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.     

基于Copula的洞庭湖-流域-长江系统水文干旱概率分析

洞庭湖是长江中游重要的通江湖泊,水系格局复杂.近年来在气候变化和人类活动的双重影响下,江湖关系发生变化,湖泊水文干旱事件频发.基于洞庭湖、流域和长江干流水文站点的实测数据,通过标准化水位指数和标准化径流指数识别了水文干旱事件,并运用Copula函数分析了洞庭湖-流域-长江系统水文干旱的联合概率分布特征.结果表明:在年尺度上,1964—2016年间洞庭湖共发生了9次水文干旱事件,水文干旱的发生概率为14.01%,洞庭湖-流域系统、洞庭湖-长江系统的水文干旱联合概率分别为9.65%和8.58%,表明年尺度上流域来水对洞庭湖水文干旱的影响更大.在季节尺度上,洞庭湖-流域系统春季水文干旱联合概率最高,且两者同时发生水文干旱事件的次数最多,表明洞庭湖春季水文干旱与流域入湖补给减少有密切关系;而洞庭湖-长江系统,其秋季水文干旱联合概率最大,尤其自2003年以后更加极端和频发,这一方面受秋季降水减少和流域内人类活动的影响,另一方面三峡水库秋季蓄水使长江中下游干流水位降低,长江对湖泊顶托作用减弱也是重要原因之一.     

1960-2012年鄱阳湖流域旱涝急转事件时空演变特征

基于鄱阳湖流域五河7个主要入湖控制站19602012年的实测径流资料,通过短周期旱涝急转指数,结合TFPW-MK趋势检验法及集合经验模态分解法,分析了鄱阳湖流域旱涝急转事件的时空分布、演变趋势、强度及周期变化等,并探讨了旱涝急转指数的不确定性及旱涝急转事件的成因.结果表明:鄱阳湖流域旱涝急转事件主要分布在310月,其中36月主要表现为“旱转涝”,710月主要表现为“涝转旱”,且不同年代间存在一定的时空差异;五河以轻度旱涝急转事件为主,重度旱涝急转事件发生频率较低,主要发生在抚河、信江和饶河流域,且多以“涝转旱”事件为主;在年代际上,鄱阳湖流域旱涝急转事件在1990s发生的频率最高,在2000s最低.同时,除饶河外,鄱阳湖流域年最强“涝转旱”事件的发生强度呈减弱趋势,而年最强“旱转涝”事件的发生强度在赣江和修水北支有减弱趋势,在饶河和修水南支有增强趋势.五河旱涝急转的变化存在2个特征时间尺度,分别为1 a和21~35 a,而年最强旱涝急转事件的发生强度具有3 a左右的周期变化特征.这些变化与流域降水的不均匀性及强烈的人类活动等有关.本研究结果有助于全面系统认识鄱阳湖流域在全球变暖背景下极端水文事件的发生机制和变化规律,可为鄱阳湖区防汛抗旱减灾提供重要的科学依据.     

极端气候事件综合危险性等级指标构建及近60年来长江流域极端气候综合分析

本文利用经过均一化订正的长江流域共669个气象站近60年(1961—2020年)逐日观测资料,采用相对阈值和绝对阈值相结合的极值分析方法,对长江流域近60年极端高温事件、极端低温事件、极端干旱事件和极端降水事件进行识别,分析了年发生频率和线性变化趋势.在此基础上,考虑到全国极端气候事件发生情况,构建了多个极端气候事件综合危险性等级指标,比较客观地给出了长江流域极端气候事件综合危险性等级.研究结果表明,相对于全国其他地区,长江流域大部分地区极端气候综合危险性等级较高,虽然自1961年以来综合年发生频率呈现弱的线性减少趋势,但自20世纪90年代以来,长江流域极端气候事件发生的危险性相对于全国其他地区明显偏高.通过对不同极端气候事件危险性和变化规律研究,结果表明：长江流域近60年极端干旱事件年发生频率呈现线性减少趋势,与全国他其区域相比较,长江流域大部分地区极端干旱发生的危险性等级都在中级以上,说明长江流域容易发生极端干旱事件;长江流域近60年极端降水事件年发生频率呈现弱的增加趋势,危险性等级指数分析表明,高危险区主要位于长江中下游地区,湖南西部、江西大部、湖北南部等地发生极端降水事件的危险...     

