| 基于栅格径流汇流模拟的西藏林芝市泥石流灾害预警模型初探 |
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| 引用本文： | 陈宫燕,李婷,陈军,普布桑姆,阿旺卓玛,旺杰.基于栅格径流汇流模拟的西藏林芝市泥石流灾害预警模型初探[J].中国地质灾害与防治学报,2023,34(1):110-120. |
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| 作者姓名： | 陈宫燕 李婷 陈军 普布桑姆 阿旺卓玛 旺杰 |
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| 作者单位： | 1.林芝市气象局，西藏 林芝 860013 |
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| 基金项目： | 西藏自治区自然科学基金项目（XZ202101ZR0042G） |
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| 摘 要： | 西藏林芝市泥石流灾害频发，亟需建立泥石流灾害预警模型，预测林芝市泥石流灾害可能发生的区域，减少泥石流灾害导致的损失。文章提出了一种基于栅格径流汇流的林芝市泥石流灾害预警模型，从栅格像元尺度上模拟流域各位置上的水深，以提高泥石流预警的空间针对性。该模型将泥石流致灾因子分为背景因子和激发因子。通过林芝市裸岩率、河床纵比降等因子的逻辑回归，获取林芝市泥石流灾害概率，作为泥石流预警模型的背景因子；引入栅格径流汇流模型，以站点降水和雪水当量为模型的水量输入，模拟预警时段内的流域各位置上的模型水深，作为泥石流预警模型的激发因子。利用二元逻辑回归的方法计算背景因子和激发因子的权重，建立泥石流预警模型。利用2011—2020年18次历史灾害对模型进行验证，落入预警区内的灾害点占比64.4%，预警精度较高，对于林芝市泥石流灾害预警具有一定的指导意义。
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| 关 键 词： | 林芝市 泥石流灾害 径流汇流 |
| 收稿时间： | 2022-01-04 |
Primary establishment of an early warning model of debris flow hazards in Nyingchi City of Tibetan autonomous region based on raster runoff simulation |
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| Affiliation: | 1.Linzhi City Meteorological Bureau, Linzhi ,Tibet 860013, China2.College of Resources and Environment, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China |
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| Abstract: | Debris flow disasters occur frequently in Nyingchi City, Tibet. There is an urgent need to establish an early warning model to predict the possible areas of debris flow disasters in Nyingchi City and reduce the losses caused by those disasters. This paper presented an early warning model based on raster runoff simulation in Nyingchi City, which can simulate the water depth at each location in the watershed and improve the spatial pertinence of debris flow early warning. In this model, the disaster factors of debris flow are divided into background factor and excitation factor. The probability of debris flow disaster in Nyingchi City is obtained by logistic regression of many factors such as bare rock rate, vertical slope of riverbed and so on, which is used as the background factor. The raster runoff simulation model is introduced to simulate the predicted water depth at each position of the basin during the early warning period by importing the precipitation and snow water equivalent data. Using binary logistic regression method to calculate the weight of background factor and excitation factor, the final model is obtained. 18 historical disasters from 2011 to 2020 were used to verify the model. The disaster points falling into the early warning area accounted for 64.4%, which has certain guiding significance for the early warning of debris flow disaster in Nyingchi City. |
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