[1]谭红梅,贺中华*,陈莉会,等.贵州省极端降雨特征及其影响因子[J].山地学报,2023,(5):748-758.[doi:10.16089/j.cnki.1008-2786.000784]
　TAN Hongmei,HE Zhonghua,*,et al.Characteristics of Extreme Rainfall and Its Influencing Factors in Guizhou Province, China[J].Mountain Research,2023,(5):748-758.[doi:10.16089/j.cnki.1008-2786.000784]
点击复制

贵州省极端降雨特征及其影响因子
分享到：

《山地学报》[ISSN:1008-2186/CN:51-1516]

卷:
期数:
2023年第5期
页码:
748-758
栏目:
山地灾害
出版日期:
2023-11-15

文章信息/Info

Title:
Characteristics of Extreme Rainfall and Its Influencing Factors in Guizhou Province, China
文章编号:
1008-2786-(2023)5-748-11
作者:
谭红梅1; 贺中华1; 2*; 陈莉会1; 冯椰林1; 顾小林3
(1.贵州师范大学 地理与环境科学学院,贵阳 550001; 2.贵州省山地资源与环境遥感应用重点实验室,贵阳 550001; 3.贵州省水文水资源局, 贵阳 550002)
Author(s):
TAN Hongmei1;  HE Zhonghua1;  2*;  CHEN Lihui1;  FENG Yelin1;  GU Xiaolin3
(1.School of Geography and Environmental Science, Guizhou Normal University, Guiyang 550001, China; 2.Guizhou Mountain Resources and Environmental Remote Sensing Application Laboratory, Guiyang 550001, China; 3. Hydrology and Water Resources Survey Bureau of Guizhou Province, Guiyang 550002, China)
关键词:
极端降雨;  概率分布函数;  随机森林算法;  地理探测器;  贵州省
Keywords:
extreme rainfall;  probability distribution function;  random forest algorithm;  geodetector;  Guizhou province
分类号:
P426.6
DOI:
10.16089/j.cnki.1008-2786.000784
文献标志码:
A
摘要:
不同地区在下垫面结构、气候等方面存在区域异质性,极端降雨表现出不同演变趋势和独特的空间分布格局。贵州喀斯特地貌类型复杂,影响降雨空间再分配,极端降雨频发,地质灾害严重。针对贵州省极端气候的研究,大多关注其时空特征与模式数据预估,缺乏对其重现期特征及不同尺度影响因子的分析。本文基于贵州省31个站点1990—2020年逐日降雨数据计算极端降雨,采用8种分布函数对其拟合并选出各站点的最优分布函数,分析贵州省极端降雨重现期特征,探讨其不同尺度影响因子。结果表明:(1)近31年来贵州省极端降雨在时间上呈不显著增加趋势,空间上呈“南高北低、东高西低”的分布格局。(2)Weibull分布函数对贵州省大部分站点的极端降雨拟合效果最佳; 极端降雨的估计值随重现期增加而增大,在不同重现期均呈南高北低的分布格局,且南北差异随重现期增加而逐渐减弱。(3)大尺度影响因子中厄尔尼诺对极端降雨的影响最大; 局地尺度因子中温度、高程、二氧化碳为极端降雨的主要影响因子。研究结果可为贵州省防洪减灾提供科学指导。
Abstract:
Different geographical zones have regional heterogeneity in underlying earth surface structure and microclimate, which result in different trends and unique spatial pattern of extreme rainfalls in these zones. In Guizhou province of China, there are complex karst landforms, which lead to spatial redistribution of rainfall, frequent extreme rainfall, and geohazard occurrences. Research on extreme climate in Guizhou mostly paid attention to its spatio-temporal characteristics and modeling, but lacked of analysis on its recurrence interval and influencing factors on different scales.
This study investigated the characteristics of extreme rainfall recurrence period in Guizhou province and discussed influence factors on different scales. Daily rainfall data from 1990 to 2020 at 31 meteorological observation stations throughout the province were collected to calculate extreme precipitation, followed by 8 distribution functions to be selected for the determination of an optimal distribution function of each site.
This research had the following results.(1)In the past 31 years, there has been no significant increase in extreme rainfall in Guizhou province, with a spatial pattern of “high in the south and low in the north, high in the east and low in the west”.(2)The Weibull distribution function was the best fit for extreme rainfall at most stations; the estimation of extreme rainfall increased with the increase of recurrence period; the estimated values in each recurrence period showed a distribution pattern of “high in the south and low in the north”; the difference between the north and the south gradually weakened with the increase of recurrence period.(3)Among the large-scale influencing factors, El Nino had the greatest impact on extreme rainfall; among the local-scale influencing factors, temperature, elevation, and carbon dioxide were the main factors regulating extreme rainfalls.

