水利水电技术（中英文）2024，Vol.55Issue(7)：19-31,13.DOI:10.13928/j.cnki.wrahe.2024.07.002
基于窗口粒子滤波算法的土壤水分同化及滑坡灾害预警
Assimilation of soil moisture for landslide disaster warning based on particle batch smoother
摘要
Abstract
[Objective]In coupled seepage-stability analysis,soil hydraulic parameters govern the relation of conversion from soil moisture content to pore water pressure,and therefore dictate the calculation of effective stress and slope stability.The develop-ment of robust and reliable data assimilation method may reduce the uncertainty of soil hydraulic parameters and improve the accuracy of soil hydrological simulation and early-warning of rainfall-triggered landslide disasters.[Methods]In this paper,the particle batch smoother(PBS)is integrated with a seepage-stability model,and the soil moisture content data is assimilated to achieve the objective of inverse estimation of soil hydraulic parameters,simulation of soil pore water pressure,and prediction of slope stability.Both synthetic and real-case numerical experiments were used for validating the purposed method.Through the synthetic numerical experiment,it has been confirmed that the PBS algorithm can achieve more accurate simulation of unsaturated soil hydrology when specifying the time window longer than 2 days and particles numbers(parameter samples)larger than 80.The numerical simulations for selected real-case landslide disaster occurred in Yindongzi Gully,Dujiangyan,Sichuan Province also adopts the PBS algorithm to assimilate in-situ measured soil moisture content at three locations.The posterior soil hydraulic parameters are statistical result of 100 particle samples after 3 times resampling,each with a time window length of 4 days.[Re-sults]Result indicated well agreement between the simulated and measured soil moisture content,and the simulated pore water pres-sure and factor of safety also provide a clear and effective response to rainfall.After 2 to 3 windows of resampling,the uncertainty bands of the simulated pore water pressure of the three locations are all less than 0.11 m,and the uncertainty bands of the factor of safety are 0.03,0.01 and 0.11,respectively.As for the landslide disaster induced by extreme rainfall on August 28,2017,after assimilation by PBS algorithm,the uncertainty bands of simulations of soil water content,pore water pressure and factor of safety are extremely narrow.The PBS algorithm can provide a robust estimation of slope instability(Fs＜1.0)contributing an effective ear-ly-warning of disaster.[Conclusion]In both synthetic and real-case numerical experiment,the PBS algorithm can robustly and reli-ably support estimation of soil hydraulic parameters and soil hydrological processes with sufficient accuracy,and it has great poten-tial and practical value in the field of coupled seepage-stability analysis and early-warning of rainfall-induced landslides.关键词
渗流-边坡稳定分析/土壤水分数据同化/土壤水动力模拟/窗口粒子滤波/滑坡灾害预警/降雨/滑坡/渗透系数Key words
seepage-stability analysis/soil moisture data assimilation/soil hydrological modeling/particle batch smoother/early-warning of rainfall-triggered landslide disaster/rainfall/landslides/permeability coefficient分类
水利科学引用本文复制引用
林雨珊,邵伟,杨宗佶,董建志,倪钧钧,林齐根..基于窗口粒子滤波算法的土壤水分同化及滑坡灾害预警[J].水利水电技术（中英文）,2024,55(7):19-31,13.基金项目
中国科学院成都山地所自主部署创新团队项目(IMHE-CXTD-01) （IMHE-CXTD-01）
国家自然科学基金青年科学基金项目(41807286) （41807286）
国家自然科学基金项目(41877158) （41877158）
青海省科技厅基础研究项目(2023-ZJ-705) （2023-ZJ-705）
