A landslide hazard prediction framework by considering physically-based model and effective rainfall infiltration—A case study from Yarlung Zangbo River of Shannan City in the Tibetan Plateau
(1. School of Civil and Transportation Engineering，Hebei University of Technology，Tianjin 300401，China；
2. College of Geological Engineering and Geomatics，Chang?an University，Xi?an，Shaanxi 710054，China)
摘要滑坡危险性评估是山区进行防灾减灾工作的重要步骤，但以往研究多是对现阶段危险性的分析，用于区域尺度上滑坡危险性预测的有效方法较少。针对该问题，首次提出一种考虑物理模型与有效降雨入渗的新型框架用于对未来给定降雨重现期条件下的滑坡危险性进行预测。以青藏高原山南市雅鲁藏布江流域地区为例，首先使用Easy_Balance软件计算1998～2017年降雨的平均有效入渗率和前期有效降雨量Pa，并使用该期间夏季每月连续3日降雨最大值的95%分位数作为临界降雨量Pe，基于物理模型FSLAM完成土壤参数和土地利用参数的校准。使用Gumbel方法得到Pa和Pe在不同重现期时的极值，并分别计算各栅格破坏概率(probability of failure，PoF)对Pa和Pe的响应，根据栅格响应的敏感程度对研究区进行重分类后，使用危险性评估矩阵进行滑坡危险性预测。计算结果表明：当降雨重现期增大到50和100 a时，有92.1%的滑坡点落入到了极高和高危险区内，与传统的未考虑降雨对栅格PoF影响程度的TRIGRS模型相比，AUC精度高出7.6%～9.0%。当前方法能够有效预测未来极端降雨工况下的滑坡发生情况，且同时考虑了前期降雨入渗和极值降雨的影响，进一步提高了区域滑坡危险性预测的合理性。
Abstract：Landslide hazard assessment is an important step in disaster prevention and mitigation in mountainous areas. However，most of the previous studies focused on the risk analysis at the current stage，and there are very few effective methods for landslide risk prediction on a regional scale. Aiming at this problem，this study proposed a new framework by considering physical model and effective rainfall infiltration to predict the landslide hazard under the condition of a given rainfall return period in the future for the first time. Taking the Yarlung Zangbo River catchment in Shannan City of the Tibetan Plateau as an example，the average effective infiltration rate and the previous effective rainfall Pa from 1998 to 2017 were calculated by using the Easy_Balance software. The 95% quantile of the maximum rainfall for three consecutive days in each month in summer was used as the critical rainfall Pe，and the calibration of soil parameters and land use parameters was completed based on the physical model FSLAM. The extreme values of Pa and Pe at different return periods were obtained using the Gumbel method，and the response of probability of failure(PoF) of each grid to Pa and Pe was calculated. Then the study area was reclassified according to the sensitivity of the grid response，and the hazard assessment matrix was used to predict the landslide hazard in the whole area. The calculation results showed that when the rainfall return period reached 50 years and 100 years，92.1% of the landslide points fell into the very high and high hazard areas. Compared with the traditional TRIGRS model which didn?t consider the effect extent of rainfall on grid PoF，the AUC accuracy of the proposed method increased by 7.6%–9.0%. The current method can effectively predict the occurrence of landslides under extreme rainfall conditions in the future，and the influence of rainfall infiltration and extreme rainfall are considered at the same time，which can further improve the rationality of regional landslide hazard prediction.
郭子正1，周新勇1，黄 达2，田碧霞1，何 俊1. 考虑物理模型与有效降雨入渗的滑坡危险性预测框架—以青藏高原山南市雅鲁藏布江流域为例[J]. 岩石力学与工程学报, 2024, 43(4): 986-998.
GUO Zizheng1，ZHOU Xinyong1，HUANG Da2，TIAN Bixia1，HE Jun1. A landslide hazard prediction framework by considering physically-based model and effective rainfall infiltration—A case study from Yarlung Zangbo River of Shannan City in the Tibetan Plateau. , 2024, 43(4): 986-998.
[1] 祁生文，李永超，宋帅华，等. 青藏高原工程地质稳定性分区及工程扰动灾害分布浅析[J]. 工程地质学报，2022，30(3)：599–608.(QI Shengwen，LI Yongchao，SONG Shuaihua，et al. Analysis of engineering geological stability zoning and engineering disturbance disaster distribution on the Qinghai—Tibet Plateau[J]. Journal of Engineering Geology，2022，30(3)：599–608.(in Chinese))
[2] 王玉峰，明 杰，冯止依，等. 乱石包高速远程滑坡流态化运动模式及摩擦热效应研究[J]. 岩石力学与工程学报，2022，41(增2)：3 174–3 188.(WANG Yufeng，MING jie，FENG Zhiyi，et al. Research on fluidization movement mode and frictional heating effect of Luanshibao high-speed and long-distance landslide[J]. Chinese Journal of Rock Mechanics and Engineering，2022，41(Supp2)：3 174–3 188.(in Chinese))
[3] 王成虎，高桂云，杨树新，等. 基于中国西部构造应力分区的川藏铁路沿线地应力的状态分析与预估[J]. 岩石力学与工程学报，2019，38(11)：2 242–2 253.(WANG Chenghu，GAO Guiyun，YANG Shuxin，et al. State analysis and prediction of ground stress along the Sichuan—Tibet Railway based on tectonic stress zoning in Western China[J]. Chinese Journal of Rock Mechanics and Engineering，2019，38(11)：2 242–2 253.(in Chinese))
[4] CUI P，GE Y G，LI S J，et al. Scientific challenges in disaster risk reduction for the Sichuan—Tibet Railway[J]. Engineering Geology，2022，309：106837.
