| 非平稳标准化降水蒸散指数构建及中国未来干旱时空格局 |
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| 引用本文： | 温庆志,孙鹏,张强,姚蕊.非平稳标准化降水蒸散指数构建及中国未来干旱时空格局[J].地理学报,2020,75(7):1465-1482. |
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| 作者姓名： | 温庆志 孙鹏 张强 姚蕊 |
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| 作者单位： | 1. 安徽师范大学地理与旅游学院,芜湖 2410022. 北京师范大学环境演变与自然灾害教育部重点实验室,北京 1008753. 北京师范大学地表过程与资源生态国家重点实验室,北京 1008754. 北京师范大学减灾与应急管理研究院,北京 1008755. 南京师范大学虚拟地理环境教育部重点实验室,南京 210023 |
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| 基金项目： | 第二次青藏高原综合科学考察研究(2019QZKK0906);国家重点研发计划(2019YFA0606900);国家自然科学基金项目(41601023);国家自然科学基金项目(41771536);安徽省自然科学基金项目(1808085QD117) |
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| 摘 要： | 旱灾是一种致灾因子与成害机理均非常复杂的自然灾害,也是目前对其检测与风险防御最为困难的自然灾害种类之一。随着全球气候变化,干旱的变化逐渐趋于非平稳化,水文气象序列的非平稳性已有广泛研究,但在干旱检测指标中却鲜有考虑。基于标准化降水蒸散指数（SPEI）和非平稳性理论,构建非平稳性标准化降水蒸散指数（NSPEI）并进行适用性评价,利用NSPEI评估未来不同排放情景下中国气象干旱时空格局演变规律。结果表明：① 非平稳性站点集中在东北平原、黄淮海平原、长三角地区、青藏高原及周边区域,NSPEI拟合最优的站点占中国气象站点的88%（2177个站点）。② SPEI对温度较为敏感,在评估未来干旱变化时会高估干旱强度和持续时间性,而NSPEI能够克服这一弱点,较SPEI可更好的检测中国气象干旱,且能很好的刻画中国未来干旱变化。③ 低、高排放情景下中国北方干旱加剧,南方呈湿润化趋势;中排放情景下中国北方湿润化趋势明显,而中国南方则呈干旱化。基于NSPEI干旱检测结果,中高排放情景下中国未来极端干湿历时与发生频率均呈增加趋势。
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| 关 键 词： | 非平稳标准化降水蒸散指数 干旱检测 时空格局 全球变暖 |
| 收稿时间： | 2019-09-18 |
| 修稿时间： | 2020-04-15 |
A multi-scalar drought index for global warming: The non-stationary standardized precipitation evaporation index (NSPEI) and spatio-temporal patterns of future drought in China |
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| WEN Qingzhi,SUN Peng,ZHANG Qiang,YAO Rui.A multi-scalar drought index for global warming: The non-stationary standardized precipitation evaporation index (NSPEI) and spatio-temporal patterns of future drought in China[J].Acta Geographica Sinica,2020,75(7):1465-1482. |
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| Authors: | WEN Qingzhi SUN Peng ZHANG Qiang YAO Rui |
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| Abstract: | Drought is one of the most severe natural disasters that have widespread impacts on eco-environment and agriculture. Great efforts have been made on the study of the non-stationarity of hydrometeorological processes, while few reports are available addressing non-stationarity in drought index. Therefore, in this study, we attempted to develop a non-stationary standardized precipitation evaporation index (NSPEI) based on standardized precipitation evaporation index and non-stationary theory with the aim of investigating drought conditions across China in both space and time under different emission scenarios from 2006 to 2100. The results indicated that: (1) Stations with non-stationary hydrometeorological processes are concentrated in northeast China, the Huang-Huai-Hai Plain, the Yangtze River Delta, the Tibetan Plateau, the Hengduan Mountains, and the southern Xinjiang. The NSPEI has the best fitting performance at 88% of the meteorological stations considered in this study. (2) Compared with other drought indices, SPEI tends to overestimate the intensity and duration of droughts during evaluations of the future drought changes; while NSPEI avoids the weakness of SPEI in overestimation of drought intensity. Therefore, NSPEI can better monitor the meteorological droughts in China and describe the future drought changes across the country. (3) Drought monitoring results based on NSPEI indicated an increasing drought trend in northern China, and southern China is dominated by a wetting trend under the scenario of low and high emissions. Extreme dry and wet duration and occurrence frequency showed an increasing trend in China in the future under medium and high emission scenarios. |
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| Keywords: | non-stationary standardized precipitation evapotranspiration index drought monitoring spatio-temporal patterns global warming |
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