鄱阳湖流域过去1000 a径流模拟以及对气候变化响应研究

为研究过去千年尺度径流变化及其对气候变化的响应,以长江中游鄱阳湖流域为研究区,运用气候模式CCSM4和ECHAM5模拟过去1000 a气候数据,空间降尺度后驱动水文模型模拟了鄱阳湖流域过去近千年流域径流序列.利用快速傅里叶变换、小波分析等手段,分析流域极端径流变化特征、周期和该流域旱涝事件发生频率.结果表明:2种气候模式均能反映出中世纪暖期及小冰期阶段的干湿交替变化,且小冰期内中干旱状态维持时间较长;径流的丰枯变化与降水量变化具有较好的对应关系.CCSM4和ECHAM5模式下发生旱涝灾害与极大极小降水事件发生频率基本相同,径流丰枯变化与降水变化周期相近,均具有30 a左右的主周期,10~15、7 a左右的子周期.小波系数模平方图中30 a左右显著的能量信号揭示了该周期与北太平洋气候的主要环流机制的太平洋年代际振荡周期相近,因此,大气环流涛动是造成气候-水文变化的主要原因.研究结果拓展了基于近代60 a观测记录的流域水文变化的认识,探讨了千年时间长度下流域干湿变化特征和水文对气候响应的动力机制,有助于全面系统认识长江中游在全球气候暖化背景下旱涝极端水文事件的发生机制与变化规律.     

7种气象干旱指数的中国区域适应性

作为干旱问题的基础,干旱指数的确定一直是干旱研究的难点之一,至今尚没有统一的干旱指数能适用于广泛的干旱研究,因此研究干旱指数的区域适用性具有重要的科学意义.本文使用Gravity Recovery And Climate Experiment(GRACE)反演的陆地水储量、观测的土壤湿度和径流数据,评估了Palmer干旱指数(PDSI)、基于中国台站观测数据的修正PDSI(PDSI CN)、自矫正PDSI(scPDSI)、地表湿润指数(SWI)、标准化降水指数(SPI)、标准化降水蒸散发指数(SPEI)和气象观测数据驱动的陆面数值模式模拟的土壤湿度(CLM3.5/ObsFC)共7种干旱指数在中国的区域适用性.结果表明:scPDSI在中国地区的适用性最优,但其数值范围明显小于PDSI和PDSI_CN,需要制定新的旱涝等级分级标准.由于经验参数的代表性差,PDSI和PDSI CN在中国干旱区和湿润区的应用会存在一定的问题.SPI和SPEI在湿润地区的适用性较好,而在干旱半干旱地区的适用性较差.这是因为在干旱半干旱地区,SPI没有考虑气温异常的影响,因此结果偏湿;当采用Thomthwaite方法计算潜在蒸散时,SPEI会高估气温变化的影响,因此结果偏干.2000年之前,CLM3.5/ObsFC在中国区域的适用性较好,但2000年之后在干旱半干旱地区的适用性较差.在检测年尺度的干湿变化上,SWI与其他干旱指数表现出基本一致的年际与年代际演变特征.对于中国区域干湿变化的长期趋势,7种干旱指数的检测结果一致,均显示出明显的阶段性变化特征.但在量值上,不同干旱指数的检测结果存在明显的差异.这种差异既与指数自身的定义有关,也有气候变化有关.     

基于马尔科夫链模型的鄱阳湖流域水文气象干旱研究

基于气象和水文干旱的二维变量干旱状态基础上,通过一阶马尔科夫链模型对二维变量干旱状态进行频率、重现期和历时分析,建立水文气象干旱指数,从干旱灾害形成、演变和持续3方面对干旱灾害进行研究,同时预测未来6个月非水文干旱到水文干旱的概率.结果表明:(1)修河流域在干旱形成中危害大,抚河流域和修河流域在干旱演变中危害大,赣江流域和饶河流域在干旱持续中危害大;(2)鄱阳湖流域状态4(气象、水文干旱)发生的频率最高,为0.30,连续湿润或者干旱的概率最大,湿润状态(状态2)与水文干旱(状态4、状态5(气象湿润、水文干旱))的相互转移概率最低;(3)在长期干旱预测中,鄱阳湖流域从状态2转到状态4和状态5的平均概率为0.11,属最低,而状态1(气象、水文无旱)和状态3(气象干旱、水文湿润)到达状态4的概率为0.23,发生概率最大.修河流域在非水文干旱状态下未来发生气象、水文干旱状态的平均概率为0.28,是"五河"中最高的,而赣江流域在正常或者湿润状态下未来发生气象、水文干旱的概率最低,为0.18,该研究对于鄱阳湖流域水文气象干旱的抗旱减灾具有重要理论与现实意义.     

