辛星等:三维确定性模型在浅层黄土滑坡稳定性预测中的应用 ·405· 因此,两种检验方法均证明Scoops3D预测结果是可 [4]Wang T,Wu S R,Shi J S,et al.Concepts and mechanical as- 靠的,还显示数字高程模型数据分辨率对预测结果 sessment method for seismic landslide hazard:a review./Eng Ge- al,2015,23(1):93 具有重要影响,混淆矩阵法适合评价模型分类的准 (王涛,吴树仁,石菊松,等.地震滑坡危险性概念和基于力 确性,成功率曲线则更适合对预测数据本身的属性 学模型的评估方法探讨.工程地质学报,2015,23(1):93) 进行评价 5] Zhang F Y,Wang G H,Kamai T,et al.Effect of pore-water chemistry on undrained shear behavior of saturated loess.0 J Eng 4结论 Geol Hydrogeol,2014,47 (3):201 (1)Scoops.3D是基于数字高程模型数据的滑 6 Zhang F Y,Wang G H,Kamai T,et al.Undrained shear behav- ior of loess saturated with different concentrations of sodium chlo- 坡三维确定性模型,采用了三维圆弧搜索法,能考虑 ride solution.Eng Geol,2013,155:69 各类复杂水文地质情况.模型敏感性分析显示,安 Lan H X,Wang L J,Zhou C H.Study on GIS-Aided model for 全系数计算结果对研究区内的固有岩土工程参数和 analysis of landslide hazard.J Eng Geol,002,10(4):421 控制坡体结构的数字高程模型数据分辨率较为 (兰恒星,王苓涓,周成虎.地理信息系统支持下的滑坡灾害 敏感. 分析模型研究.工程地质学报,2002,10(4):421) (2)Scoops.3D模型对选择研究区内的浅层黄 8] Zhang F Y,Liu G,Chen WW,et al.A study of landslide sus- ceptibility mapping based on factor analysis and bivariate statis- 土滑坡预测结果显示,地形和数字高程模型数据分 tics-With a case study in Longnan area of national highway 辨率是影响滑坡分布的重要因素,而基本稳定区中 212.Adv Earth Sci,2008,23(10):1037 滑坡占有一定的比例,证明外界条件的变化对滑坡 (张帆字,刘高,谌文武,等.基于要素分析和二元统计模型 稳定性也会产生影响.模型预测结果和滑坡分布图 的区域滑坡危险等级制图一以国道212线陇南段为例.地 的对比结果表现良好,受微地貌的影响,点状滑坡的 球科学进展,2008,23(10):1037) ] Guzzetti F,Reichenbach P,Ardizzone F,et al.Estimating the 精度高于面状滑坡,因此,在提高研究区数字高程模 quality of landslide susceptibility models.Geomorphology,2006, 型数据分辨率的基础上,考虑外界条件变化和改进 81(12):166 测量方法,深入研究和减少微地貌对预测结果的影 [10]Baeza C,Corominas J.Assessment of shallow landslide suscepti- 响,是提高模型预测精度的关键 bility by means of multivariate statistical techniques.Earth Surf (3)混淆矩阵和成功率曲线两种方法对模型预 Processes Landforms,2001,26(12):1251 测精度的评价表明,Scoops3D对研究区的浅层黄土 [11]Montgomery D R,Dietrich W E.A physically-based model for the topographic control on shallow landsliding.Water Resour Res, 滑坡稳定性的预测精度符合要求.这说明该模型不 1994,30(4):1153 仅可以成功地预测火山灰地区大型深层滑坡的稳定 [12]Godt J W,Baum R L,Savage WZ,et al.Transient determinis- 性,而且在复杂沟壑地貌的黄土流域中具有较好的 tic shallow landslide modeling:requirements for susceptibility 适用性,能作为预测黄土滑坡灾害的一种有效工具. and hazard assessments in a GIS framework.Eng Geol,2008 (4)在黄土覆盖厚度大的地区,使用Scoops3D 102(34):214 预测浅层滑坡稳定性时需重点考虑黄土的非饱和特 [13]Wu W M,Sidle R C.Application of a distributed shallow land- slide analysis model (dSLAM)to managed forested catchments in 性和水分的空间差异性,在水文地质条件复杂的区 Oregon,USA //Proceedings of Rabat Symposium S6.Rabat 域需重点考虑地下水的三维空间分布,以及不同地 1997:213 层的岩土体力学参数差异 14]Iverson R M.Landslide