采用Geodatabase技术构建流域水文系统地理数据库——以太湖地区西苕溪流域为例

如何表达流域复杂的系统结构是实现流域信息与模型集成,构建流域决策支持系统需要研究的首要问题.在分析现有流域数据库存在问题的基础上,以太湖流域西南部的西苕溪流域为研究区,采用面向对象的Geodatabase地理数据技术,通过分析流域系统的组成要素及过程,提出面向流域水文、水质应用需求的数据库信息组织体系;应用Arcgis的Archydro水文分析模块,基于国家基础地理数据库中的数字地形提取流域要素信息,构建了包括河流流线、集水区出水口、监测台站位置、湖库出口等要素的完整水文网络,并分析水文网络要素上下游关系,对流域集水区与河流的水力联系进行表达;通过分析流域监测台站空间信息、监测项目、时间序列的信息特征,设计Geodatabase的表结构和连接类,实现流域空间特征与状态序列的一体化表达,研究可以为流域数据库建设及流域决策支持系统信息平台构建提供一些技术参考.     

21世纪以来泛北极湖泊水位变化时空特征及原因探讨

在全球气候变暖和极端气候事件增加的背景下,流域水文循环过程受到的影响越来越强烈,导致湖泊水位变化表现出复杂的时空特征。而泛北极地区是地球上湖泊数量与面积分布最为集中的区域之一,该地区湖泊对气候变化响应非常敏感。因此,了解这些湖泊近期水文变化特征十分必要。本研究共搜集了36个泛北极大型湖泊(>500 km²)基于遥感或站点观测的近20年水位数据,分析其时空变化特征。本文使用线性回归模型来估算湖泊水位的变化趋势,进而利用皮尔逊相关分析了其主要水文影响变量和大气环流机制,并运用Mann-Kendall突变检验法探讨了水位突变的原因。结果表明,泛北极湖泊的水位整体上呈现不同程度上升(平均速率为0.013 m/a),有23个(64%)湖泊的水位呈上升趋势;研究湖泊中有10个通过90%统计显著性检验。其中,水位上升速率最大的湖泊是位于哈萨克斯坦的腾吉兹湖,上升速率为0.078 m/a。泛北极湖泊水位的波动主要与径流有关,有19个(53%)湖泊的水位波动与径流的增加更为相关;相比而言,位于亚洲的极地湖泊水位的上升与流域蒸发的降低显著相关,尤其是库苏古尔湖。从区域大气环流影响来看,泛北极湖泊水位变化主要与厄尔尼诺-南方涛动有关,其次是北极涛动和北大西洋涛动。本研究有助于加深对泛北极湖泊近20年水位变化规律及气候影响特征的科学理解。     

云南杞麓湖沉积物记录的近现代生态环境变化及影响因子识别

随着云南社会经济的持续发展与极端气候事件的频发,高原大中型湖泊面临着水质恶化、生态与环境功能退化的长期胁迫.为识别亚热带大型湖泊面临的主要环境压力,以杞麓湖为研究对象,在对沉积物钻孔进行物理(粒度、烧失量)、生物(色素、硅藻)等指标分析的基础上,结合现代监测和湖泊调查数据,重建了近两百年来湖泊水文条件、富营养化和环境变化的历史,并对硅藻群落结构的演化进行了驱动过程识别.沉积物粒度在1958年之前变化总体较为稳定且有较高的黏土含量;随着围湖造田等流域开发的增强,沉积物粒度组成自1960s开始频繁波动且粗颗粒组分快速增加.1981—2000年期间,随着落水洞泄水工程的修建杞麓湖的水位控制与水文调控得到加强,沉积物砂质含量降低且粒度组成变化较小;2000—2013年期间,湖泊疏浚工程的开展和区域降水的持续减少都导致了沉积物粒度组成波动较大、粗颗粒组成较高.沉积物色素记录了湖泊初级生产力的缓慢上升出现于19世纪中后期,并自1960s开始总叶绿素与蓝藻色素含量总体出现了较大幅度的增加趋势并持续至今.而在2000—2005年期间,湖泊浅水区的疏浚清淤导致了内源营养盐输入量的降低与藻类生物量的明显下降;沉积物蓝藻色素含量在1998、2008和2012—2013年左右出现明显的峰值,指示杞麓湖可能出现了较大范围的蓝藻暴发事件.统计分析结果显示,湖泊硅藻群落结构出现了多次明显转变且呈现底栖硅藻百分比长期降低的特征,水体富营养化的持续是驱动硅藻群落结构演替的主要因子,而水生植物退化、水文条件与气候变化也对硅藻群落的构建产生了重要的叠加影响.本文的沉积物分析结果表明,亚热带大型湖泊的生态治理与环境保护需要重点围绕营养盐负荷控制、水文调控优化与底栖生境恢复,并需应对全球变暖与极端气候事件产生的叠加影响.     

鄱阳湖流域水文极值演变特征、成因与影响

选用11种概率分布函数,系统分析了鄱阳湖流域"五河"的6个水文站年最大径流量与连续3d、7d最大平均日流量,函数参数以及拟合优度分别由线性矩法与柯尔莫哥洛夫-斯米尔诺夫方法检验,选出最适合该区流量极值分布函数.在此基础上,对引起该流域水文极值变化的原因及其影响作了有益的探讨.结果表明:(1)韦克比分布是用于研究都阳湖流...     