基于SPEI的黄河流域干旱时空格局研究

干旱是对人类社会影响最为严重的自然灾害之一,在中国干旱灾害频发,严重威胁着人们的生存环境.黄河流域是中国各大流域中受干旱影响最严重的区域,所以对黄河流域旱情进行监测尤为重要.文章基于1961~2015年黄河流域124个站点的月值气象数据,以标准化降水蒸散指数SPEI作为干旱指标,应用极点对称模态分解ESMD方法对SPEI序列进行时频周期与趋势分解,运用B-G分割算法进行阶段划分,从干旱年际变化、季节变化、干旱频率和干旱强度等方面对黄河流域及其8个水资源分区的干旱时空格局进行研究.结果表明:(1)近55年来黄河流域的干旱呈显著增加趋势, SPEI倾向率为-0.148 (10a)~(-1),其中兰州至河口镇地区干旱化趋势最为明显(-0.214 (10a)~(-1));(2)黄河流域干旱具有准2.9年、准5年、准10.2年和准18.3年的周期特征,且可划分为3个阶段(1961~1996年、1997~2002年和2003~2015年),对应SPEI均值分别为0.20、-0.71和-0.21;(3)干旱频率从大到小依次为夏季春季秋季冬季,均值分别为71.0%、47.2%、10.2%和6.9%;(4)干旱强度从大到小依次为夏季春季冬季秋季,均值分别为0.93、0.40、0.05和0.04.     

长江流域降水极值时间序列的分布特征

在1960-2005年长江流域147气象观测站汛期4-9月逐日降水资料基础上,通过计算逐站大于95th强降水及其间隔天数、小于1.27mm/d的持续天数,分析长江流域降水极值时间序列的时空分布特征,并建立概率分布模式.研究发现,长江上游四川盆地附近及中下游鄱阳湖流域东南部是汛期强降水中心,也是长江流域强降水最集中发生的地区.汛期降水强度小于1.27mm/d的天数,在上游干流、岷沱江流域、乌江上游地区为多.但此处干旱持续天数最短,干旱形式并不严重.而在金沙江上、下游,洞庭湖流域,鄱阳湖流域东南部支流及下游干流区干旱持续天数较长.长江流域大于95th强降水的间隔天数与小于1.27mm/d的干旱持续天数服从Weibull-Ⅱ型分布.分布参数变化的模式较准确的反映降水极值时间序列的时空变化特征.     

全球变暖背景下中亚干旱区降水变化特征及其空间差异

依据Climatic Research Unit（CRU）1930～2009年间的最新0.5°×0.5°网格点的月均降水量序列,本文分析了中亚干旱区近80年来的降水变化特征及其区域差异.结果发现,近80年来主要受西风环流控制的中亚干旱区年降水整体上表现出增加趋势,年降水中以冬季降水的增加趋势最明显（0.7mm/10a）.中亚干旱区近80年来的降水变化存在空间差异,可划分为五个降水变化区域（Ⅰ-哈萨克斯坦西区,Ⅱ-哈萨克斯坦东区,Ⅲ-中亚平原区,Ⅳ-吉尔吉斯斯坦区,Ⅴ-伊朗高原区）,根据年降水分布模式以45°N为界划分为两类：研究区北部的两个区（Ⅰ和Ⅱ区）四季降水较均匀,南部的三个区均以春、冬季降水为主（占全年降水的60%～82%）.在降水变化趋势上,除了中亚干旱区西南（Ⅴ区）在近80年来有微弱的减少趋势外,其他四区均表现为增加趋势,尤以干旱区西部的Ⅰ区和Ⅲ区降水增加显著.近80年来降水增加或者减少的趋势主要取决于冬季的变化趋势.研究还发现,中亚干旱区降水存在较明显的年际变化, 中亚干旱区及其各分区都具有2～3 a的显著周期,南部三区（Ⅲ,Ⅳ,Ⅴ区）还存在5～6 a的显著周期,在此基础上都具有3～4个阶段性的变化趋势.最近一次趋势性变化开始于20世纪70年代中后期,研究区降水更多的表现出区域的差异性.近80年来,中亚干旱区降水对全球变暖的响应复杂,西风环流变化可能是影响中亚干旱区降水变化的主要因素.     