triggering by rain infiltration.Water Re- sour Res,2000,36(7):1897 [15] Baum RL,Savage WZ,Godt J W.TRIGRS:a Fortran program 参考文献 for transient rainfall infiltration and grid-based regional slope-sta- Zhang F Y,Chen WW,Liu G,et al.Relationships between bility analysis [J/OL].US Geological Survey Open-file Report landslide types and topographic attributes in a loess catchment, (2008[2017-04-07].htp:/pubs.usg.g0v/of/2008/1159 China.J Mountain Sci,2012,9(6):742 6]Reid M E,Christian S B,Brien D L,et al.Scoops3D- 一sof- Zhou J X,Zhu C Y,Zheng J M,et al.Landslide disaster in the ware to analyze three-dimensional slope stability throughout a dig- loess area of China.J Forestry Res,2002,13(2)157 ital landscape U.S.Geological Surrey Techniques and B3]Peng J B,Lin HC,Wang Q Y,et al.The critical issues and cre- Methods(2017-01-11)[2017-04-07].https:/1pubs.usgs. ative concepts in mitigation research of loess geological hazards.J gov/m/14/a01/ Eng Geol,.2014,22(4):684 [17]Alvioli M,Raum R L.Parallelization of the TRIGRS model for (彭建兵,林鸿州,王启耀,等.黄土地质灾害研究中的关键 rainfall-induced landslides using the message passing interface. 问题与创新思路.工程地质学报,2014,22(4):684) Environ Modell Softwe,2016,81:122辛 星等: 三维确定性模型在浅层黄土滑坡稳定性预测中的应用 因此,两种检验方法均证明 Scoops3D 预测结果是可 靠的,还显示数字高程模型数据分辨率对预测结果 具有重要影响,混淆矩阵法适合评价模型分类的准 确性,成功率曲线则更适合对预测数据本身的属性 进行评价. 4 结论 ( 1) Scoops3D 是基于数字高程模型数据的滑 坡三维确定性模型,采用了三维圆弧搜索法,能考虑 各类复杂水文地质情况. 模型敏感性分析显示,安 全系数计算结果对研究区内的固有岩土工程参数和 控制坡体结构的数字高程模型数据分辨率较为 敏感. ( 2) Scoops3D 模型对选择研究区内的浅层黄 土滑坡预测结果显示,地形和数字高程模型数据分 辨率是影响滑坡分布的重要因素,而基本稳定区中 滑坡占有一定的比例,证明外界条件的变化对滑坡 稳定性也会产生影响. 模型预测结果和滑坡分布图 的对比结果表现良好,受微地貌的影响,点状滑坡的 精度高于面状滑坡,因此,在提高研究区数字高程模 型数据分辨率的基础上,考虑外界条件变化和改进 测量方法,深入研究和减少微地貌对预测结果的影 响,是提高模型预测精度的关键. ( 3) 混淆矩阵和成功率曲线两种方法对模型预 测精度的评价表明,Scoops3D 对研究区的浅层黄土 滑坡稳定性的预测精度符合要求. 这说明该模型不 仅可以成功地预测火山灰地区大型深层滑坡的稳定 性,而且在复杂沟壑地貌的黄土流域中具有较好的 适用性,能作为预测黄土滑坡灾害的一种有效工具. ( 4) 在黄土覆盖厚度大的地区,使用 Scoops3D 预测浅层滑坡稳定性时需重点考虑黄土的非饱和特 性和水分的空间差异性,在水文地质条件复杂的区 域需重点考虑地下水的三维空间分布,以及不同地 层的岩土体力学参数差异. 参 考 文 献 [1] Zhang F Y,Chen W W,Liu G,et al. Relationships between landslide types and topographic attributes in a loess catchment, China. J Mountain Sci,2012,9( 6) : 742 [2] Zhou J X,Zhu C Y,Zheng J M,et al. Landslide disaster in the loess area of China. J Forestry Res,2002,13( 2) : 157 [3] Peng J B,Lin H C,Wang Q Y,et al. The critical issues and creative concepts in mitigation research of loess geological hazards. J Eng Geol,2014,22( 4) : 684 ( 彭建兵,林鸿州,王启耀,等. 黄土地质灾害研究中的关键 问题与创新思路. 工程地质学报,2014,22( 4) : 684) [4] Wang T,Wu S R,Shi J S,et al. Concepts and mechanical assessment method for seismic landslide hazard: a review. J Eng Geol,2015,23( 1) : 93 ( 王涛,吴树仁,石菊松,等. 地震滑坡危险性概念和基于力 学模型的评估方法探讨. 工程地质学报,2015,23( 1) : 93) [5] Zhang F Y,Wang G H,Kamai T,et al. Effect of pore-water chemistry on undrained shear behavior of saturated loess. Q J Eng Geol Hydrogeol,2014,47( 3) : 201 [6] Zhang F Y,Wang G H,Kamai T,et al. Undrained shear behavior of loess saturated with different concentrations of sodium chloride solution. Eng Geol,2013,155: 69 [7] Lan H X,Wang L J,Zhou C H. Study on GIS—Aided model for analysis of landslide hazard. J Eng Geol,2002,10( 4) : 421 ( 兰恒星,王苓涓,周成虎. 地理信息系统支持下的滑坡灾害 分析模型研究. 工程地质学报,2002,10( 4) : 421) [8] Zhang F Y,Liu G,Chen W W,et al. A study of landslide susceptibility mapping based on factor analysis and bivariate statistics———With a case study in Longnan area of national highway 212. Adv Earth Sci,2008,23( 10) : 1037 ( 张帆宇,刘高,谌文武,等. 基于要素分析和二元统计模型 的区域滑坡危险等级制图———以国道 212 线陇南段为例. 地 球科学进展,2008,23( 10) : 1037) [9] Guzzetti F,Reichenbach P,Ardizzone F,et al. Estimating the quality of landslide susceptibility models. Geomorphology,2006, 81( 1-2) : 166 [10] Baeza C,Corominas J. Assessment of shallow landslide susceptibility by means of multivariate statistical techniques. Earth Surf Processes Landforms,2001,26( 12) : 1251 [11] Montgomery D R,Dietrich W E. A physically-based model for the topographic control on shallow landsliding. Water Resour Res, 1994,30( 4) : 1153 [12] Godt J W,Baum R L,Savage W Z,et al. Transient deterministic shallow landslide modeling: requirements for susceptibility and hazard assessments in a GIS framework. Eng Geol,2008, 102( 3-4) : 214 [13] Wu W M,Sidle R C. Application of a distributed shallow landslide analysis model ( dSLAM) to managed forested catchments in Oregon,USA / /Proceedings of Rabat Symposium S6. Rabat, 1997: 213 [14] Iverson R M. Landslide triggering by rain infiltration. Water Resour Res,2000,36( 7) : 1897 [15] Baum R L,Savage W Z,Godt J W. TRIGRS: a Fortran program for transient rainfall infiltration and grid-based regional slope-stability analysis [J/OL]. US Geological Survey Open-file Report ( 2008) [2017--04--07]. http: / / pubs. usgs. gov /of /2008 /1159 [16] Reid M E,Christian S B,Brien D L,et al. Scoops3D———software to analyze three-dimensional slope stability throughout a digital landscape [J/OL]. U. S. Geological Survey Techniques and Methods ( 2017--01--11) [2017--04--07]. https: / / pubs. usgs. gov /tm /14 /a01 / [17] Alvioli M,Raum R L. Parallelization of the TRIGRS model for rainfall-induced landslides using the message passing interface. Environ Modell Softw,2016,81: 122 · 504 ·