云南中北部地区1954-2012年干旱评价研究

利用云南中北部地区6个气象站点1954-2012年资料,选用标准化指数计算各站点干旱指数,统计分析了云南中北部地区1954-2012年发生干旱的年份及发生不同干旱的频次。研究结果表明:1临沧站出现干旱的年份较多,但蒙自站出现极端干旱的年份明显高于其他5站;2各站点在不同季节出现干旱的频次不同,其中腾冲在春季相比于其他5站,发生干旱的频率较高35.6%,临沧站在夏季和冬季发生干旱频率均较大,分别为35.6%和37.9%,蒙自站在秋季发生干旱频率最大,为34.8%。研究成果可为云南中北部地区的干旱评价分析和水资源保护提供一定的参考价值。     

渭河流域降水时空变化与干旱特征分析

以渭河流域14个典型气象站降水资料为基础,应用Mann-Kendall趋势检验法、频率分析法、差积曲线法以及游程分析法对研究区的降水变化规律及少水概率特征进行了研究。结果显示:40多年来渭河流域降水量呈明显减少趋势,以春、秋两季最为明显,这增加了区域发生干旱的可能性;流域降水过程呈丰枯交替的周期性现象,连丰或连枯较易发生,且存在干旱与洪涝并发现象;连枯年的概率比连丰年概率大,且少水期常持续2~3a,引发的干旱强度较大;1991年以后渭河流域干旱事件的频率、强度和烈度均有增加趋势,未来渭河流域的农业发展与水安全将面临更大的威胁,必须予以高度关注。     

A Different Perspective on the Evolution of UK Income Inequality

This paper scrutinizes the conventional wisdom about trends in UK income inequality and also places contemporary inequality in a much longer historical perspective. We combine household survey and income tax data to provide better coverage of all income ranges from the bottom to the very top (and make our estimates available to other researchers). We make a case for studying distributions of income between tax units (i.e. not assuming the full income sharing that goes with the use of the household as the unit of analysis) for reasons of principle as well as data harmonization. We present evidence that income inequality in the UK is as least as high today as it was just before the start of World War 2.     

干旱指数在辽河流域的应用分析

由于农业用水增加、工业污染严重,造成辽河流域干旱程度加重,利用2010—2015年辽河流域昌图县、康平县、法库县逐月降水量资料及年降雨量数据,通过降水距平百分率、标准化降水指数(SPI)、降水Z指数合理评价了辽河流域干旱情况,并比较3种干旱指数的评价效果。分析了三个地方的干旱情况,研究并比较了降水距平百分率、 SPI、降水Z指数的评价效果。结果表明：降水距平百分率反映干旱程度较轻;与降水Z指数相比,SPI指数能较客观地反映辽河流域干旱程度。为辽河流域定量研究干旱事件提供合理的指标依据,为不同研究区根据自身特点选择适合的干旱指标奠定理论基础。     

标准化降水指数与有效干旱指数在新疆干旱监测中的应用

基于干旱监测理论,根据新疆测站1961—2010年逐日降水资料,对比分析了基于不同时间尺度(1、3、6、9、12、24个月)标准化降水指标(SPI)与有效干旱指数(EDI)对干旱监测的有效性与实用性。结果表明:不论针对短期干旱还是长期干旱,EDI监测能力均明显优于SPI。短时间尺度的SPI受短时间降水影响较大,能反映短时间新疆地区的干旱变化特征;随时间尺度的增加,SPI对短时间降水的响应能力较差,但仍可反映长时间序列下明显的干旱变化趋势。与SPI相比,EDI能够很好地反映出短期干旱和当时降水量的影响;同时能够随时间迁移,给每日降水量分配以不同权重,考虑前期降水量对当前干湿状况的影响。相关研究结果可为湿润区及其他气候区洪旱灾害监测提供重要理论依据。     

Towards a Drought Watch System based on Spatial SPI

Regional Drought can be assessed through various meaningfulprocedures mainly related to the expected consequences. However, a general knowledge of the occurrence of drought, thearea which is affected, its severity and its duration are ofgreat importance for a series of decisions, which may beappropriate for a variety of activities. From the existingsimple and popular indices used for the estimation of drought,the Standardised Precipitation Index, known as SPI, seems to winuniversal applicability. A method based on the estimation of SPIover a geographical area and its use for characterising drought,is presented in this paper. Applications of the method arepresented using a digital terrain model and a simple computercalculating routine. It is shown that the proposed procedurecan be easily applied and can support a Drought Watch System foran area of mesoscale dimensions.     