参考文献/References:

[1] 徐飞, 张汶海, 赵玲玲, 等. 1960—2018年珠江流域极端气温时空变化特征[J]. 山地学报,2022, 40(3): 343-354. [XU Fei, ZHANG Wenhai, ZHAO Lingling, et al. Spatio-temporal variability in extreme temperature from 1960 to 2018 in the Pearl River basin, China [J]. Mountain Research, 2022, 40(3): 343-354] DOI: 10.16089/j.cnki.1008-2786.000676
[2] OLIVER E C J, DONAT M G, BURROWS M T, et al. Longer and more frequent marine heatwaves over the past century [J]. Nature Communications, 2018, 9(1): 1324. DOI: 10.1038/s41467-018-03732-9
[3] 甘露, 刘睿, 冀琴, 等. 四川省极端降水事件时空演变特征[J]. 山地学报, 2021, 39(1): 10-24. [GAN Lu, LIU Rui, JI Qin, et al. Spatio-temporal evolution characteristics analysis of extreme precipitation in Sichuan province, China [J]. Mountain Research, 2021, 39(1): 10-24] DOI: 10.16089/j.cnki.1008-2786.000572
[4] LI Linchao, ZOU Yufeng, LI Yi, et al. Trends, change points and spatial variability in extreme precipitation events from 1961 to 2017 in China [J]. Hydrology Research, 2020, 51(3): 484-504. DOI: 10.2166/nh.2020.095
[5] 曹瑜, 游庆龙, 马茜蓉, 等. 青藏高原夏季极端降水概率分布特征[J]. 高原气象, 2017, 36(5): 1176-1187. [CAO Yu, YOU Qinglong, MA Qianrong, et al. Probability distribution for the summer extreme precipitation in the Qinghai-Tibetan Plateau [J]. Plateau Meteorology, 2017, 36(5): 1176-1187] DOI: 10.7522/j.issn.1000-0534.2016.00131
[6] 史维良, 车璐阳, 李涛. 陕西省汛期极端降水概率分布及综合危险性评估[J]. 干旱区地理, 2023, 46(9): 1407-1417. [SHI Weiliang, CHE Luyang, LI Tao. Probability distribution and comprehensive risk assessment of extreme precipitation in flood season in Shaanxi province [J]. Arid Land Geography, 2023, 46(9): 1407-1417] DOI: 10.12118/j.issn.1000-6060.2022.567
[7] 陈子凡, 王磊, 李谢辉, 等. 西南地区极端降水时空变化特征及其与强ENSO事件的关系 [J].高原气象, 2022, 41(3): 604-616. [CHEN Zifan, WANG Lei, LI Xiehui, et al. Spatiotemporal change characteristics of extreme precipitation in south-western China and its relationship with intense ENSO events [J]. Plateau Meteorology, 2022, 41(3): 604-616] DOI: 10.7522/j.issn.1000-0534.2022.00004
[8] 邹磊, 夏军, 张印. 长江中下游极端降水时空演变特征研究[J]. 长江流域资源与环境, 2021, 30(5): 1264-1274. [ZOU Lei, XIA Jun, ZHANG Yin. Spatial-temporal characteristics of extreme precipitation in the middle and lower reaches of the Yangtze River [J]. Resources and Environment in the Yangtze Basin, 2021, 30(5): 1264-1274] DOI: 10.11870/cjlyzyyhj202105023
[9] WENTZ F J, RICCIARDULLI L, HILBURN K, et al. How much more rain will global warming bring [J]. Science, 2007, 317(5835): 233-235. DOI: 10.1126/science.1140746
[10] 王卫平, 刘永强, 赵求东, 等. 新疆地区极端降水时空变化特征及对气温变化的响应[J]. 农业工程学报, 2022, 38(4): 133-142. [WANG Weiping, LIU Yongqiang, ZHAO Qiudong, et al. Spatiotemporal characteristics of extreme precipitation and its response to temperature change in Xinjiang, China [J]. Transactions of the Chinese Society of Agricultural Engineering, 2022, 38(4): 133-142] DOI: 10.11975/j.issn.1002-6819.2022.04.016
[11] MIAO Chiyuan, DUAN Qingyun, SUN Qiaohong, et al. Non-uniform changes in different categories of precipitation intensity across China and the associated large-scale circulations [J]. Environmental Research Letters, 2019, 14(2): 025004. DOI: 10.1088/1748-9326/aaf306
[12] LIU Meixian, XU Xianli, SUN Alex. Decreasing spatial variability in precipitation extremes in southwestern China and the local/large-scale influencing factors [J]. Journal of Geophysical Research: Atmospheres, 2015, 120(13): 6480-6488. DOI: 10.1002/2014JD022886
