Tajikistan,a mountainous country and a vital water tower for Central Asia,is becoming increasingly vulnerable to snow drought under climate change,threatening its snow-and glacier-fed streamflow.Yet,the impacts of sno...Tajikistan,a mountainous country and a vital water tower for Central Asia,is becoming increasingly vulnerable to snow drought under climate change,threatening its snow-and glacier-fed streamflow.Yet,the impacts of snow drought on the regional hydrology remain insufficiently understood.In this study,we integrated multisource data,including the Fifth Generation European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis for Land Applications(ERA5-Land)data and hydrological station data,to systematically assess the snow drought patterns and their impacts on streamflow during 1950–2023.We identified snow drought events based on precipitation and snow fraction anomalies relative to climatological means and classified them into warm snow drought,dry snow drought,and warm&dry snow drought.The results revealed that snow drought was a recurrent phenomenon,occurring in 51.70%of the years during the study period,with warm&dry snow drought accounting for 21.90%of the total events.Both the frequency and severity exhibited pronounced spatial variability,largely governed by the elevation and snowfall fraction.Specifically,the frequency of warm snow drought was negatively correlated with the snowfall fraction,decreasing on average by 0.20 per unit increase in snowfall fraction,whereas the frequency of dry snow drought was positively correlated,increasing by 0.07 per unit increase.The streamflow analysis results demonstrated that snow drought typically reduced the warm-season discharge by 5.00%–18.00%in certain rivers,thereby exacerbating the water stress during the dry season.The results of this study advance our understanding by explicitly linking the types of snow drought to hydrological responses in Central Asia’s high mountains,providing a scientific basis for climate adaptation and sustainable water resource management in Tajikistan.展开更多
华南前汛期降水量大,且常出现持续3天以上、甚至长达10天以上的持续性强降水事件(Persistent Heavy Rainfall Event,PHRE),给该地区带来严重的洪涝灾害,提升前汛期降水的延伸期(提前10~30天或2~6候)预报水平至关重要。重点论述华南降水...华南前汛期降水量大,且常出现持续3天以上、甚至长达10天以上的持续性强降水事件(Persistent Heavy Rainfall Event,PHRE),给该地区带来严重的洪涝灾害,提升前汛期降水的延伸期(提前10~30天或2~6候)预报水平至关重要。重点论述华南降水延伸期预报可预报性的来源,以及当前数值模式、动力-统计释用和机器学习在延伸期预报领域的应用情况,以期了解华南前汛期降水延伸期预报的主要进展。展开更多
随着气候变化加剧干旱风险,精准监测干旱对水资源管理和生态保护至关重要。标准化蒸散发亏缺指数(SEDI)与标准化降水蒸散指数(SPEI)作为新一代干旱监测指标,其适用性研究具有显著的理论与应用价值。文中基于CiteSpace软件对2010—2025年...随着气候变化加剧干旱风险,精准监测干旱对水资源管理和生态保护至关重要。标准化蒸散发亏缺指数(SEDI)与标准化降水蒸散指数(SPEI)作为新一代干旱监测指标,其适用性研究具有显著的理论与应用价值。文中基于CiteSpace软件对2010—2025年间CNKI与Web of Science核心数据库的652篇中英文文献进行可视化分析,系统梳理了SEDI与SPEI的研究趋势、热点及区域适用性。核心发现与突破在于:1)机理互补与精度提升:SEDI基于实际蒸散发亏缺(P-AET),对植被水分胁迫高度敏感,在干旱半干旱区(PET/P>1.5)监测误差较传统指数降低62%;SPEI基于降水与潜在蒸散差值(P-PET),在多时间尺度气象干旱表征中误差降低35%,突破SPI忽视温度影响、PDSI参数复杂的局限。2)动态阈值模型的突破:基于Budyko水热耦合理论,创新性建立了以PET/P比值为核心的动态阈值模型(阈值1.5),明确了干旱半干旱区优先适用SEDI、湿润区优选SPEI、过渡区需双指数交叉验证的区域适用原则,显著提升了不同气候区干旱监测的针对性和准确性。3)实际应用成果:研究表明,SEDI在季风区雨季可提前2—3周识别干旱信号,为农业灌溉决策提供关键时间窗口;融合高分卫星数据的SEDI/SPEI协同应用在国内已实现30m/日级高精度监测,为黄河流域等脆弱生态区干旱风险管理提供了有力支撑。由此可见,SEDI与SPEI通过其互补机理与区域适配性,在提升干旱监测精度、时效性及生态响应表征方面取得了实质性突破,但仍需在复杂下垫面适应性、数据融合模型等方面深化研究。展开更多
基金supported by the National Key Research and Development Project of China(2025YFE0103300)the National Natural Science Foundation of China(W2412135)+2 种基金the Natural Science Foundation of Xinjiang Uygur Autonomous Region(2024D01A143,2025D01B165)the China Postdoctoral Science Foundation(GZC20250226)the S&T Innovation and Development Project of Information Institution of Ministry of Emergency Management,China(2024506).
