Climatology and Hydrology

Fine meteorological risk early warning forecast of main geological disasters in Gansu Province

  • Junxia ZHANG ,
  • Wubin HUANG ,
  • Antai LI ,
  • Xiumei YANG ,
  • Qian LI ,
  • Hongwei BIAN
Expand
  • 1. Lanzhou Central Meteorological Observatory, Lanzhou 730000, Gansu, China
    2. Lanzhou Dafang Electronics Co. Ltd., Lanzhou 730000, Gansu, China

Received date: 2022-12-13

  Revised date: 2023-03-31

  Online published: 2023-09-28

Abstract

Geological disasters frequently occur in Gansu Province, China, and the proportion of precipitation-type geological disasters is significant in this region. Based on the geological disaster data, encrypted precipitation observations and the CMA multi-source merged precipitation analysis system pertinent to April to October of each year from 2013 to 2021 in Gansu Province, the effective rainfall data were selected as the precipitation factor; and further the geological disaster probability fitting equations of effective rainfall for the two regions were established. A refined grid geological disaster meteorological risk early warning model is constructed using the disaster probability of the precipitation factor, potential risk of geological disaster, and vulnerability. Using real precipitation data and the fine gridded prediction forecasts (QPF) of the Lanzhou Central Meteorological Observatory, a mesh refinement forecast test of the risk model was established to test the geological disaster events that occurred in October 2021 in Gansu Province. The study results show the following: (1) Based on the disaster probability caused by effective rainfall, the critical effective rainfall thresholds of blue, yellow, orange, and red warning levels of geological disasters in the Loess Plateau and Longnan Mountains, respectively. Among them, the critical effective rainfall thresholds for blue and red warning levels in Longnan Mountains are 40.6 mm and 113.5 mm, respectively, which were significantly higher than the blue and red warning levels of 18.0 mm and 73.6 mm, respectively, in the Loess Plateau. (2) The risk discrimination indices of blue, yellow, orange, and red early warning levels of geological disaster meteorological risk in Gansu Province were determined. The index values ranged from 0.004 to 1.000, with values ranging from 0.336 to 1.000, indicating an early red warning level. (3) The refined grid geological disaster meteorological risk early warning model in Gansu Province can effectively provide a warning of geological disaster events, the proportion of each level of early warning is reasonable, and it can effectively reduce the high-level early warning rate and false alarm rate. Thus, the model shows a strong ability to provide geological disaster meteorological risk early warnings.

Cite this article

Junxia ZHANG , Wubin HUANG , Antai LI , Xiumei YANG , Qian LI , Hongwei BIAN . Fine meteorological risk early warning forecast of main geological disasters in Gansu Province[J]. Arid Land Geography, 2023 , 46(9) : 1443 -1452 . DOI: 10.12118/j.issn.1000-6060.2022.659