[13] 韦小茶, 周秋文, 张继, 等. 1982—2016年广西NDVI时空变化及其影响因素[J]. 山地学报, 2020, 38(4): 520-531. [WEI Xiaocha, ZHOU Qiuwen, ZHANG Ji, et al. Spatial-temporal changes of NDVI and its influence factors in Guangxi, China during 1982-2016 [J]. Mountain Research, 2020, 38(4): 520-531] DOI: 10.16089/j.cnki.1008-2786.000530
[14] 冯椰林, 贺中华, 焦树林, 等. 基于CMIP6气候模式的贵州省极端降水情景预估[J]. 水土保持研究, 2023, 30(1): 282-290. [FENG Yelin, HE Zhonghua, JIAO Shulin, et al. Scenario prediction of extreme precipitation in Guizhou province based on CMIP6 climate model [J]. Research of Soil and Water Conservation, 2023, 30(1): 282-290] DOI: 10.13869/j.cnki.rswc.20220621.004
[15] 张娇艳, 李扬, 张东海, 等. 基于CMIP5全球气候模式的21世纪贵州省极端降水事件预估[J]. 中国农业气象, 2017, 38(10): 655-662. [ZHANG Jiaoyan, LI Yang, ZHANG Donghai, et al. Projected changes in extreme precipitation events in Guizhou based on CMIP5 simulations over the 21st century [J]. Chinese Journal of Agrometeorology, 2017, 38(10): 655-662] DOI: 10.3969/j.issn.1000-6362.2017.10.004
[16] 贺中华, 陈晓翔. 基于土壤因素耦合的喀斯特流域水文干旱模拟——以贵州省为例[J]. 地理科学, 2013, 33(6): 724-734. [HE Zhonghua, CHEN Xiaoxiang. The hydrological drought simulating in karst basin based on coupled soil factors-taking Guizhou province as a case [J]. Scientia Geographica Sinica, 2013, 33(6): 724-734] DOI: 10.13249/j.cnki.sgs.2013.06.016
[17] 张玉虎, 王琛茜, 刘凯利, 等. 不同概率分布函数降雨极值的适用性分析[J]. 地理科学, 2015, 35(11): 1460-1467. [ZHANG Yuhu, WANG Chenxi, LIU Kaili, et al. Applicability of different probability distributions to estimated extreme rainfall [J]. Scientia Geographica Sinica, 2015, 35(11): 1460-1467] DOI: 10.13249/j.cnki.sgs.2015.11.015
[18] ZHAO Ruxin, WANG Huixiao, ZHAN Chesheng, et al. Comparative analysis of probability distributions for the Standardized Precipitation Index and drought evolution in China during 1961-2015 [J]. Theoretical and Applied Climatology, 2020, 139(3-4): 1363-1377. DOI: 10.1007/s00704-019-03050-0
[19] 王晶. 偏正态分布拟合真实数据的效果研究[D]. 南京: 南京邮电大学, 2022: 49. [WANG Jing. A study of the effect of fitting real data to the skew-normal distribution [D]. Nanjing: Nanjing University of Posts and Telecommunications, 2022: 49] DOI: 10.27251/d.cnki.gnjdc.2022.000043
[20] 吴孝情, 陈晓宏, 唐亦汉, 等. 珠江流域非平稳性降雨极值时空变化特征及其成因[J]. 水利学报, 2015, 46(9): 1055-1063. [WU Xiaoqing, CHEN Xiaohong, TANG Yihan, et al. Spatiotemporal variations and the causes of non-stationary extreme precipitation in the Pearl River basin [J]. Journal of Hydraulic Engineering, 2015, 46(9): 1055-1063] DOI: 10.13243/j.cnki.slxb.20141415
[21] 徐勇, 郭振东, 郑志威, 等. 2000—2021年成渝城市群PM2.5时空变化及驱动机制多维探测[J]. 环境科学, 2023, 44(7): 3724-3737. [XU Yong, GUO Zhendong, ZHENG Zhiwei, et al. Spatio-temporal variation and multi-dimensional detection of driving mechanism of PM2.5 concentration in the Chengdu-Chongqing urban agglomeration from 2000 to 2021 [J]. Environmental Science, 2023, 44(7): 3724-3737] DOI: 10.13227/j.hjkx.202207276
[22] 肖瑶, 赵林, 邹德富, 等. 基于地理探测器的青藏高原多年冻土分布影响因子分析[J]. 冰川冻土, 2021, 43(1): 311-321. [XIAO Yao, ZHAO Lin, ZOU Defu, et al. Analyses of the influence factors of permafrost distribution on the Qinghai-Tibet Plateau based on geographical detector [J]. Journal of Glaciology and Geocryology, 2021, 43(1): 311-321] DOI: 10.7522/j.issn.1000-0240.2019.0063
[23] 卢瑞荆. 贵州暴雨洪涝的气候特征分析[D]. 兰州: 兰州大学, 2010: 88. [LU Ruijing. Analysis of climate characteristic of rainstorm in Guizhou province [D]. Lanzhou: Lanzhou University, 2010: 88] DOI: 10.7666/d.Y1703527
[24] 丁立国. 贵州山地复杂地形下暴雨洪涝灾害风险研究[D]. 南京: 南京信息工程大学, 2022: 60. [DING Liguo. Study on the risk of heavy rainfall and flooding in the complex terrain of Guizhou mountains [D]. Nanjing: Nanjing University of Information Engineering, 2022: 60] DOI: 10.27248/d.cnki.gnjqc.2022.000181