基于Copula函数的鄱阳湖水系径流丰枯遭遇多维分析

鄱阳湖流域5大水系来水变化与湖区水文极值事件有密切关系,研究径流变化特征与丰枯遭遇规律对区域防洪抗旱有重要意义.本文运用Copula函数构建了鄱阳湖水系多维径流联合分布模型,采用特枯、偏枯、平水、偏丰和特丰的径流丰枯分类,定量研究了鄱阳湖5大水系丰枯遭遇的问题,探讨了多维丰枯遭遇同步联合概率的变化特征.结果表明：鄱阳湖水系河流之间的径流具有较高的相关性,Gaussian Copula函数能较好地模拟二维至五维的径流联合分布.多条河流的丰枯遭遇随着维数的增加,丰枯组合增加,丰枯同步的联合概率明显下降,且丰枯同步的最大联合概率趋向于丰枯两端.对于相同的概率区间,非汛期径流的丰枯同步联合概率明显大于年径流和汛期径流,而年径流和汛期径流之间的丰枯同步联合概率差别较小.同处于流域北部或南部或相邻的河流之间的组合,其同步联合概率相较其他组合大,而南、北河流组合的同步联合概率相对较小.该研究可为流域水资源管理及水旱灾害预防提供科学依据.     

我国湖泊水文学研究进展与展望

湖泊是地球表层水体的重要组成部分,在区域社会经济发展和生物多样性保护等方面发挥着不可替代的作用.气候变化和高强度的水资源开发利用等,导致湖泊物理、化学特性在时空格局上发生显著的变化,引起一系列的社会、环境、气候等响应.湖泊水文学研究湖泊水文要素及其时空变化特征、平衡关系与变化规律,在水文过程演变与归因解析、湖泊洪旱发生机理与调控、湖泊资源评估与可持续利用等方面,解决了众多理论和实践问题,为区域发展提供了强大支撑.本文评述了近50年来我国湖泊水文学的发展与研究进展,重点阐述湖泊水量平衡与水量变化、湖泊水动力与水文过程调蓄、湖泊极端水文事件成因、湖泊水文遥感反演等方面的研究进展,展望了湖泊水文学的未来发展趋势.     

Hydrological extremes in a southwestern Ontario river basin under future climate conditions/Extrêmes hydrologiques dans un basin versant du sud-ouest de l'Ontario sous conditions climatiques futures

Abstract

The global climate change may have serious impacts on the frequency, magnitude, location and duration of hydrological extremes. Changed hydrological extremes will have important implications on the design of future hydraulic structures, flood-plain development, and water resource management. This study assesses the potential impact of a changed climate on the timing and magnitude of hydrological extremes in a densely populated and urbanized river basin in southwestern Ontario, Canada. An ensemble of future climate scenarios is developed using a weather generating algorithm, linked with GCM outputs. These climate scenarios are then transformed into basin runoff by a semi-distributed hydrological model of the study area. The results show that future maximum river flows in the study area will be less extreme and more variable in terms of magnitude, and more irregular in terms of seasonal occurrence, than they are at present. Low flows may become less extreme and variable in terms of magnitude, and more irregular in terms of seasonal occurrence. According to the evaluated scenarios, climate change may have favourable impacts on the distribution of hydrological extremes in the study area.     

Quantifying and Reducing Uncertainty in the Large-Scale Response of the Water Cycle

Despite their obvious environmental, societal and economic importance, our understanding of the causes and magnitude of the variations in the global water cycle is still unsatisfactory. Uncertainties in hydrological predictions from the current generation of models pose a serious challenge to the reliability of forecasts and projections across time and space scales. This paper provides an overview of the current issues and challenges in modelling various aspects of the Earth’s hydrological cycle. These include: the global water budget and water conservation, the role of model resolution and parametrisation of precipitation-generating processes on the representation of the global and regional hydrological cycle, representation of clouds and microphysical processes, rainfall variability, the influence of land–atmosphere coupling on rainfall patterns and their variability, monsoon processes and teleconnections, and ocean and cryosphere modelling. We conclude that continued collaborative activity in the areas of model development across timescales, process studies and climate change studies will provide better understanding of how and why the hydrological cycle may change, and better estimation of uncertainty in model projections of changes in the global water cycle.     