[5] 郭长宝，闫怡秋，张永双，等. 青藏高原大型深层蠕滑型滑坡变形机制研究进展与展望[J]. 地球科学，2022，47(10)：3 677–3 700. (GUO Changbao，YAN Yiqiu，ZHANG Yongshuang，et al. Research progress and prospects on the deformation mechanism of large-scale deep creep-type landslides in the Qinghai—Tibet Plateau[J]. Earth Science，2022，47(10)：3 677–3 700.(in Chinese))
[6] 李彩虹，李 雪，郭长宝，等. 青藏高原东部鲜水河断裂带地震滑坡危险性评价[J]. 地质通报，2022，41(8)：1 473–1 486.(LI Caihong，LI Xue，GUO Changbao，et al. Hazard assessment of earthquake landslides in the Xianshuihe fault zone in the eastern Qinghai—Tibet Plateau[J]. Geological Bulletin，2022，41(8)：1 473–1 486.(in Chinese))
[7] 郭子正，何 俊，黄 达，等. 降雨诱发浅层滑坡危险性的快速评估模型及应用[J]. 岩石力学与工程学报，2023，42(5)：1 188–1 201. (GUO Zizheng，HE Jun，HUANG Da，et al. Rapid assessment model and application of rainfall-induced shallow landslide risk[J]. Chinese Journal of Rock Mechanics and Engineering，2023，42(5)：1 188–1 201.(in Chinese))
[8] ALEOTTI P，CHOWDHURY R. Landslide hazard assessment：summary review and new perspectives[J]. Bulletin of Engineering Geology and the Environment，1999，58(1)：21–44.
[9] FELL R，COROMINAS J，BONNARD C，et al. Guidelines for landslide susceptibility，hazard and risk zoning for land use planning[J]. Engineering Geology，2008，102(3/4)：85–98.
[10] 许 冲，徐锡伟. 逻辑回归模型在玉树地震滑坡危险性评价中的应用与检验[J]. 工程地质学报，2012，20(3)：326–333.(XU Chong，XU Xiwei. Application and test of logistic regression model in risk assessment of Yushu earthquake landslide[J]. Journal of Engineering Geology，2012，20(3)：326–333.(in Chinese))
[11] 庄建琦，彭建兵，张利勇. 不同降雨条件下黄土高原浅层滑坡危险性预测评价[J]. 吉林大学学报：地球科学版，2013，43(3)：867–876.(ZHUANG Jianqi，PENG Jianbing，ZHANG Liyong. Risk prediction and evaluation of shallow landslides in the Loess Plateau under different rainfall conditions[J]. Journal of Jilin University：Earth Science，2013，43(3)：867–876.(in Chinese))
[12] HUANG F M，CHEN J W，LIU W P，et al. Regional rainfall-induced landslide hazard warning based on landslide susceptibility mapping and a critical rainfall threshold[J]. Geomorphology，2022，408：108236.
[13] LEE J H，KIM H，PARK H J，et al. Temporal prediction modeling for rainfall-induced shallow landslide hazards using extreme value distribution[J]. Landslides，2021，18：321–338.
[14] CUI Y L，JIN J L，HUANG Q B，et al. A data-driven model for spatial shallow landslide probability of occurrence due to a typhoon in Ningguo City，Anhui Province，China[J]. Forests，2022，13(5)：732.
[15] GUZZETTI F，REICHENBACH P，CARDINALI M，et al. Probabilistic landslide hazard assessment at the basin scale[J]. Geomorphology，2005，72(1/4)：272–299.
[16] 吴益平，张秋霞，唐辉明，等. 基于有效降雨强度的滑坡灾害危险性预警[J]. 地球科学：中国地质大学学报，2014，39(7)：889–895.(WU Yiping，ZHANG Qiuxia，TANG Huiming，et al. Landslide hazard early warning based on effective rainfall intensity[J]. Earth Science：Journal of China University of Geosciences，2014，39(7)：889–895.(in Chinese))
[17] 童立强，祁生文，刘春玲. 喜马拉雅山东南地区地质灾害发育规律初步研究[J]. 工程地质学报，2007，62(6)：721–729.(TONG Liqiang，QI Shengwen，LIU Chunling. Preliminary study on the development law of geological hazards in the southeastern Himalayas[J]. Journal of Engineering Geology，2007，62(6)：721–729.(in Chinese))
[18] LIU Z F，YAO Z J，WANG R，et al. Estimation of the Qinghai—Tibetan Plateau runoff and its contribution to large Asian rivers[J]. Science of the Total Environment，2020，749：141570.