References

[1] 李媛, 孟晖, 董颖, 等. 中国地质灾害类型及其特征——基于全国县市地质灾害调查成果分析[J]. 中国地质灾害与防治学报, 2004, 15(2): 29-34.
[1] [Li Yuan, Meng Hui, Dong Ying, et al. Main types and characteristics of geo-hazard in China: Based on the results of geo-hazard survey in 290 counties[J]. The Chinese Journal of Geological Hazard and Control, 2004, 15(2): 29-34.]
[2] 狄靖月, 许凤雯, 李宇梅, 等. 东南地区引发地质灾害降水分型及阈值分析[J]. 灾害学, 2019, 34(1): 62-67.
[2] [Di Jingyue, Xu Fengwen, Li Yumei, et al. Precipitation type and threshold analysis of geological disasters in southeast[J]. Journal of Catastrophology, 2019, 34(1): 62-67.]
[3] 高速, 周平根, 董颖, 等. 泥石流预测、预报技术方法的研究现状浅析[J]. 工程地质学报, 2002, 10(3): 279-283.
[3] [Gao Su, Zhou Pinggen, Dong Ying, et al. Study on techniques and methods for prediction and warning of debris flow[J]. Journal of Engineering Geology, 2002, 10(3): 279-283.]
[4] 魏永明, 谢又予. 降雨型泥石流(水石流)预报模型研究[J]. 自然灾害学报, 2015, 6(4): 48-54.
[4] [Wei Yongming, Xie Youyu. Study on prediction models of precipitation-type debris flow[J]. Journal of natural disasters, 2015, 6(4): 48-54.]
[5] 张友谊, 胡卸文, 朱海勇. 滑坡与降雨关系研究展望[J]. 自然灾害学报, 2007, 16(1): 104-107.
[5] [Zhang Youyi, Hu Xiewen, Zhu Haiyong. Prospect of research on relationship between landslide and rainfall[J]. Journal of natural disasters, 2007, 16(1): 104-107.]
[6] 李宇梅, 杨寅, 狄靖月, 等. 全国地质灾害气象风险精细化网格预报方法及其应用[J]. 气象, 2020, 46(10): 1310-1319.
[6] [Li Yumei, Yang Yin, Di Jingyue, et al. Meteorological risk assessment method of geological disaster in China and its mesh refinement application[J]. Meteorological Monthly, 2020, 46(10): 1310-1319.]
[7] Wang T, Li Q, Hao L Y, et al. Study on the analysis system of meteorological and geological disaster grads early warning of WebGIS[J]. Meteorological and Environment Research, 2014, 5(12): 44-48.
[8] 张国平. 有效雨量和滑坡泥石流灾害概率模型[J]. 气象, 2014, 40(7): 886-890.
[8] [Zhang Guoping. Study on the relation between effective precipitation and landslide/debris-flow with probabilistic model[J]. Meteorological Monthly, 2014, 40(7): 886-890.]
[9] 郭富赟, 宋晓玲, 谢煜, 等. 甘肃地质灾害气象预警技术方法探讨[J]. 中国地质灾害与防治学报, 2015, 26(1): 127-133.
[9] [Guo Fuyun, Song Xiaoling, Xie Yu, et al. A discussion on the geological hazards meteorological warning system in Gansu Province[J]. The Chinese Journal of Geological Hazard and Control, 2015, 26(1): 127-133.]
[10] 陈静静, 姚蓉, 文强, 等. 湖南省降雨型地质灾害致灾雨量阈值分析[J]. 灾害学, 2014, 29(2): 42-47.
[10] [Chen Jingjing, Yao Rong, Wen Qiang, et al. Hazard rainfall threshold analysis of rainfall-induced geological disasters in Hunan Province[J]. Journal of Catastrophology, 2014, 29(2): 42-47.]
[11] 沈玲玲, 刘连友, 杨文涛, 等. 基于TRMM降雨数据的四川省地质灾害降雨阈值分析[J]. 灾害学, 2015, 30(2): 220-227.
[11] [Shen Lingling, Liu Lianyou, Yang Wentao, et al. Rainfall threshold analysis for the initiation of geological disasters in Sichuan Province based on TRMM data[J]. Journal of Catastrophology, 2015, 30(2): 220-227.]
[12] Inagaki K, Sadohara S. Slope management planning for the mitigation of landslide disaster in urban areas[J]. Journal of Asian Architecture & Building Engineering, 2006, 5(1): 183-190.
[13] 姚学祥, 徐晶, 薛建军, 等. 基于降水量的全国地质灾害潜势预报模式[J]. 中国地质灾害与防治学报, 2005(4): 101-106, 133.
[13] [Yao Xuexiang, Xu Jing, Xue Jianjun, et al. A potential forecast model for geological-related disasters based on precipitation[J]. The Chinese Journal of Geological Hazard and Control, 2005(4): 101-106, 133.]
[14] 李宇梅, 狄靖月, 许凤雯, 等. 基于当日临界雨量的国家级地质灾害风险预警方法[J]. 气象科技进展, 2018, 8(3): 77-83.
