长江科学院院报 ›› 2020, Vol. 37 ›› Issue (10): 28-36.DOI: 10.11988/ckyyb.201908306

• 水资源与环境 • 上一篇    下一篇

长江流域气象干旱演变特征及未来变化趋势预估

刘君龙1, 袁喆1, 许继军1, 刘雁翼2, 程卫帅1, 田承伟3, 苗恒录4   

  1. 1.长江科学院 水资源综合利用研究所,武汉 430010;
    2.江西省水利规划设计研究院,南昌 330029;
    3.抚州市水文局,江西 抚州 344000;
    4.水利部牧区水利科学研究所,呼和浩特 010020
  • 收稿日期:2019-07-16 修回日期:2019-11-26 出版日期:2020-10-01 发布日期:2020-10-29
  • 通讯作者: 袁 喆(1988-),男,湖北武汉人,高级工程师,博士,主要从事气候变化下的水资源综合应对研究。E-mail:yuanzhe_0116@126.com
  • 作者简介:刘君龙(1992-),男,安徽亳州人,硕士研究生,研究方向为水文水资源。E-mail:673095036@qq.com
  • 基金资助:
    国家重点研发计划项目(2016YFC0400901);江西省自然科学基金项目(20181BAA208043);国家自然科学基金项目(51709008);中央级公益性科研院所基本科研业务费项目(CKSF2017061/SZ,CKSF2019292/SH+SZ)

Meteorological Drought Evolution Characteristics and Future Trends in the Yangtze River Basin

LIU Jun-long1, YUAN Zhe1, XU Ji-jun1, LIU Yan-yi2, CHENG Wei-shuai1, TIAN Cheng-wei3, MIAO Heng-lu4   

  1. 1. Water Resources Department, Yangtze River Scientific Research Institute, Wuhan 430010, China;
    2. Jiangxi Provincial Water Conservancy Planning, Design and Research Institute, Nanchang 330029, China;
    3. Fuzhou Hydrological Bureau, Fuzhou 344000, China;
    4. Research Institute of Pastoral Water Conservancy, Ministry of Water Resources, Hohhot 010020, China
  • Received:2019-07-16 Revised:2019-11-26 Published:2020-10-01 Online:2020-10-29

摘要: 基于长江流域及周边范围在内的318个气象站点1956—2018年的实测资料和CMIP5全球气候模式在3种RCPs情景下的预估数据,以标准化降水蒸散发指数作为干旱等级的划分指标,对流域历史气象干旱时空演变特征进行了分析,并预估了流域未来不同排放情景下的气象干旱时空变化趋势。结果表明:①近60 a,流域干旱率年际变化较大,平均干旱率为18.21%。从年代变化来看,近20 a干旱影响范围普遍较大;干旱频发地区主要位于岷江流域,干旱次数呈从上游向下游递减的趋势;高强度的干旱多发生于金沙江中下游地区和成都平原地区,平均场次干旱强度也呈从上游向下游递减的趋势;②在RCP2.6、RCP4.5和RCP8.5情景下,2020—2050年长江流域多年平均干旱面积分别为74.1万km2、75.7万km2和126.4万km2;流域上、中、下游干旱频次多年平均值分别为1.1~1.2次/a、1.0~1.1次/a、1.0~1.1次/a。预估时段内上、中、下游干旱频次较历史时段分别增加38.4%~50.7%,33.7%~45.3%和32.6%~49.6%;预估时段内上、中、下游干旱强度多年平均值分别为-1.68,-1.64,-1.60,与历史时段差别不大。研究结果可为相关部门制订科学合理的干旱灾害防范措施和对策提供科学依据。

关键词: 气候模式, 气象干旱, 标准化降水蒸散发指数, 长江流域, 时空变化

Abstract: The temporal and spatial evolution characteristics of historical meteorological drought in the Yangtze River basin (YRB) were analyzed, and the temporal and spatial variation trend of meteorological drought under different discharge scenarios in the basin in the future was predicted. The standardized precipitation evapotranspiration index is used as the index to classify drought grade according to the observed data of 318 meteorological stations in the basin and its surrounding areas from 1956 to 2018 and the predicted data of CMIP5 global climate model under three typical RCPs. Results show that: 1) In the past six decades, the drought rate in the YRB has changed greatly, with an average drought rate of 18.21%, while in ages scale, drought has had a widespread impact in the past two decades; the drought-prone areas in the YRB were mainly located in the Minjiang River basin, and the number of droughts decreased from the upper to the lower reaches; the high-intensity droughts in the YRB mostly occurred in the middle and lower reaches of the Jinsha River and in the Chengdu Plain, and the average drought intensity followed the trend of drought frequency. 2) Under RCP2.6, RCP4.5 and RCP8.5 scenarios, the annual average drought area of the YRB in 2020-2050 was 741 000 km2, 757 000 km2 and 1 264 000 km2, respectively; the annual average drought frequency of the upper, middle and lower reaches of the basin is 1.1-1.2 per year, 1.0-1.1 per year, and 1.0-1.1 per year, respectively. The frequency of drought in the upper, middle and lower reaches of the YRB increases by 38.4%-50.7%, 33.7%-45.3% and 32.6%-49.6% respectively compared with that in historical period; the average annual drought intensity of the upper, middle and lower reaches of the river basin in the predicted period is -1.68, -1.64, -1.60 respectively, which is not significantly different from that in historical period. The research results offer scientific basis for scientific and reasonable drought disaster prevention measures and countermeasures.

Key words: climate model, meteorological drought, standardized precipitation evapotranspiration index, Yangtze River basin, spatial and temporal variations

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