A Parameter Genetic Algorithm for Evolutionary Calibration in Coupled Dynamics Models of Geological Hazard Chain
-
摘要: 滑坡-堰塞湖-溃决洪水地质灾害链精准模拟是山区地质灾害综合防灾减灾的关键手段，可靠的模型参数是保证模拟结果准确性的重要前提。然而，该地质灾害链多阶段机理模型间的耦合关系复杂、参数众多，传统面向单灾种模型的参数率定方法较少考虑不同灾害之间的链式关系，灾害链模型群协同交互运算过程中多参数率定计算复杂、误差累积问题突出。针对上述问题，提出了一种顾及动力耦合关系的地质灾害链模型参数遗传进化率定方法，首先建立了由颗粒流模型、漂移通量模型、泥沙冲刷模型耦合的滑坡灾害链动力耦合模型，其次提出了模型参数遗传进化率定方法，通过选择-交叉-变异等迭代遗传进化运算，得到最优种群的参数集。选用2018年白格滑坡灾害链进行试验验证，结果表明，最优参数组的模拟结果与实测数据吻合度较好，在400次迭代后种群最大适应度为0.932，偏差值在±5%以内，证明了此参数率定方法的可行性和准确性。Abstract: Objectives: Complex terrain and geological conditions in the western mountainous areas of China have resulted in frequent hazard chains. The simulation assessments of the landslide-barrier lake-outburst flood hazard chains are an effective tool for integrated hazard management, and reasonable model parameters are the primary prerequisite to ensure the reliability of simulation assessment results. However, the coupling relationships among the multi-stage mechanism models of hazard chain are complex. The traditional parameter calibration methods for single-hazard models seldom consider the chain relationships among different hazards, and the multi-parameter calibration calculations are complicated and the error accumulation problem is prominent during the cooperative interaction operation of the hazard chain model groups. Methods: In response to the demand for tightly coupled modeling and global calibration of nonlinear cascade relationships, we proposes a dynamic data-driven multi-parameter genetic calibration method for landslide-weir- flood hazard chain coupled dynamical model. Firstly, a landslide hazard chain coupled dynamical model coupled by granular flow model, drift flux model, and sediment scour model is established. Secondly, a multi-parameter genetic evolutionary under dynamic observation data constraint is studied The calibration method is used to obtain the parameter set of the optimal population by iterative genetic evolution operations such as selection-crossover-variation. Results: The proposed method was validated using the 2018 Baige landslide hazard chain experiment, and the simulation results of the optimal parameter set were found to be in good agreement with the measured data after 400 iterations. The maximum fitness of the population was 0.932, with a deviation of less than ±5%, demonstrating the feasibility and accuracy of this parameter calibration method. The advantages of this method over traditional calibration methods in terms of effectiveness, stability, time consumption, and efficiency were discussed from multiple perspectives. Conclusions: This method effectively utilizes temporal observation data to dynamically calibrate model parameters and accurately describes the spatiotemporal variation process of the hazard chain, providing support for the comprehensive management of geological hazard chains. Further research will focus on knowledge-guided reliable simulation and evaluation methods for hazard chains, enabling reliable analysis of hazard risks under incomplete data conditions.
-
Keywords:
- parameter calibration /
- hazard chain /
- simulation /
- genetic algorithm /
- landslide
-
-
[1] GE Daqing, DAI Keren, GUO Zhaocheng, et al. Early Identification of Serious Geological Hazards with Integrated Remote Sensing Technologies:Thoughts and Recommendations[J]. Geomatics and Information Science of Wuhan University, 2019, 44(7):949-956. (葛大庆, 戴可人, 郭兆成, 等. 重大地质灾害隐患早期识别中综合遥感应用的思考与建议[J]. 武汉大学学报(信息科学版), 2019, 44(7):949-956.) [2] XU Qiang. Understanding and Consideration of Related Issues in Early Identification of Potential Geohazards[J]. Geomatics and Information Science of Wuhan University, 2020, 45(11):1651-1659.(许强. 对地质灾害隐患早期识别相关问题的认识与思考[J]. 武汉大学学报(信息科学版), 2020, 45(11):1651- 1659.) [3] CUI Peng, WEI Fangqiang, CHEN Xiaoqing, et al. The secondary mountain disasters caused by Wenchuan earthquake and their mitigation countermeasures[J]. Bulletin of Chinese Academy of Sciences, 2008, 23(4):317-323.(崔鹏, 韦方强, 陈晓清, 等. 汶川地震次生山地灾害及其减灾对策[J]. 中国科学院院刊, 2008, 23(4):317-323.) [4] DU Zhiqiang, LI Yu, ZHANG Yeting, et al. Knowledge Graph Construction Method on Natural Disaster Emergency[J]. Geomatics and Information Science of Wuhan University, 2020, 45(9):1344-1355.(杜志强, 李钰, 张叶廷, 等. 自然灾害应急知识图谱构建方法研究[J]. 武汉大学学报(信息科学版), 2020, 45(9):1344-1355.) [5] Nguyen V B Q, Kim Y T. Rainfall-earthquake-induced landslide hazard prediction by Monte Carlo simulation:A case study of MT. Umyeon in Korea[J]. KSCE Journal of Civil Engineering, 2020, 24(1):73-86.