基于小波分析的河北平原降水变化规律研究

利用1955～2000年月平均降水和年平均降水资料, 采用墨西哥帽小波函数, 对河北平原近45年来降水的季节变化和年际变化时间序列进行了小波分析, 揭示了河北平原降水变化的多时间尺度的复杂结构, 分析了不同时间尺度下降水序列变化的周期和突变点, 并根据主周期对未来降水变化进行了预测. 结果表明, 各季节和年降水均存在8～12年左右时间尺度的周期特征; 其次, 4～6年左右时间尺度的周期特征也较明显. 夏季和年降水变化趋势一致, 均有1年和12年尺度的主周期, 夏季降水完全控制年降水. 经降水变化趋势分析, 预测2003年前后河北平原降水将偏少, 大约在2004～2007年河北平原降水将偏多.     

干旱指数在“西风模态”核心区的适用性评估

干旱指数作为衡量干旱事件变化的方法之一,由于其在区域适用性上存在差异,因此准确评估干旱指数的区域适用性是进行干旱事件研究的前提.本文基于多套资料集的降水、潜在蒸散发(PET)、土壤湿度和归一化植被指数数据,评估了自校正Palmer干旱指数(scPDSI)、标准化降水蒸散发指数(SPEI)和标准水分异常指数(SZI)对“西风模态”核心区干湿演变特征和干旱事件的描述能力.结果表明, 12个月尺度SZI(SZI12)、SPEI(SPEI12)分别与降水、PET有较好的相关性, scPDSI则能较好地表征降水和土壤湿度的变化.在趋势分析中, SZI12和scPDSI指示1961～2014年新疆逐渐变湿的特征与其降水增加、PET减少、植被改善的趋势一致.相比之下, SPEI12受到PET的强烈影响,显示区域显著变干,导致其在该地区适用性受限.哈萨克斯坦和中亚南部四国的降水在过去50年有微弱增多,但PET增加强烈,这与三种指数均指示中亚有变干的趋势相符.基于上述结果,对比指数识别新疆典型干旱事件的能力,发现scPDSI能够准确地识别新疆典型干旱事件,而SZI12所指示的大多与实际不符.综上,scP...     

基于CMIP5模式鄱阳湖流域未来参考作物蒸散量预估

预测未来气候情境下鄱阳湖流域参考作物蒸散量(Reference crop Evapotranspiration,ET0)的时空分布可为流域水资源的优化管理,为科学应对气候变化对农业生产的影响提供基础数据支撑.利用鄱阳湖流域14个气象站点1961-2014年逐日气象数据,采用Penman-Monteith公式计算出历史ET0;基于同期美国环境中心(NCEP)再分析数据及2006-2100年CMIP5中CNRM-CM5模式在RCP4. 5和RCP8. 5情景下的预测数据,经统计降尺度模型(statistical downscaling model,SDSM)模拟和偏差校正,预测流域未来ET0;通过Mann-Kendall检验、普通克里金插值和空间自相关法分析了流域1961-2100年ET0的时空演变特征.结果表明:NCEP再分析资料与流域ET0建立的逐步回归降尺度模型模拟效果较好,CNRMCM5模式降尺度模拟结果经偏差校正后,精度明显提高,适宜流域未来ET0的预估.鄱阳湖流域在基准期1961-2010年ET0整体上呈减小趋势,空间分布上呈南北高、中间低的特点,表现出明显的空间差异性.RCP4.5、RCP8.5情景下未来3个时期鄱阳湖流域ET0较基准期均呈不同程度的增加趋势,其空间分布整体表现为东高西低、局地略有突出;无论是在基准期或是未来情景下的3个时期,ET0均具有较强的空间自相关性.在RCP8.5情景下,鄱阳湖1961-2100年干旱指数呈现出较为明显的上升趋势,流域的干旱状况随时间加剧,2011-2100年间流域绝大部分地区由湿润区转为半湿润区,干旱指数自南向北递减,赣江流域将是鄱阳湖流域未来干旱风险的重点防范区.     