文摘Tajikistan,a mountainous country and a vital water tower for Central Asia,is becoming increasingly vulnerable to snow drought under climate change,threatening its snow-and glacier-fed streamflow.Yet,the impacts of snow drought on the regional hydrology remain insufficiently understood.In this study,we integrated multisource data,including the Fifth Generation European Centre for Medium-Range Weather Forecasts Atmospheric Reanalysis for Land Applications(ERA5-Land)data and hydrological station data,to systematically assess the snow drought patterns and their impacts on streamflow during 1950–2023.We identified snow drought events based on precipitation and snow fraction anomalies relative to climatological means and classified them into warm snow drought,dry snow drought,and warm&dry snow drought.The results revealed that snow drought was a recurrent phenomenon,occurring in 51.70%of the years during the study period,with warm&dry snow drought accounting for 21.90%of the total events.Both the frequency and severity exhibited pronounced spatial variability,largely governed by the elevation and snowfall fraction.Specifically,the frequency of warm snow drought was negatively correlated with the snowfall fraction,decreasing on average by 0.20 per unit increase in snowfall fraction,whereas the frequency of dry snow drought was positively correlated,increasing by 0.07 per unit increase.The streamflow analysis results demonstrated that snow drought typically reduced the warm-season discharge by 5.00%–18.00%in certain rivers,thereby exacerbating the water stress during the dry season.The results of this study advance our understanding by explicitly linking the types of snow drought to hydrological responses in Central Asia’s high mountains,providing a scientific basis for climate adaptation and sustainable water resource management in Tajikistan.
文摘华南前汛期降水量大,且常出现持续3天以上、甚至长达10天以上的持续性强降水事件(Persistent Heavy Rainfall Event,PHRE),给该地区带来严重的洪涝灾害,提升前汛期降水的延伸期(提前10~30天或2~6候)预报水平至关重要。重点论述华南降水延伸期预报可预报性的来源,以及当前数值模式、动力-统计释用和机器学习在延伸期预报领域的应用情况,以期了解华南前汛期降水延伸期预报的主要进展。
文摘随着气候变化加剧干旱风险,精准监测干旱对水资源管理和生态保护至关重要。标准化蒸散发亏缺指数(SEDI)与标准化降水蒸散指数(SPEI)作为新一代干旱监测指标,其适用性研究具有显著的理论与应用价值。文中基于CiteSpace软件对2010—2025年间CNKI与Web of Science核心数据库的652篇中英文文献进行可视化分析,系统梳理了SEDI与SPEI的研究趋势、热点及区域适用性。核心发现与突破在于:1)机理互补与精度提升:SEDI基于实际蒸散发亏缺(P-AET),对植被水分胁迫高度敏感,在干旱半干旱区(PET/P>1.5)监测误差较传统指数降低62%;SPEI基于降水与潜在蒸散差值(P-PET),在多时间尺度气象干旱表征中误差降低35%,突破SPI忽视温度影响、PDSI参数复杂的局限。2)动态阈值模型的突破:基于Budyko水热耦合理论,创新性建立了以PET/P比值为核心的动态阈值模型(阈值1.5),明确了干旱半干旱区优先适用SEDI、湿润区优选SPEI、过渡区需双指数交叉验证的区域适用原则,显著提升了不同气候区干旱监测的针对性和准确性。3)实际应用成果:研究表明,SEDI在季风区雨季可提前2—3周识别干旱信号,为农业灌溉决策提供关键时间窗口;融合高分卫星数据的SEDI/SPEI协同应用在国内已实现30m/日级高精度监测,为黄河流域等脆弱生态区干旱风险管理提供了有力支撑。由此可见,SEDI与SPEI通过其互补机理与区域适配性,在提升干旱监测精度、时效性及生态响应表征方面取得了实质性突破,但仍需在复杂下垫面适应性、数据融合模型等方面深化研究。