[6] ZHOU W, QIU H, WANG L, et al. Combining rainfall-induced shallow landslides and subsequent debris flows for hazard chain prediction[J]. Catena, 2022, 213:106199.
[7] LI Junfeng, ZHANG Xiaochen, LIU Hongyan,等. 2016:Application Of Numerical Simulation Technology To Emergent Rescuing Of Geological Disaster[J]. Journal Of Engineering Geology, 24(4):569-577.(李俊峰, 张小趁, 刘红岩, 等. 突发地质灾害中应急数值模拟技术应用浅析[J]. 工程地质学报, 2016, 24(4):569- 577.) [8] Kurganov A, Miller J. Central-upwind scheme for Savage-Hutter type model of submarine landslides and generated tsunami waves[J]. Computational Methods in Applied Mathematics, 2014, 14(2):177-201.
[9] Scaringi G, Fan X, Xu Q, et al. Some considerations on the use of numerical methods to simulate past landslides and possible new failures:the case of the recent Xinmo landslide (Sichuan, China)[J]. Landslides, 2018, 15:1359-1375.
[10] Iannacone J P, Quan Luna B, Corsini A. Forward simulation and sensitivity analysis of run-out scenarios using MassMov2D at the Trafoi rockslide (South Tyrol, Italy)[J]. Georisk:Assessment and Management of Risk for Engineered Systems and Geohazards, 2013, 7(4):240-249.
[11] Hafiyyan Q, Adityawan M B, Harlan D, et al. Comparison of Taylor Galerkin and FTCS models for dam-break simulation[C]. IOP Conference Series:Earth and Environmental Science. IOP Publishing, 2021, 737(1):012050.
[12] Nurlan O,Farida A,Yergali K, et al. Application of HEC-RAS (2D) for Flood Hazard Maps Generation for Yesil (Ishim) River in Kazakhstan[J]. Water, 2020, 12(10).
[13] Yang Zheng, Xiang Zhimin, Ma Shiwen. A Method of Loose Coupling Entity Modeling Based on Variable Rules[J]. Journal of System Simulation, 2022, 34(7):1506-1511. (杨正, 向智敏, 马世文. 一种基于可变规则的松耦合实体建模方法[J]. 系统仿真学报, 2022, 34(7):1506-1511.) [14] CHEN Ruizhi, WANG Lei, LI Deren, et al. A survey on the fusion of the navigation and the remote sensing techniques[J]. Acta Geodaetica et Cartographica Sinica, 2019, 48(12):1507-1522.(陈锐志, 王磊, 李德仁, 等. 导航与遥感技术融合综述. 测绘学报, 2019, 48(12):1507-1522.) [15] ZHAO Zhan'ao, WANG Jizhou, MAO Xi, et al. A multi-dimensional CNN coupled landslide susceptibility assessment method[J]. Geomatics and Information Science of Wuhan University, 2023, DOI:10.13203/j.whugis20220325.(赵占骜, 王继周, 毛曦, 等. 多维CNN耦合的滑坡易发性评价方法[J]. 武汉大学学报(信息科学版), 2023, DOI:10.13203/j.whugis20220325.) [16] WANG Fei, JIANG Wenyu, LIU Binbin, et al. Disaster Model Service Chain Orchestration Method Using Disaster Chain Rules[J]. Geomatics and Information Science of Wuhan University, 2020, 45(8):1168-1178.(王飞, 姜文宇, 刘彬彬, 等. 利用灾害链规则的灾害模型服务链编制方法[J]. 武汉大学学报(信息科学版), 2020, 45(8):1168-1178.) [17] Golberg D E. Genetic algorithms in search, optimization, and machine learning[J]. Addion wesley, 1989, 1989(102):36.
