/17499518.2022.2132263","url":null,"abstract":"ABSTRACT The inverse velocity (INV) method is widely used for predicting the slope failure time. When applying the INV method, the inverse velocity can be assumed to be a linear and non-linear function of time, respectively, which are called linear and non-linear INV methods in this paper, respectively. Very few guidance is available in the literatures on the use of the two types of INV methods. In this paper, the performances of the linear and non-linear INV methods are assessed using a landslide database with 55 case histories. It is found that, two types of pitfalls may be encountered when applying the non-linear INV method, i.e. the saddle point and the ill-conditioned Hessian matrix. For the landslides examined in this paper, the linear INV method is free from the two pitfalls. When these pitfalls are encountered, the failure time predicted based on the non-linear INV methods may be significantly different from the actual slope failure time. For the landslides examined in this paper, the linear INV method is not only more stable, but also more accurate than the non-linear INV method. It is suggested that the linear INV method should be preferred over the non-linear INV method in future applications.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"17 1","pages":"114 - 126"},"PeriodicalIF":4.8,"publicationDate":"2022-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44941635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-11-07DOI: 10.1080/17499518.2022.2136717
M. Chwała, K. Phoon, M. Uzielli, Jie Zhang, Limin Zhang, J. Ching
ABSTRACT This paper is motivated by the Time Capsule Project (TCP) of the International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE). The historical developments of geotechnical risk and reliability are reviewed for the past six decades. The key features distinguishing geotechnical and structural engineering are the natural origin of the ground and the lack of sufficient data to characterize the ground using the more familiar frequentist interpretation of probability. For the first feature, random field theory is applied to model spatial variability and the random finite element method or other methods are proposed for solving soil-structure interaction problems in spatially variable soil. For the second feature, compilation of databases is essential to serve as priors for Bayesian updating and more recently for Bayesian machine learning. There is a gradual evolution towards reliability-based design because probabilistic methods offer a pathway to address big data and implement data-centric geotechnics as one step towards digital transformation. Given the complexity of the natural ground (known unknowns can be large and there are unknown unknowns), engineering judgment remains important to bridge the gap between theory and practice. However, the role of engineering judgment needs to be updated as modern machine learning methods become more powerful.
{"title":"Time capsule for geotechnical risk and reliability","authors":"M. Chwała, K. Phoon, M. Uzielli, Jie Zhang, Limin Zhang, J. Ching","doi":"10.1080/17499518.2022.2136717","DOIUrl":"https://doi.org/10.1080/17499518.2022.2136717","url":null,"abstract":"ABSTRACT This paper is motivated by the Time Capsule Project (TCP) of the International Society for Soil Mechanics and Geotechnical Engineering (ISSMGE). The historical developments of geotechnical risk and reliability are reviewed for the past six decades. The key features distinguishing geotechnical and structural engineering are the natural origin of the ground and the lack of sufficient data to characterize the ground using the more familiar frequentist interpretation of probability. For the first feature, random field theory is applied to model spatial variability and the random finite element method or other methods are proposed for solving soil-structure interaction problems in spatially variable soil. For the second feature, compilation of databases is essential to serve as priors for Bayesian updating and more recently for Bayesian machine learning. There is a gradual evolution towards reliability-based design because probabilistic methods offer a pathway to address big data and implement data-centric geotechnics as one step towards digital transformation. Given the complexity of the natural ground (known unknowns can be large and there are unknown unknowns), engineering judgment remains important to bridge the gap between theory and practice. However, the role of engineering judgment needs to be updated as modern machine learning methods become more powerful.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"17 1","pages":"439 - 466"},"PeriodicalIF":4.8,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43944986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-27DOI: 10.1080/17499518.2022.2101067
Saeed Askarian, A. Fakher
ABSTRACT The life cycle cost (LCC) design method tries to improve conventional design practices with different costs, such as risk costs, over the life cycle of the structure in the design procedure. The present study introduces a modified life cycle cost (MLCC) approach for the design of excavations. Some modifications proposed in the typical LCC design method include considering the effect of risk aversion/seeking of decision-makers in the main LCC formula by a risk-seeking factor and taking in the effect of risk exposure time on risk cost by a risk duration as an impact factor. The risk-seeking factor is obtained by identifying the risky behaviour of decision-makers based on the expected utility theory. The risk duration impact factor is evaluated by analysing statistical information about high-risk excavations versus their lifetime. The novel MLCC design method is evaluated in real deep urban excavation projects and the method is applicable for design and yields sensible outputs.