太阳黑子磁场极性指数时间序列

本文根据苏黎世天文台太阳黑子11年周期资料和太阳黑子磁场磁性变化周期特征,构建了太阳黑子磁场磁性指数IM(Magnetic Index)时间序列,用IM(i)表示.为了便于采用数学方法研究太阳黑子磁场磁性指数变化与诸多地球物理现象之间的联系,本文给出了1749～2007年月平均太阳黑子磁场磁性指数时间序列数据.     

Spatio‐temporal variability of dryness/wetness in the Danube River Basin

The present study focuses on the analysis of dryness/wetness conditions in the Danube River catchment area from 1901 to 2013 based on reanalysis data. The spatio‐temporal variability of dryness/wetness conditions is analyzed by means of the Standardized Precipitation Index (SPI) for an accumulation periods of 6 months. To characterize the spatial variability of SPI6 at monthly time scales, an empirical orthogonal function (EOF) analysis was applied. The leading mode of SPI variability captures in‐phase variability of SPI over the entire catchment area of Danube River. The leading mode of dryness/wetness variability was found to be strongly related to the different phases of the Arctic Oscillation. The second and third modes of variability show a more regional character of the dryness/wetness variability over the Danube River catchment area. Based on a composite map analysis, between the time series corresponding to the first three leading modes of dryness/wetness variability and the geopotential height at 850 mb and precipitation totals, it is shown that dryness (wetness) conditions over the Danube catchment area are associated with an anticyclonic (cyclonic) circulation, transport of dry (humid) air towards the Danube catchment area and reduced (enhanced) number of rain days. Copyright © 2015 John Wiley & Sons, Ltd.     

A drought climatology for Mauritius using the standardized precipitation index

This study presents a high-resolution and multi-temporal drought climatology for Mauritius based on calculated standardized precipitation index (SPI) using mean monthly rainfall for the period 1953–2007. A monthly mean SPI varying from +3.4 to ?2.7 indicates the occurrence of extremely wet and dry conditions, and collocated SPI indicates more frequent mild drought conditions. Spatial maps of rainfall trends and SPI show mostly neutral to severely dry conditions, but sparse regions of extremely wet and dry conditions are also observed. An increase in the frequency of dry years after the 1990s is noted, while most of the extreme wet conditions are found to have occurred between 1972 and 1988. More frequent short-duration wet events are observed on the 3- and 6-month time scales compared to dry events. On the 12- and 24-month time scales the frequency of both dry and wet periods is almost the same, with the dry events lasting longer.     

Teleconnections between oceanic–atmospheric indices and drought over Iran using quantile regressions

ABSTRACT

In this research, the Bayesian quantile regression model is applied to investigate the teleconnections between large oceanic–atmospheric indices and drought standardized precipitation index (SPI) in Iran. The 12-month SPI time series from 138 synoptic stations for 1952–2014 were selected as the drought index. Three oceanic–atmospheric indices, the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI) and the Multivariate El Niño/Southern Oscillation Index (MEI), were selected as covariates. The results show that NAO has the weakest impact on drought in different quantiles and different regions in Iran. La Niña conditions amplified droughts through all SPI quantiles in western, Caspian Sea coastal regions and southern regions. The positive phase of MEI significantly modulates low SPI quantiles (i.e. drought conditions) throughout the Zagros region, Caspian Sea coastal regions and southern regions. The study shows that the effect of large oceanic–atmospheric indices have heterogeneous impacts on extreme dry and wet conditions.     