[14] [Li Yumei, Di Jingyue, Xu Fengwen, et al. A risk warning method based on the intraday critical precipitation for national geological disaster[J]. Advances in Meteorological Science and Technology, 2018, 8(3): 77-83.]
[15] 杨寅, 包红军, 彭涛. 台风“鲇鱼”强降水引发的地质灾害气象风险预警检验与分析[J]. 暴雨灾害, 2019, 38(3): 221-228.
[15] [Yang Yin, Bao Hongjun, Peng Tao. Verification and analysis of meteorological early warning of geological hazards during precipitation of typhoon ‘MEGI’[J]. Torrential Rain and Disasters, 2019, 38(3): 221-228.]
[16] 李阳春, 刘黔云, 李潇, 等. 基于机器学习的滑坡崩塌地质灾害气象风险预警研究[J]. 中国地质灾害与防治学报, 2021, 32(3): 118-123.
[16] [Li Yangchun, Liu Qianyun, Li Xiao, et al. Exploring early warning and forecasting of meteorological risk of landslide and rockfall induced by meteorological factors by the approach of machine learning[J]. The Chinese Journal of Geological Hazard and Control, 2021, 32(3): 118-123.]
[17] 周明浪, 邵新民, 罗美芳. 浙江温州滑坡地质灾害预警方法及应用[J]. 中国地质灾害与防治学报, 2014, 25(2): 90-97.
[17] [Zhou Minglang, Shao Xinmin, Luo Meifang. Method and application of landslide geological hazard early-warning in Wenzhou City[J]. The Chinese Journal of Geological Hazard and Control, 2014, 25(2): 90-97.]
[18] 薛群威, 刘艳辉, 唐灿. 突发地质灾害气象预警统计模型与应用[J]. 吉林大学学报(地球科学版), 2013, 43(5): 1614-1622.
[18] [Xue Qunwei, Liu Yanhui, Tang Can. Early warning statistical model of sudden geological hazards and its application[J]. Journal of Jilin University (Earth Science Edition), 2013, 43(5): 1614-1622.]
[19] 姚令侃. 用泥石流发生频率及暴雨频率推求临界雨量的探讨[J]. 水土保持学报, 1988, 2(4): 72-77.
[19] [Yao Lingkan. A research on the calculation of critical rainfall with frequency of debris flow and torrential rain[J]. Acta Conservations Soli Et Aquae Sinica, 1988, 2(4): 72-77.]
[20] 杨绚, 代刊, 朱跃建. 深度学习技术在智能网格天气预报中的应用进展与挑战[J]. 气象学报, 2022, 80(5): 649-667.
[20] [Yang Xuan, Dai Kan, Zhu Yuejian. Progress and challenges of deep learning techniques in intelligent grid weather forecasting[J]. Acta Meteorologica Sinica, 2022, 80(5): 649-667.]
[21] 孙帅, 师春香, 潘旸, 等. 中国区域三源融合降水产品的改进效果评估[J]. 水文, 2020, 40(6): 10-15.
[21] [Sun Shuai, Shi Chunxiang, Pan Yang, et al. The improved effects evaluation of three-source merged of precipitation products in China[J]. Journal of China Hydrology, 2020, 40(6): 10-15.]
[22] 金荣花, 代刊, 赵瑞霞, 等. 我国无缝隙精细化网格天气预报技术进展与挑战[J]. 气象, 2019, 45(4): 445-457.
[22] [Jin Ronghua, Dai Kan, Zhao Ruixia, et al. Progress and challenge of seamless fine gridded weather forecasting technology in China[J]. Meteorological Monthly, 2019, 45(4): 445-457.]
[23] 田冰, 王裕宜, 洪勇. 泥石流预报中前期降水量与始发日降水量的权重关系—以云南省蒋家沟为例[J]. 水土保持通报, 2008, 28(2): 71-75.
[23] [Tian Bing, Wang Yuyi, Hong Yong. Weighted relation between antecedent rainfall and process precipitation in debris flow prediction: A case study of Jiangjia Gully in Yunnan Province[J]. Bulletin of Soil and Water Conservation, 2008, 28(2): 71-75.]
[24] 沈军, 方琼, 吴贤云, 等. 湖南古丈山体滑坡影响因子分析[J]. 气象, 2017, 43(11): 1410-1419.
[24] [Shen Jun, Fang Qiong, Wu Xianyun, et al. Analysis of impact factor of landslide in Guzhang County of Hunan Province[J]. Meteorological Monthly, 2017, 43(11): 1410-1419.]
[25] 刘业伟, 许小华, 韩会明. 基于前期有效降雨量推求山洪灾害临界雨量[J]. 水利技术监督, 2021, 40(11): 148-151.
[25] [Liu Yewei, Xu Xiaohua, Han Huiming. The critical rainfall of mountain flood disaster was calculated based on the previous effective rainfall[J]. Technical Supervision in Water Resources, 2021, 40(11): 148-151.]
Outlines

/