Risk assessment of landslide geological hazards under different rainfall conditions based on the Pearson Ⅲ curves
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摘要:
降雨是诱发滑坡崩塌等地质灾害的重要因素之一，极大地威胁着群众的生命财产安全，为有依据地采取防治措施以及避险搬迁。以云南省维西县叶枝镇为研究区，选取高程、土地利用类型、坡度、坡向、地貌类型、工程地质岩组、河流距离、断层距离、曲率9个评价因子，以栅格单元作为评价单元，采用随机森林算法和加权信息量法对评价因子进行权重分析，作出易发性评价，并在此基础上选择降雨量作为危险性评价因子，通过计算和皮尔逊Ⅲ型曲线预测研究区10 a一遇、20 a一遇、50 a一遇、100 a一遇的降雨量，得出4种不同的降雨工况，作出危险性评价。由统计所得，将易发性评价结果按照自然间断点法分成低、中、高、极高易发区4个等级，分别占据研究区面积32.80%，34.02%，21.96%，11.22%，用ROC曲线对其作精度验证，
AUC 值为89.2%；基于4种降雨工况条件下的地质灾害危险性评价结果，分别分出低、中、高、极高危险区4种等级，并对评价结果进行了对比分析。通过与实际调查情况对比，本研究得出的崩滑地质灾害危险性评价结果与实际情况较为吻合，能够为防灾减灾、避险搬迁提供合理依据。Abstract:Objective Rainfall is one of the important factors that induce geological disasters, such as landslides and collapses, posing a great threat to the safety of people's lives and property. Therefore, it is necessary to take effective prevention and control measures as well as to avoid and relocate.
Methods This study takes Yezhi Town, Weixi County, Yunnan Province as the study area, and the grid unit is used as the evaluation unit. Nine evaluation factors, including elevation, land use type, slope, aspect, elevation, landform type, engineering geological rock group, land use type, distance from river, distance from fault, and curvature were selected. The random forest algorithm and weighted information method were used to analyze the weight of evaluation factors, and a susceptibility evaluation was also made. Based on this, rainfall was selected as the risk assessment factor. By calculating and predicting the rainfall in the study area with Pearson Ⅲ curve, rainfall in the study area was predicted for every 10 years, 20 years, 50 years, and 100 years, and a risk assessment was obtained.
Results According to statistics, the susceptibility assessment results are divided into four levels using the natural discontinuity method: low, medium, high, and extremely high-susceptibility areas, which account for 32.80%, 34.02%, 21.96%, and 11.22% of the study area respectively. The ROC curves were used to verify the accuracy, and the
AUC value was 89.2%.Conclusion By comparing the actual investigation situation, the landslide and collapse risk assessment results under different rainfall conditions are highly consistent with the actual situation. This study provides a basis for reasonable disaster prevention and mitigation, as well as risk avoidance and relocation.
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图 2 评价因子图
a. 高程；b. 坡度；c. 坡向；d. 曲率；e. 工程地质岩组；f. 地貌类型；g. 断层距离；h. 河流距离；i. 土地利用类型
Figure 2. Evaluation factor diagram
表 1 加权信息量
Table 1. Weighted information scale
评价因子 因子分级 栅格数量 崩滑数量 信息量值 权重 地貌类型 构造侵蚀高山地貌 111746 0 0.0000 0.0555 堆积地貌 36567 8 0.9233 构造侵蚀高中山地貌 415576 41 0.1269 土地利用类型 林地 454821 21 − 0.6303 0.1570 灌木 875 0 0.0000 草地 73323 20 1.1459 耕地 16868 0 0.0000 建筑 2004 1 1.7499 裸地 8943 5 1.8636 开阔水域 8198 2 1.0343 苔藓 7 0 0.0000 断层距离/m [0，500） 200491 22 0.2333 0.0555 [500， 1000 ）156470 20 0.3859 [ 1000 ，1500 ）95877 6 − 0.3283 [ 1500 ，2500 ]78132 1 − 1.9154 > 2500 32919 0 0.0000 高程/m [ 1600 ，2400 ）172759 42 1.0288 0.1832 [ 2400 ，3200 ）212125 7 − 0.9682 [ 3200 ，4400 ]179001 0 0.0000 工程地质岩组 黏性土单层土体 38419 9 0.9917 0.1008 较软-较硬薄-中层状砂岩、角砾岩强风化岩组 44628 8 0.7241 卵石、碎石、砂土多层土体 43376 12 1.1580 软薄-中层状片岩、变质凝灰岩、板岩、千枚岩岩组 239541 18 − 0.1453 较硬-坚硬岩浆岩、变质岩浆岩岩组 114498 2 − 1.6044 较坚硬块状-中层状灰岩、砾岩、凝灰岩 83427 0 0.0000 坡度/（°） [0，15） 61903 7 0.2574 0.1570 [15，25） 113569 13 0.2696 [25，35） 175621 16 0.0414 [35，45） 148755 4 − 1.1789 [45，90] 60707 9 0.5283 坡向 平面 1748 0 0.0000 0.1176 北（0°～10°） 41163 0 0.0000 东北 65200 2 − 1.0472 东 44842 3 − 0.2674 东南 60243 5 − 0.0518 南 68086 13 0.7813 西南 79290 9 0.2612 西 69350 2 − 1.1089 西北 86134 6 − 0.2270 北（350°～0°） 44499 3 − 0.2597 曲率 凹型坡 279981 32 0.2740 0.0555 平面坡 5519 0 0.0000 凸型坡 278385 17 − 0.3528 河流距离/m [0，300） 244079 43 0.7067 0.1176 [300，600） 185425 5 − 1.1702 [600， 1000 ]125862 1 − 2.3921 > 1000 8523 0 0.0000 
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表 2 易发性评价结果统计
Table 2. Statistical of the susceptibility evaluation results
易发性等级 面积比例/% 崩滑数量 崩滑比例/% 灾害密度/(处·km−2) 低 32.80 1 2.0 0.01 中 34.02 3 6.1 0.03 高 21.96 16 32.7 0.35 极高 11.22 29 59.2 1.15
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表 3 2010-2020 a各年月最大降雨量
Table 3. Maximum rainfall in each month from 2010 to 2020
年份 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 月最大降
雨量/mm302.9 159.6 139.3 122.9 197.7 176.5 223.7 223.5 213.6 157.6 191.4
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表 4 K值结算结果
Table 4. Results of K value settlement
年份 降雨量X/mm ${K}=X{/\overline{X}} $ 2010 302.9 1.580073 2011 159.6 0.832551 2012 139.3 0.726656 2013 122.9 0.641106 2014 197.7 1.031299 2015 176.5 0.920709 2016 223.7 1.166927 2017 223.5 1.165884 2018 213.6 1.114241 2019 157.6 0.822118 2020 191.4 0.998435 合计 2108.7
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表 5 叶枝镇不同概率的月最大降雨量
Table 5. Monthly maximum rainfall with different probabilities in Yezhi Town
概率 $\phi$ $ {A}=\overline{X}(\phi{C}_{{\mathrm{v}}}+1) $/mm 10 a一遇(10%) 1.34 258.5 20 a一遇(5%) 1.86 284.4 50 a一遇(2%) 2.50 316.2 100 a一遇(1%) 2.96 339.2 注：ϕ为离散系数；A为各概率下的月最大降雨量；Cv为变差系数
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