[19] 蒋万钰，陈 冠，孟兴民，等. 基于卷积神经网络模型的区域滑坡敏感性评价——以川藏铁路沿线为例[J]. 兰州大学学报：自然科学版，2022，58(2)：203–211.(JIANG Wanyu，CHEN Guan，MENG Xingmin，et al. Regional landslide sensitivity evaluation based on convolutional neural network model—taking the Sichuan—Tibet railway as an example[J]. Journal of Lanzhou University：Natural Science，2022，58(2)：203–211.(in Chinese))
[20] 汤明高，王李娜，刘昕昕，等. 青藏高原冰崩隐患发育分布规律及危险性[J]. 地球科学，2022，47(12)：4 647–4 662.(TANG Minggao，WANG Lina，LIU Xinxin，et al. Development，distribution and danger of glaciation hazards on the Qinghai—Tibet Plateau[J]. Earth Science，2022，47(12)：4 647–4 662.(in Chinese))
[21] PACK R T，TARBOTON D G，GOODWIN C N. The SINMAP approach to terrain stability mapping[C]// Proceedings of the 8th Congress of the International Association of Engineering Geology. 1998：1 157–1 165.
[22] GUO Z Z，ONA T，MARCEL H，et al. FSLAM：A QGIS plugin for fast regional susceptibility assessment of rainfall-induced landslides[J]. Environmental Modelling and Software，2022，150：105354.
[23] TAN M L，GASSMAN P W，YANG X Y，et al. A review of SWAT applications，performance and future needs for simulation of hydro-climatic extremes[J]. Advances in Water Resources，2020，143：103662.
[24] VICENTE M，MARCEL H，GUO Z Z，et al. Fast physically-based model for rainfall-induced landslide susceptibility assessment at regional scale[J]. Catena，2021，201：105213.
[25] JUAN A S，CRIOLLO R，SUÑÉ E V，et al. Customization，extension and reuse of outdated hydrogeological software[J]. Geologica Acta，2020，18：1–11.
[26] MUSHTAHA A M，CAMP M V，WALRAEVENS K. Quantification of recharge and runoff from rainfall using new GIS tool：example of the Gaza strip aquifer[J]. Water，2019，11(1)：84.
[27] MIGUEL F M，MIGUEL A J，ERNESTO G S，et al. An assessment of groundwater recharge at a regional scale for sustainable resource management：province of Alicante (SE Spain)[J]. Water，2021，13(6)：862.
[28] ARNONE E，FRANCIPANE A，SCARBACI A，et al. Effect of raster resolution and polygon-conversion algorithm on landslide susceptibility mapping [J]. Environment Modelling and Software，2016，84：467–481.
[29] YOUSSEF K，SHAO K，MOON S，et al. Landslide susceptibility modeling by interpretable neural network[J]. Communications Earth and Environment，2023，(4)：162.
[30] SCHWARZ M，PRETI F，GIADROSSICH F，et al. Quantifying the role of vegetation in slope stability：A case study in Tuscany (Italy)[J]. Ecological Engineering，2010，36 (3)：285–291.
[31] HÜRLIMANN M，GUO Z，PUIG-POLO C，et al. Impacts of future climate and land cover changes on landslide susceptibility：Regional scale modelling in the Val d? Aran region(Pyrenees，Spain)[J]. Landslides，2022，19：99–118.
[32] HUANG F，YAN J，FAN X，et al. Uncertainty pattern in landslide susceptibility prediction modelling：Effects of different landslide boundaries and spatial shape expressions[J]. Geoscience Frontiers，2022，13(2)：101317.
[33] GONG Y，YAO A，LI Y. Classification and distribution of large-scale high-position landslides in southeastern edge of the Qinghai–Tibet Plateau，China [J]. Environmental Earth Sciences，2022，81：311.
[34] 王佳佳，殷坤龙，肖莉莉. 基于GIS和信息量的滑坡灾害易发性评价—以三峡库区万州区为例[J]. 岩石力学与工程学报，2014，33(4)：797–808.(WANG Jiajia，YIN Kunlong，XIAO Lili. Landslide susceptibility assessment based on GIS and weighted information value：A case study of Wanzhou District，Three Gorges Reservoir[J]. Chinese Journal of Rock Mechanics and Engineering，2014，33(4)：797–808.(in Chinese))
[35] 彭建兵，张永双，黄 达，等. 青藏高原构造变形圈–岩体松动圈–地表冻融圈–工程扰动圈互馈灾害效应[J]. 地球科学，2023，48(8)：3 099–3 114.(PENG Jianbing，ZHANG Yongshuang，HUANG Da，et al. Interaction disaster effects of the tectonic deformation sphere，rock mass loosening sphere，surface freeze-thaw sphere and engineering disturbance sphere on the Tibetan plateau[J]. Earth Science，2023，48(8)：3 099–3 114.(in Chinese))
2024, Vol. 43 