[25] 王涛, 伊丽努尔·阿力甫江, 李思颖, 等. 三种趋势分析法在东帕米尔高原降水特征分析中的应用[J]. 气象, 2022, 48(10): 1312-1320. [WANG Tao, YILINUER Alifujiang, LI Siying, et al. Three trend analysis methods in precipitation characteristic analysis of eastern Pamirs [J]. Meteorlogical Monthly, 2022, 48(10): 1312-1320] DOI: 10.7519/j.issn.1000-0526.2022.080501
[26] 徐乔婷, 陈涟, 范月华, 等. 基于SPEI指数的兰州干旱特征与气候指数的关系[J]. 水文, 2021, 41(2): 56-62. [XU Qiaoting, CHEN Lian, FAN Yuehua, et al. Relationship between Lanzhou drought and climate indices based on SPEI index [J]. Journal of China Hydrology, 2021, 41(2): 56-62] DOI: 10.19797/j.cnki.1000-0852.20200213
[27] 查雪婷. 淮河流域极端降水时空演变特征及重现期研究[D]. 蚌埠: 安徽财经大学, 2022: 65. [ZHA Xueting. Spatial and temporal evolution characteristics and recurrence periods of extreme precipitation in the Huaihe River basin [D]. Bengbu: Anhui University of Finance and Economics, 2022: 65] DOI: 10.26916/d.cnki.gahcc.2022.000518
[28] 唐莉, 杨冰冰, 魏希, 等. 气候变化对江西省主汛期降雨极值时空差异的影响研究[J]. 水利水电技术, 2023, 54(1): 53-63. [TANG Li, YANG Bingbing, WEI Xi, et al. Study on the impact of climate change on the extreme rainfall distribution in main flood season of Jiangxi province [J]. Water Resources and Hydropower Engineering, 2023, 54(1): 53-63] DOI: 10.13928/j.cnki.wrahe.2023.01.005
[29] 黄国如, 陈易偲, 姚芝军. 高度城镇化背景下珠三角地区极端降雨时空演变特征[J]. 水科学进展, 2021, 32(2): 161-170. [HUANG Guoru, CHEN Yisi, YAO Zhijun. Spatial and temporal evolution characteristics of extreme rainfall in the Pearl River Delta under high urbanization [J]. Advances in Water Science, 2021, 32(2): 161-170] DOI: 10.14042/j.cnki.32.1309.2021.02.001
[30] QIAO Panjie, GONG Zhiqiang, LIU Weiqi, et al. Extreme rainfall synchronization network between southwest China and Asia-Pacific region [J]. Climate Dynamics, 2021, 57: 3207-3221. DOI: 10.1007/s00382-021-05865-y
[31] 王昊. 西南地区极端气候指数时空变化及其对NDVI的影响特征研究[D]. 北京: 北京林业大学, 2019: 81. [WANG Hao. Temporal and spatial variation of extreme climate indices and its impact on NDVI in southwestern China [D]. Beijing: Beijing Forestry University, 2019: 81] DOI: 10.26949/d.cnki.gblyu.2019.000881
[32] 李帅, 陈鲜艳, 龚文婷, 等. 1961—2020年三峡区间降水极值特征分析[J]. 长江流域资源与环境, 2022, 31(10): 2166-2175. [LI Shuai, CHEN Xianyan, GONG Wenting, et al. Characteristics of precipitation extremes in Three Gorges Reservoir intervening basin during 1961-2020 [J]. Resources and Environment in the Yangtze Basin, 2022, 31(10): 2166-2175] DOI: 10. 11870 /cjlyzyyhj202210006
[33] 孔锋, 孙劭. 基于SSPs的未来全球陆地极端降水强度的空间分异特征预估[J]. 灾害学, 2021, 36(4): 107-112+118. [KONG Feng, SUN Shao. Spatial differentiation prediction of global land extreme precipitation intensity based on SSPs [J]. Journal of Catastrophology, 2021, 36(4): 107-112+118] DOI: 10.3969/j.issn.1000-811X.2021.04.018
[34] 陈世发. ENSO对韶关市1951—2013年降雨侵蚀力影响研究[J]. 地理科学, 2016, 36(10): 1573-1580. [CHEN Shifa. Impact of ENSO on rainfall erosivity in Shaoguan city during 1951-2013[J]. Scientia Geographica Sinica, 2016, 36(10): 1573-1580] DOI: 10.13249/j.cnki.sgs.2016.10.015
[35] LAN Yongchao, KANG Ersi, MA Quanjie, et al. Runoff of the upper Yellow River above Tangnag: Characteristics, evolution and changing trends [J]. Journal of Geographical Sciences, 2001, 11(3): 46-53. DOI: 10.1007/bf02892313
[36] ANDERSON T R, HAWKINS E, JONES P D. CO2, the greenhouse effect and global warming: From the pioneering work of Arrhenius and Callendar to today's Earth System Models [J]. Endeavour, 2016, 40(3): 178-187. DOI: 10.1016/j.endeavour.2016.07.002