{"title":"The modified life cycle cost method for the risk-based design of excavation projects","authors":"Saeed Askarian, A. Fakher","doi":"10.1080/17499518.2022.2101067","DOIUrl":"https://doi.org/10.1080/17499518.2022.2101067","url":null,"abstract":"ABSTRACT The life cycle cost (LCC) design method tries to improve conventional design practices with different costs, such as risk costs, over the life cycle of the structure in the design procedure. The present study introduces a modified life cycle cost (MLCC) approach for the design of excavations. Some modifications proposed in the typical LCC design method include considering the effect of risk aversion/seeking of decision-makers in the main LCC formula by a risk-seeking factor and taking in the effect of risk exposure time on risk cost by a risk duration as an impact factor. The risk-seeking factor is obtained by identifying the risky behaviour of decision-makers based on the expected utility theory. The risk duration impact factor is evaluated by analysing statistical information about high-risk excavations versus their lifetime. The novel MLCC design method is evaluated in real deep urban excavation projects and the method is applicable for design and yields sensible outputs.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"17 1","pages":"310 - 329"},"PeriodicalIF":4.8,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46495625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-26DOI: 10.3390/geohazards3040025
Giovanni Cárdenas, P. Catalán
The role of the Manning roughness coefficient in modifying a tsunami time series of flow depth inundation was studied in Iquique, Chile, using a single synthetic earthquake scenario. A high-resolution digital surface model was used as a reference configuration, and several bare land models using constant roughness were tested with different grid resolutions. As previously reported, increasing the Manning n value beyond the standard values is essential to reproduce mean statistics such as the inundated area extent and maximum flow depth. The arrival time showed to be less sensitive to changes in the Manning n value, at least in terms of the magnitude of the error. However, increasing the Manning n value too much leads to a critical change in the characteristics of the flow, which departs from its bore-like structure to a more gradual and persistent inundation. It was found that it is possible to find a Manning n value that resembles most features of the reference flow using less resolution in the numerical grids. This allows us to speed up inundation tsunami modeling, which could be useful when multiple inundation simulations are required.
{"title":"Accelerating Tsunami Modeling for Evacuation Studies through Modification of the Manning Roughness Values","authors":"Giovanni Cárdenas, P. Catalán","doi":"10.3390/geohazards3040025","DOIUrl":"https://doi.org/10.3390/geohazards3040025","url":null,"abstract":"The role of the Manning roughness coefficient in modifying a tsunami time series of flow depth inundation was studied in Iquique, Chile, using a single synthetic earthquake scenario. A high-resolution digital surface model was used as a reference configuration, and several bare land models using constant roughness were tested with different grid resolutions. As previously reported, increasing the Manning n value beyond the standard values is essential to reproduce mean statistics such as the inundated area extent and maximum flow depth. The arrival time showed to be less sensitive to changes in the Manning n value, at least in terms of the magnitude of the error. However, increasing the Manning n value too much leads to a critical change in the characteristics of the flow, which departs from its bore-like structure to a more gradual and persistent inundation. It was found that it is possible to find a Manning n value that resembles most features of the reference flow using less resolution in the numerical grids. This allows us to speed up inundation tsunami modeling, which could be useful when multiple inundation simulations are required.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"99 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2022-10-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81649974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-14DOI: 10.1080/17499518.2022.2132262
Yajun Li, Jianguang Li, N. Xu, G. Fenton, P. Vardon, M. Hicks
ABSTRACT Correlation length or scale of fluctuation (SOF) is often used as a primary parameter in defining the spatial correlation characteristics of varying soil properties. However, geotechnical site investigations are rather limited so that proper determination of correlation length is not always possible. The concept of a worst-case correlation length thus has important implications in reliability-based designs. In the case of insufficient information, the worst-case correlation length can be used to conservatively estimate the reliability or probability of failure of geotechnical structures. However, the definition of the worst-case correlation length in the literature is not very clear and has been seen in some investigations to not exist. This paper, in the context of bearing capacity of 3D spatially varying soils, investigates the worst-case correlation length based on different definitions to clarify past findings. Further analyses provide insight into practical applications, where the impact of site sampled data and realistic uncertainties are considered. Using realistic values of the coefficient of variation, and taking account of the distance at which site investigation is likely to occur from the loaded area, a worst-case SOF is identified and found to be similar using all definitions.