Letters to the Editor

Abstract

This work investigates historical trends of meteorological drought in Taiwan by means of long-term precipitation records. Information on local climate change over the last century is also presented. Monthly and daily precipitation data for roughly 100 years, collected by 22 weather stations, were used as the study database. Meteorological droughts of different levels of severity are represented by the standardized precipitation index (SPI) at a three-monthly time scale. Additionally, change-point detection is used to identify meteorological drought trends in the SPI series. Results of the analysis indicate that the incidence of meteorological drought has decreased in northeastern Taiwan since around 1960, and increased in central and southern Taiwan. Long-term daily precipitation series show an increasing trend for dry days all over Taiwan. Finally, frequency analysis was performed to obtain further information on trends of return periods of drought characteristics.     

Using standardized indicators to analyse dry/wet conditions and their application for monitoring drought/floods: a study in the Logone catchment,Lake Chad basin

The standardized precipitation index (SPI) and standardized streamflow index (SSI) were used to analyse dry/wet conditions in the Logone catchment over a 50-year period (1951–2000). The SPI analysis at different time scales showed several meteorological drought events ranging from moderate to extreme; and SSI analysis showed that wetter conditions prevailed in the catchment from 1950 to 1970 interspersed with a few hydrological drought events. Overall, the results indicate that both the Sudano and Sahelian zones are equally prone to droughts and floods. However, the Sudano zone is more sensitive to drier conditions, while the Sahelian zone is sensitive to wetter conditions. Correlation analysis between SPI and SSI at multiple time scales revealed that the catchment has a low response to rainfall at short time scales, though this progressively changed as the time scale increased, with strong correlations (≥0.70) observed after 12 months. Analysis using individual monthly series showed that the response time reduced to 3 months in October.     

Combined analysis of precipitation and water deficit for drought hazard assessment

Abstract

The combined analysis of precipitation and water scarcity was done with the use of the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), developed as a monthly, two-variable SPI-SRI indicator to identify different classes of hydrometeorological conditions. Stochastic analysis of a long-term time series (1966–2005) of monthly SPI-SRI indicator values was performed using a first-order Markov chain model. This provided characteristics of regional features of drought formation, evolution and persistence, as well as tools for statistical long-term drought hazard prediction. The study was carried out on two subbasins of the Odra River (Poland) of different orography and land use: the mountainous Nysa K?odzka basin and the lowland, agricultural Prosna basin. Classification obtained with the SPI-SRI indicator was compared with the output from the NIZOWKA model that provided identification of hydrological drought events including drought duration and deficit volume. Severe and long-duration droughts corresponded to SPI-SRI Class 3 (dry meteorological and dry hydrological), while severe but short-term droughts (lasting less than 30 days) corresponded to SPI-SRI Class 4 (wet meteorological and dry hydrological). The results confirm that, in Poland, meteorologically dry conditions often shift to hydrologically dry conditions within the same month, droughts rarely last longer than 2 months and two separate drought events can be observed within the same year.     

Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China

Local dry/wet conditions and extreme rainfall events are of great concern in regional water resource and disaster risk management. Extensive studies have been carried out to investigate the change of dry/wet conditions and the adaptive responses to extreme rainfall events within the context of climate change. However, applicable tools and their usefulness are still not sufficiently studied, and in Hunan Province, a major grain-producing area in China that has been frequently hit by flood and drought, relevant research is even more limited. This paper investigates the spatiotemporal variation of dry/wet conditions and their annual/seasonal trends in Hunan with the standardized precipitation index (SPI) at various time scales. Furthermore, to verify the potential usefulness of SPI for drought/flood monitoring, the correlation between river discharge and SPI at multiple time scales was examined, and the relation between extreme SPI and the occurrence of historical drought/flood events is explored. The results indicate that the upper reaches of the major rivers in Hunan Province have experienced more dry years than the middle and lower reaches over the past 57 years, and the region shows a trend of becoming drier in the spring and autumn seasons and wetter in the summer and winter seasons. We also found a strong correlation between river discharge and SPI series, with the maximum correlation coefficient occurred at the time scale of 2 months. SPI at different time scales may vary in its usefulness in drought/flood monitoring, and this highlights the need for a comprehensive consideration of various time scales when SPI is employed to monitor droughts and floods.     