相似文献/References:

[1]王鑫盈a,马 超a,b,等.浅层黄土滑坡易发性评价:以晋西黄土区蔡家川农地小流域为例[J].山地学报,2023,(6):904.[doi:10.16089/j.cnki.1008-2786.000796]
　WANG Xinyinga,MA Chaoa,b,et al.Risk Assessment of Shallow Loess Landslides: Taking a Small Watershed of Caijiachuan Farmland in the Loess Region of Western Shanxi of China as an Example[J].Mountain Research,2023,(5):904.[doi:10.16089/j.cnki.1008-2786.000796]

备注/Memo

备注/Memo:
收稿日期(Received date): 2023-06-20; 改回日期(Accepted date):2023-10-11
基金项目(Foundation item): 贵州省水利厅自然科学基金(KT202237); 国家自然科学基金(u1612441,41471032)。[National Natural Science Foundation of Guizhou Provincial Water Resources Bureau(KT202237); National Natural Science Foundation of China(u1612441, 41471032)]
作者简介(Biography): 谭红梅(2000-),女,贵州遵义人,硕士研究生,主要研究方向:喀斯特水文水资源与遥感。[TAN Hongmei(2000-), female, born in Zunyi, Guizhou province, M.Sc. candidate, research on karst hydrology and water resources and remote sensing] E-mail: ketan_biu@163.com
*通讯作者(Corresponding author): 贺中华(1976-),男,博士,教授,主要研究方向:喀斯特水文水资源与遥感。[HE Zhonghua, male, Ph.D., professor, research on karst hydrology and water resources and remote sensing] E-mail: hezhonghua7621@126.com
更新日期/Last Update: 2023-09-30