[18] WANG Zhong-gen, XIA Jun, LIU Chang-ming, et al. Comments on Sensitivity Analysis, Calibration of Distributed Hydrological Model[J]. Journal Of Natural Resources, 2007, 22(4):649-655.(王中根, 夏军, 刘昌明, 等. 分布式水文模型的参数率定及敏感性分析探讨[J]. 自然资源学报, 2007, 22(4):649-655.) [19] FENG Qian, LI Qing, QUAN Wei, el al. Overview of multiobjective particle swarm optimization algorithm[J]. Chinese Journal of Engineering, 2021, 43(6):745-753.(冯茜, 李擎, 全威, 等. 多目标粒子群优化算法研究综述[J]. 工程科学学报, 2021, 43(6):745-753.) [20] REN T Y, LIANG Z Y, LIU Y, et al. 2019. The parameters estimation method based on Bayesian optimization for complex water quality models[J]. Acta Scientiae Circumstantiae, 39(6):2024-2032.(任婷玉, 梁中耀, 刘永, 等. 2019. 基于贝叶斯优化的三维水动力-水质模型参数估值方法[J]. 环境科学学报, 39(6):2024- 2032.) [21] LI Zixuan, DU Juan, XU Wei. Vulnerability assessment of direct economic loss of rainfall-landslide disaster chain based on machine learning[J]. Journal of Catastrophology, 2022,37(4):220-224. (李子轩, 杜鹃, 徐伟. 基于机器学习的降雨-滑坡灾害链直接经济损失脆弱性评估[J]. 灾害学,2022,37(4):220-224.) [22] Sadeghiamirshahidi M, Vitton S J. Tropical storm-induced landslide-dammed lakes and debris flow hazards at Ocotepeque, Western Honduras[J]. Landslides, 2019, 16(1):55-64.
[23] Bagnold R A. Bed load transport by natural rivers[J]. Water Resources Research, 1977, 13(2):303-312.
[24] Armanini A, Capart H, Fraccarollo L, et al. Rheological stratification in experimental free-surface flows of granular-liquid mixtures[J]. Journal of Fluid Mechanics, 2005, 532:269-319.
[25] Li M Z, He Y P, Liu Y D, et al. Hydrodynamic simulation of multi-sized high concentration slurry transport in pipelines[J]. Ocean Engineering, 2018, 163(SEP.1):691-705.
[26] Hibiki T, Takamasa T, Ishii M. One-Dimensional Drift-Flux Model and Constitutive Equations for Relative Motion Between Phases in Various Two-Phase Flow Regimes at Microgravity Conditions[J]. American Society of Mechanical Engineers, 2004:377-386.
[27] Brennen C E. Fundamentals of Multiphase Flow:Drift Flux Models[M]. Cambridge University Press. 2005.
[28] Richardson J F, Zaki W N. The sedimentation of a suspension of uniform spheres under conditions of viscous flow[J]. Chemical Engineering Science, 1954, 3(2):65-73.
[29] Mastbergen D R, Berg J. Breaching in fine sands and the generation of sustained turbidity currents in submarine canyons[J]. Sedimentology, 2010, 50(4):625-637.
[30] Ryan D A, Brooke B P, Bostock H C, et al. Bedload sediment transport dynamics in a macrotidal embayment, and implications for export to the southern Great Barrier Reef shelf[J]. Marine Geology, 2007, 240(1-4):197- 215.
[31] Guo Chen, Xu Qiang, Peng Shuangqi, et al. Application of UAV photogrammetry technology in emergency rescue of Baige landslide in Jinsha River[J]. Journal of Catastrophology, 2020, 35(1):203-210. (郭晨, 许强, 彭双麒, 等. 无人机摄影测量技术在金沙江白格滑坡应急抢险中的应用[J]. 灾害学, 2020, 35(1):203- 210.) [32] Zhao Cheng, Fan Xuanmei, Yang Fan, et al. Analysis of movement process of Baige landslide in Jinsha River and prediction of potentially unstable rock mass[J]. Science and Technology and Engineering, 2020,20(10):3860-3867.(赵程,范宣梅,杨帆,等.金沙江白格滑坡运动过程分析及潜在不稳定岩体预测[J]. 科学技术与工程,2020,20(10):3860-3867.)
计量
- 文章访问数: 260
- HTML全文浏览量: 47
- PDF下载量: 36
下载:
