Rainfall-Induced Meteorological Early Warning of Geo-Hazards Model:Application to the Monitoring Demonstration Area in Honghe Prefecture, Yunnan Province
-
摘要: 地质灾害气象风险预警模型研究一直是相关部门以及业界学者的研究热点,其预警可靠性问题也一直是研究的难点与技术核心,红河州是云南省地质灾害最为严重的地区之一,然而对于在红河州区域内的地质灾害气象预警却研究甚少.在云南省红河州示范区首次采用100 m×100 m的预警单元,综合考虑地质灾害的降雨诱发因子、地质环境因素,并基于信息量法构建地质灾害气象风险预警模型.该预警模型通过历史灾害事件回代验证,预警准确率可达81.8%.结果表明将气象因素与地质环境因素综合考虑纳入模型是可行的,是提高地质灾害气象预警水平的有效途径.Abstract: The researching on geo-hazards risk indicator model has been the hot spot of related departments and scholars, indicating reliability problems have always been a research difficult point and technology core.Honghe prefecture is one of the most serious areas of geo-hazards in Yunnan Province, but little research about geo-hazards risk indicator has been done in this region.Based on the information value method, a geo-hazards indicator model about Honghe prefecture was established considering the rainfall-induced factors, hazard-formative environment of this region which is the first time using 100 m×100 m warning unit. Through the verification of historical geological hazard happening, the accuracy rate of warning can highly reach 81.8%. The result indicated that it's workable to integrate meteorological factors and geological environment factors into the indicator model which can be an effective way to improve the level of geo-hazard warning.
-
Key words:
- rainfall /
- geo-hazards /
- meteorological early warning /
- Honghe prefecture /
- information value method
-
图 2 研究区坡度(a)和岩土体类型(b)空间分布
1.层状软硬相间碎屑岩岩组;2.层状软硬相间浅变质岩岩组;3.薄-中层极软-较硬含煤砂岩、泥岩岩组;4.层状软硬相间碎屑岩夹碳酸盐岩岩组;5.层状软的页岩、泥岩夹硬的砂岩岩组;6.层状中-强岩溶化软硬相间的碳酸盐岩夹碎屑岩岩组;7.层状中-强岩溶化软硬相间的碳酸盐岩、碎屑岩岩组;8.层状、块状较硬-坚硬喷出岩岩组;9.多层土体;10.块状坚硬片麻岩、混合岩、变粒岩岩组;11.块状坚硬侵入岩岩组;12.中厚层状坚硬砂岩、砾岩夹软弱薄层页岩、泥岩岩组;13.中厚层状强岩溶化较硬-坚硬灰岩、白云岩岩组
Fig. 2. The spatial distribution of slope gradient (a) and rock and soil types (b) in the study area
表 1 降雨特征临界值
Table 1. The critical value of rainfall
降雨等级 1级 2级 3级 4级 5级 5级以上 有效降雨量(mm) 0~30 30~80 80~120 120~160 160~260 >260 表 2 研究区地质灾害环境控制因子信息量值
Table 2. The information value of environmental controls of geological disaster in the study area
评价因子 类型 信息量计算 S0 S A0 A Mi 密度低 91 992 110 573 679 264 -0.827 430 密度较低 425 992 217 360 679 264 0.421 009 断层密度 密度中等 237 992 170 894 679 264 -0.074 580 密度较高 181 992 141 922 679 264 -0.195 480 密度高 58 992 38 515 679 264 0.044 265 平缓 61 992 47 267 679 264 -0.178 390 缓坡 192 992 131 930 679 264 -0.005 030 坡度 稍陡 458 992 291 127 679 264 0.107 331 较陡 273 992 184 224 679 264 0.021 072 陡峭 8 992 14 716 679 264 -1.425 680 低 243 992 166 021 679 264 0.003 223 河网密度 中等 318 992 222 490 679 264 -0.031 080 较高 273 992 189 911 679 264 -0.022 790 高 158 992 100 842 679 264 0.101 460 地貌 哀牢山中山亚区 627 992 342 673 679 264 0.325 265 文山岩溶中山台地区 365 992 336 591 679 264 -0.429 470 地震烈度 Ⅵ 434 992 393 382 679 264 -0.404 600 Ⅶ 558 992 285 882 679 264 0.418 478 一般区 853 992 575 670 679 264 0.020 936 矿山开采度 较严重区 36 992 36 837 679 264 -0.579 530 严重区 103 992 65 757 679 264 0.101 060 低 433 992 418 219 679 264 -0.496 260 较低 215 992 121 467 679 264 0.277 405 路网密度 中等 241 992 80 220 679 264 1.040 632 较高 71 992 42 572 679 264 0.191 546 高 32 992 16 786 679 264 0.384 446 块状坚硬侵入岩岩组 135 992 83 605 679 264 0.144 931 多层土体 5 992 3 082 679 264 0.151 694 层状、块状较硬-坚硬喷出岩岩组 37 992 28 089 679 264 -0.148 850 块状坚硬片麻岩、混合岩、变粒岩 302 992 154 613 679 264 0.419 519 层状软硬相间碎屑岩夹碳酸盐岩岩组 40 992 50 917 679 264 -0.894 520 层状软硬相间浅变质岩岩组 47 992 41 514 679 264 -0.367 300 岩土体类型 层状软硬相间碎屑岩岩组 87 992 49 469 679 264 0.268 123 中-厚层状强岩溶化较硬-坚硬灰岩 46 992 58 916 679 264 -0.903 390 中厚层状坚硬砂岩、砾岩夹软弱薄层 37 992 35 246 679 264 -0.476 300 层状中-强岩溶化软硬相间的碳酸盐岩 17 992 25 384 679 264 -1.124 750 层状软的页岩、泥岩夹硬的砂岩岩组 112 992 67 033 679 264 0.194 188 层状中-强岩溶化软硬相间的碳酸盐夹碎屑岩 120 992 72 108 679 264 0.188 435 薄-中层状极软-较硬含煤砂岩、泥岩 7 992 9 288 679 264 -0.954 380 表 3 评价因子权重取值
Table 3. The weight of evaluation factor
评价因子 地貌类型 地震烈度 断裂密度 岩土体类型 河网密度 路网密度 坡度 矿山环境影响 权重(k) 0.129 0 0.096 8 0.129 0 0.225 8 0.096 8 0.064 5 0.096 8 0.161 3 表 4 地质灾害气象预报预警等级划分
Table 4. The classification of weather forecast and early warning
预警等级 风险低 风险中等 风险较高 风险高 风险很高 预警指数 <0.235 0.235~0.770 0.770~1.155 1.155~1.485 >1.485 表 5 研究区地质灾害气象预警等级与实际调查灾害点的对比(2014-07-22)
Table 5. The comparison between evaluation results and the investigative hazards distribution of study area
预警等级 分布面积
(km2)a 地质灾害
点个数b b/a 低 4 382.05 65.26% 488 49.19% 0.75 中等 1 749.51 26.05% 282 28.43% 1.09 较高 487.83 7.26% 178 17.94% 2.47 高 95.61 1.42% 44 4.44% 3.12 注:a为本预警等级的面积占研究区总面积的百分比;b为落在该等级内的地质灾害点个数占地质灾害点总数的百分比;b/a为本预警等级中的地质灾害点密度与研究区总的地质灾害风险密度的比值. 表 6 研究区历史灾害事件与对应预警级别对照(2014—2015年)
Table 6. The comparison table of historical disaster events and corresponding warning level
发生日期 所属县 乡镇、村组及具体地点 类型 对应预警等级 2014-08-15 金平县 金水河镇普角村委会普角村 滑坡 较高 2014-08-11 金平县 铜厂乡勐谢村委会新寨村 滑坡 高 2014-08-10 金平县 马鞍底乡中寨村委会黄家寨 滑坡 中等 2014-07-23 金平县 金河镇哈尼田村委会上卢下寨 滑坡 高 2014-07-22 金平县 沙依坡乡沙依坡村委会邮电所上方 滑坡 高 2014-07-22 金平县 大寨乡敬老院 滑坡 高 2014-07-22 金平县 大寨乡中心小学 滑坡 较高 2014-07-22 金平县 沙依坡乡阿哈迷村委会丫口寨 滑坡 高 2014-07-21 金平县 沙依坡乡土马村委会骂居迷村 滑坡 中等 2015-10-10 金平县 阿得博乡阿得博村委会刘家寨 滑坡 较高 2015-10-09 金平县 阿得博乡阿得博中学 滑坡 高 -
[1] Bruce, J.P., Clark, R.H., 1969.Introduction to Hydrometeorology.Pergamon Press, London, 252-270. [2] Chen, X.W., Pei, Z.Y., Wang, F., et al., 2016.GIS-Based Assessment of Rainstorm-Induced Geological Hazards Risk in Enshi Autonomous Prefecture. Journal of Geo-Information Science, 18(3):343-352(in Chinese with English abstract). doi: 10.3724/SP.J.1047.2016.00343 [3] Chu, H.B., Mu, H.D., Wang, J.Z., et al., 2003.Application of Analytic Hierarchy Procession Zoning Hazard Degree of Geologic Disaster in Taihang Mountain Region. The Chinese Journal of Geological Hazard and Control, 14(3):125-129(in Chinese with English abstract). doi: 10.1007/BF02830163 [4] Feng, H.J., Tang, X.M., Zhou, A.G., 2013.Study on Relationship between Rainfall Duration and Occurrence of Debris Flow in Zhejiang Province and Its Application Examination. Journal of Natural Disasters, 22(1):159-168(in Chinese with English abstract). http://www.oalib.com/paper/4488598 [5] Feng, H.J., Zhou, A.G., Tang, X.M., et al., 2016.Development and Distribution Characteristics of Debris Flow in Zhejiang Province and Its Regional Forecast. Earth Science, 41(12):2088-2099 (in Chinese with English abstract). http://www.en.cnki.com.cn/Article_en/CJFDTotal-DQKX201612012.htm [6] Gariano, S.L., Brunetti, M.T., Iovine, G., et al., 2015.Calibration and Validation of Rainfall Thresholds for Shallow Landslide Forecasting in Sicily, Southern Italy. Geomorphology, 228:653-665.doi: 10.1016/j.geomorph.2014.10.019 [7] Gou, M., 2009.Developing Characteristics and Preventions of Geological Disasters in Yunnan Province. Journal of Hebei University of Engineering (Social Science Edition), 26(2):15-17(in Chinese with English abstract). doi: 10.1007/s11069-015-1931-3 [8] Inagaki, K., Sadohara, S., 2006.Slope Management Planning for the Mitigation of Landslide Disaster in Urban Areas. Journal of Asian Architecture and Building Engineering, 5(1):183-190.doi: 10.3130/jaabe.5.183 [9] Li, H., Wu, J.J., Li, C.F., et al., 2010.BP Neural Network Model and Its Application to the Geological Hazard Warning in Henan. Journal of Safety and Environment, 10(2):119-122(in Chinese with English abstract). doi: 10.1007/s12517-009-0039-z [10] Liu, X.Q., Jiang, Q.O., Zhan, J.Y., 2008.Design and Application of Geo-Hazard Early-Warning Model. Journal of Engineering Geology, 16(3):342-347(in Chinese with English abstract). http://www.lirds.org/OCCASIONALPUBLICATIONS/Applications%20of%20GIS%20for%20Disaster%20EWS%20by%20Jacob%20Opadeyi.pdf [11] Ma, T.H., Li, C.J., Lu, Z.M., et al., 2015.Rainfall Intensity-Duration Thresholds for the Initiation of Landslides in Zhejiang Province, China. Geomorphology, 245:193-206.doi: 10.1016/j.geomorph.2015.05.016 [12] Ma, Y., Li, S.Z., Xia, Z., et al., 2014.Characteristics of Hazardous Geological Factors on Shenhu Continental Slope in the Northern South China Sea. Earth Science, 39(9):1364-1372 (in Chinese with English abstract). http://d.wanfangdata.com.cn/Periodical_dqkx201409013.aspx [13] Peng, G.F., 2006.PP-ES Method for Predicting Hazard Grades of Meteorological-Geological Disasters in Yunnan Province. Meteorological Science and Technology, 34(6):745-749 (in Chinese with English abstract). http://en.cnki.com.cn/Article_en/CJFDTotal-QXKJ200903005.htm [14] Wang, J.J., Yin, K.L., Xiao, L.L., 2014.Landslide Susceptibility Assessment Based on GIS and Weighted Information Value:A Case Study of Wanzhou District, Three Gorges Reservoir. Chinese Journal of Rock Mechanics and Engineering, 33(4):797-808(in Chinese with English abstract). http://www.rockmech.org/EN/Y2014/V33/I4/797 [15] Wang, X.J., Sun, S.Q., Lu, P.F., 2014.Application of AHP to Geological Hazards Risk Assessment in a County, Chongqing. Earth and Environment, 42(3):419-423 (in Chinese with English abstract). [16] Wang, Y.Q., Yang, Y.D., Zhou, C.Q., et al., 2015.Meteorological Early Warning of Geo-Hazards System in Yunnan Province Based on GIS Spatial Analysis. The Chinese Journal of Geological Hazard and Control, 26(1):134-137, 144 (in Chinese with English abstract). doi: 10.1007/s11859-006-0313-9 [17] Wu, S.R., Shi, J.S., Zhang, C.S., et al., 2009.Geo-Hazard Activity Intensity Evaluation:Theory, Methods and Practice. Geological Bulletin of China, 28(8):1127-1137(in Chinese with English abstract). http://www-pub.iaea.org/MTCD/publications/PDF/TCS-11.pdf [18] Wu, Y.P., Zhang, Q.X., Tang, H.M., et al., 2014.Landslide Hazard Warning Based on Effective Rainfall Intensity. Earth Science, 39(7):889-895 (in Chinese with English abstract). http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.483.4152&rep=rep1&type=pdf [19] Yu, Y.P., Mei, H.B., Li, J.H., et al., 2016.Landslide Displacement Prediction based on Varying Coefficient Regression Model in Three Gorges Reservoir Area. Earth Science, 41(9):1593-1602 (in Chinese with English abstract). http://www.sciencedirect.com/science/article/pii/S0013795217300856 [20] Zhou, X.M., Miao, Y., Cheng, L., et al., 2012.Research on Critical Precipitation and Forecasting Methods of Geological Hazards of Honghe Prefecture. Yunnan Geographic Environment Research, 24(3):37-42(in Chinese with English abstract). doi: 10.1007/s12665-015-4899-0 [21] 陈曦炜, 裴志远, 王飞, 2016.基于GIS的贫困地区降雨诱发型地质灾害风险评估——以湖北省恩施州为例.地球信息科学, 18(3):343-352. http://www.cnki.com.cn/Article/CJFDTOTAL-DQXX201603009.htm [22] 褚洪斌, 母海东, 王金哲, 等, 2003.层次分析法在太行山区地质灾害危险性分区中的应用.中国地质灾害与防治学报, 14 (3):125-129. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH200303026.htm [23] 冯杭建, 唐小明, 周爱国, 2013.浙江省泥石流与降雨历时关系研究及应用检验.自然灾害学报, 22(1):159-168. http://www.cnki.com.cn/Article/CJFDTOTAL-ZRZH201301022.htm [24] 冯杭建, 周爱国, 唐小明, 等, 2016.浙江省泥石流灾害发育分布规律及区域预报.地球科学, 41(12):2088-2099. http://www.earth-science.net/WebPage/Article.aspx?id=3403 [25] 苟敏, 2009.云南省地质灾害的发育特征及防治对策.河北工程大学学报(社会科学版), 26(2):15-17. http://www.cnki.com.cn/Article/CJFDTOTAL-SCDB201203021.htm [26] 李华, 吴俊俊, 李长发, 等, 2010.河南省汛期地质灾害预警的BP神经网络模型及应用.安全与环境学报, 10(2):119-122. http://www.cnki.com.cn/Article/CJFDTOTAL-AQHJ201002031.htm [27] 刘兴权, 姜群鸥, 战金艳, 等, 2008.地质灾害预警预报模型设计与应用.工程地质学报, 16(3):342-347. http://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ200803010.htm [28] 马云, 李三忠, 夏真, 等, 2014.南海北部神狐陆坡区灾害地质因素特征.地球科学, 39(9):1364-1372. http://www.earth-science.net/WebPage/Article.aspx?id=2934 [29] 彭贵芬, 2006.云南气象地质灾害危险等级PP-ES预报方法.气象科技, 34(6):745-749. http://www.cnki.com.cn/Article/CJFDTOTAL-QXKJ200606019.htm [30] 王佳佳, 殷坤龙, 肖莉丽, 2014.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.岩石力学与工程学报, 33(4):797-808. http://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201404018.htm [31] 王小江, 孙书勤, 卢鹏飞, 2014.层次分析法在重庆某县地质灾害危险性评价中的应用.地球与环境, 42(3):419-423. http://www.cnki.com.cn/Article/CJFDTOTAL-DZDQ201403022.htm [32] 王裕琴, 杨迎冬, 周翠琼, 等, 2015.基于GIS空间分析技术的云南省地质灾害气象风险预警系统.中国地质灾害与防治学报, 26(1):134-137, 144. http://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201501028.htm [33] 吴树仁, 石菊松, 张春山, 等, 2009.地质灾害活动强度评估的原理、方法和实例.地质通报, 28(8):1127-1137. http://www.cnki.com.cn/Article/CJFDTOTAL-CSDI201422015.htm [34] 吴益平, 张秋霞, 唐辉明, 等, 2014.基于有效降雨强度的滑坡灾害危险性预警.地球科学, 39(7):889-895. http://www.earth-science.net/WebPage/Article.aspx?id=2892 [35] 喻孟良, 梅红波, 李冀骅, 等, 2016.基于变系数回归的三峡库区滑坡位移预测.地球科学, 41(9):1593-1602. http://www.earth-science.net/WebPage/Article.aspx?id=3364 [36] 周秀美, 苗芸, 程林, 等, 2012.红河州地质灾害临界雨量及预报方法初探.云南地理环境研究, 24(3):37-42. http://www.cnki.com.cn/Article/CJFDTOTAL-YNDL201203009.htm