{"title":"On worst-case correlation length in probabilistic 3D bearing capacity assessments","authors":"Yajun Li, Jianguang Li, N. Xu, G. Fenton, P. Vardon, M. Hicks","doi":"10.1080/17499518.2022.2132262","DOIUrl":"https://doi.org/10.1080/17499518.2022.2132262","url":null,"abstract":"ABSTRACT Correlation length or scale of fluctuation (SOF) is often used as a primary parameter in defining the spatial correlation characteristics of varying soil properties. However, geotechnical site investigations are rather limited so that proper determination of correlation length is not always possible. The concept of a worst-case correlation length thus has important implications in reliability-based designs. In the case of insufficient information, the worst-case correlation length can be used to conservatively estimate the reliability or probability of failure of geotechnical structures. However, the definition of the worst-case correlation length in the literature is not very clear and has been seen in some investigations to not exist. This paper, in the context of bearing capacity of 3D spatially varying soils, investigates the worst-case correlation length based on different definitions to clarify past findings. Further analyses provide insight into practical applications, where the impact of site sampled data and realistic uncertainties are considered. Using realistic values of the coefficient of variation, and taking account of the distance at which site investigation is likely to occur from the loaded area, a worst-case SOF is identified and found to be similar using all definitions.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"17 1","pages":"543 - 553"},"PeriodicalIF":4.8,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41611230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-14DOI: 10.3390/geohazards3040024
Shampa, Bina Roy, M. Hussain, A. Islam, Md. Ashiqur Rahman, K. Mohammed
Climate change is expected to raise river discharge and sea level in the future, and these near-term changes could alter the river flow regime and sedimentation pattern of future floods. Present hazard assessment studies have limitations in considering such morpho-dynamic responses in evaluating flood hazards or risks. Here, we present a multi-model-based approach to quantify such potential hazard parameters influenced by climate change for the most vulnerable communities living on river bars and islands of the Brahmaputra–Jamuna River. River flood-flow and flood wave propagation characteristics are predicted to be affected by changing temporal distribution patterns of precipitation as a result of enhanced global warming. Increased incidences of large multi-peak floods or uncommon floods resulting in long-duration floods driven by sea-level rise may happen as a result of this. To assess it, we have set up a hydromorphic model, Delft3D, for the Brahmaputra–Jamuna River forced by upstream flow, generated from a hydrological model SWAT, over the Brahmaputra basin. The simulations cover moderate, wettest, and driest conditions of the RCP8.5 scenario, and the results reflect the flooding consequences of the near-future, mid-century, and end-century. Floods in the Brahmaputra–Jamuna River are becoming more severe, frequent, and long-lasting, as a result of climate change, and are expected to last until the end of November rather than the current September timeline. While assessing the hazard, we found that the pattern and timing of the flood are as equally important as the peak of the flood, as the river continuously adjusts its cross-sectional area with the flow. The study also demonstrates that, depending on their location/position, climate-induced hazards can affect sand bars/islands disproportionally. The high flood depth, duration, and sedimentation have a significant impact on the sand bars downstream of the river, making them more vulnerable.
{"title":"Assessment of Flood Hazard in Climatic Extreme Considering Fluvio-Morphic Responses of the Contributing River: Indications from the Brahmaputra-Jamuna’s Braided-Plain","authors":"Shampa, Bina Roy, M. Hussain, A. Islam, Md. Ashiqur Rahman, K. Mohammed","doi":"10.3390/geohazards3040024","DOIUrl":"https://doi.org/10.3390/geohazards3040024","url":null,"abstract":"Climate change is expected to raise river discharge and sea level in the future, and these near-term changes could alter the river flow regime and sedimentation pattern of future floods. Present hazard assessment studies have limitations in considering such morpho-dynamic responses in evaluating flood hazards or risks. Here, we present a multi-model-based approach to quantify such potential hazard parameters influenced by climate change for the most vulnerable communities living on river bars and islands of the Brahmaputra–Jamuna River. River flood-flow and flood wave propagation characteristics are predicted to be affected by changing temporal distribution patterns of precipitation as a result of enhanced global warming. Increased incidences of large multi-peak floods or uncommon floods resulting in long-duration floods driven by sea-level rise may happen as a result of this. To assess it, we have set up a hydromorphic model, Delft3D, for the Brahmaputra–Jamuna River forced by upstream flow, generated from a hydrological model SWAT, over the Brahmaputra basin. The simulations cover moderate, wettest, and driest conditions of the RCP8.5 scenario, and the results reflect the flooding consequences of the near-future, mid-century, and end-century. Floods in the Brahmaputra–Jamuna River are becoming more severe, frequent, and long-lasting, as a result of climate change, and are expected to last until the end of November rather than the current September timeline. While assessing the hazard, we found that the pattern and timing of the flood are as equally important as the peak of the flood, as the river continuously adjusts its cross-sectional area with the flow. The study also demonstrates that, depending on their location/position, climate-induced hazards can affect sand bars/islands disproportionally. The high flood depth, duration, and sedimentation have a significant impact on the sand bars downstream of the river, making them more vulnerable.","PeriodicalId":48524,"journal":{"name":"Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards","volume":"22 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2022-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80847777","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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