Ensemble prediction of regional droughts using climate inputs and the SVM–copula approach

In this study, the climate teleconnections with meteorological droughts are analysed and used to develop ensemble drought prediction models using a support vector machine (SVM)–copula approach over Western Rajasthan (India). The meteorological droughts are identified using the Standardized Precipitation Index (SPI). In the analysis of large‐scale climate forcing represented by climate indices such as El Niño Southern Oscillation, Indian Ocean Dipole Mode and Atlantic Multidecadal Oscillation on regional droughts, it is found that regional droughts exhibits interannual as well as interdecadal variability. On the basis of potential teleconnections between regional droughts and climate indices, SPI‐based drought forecasting models are developed with up to 3 months' lead time. As traditional statistical forecast models are unable to capture nonlinearity and nonstationarity associated with drought forecasts, a machine learning technique, namely, support vector regression (SVR), is adopted to forecast the drought index, and the copula method is used to model the joint distribution of observed and predicted drought index. The copula‐based conditional distribution of an observed drought index conditioned on predicted drought index is utilized to simulate ensembles of drought forecasts. Two variants of drought forecast models are developed, namely a single model for all the periods in a year and separate models for each of the four seasons in a year. The performance of developed models is validated for predicting drought time series for 10 years' data. Improvement in ensemble prediction of drought indices is observed for combined seasonal model over the single model without seasonal partitions. The results show that the proposed SVM–copula approach improves the drought prediction capability and provides estimation of uncertainty associated with drought predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

SPI drought class prediction using log-linear models applied to wet and dry seasons

A log-linear modelling for 3-dimensional contingency tables was used with categorical time series of SPI drought class transitions for prediction of monthly drought severity. Standardized Precipitation Index (SPI) time series in 12- and 6-month time scales were computed for 10 precipitation time series relative to GPCC datasets with 2.5° spatial resolution located over Portugal and with 112 years length (1902–2014). The aim was modelling two-month step class transitions for the wet and dry seasons of the year and then obtain probability ratios – Odds – as well as their respective confidence intervals to estimate how probable a transition is compared to another. The prediction results produced by the modelling applied to wet and dry season separately, for the 6- and the 12-month SPI time scale, were compared with the results produced by the same modelling without the split, using skill scores computed for the entire time series length. Results point to good prediction performances ranging from 70 to 80% in the percentage of corrects (PC) and 50–70% in the Heidke skill score (HSS), with the highest scores obtained when the modelling is applied to the SPI12. The adding up of the wet and dry seasons introduced in the modelling brought improvements in the predictions, of about 0.9–4% in the PC and 1.3–6.8% in the HSS, being the highest improvements obtained in the SPI6 application.     

The spatial–temporal variation of dry and wet periods in Iran based on comparing SPI and RDI indices

Drought is a natural hazard which can cause harmful effects on water resources. To monitor drought, the use of an indicator and determination of wet and dry period trend seem to have an important role in quantifying the drought analysis. In this paper, in addition to the comparison of Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), based on the most appropriate probability distribution function, it was tried to examine the trends of dry and wet periods based on the mentioned indices. Accordingly, the meteorological data of 30 synoptic stations in Iran (1960–2014) was used and the trend was analyzed using the Mann–Kendall test by eliminating the effect of any significant autocorrelation coefficients at 95% confidence level (modified Mann–Kendall). Comparing results between the time series of RDI and SPI drought indices based on statistical indicators (RMSE?<?0.434, R²?>?0.819 and T-statistic?<?0.419) in all studied stations revealed that the behavior of the two indices was roughly the same and the difference between them was not significant. The trend analysis results of RDI and SPI indices based on modified Mann–Kendall test showed that the variation of dry and wet periods was decreasing in most of the studied stations (five cases were significant). In addition, the results of the trend line slope of dry and wet periods related to the drought indices in the studied area indicated that the slope was negative for SPI and RDI indices in 70% and 50% of stations, respectively.