基于三种干旱指标的朝阳市干旱特征分析

旱灾具有出现频率高、持续时间长、波及范围广等特点,本文运用降水距平百分率、Z指数、SPI标准化降水指数,对朝阳地区50a（1969～2018）干旱特征进行分析。结果表明：Z指数与SPI标准化降水指标得到的朝阳地区干旱特征情况基本一致,能较好地反映出该地区的干旱特征,朝阳地区1969～2018年自然灾害频繁发生,严重干旱年份主要集中在1980、1981、1982 年,与实际相符。     

近50年长江中下游地区旱涝时空分布

长江中下游地区是我国重要的粮棉油产地之一,但是频繁发生的旱涝灾害经常造成该区域作物减产。利用长江中下游地区72个气象站的逐月气象观测数据,采用标准化降水指数(SPI)、正交经验分解函数(EOF)等方法,结合GIS技术,分析了近50年长江中下游地区旱涝时空变化分布特征。结果表明:长江中下游地区的旱涝SPI3空间格局既有全区一致的现象,也存在区域内部南北、东西方向的差异,但是其主要特点依然为纬向分布型。由于受气候影响,长江中下游地区夏秋两季旱涝灾害交替发生,但以涝灾为主。     

基于分布式水文模型的怒江流域气象干旱和水文干旱分析

为了评估气候变化对怒江流域干旱演变的影响,本研究建立了GBHM-NJ分布式水文模型,利用实测站点资料率定参数并验证模型精度,模拟了1961—2010年长时间序列流域水文过程,并分别采用标准化降水指数(SPI)和标准化径流指数(SSI)分析了流域气象干旱和水文干旱的时空演变特点。结果表明:(1)GBHM-NJ模型能较好地模拟怒江流域的径流过程和水文响应的空间特征。(2)1961—2010年间,怒江流域发生气象干旱的频率、覆盖面积和强度呈增加趋势,其中1994年和2009年气象干旱最为严重。(3)在空间上,怒江流域的年度气象干旱频率约为28%,中游地区干旱频率比较高、主要分布在左贡站和八宿站附近,上游地区次之,下游地区相对较低。(4)水文干旱进入20世纪90年代和21世纪以后明显增强,年尺度干旱以轻旱为主,季尺度干旱特旱多发生在秋冬季。总之,气候变化环境下怒江流域干旱呈现增强趋势。     

Drought forecasting using the Standardized Precipitation Index

Unlike other natural disasters, drought events evolve slowly in time and their impacts generally span a long period of time. Such features do make possible a more effective drought mitigation of the most adverse effects, provided a timely monitoring of an incoming drought is available. Among the several proposed drought monitoring indices, the Standardized Precipitation Index (SPI) has found widespread application for describing and comparing droughts among different time periods and regions with different climatic conditions. However, limited efforts have been made to analyze the role of the SPI for drought forecasting. The aim of the paper is to provide two methodologies for the seasonal forecasting of SPI, under the hypothesis of uncorrelated and normally distributed monthly precipitation aggregated at various time scales k. In the first methodology, the auto-covariance matrix of SPI values is analytically derived, as a function of the statistics of the underlying monthly precipitation process, in order to compute the transition probabilities from a current drought condition to another in the future. The proposed analytical approach appears particularly valuable from a practical stand point in light of the difficulties of applying a frequency approach due to the limited number of transitions generally observed even on relatively long SPI records. Also, an analysis of the applicability of a Markov chain model has revealed the inadequacy of such an approach, since it leads to significant errors in the transition probability as shown in the paper. In the second methodology, SPI forecasts at a generic time horizon M are analytically determined, in terms of conditional expectation, as a function of past values of monthly precipitation. Forecasting accuracy is estimated through an expression of the Mean Square Error, which allows one to derive confidence intervals of prediction. Validation of the derived expressions is carried out by comparing theoretical forecasts and observed SPI values by means of a moving window technique. Results seem to confirm the reliability of the proposed methodologies, which therefore can find useful application within a drought monitoring system.