Multi-site bias correction of climate model outputs for hydro-meteorological impact studies: An application over a watershed in China

Bias correction methods remove systematic differences in the distributional properties of climate model outputs with respect to observations, often as a means of pre-processing model outputs for use in hydrological impact studies. Traditionally, bias correction is applied at each weather station individually, neglecting the dependence that exists between different sites, which could negatively affect simulations from a distributed hydrological model. In this study, three multi-variate bias correction (MBC) methods—initially proposed to correct the inter-variable correlation or multi-variate dependence of climate model outputs—are used to correct biases in distributional properties and spatial dependence at multiple weather stations. To reveal the benefits of correcting spatial dependence, two distribution-based single-site bias correction methods are used for comparison. The effects of multi-site correction on hydro-meteorological extremes are assessed by driving a distributed hydrological model and then evaluating the model performance in terms of several meteorological and hydrological extreme indices. The results show that the multi-site bias correction methods perform well in reducing biases in spatial correlation measures of raw global climate model outputs. In addition, the multi-site methods consistently reproduce watershed-averaged meteorological variables better than single-site methods, especially for extreme values. In terms of representing hydrological extremes, the multi-site methods generally perform better than the single-site methods, although the benefits vary according to the hydrological index. However, when applying the multi-site methods, the original temporal sequence of precipitation occurrence may be altered to some extent. Overall, all multi-site bias correction methods are able to reproduce the spatial correlation of observed meteorological variables over multiple stations, which leads to better hydrological simulations, especially for extremes. This study emphasizes the necessity of considering spatial dependence when applying bias correction to ccc outputs and hydrological impact studies.     

Hydrological extreme variability in the headwater of Tarim River: links with atmospheric teleconnection and regional climate

Variability and possible relationship between monthly 1-day maximum/minimum flow from headwater of Tarim River basin, climatic indices and regional climate were detected by Mann–Kendall test, continuous wavelet transform, cross-wavelet and wavelet coherence methods. The results showed that: (1) hydrological extremes have increased during past 50 years, and the trends of 1-day minimum flow were larger than that of 1-day maximum flow. The most significant change occurred in winter; (2) the hydrological extremes exhibited significant 1-year period and 0.5-year period along the whole hydrological series; (3) different circulation indices may influence the trends of hydrological extremes in different river. The area of polar vortex in North American (i25) and area of Northern Hemisphere polar vortex (i5) showed most significant correlation with 1-day maximum flow and 1-day minimum flow in Aksu River, respectively. In Hotan River, the most significant correlated climate indices with 1-day maximum and minimum flow were Southern oscillation index and area of Northern American Subtropical High (i15), respectively. The area of polar vortex in Atlantic and Europe Sector (i35) showed significant relationships with 1-day minimum flow in Yarkand River; (4) regions of shared power at 0.8–1.5 year mode were found between selected climate indices and the hydrological extremes, anti-phase relations were detected for most of the series; (5) the fluctuations of temperature have strong effects on hydrological extremes, and significant coherence between regional climate and extremes was found at 0.7–1.5 year scale. The results of the study provide valuable information for improving the long-term forecasting of the hydrological extremes using its relationship with climate indices.     

Review of Understanding of Earth’s Hydrological Cycle: Observations,Theory and Modelling

Water is our most precious and arguably most undervalued natural resource. It is essential for life on our planet, for food production and economic development. Moreover, water plays a fundamental role in shaping weather and climate. However, with the growing global population, the planet’s water resources are constantly under threat from overuse and pollution. In addition, the effects of a changing climate are thought to be leading to an increased frequency of extreme weather causing floods, landslides and drought. The need to understand and monitor our environment and its resources, including advancing our knowledge of the hydrological cycle, has never been more important and apparent. The best approach to do so on a global scale is from space. This paper provides an overview of the major components of the hydrological cycle, the status of their observations from space and related data products and models for hydrological variable retrievals. It also lists the current and planned satellite missions contributing to advancing our understanding of the hydrological cycle on a global scale. Further details of the hydrological cycle are substantiated in several of the other papers in this Special Issue.     

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.     

An inverse-modelling approach to assess the impacts of climate change in the Seyhan River basin,Turkey / Une approche de modélisation inverse pour évaluer les impacts du changement climatique dans le bassin versant de la Rivière Seyhan,Turquie

Abstract

One of the most significant anticipated consequences of global climate change is the change in frequency of hydrological extremes. Predictions of climate change impacts on the regime of hydrological extremes have traditionally been conducted by a top-down approach that involves a high degree of uncertainty associated with the temporal and spatial characteristics of general circulation model (GCM) outputs and the choice of downscaling technique. This study uses the inverse approach to model hydrological risk and vulnerability to changing climate conditions in the Seyhan River basin, Turkey. With close collaboration with the end users, the approach first identifies critical hydrological exposures that may lead to local failures in the Seyhan River basin. The Hydro-BEAM hydrological model is used to inversely transform the main hydrological exposures, such as floods and droughts, into corresponding meteorological conditions. The frequency of critical meteorological conditions is investigated under present and future climate scenarios by means of a weather generator based on the improved K-nearest neighbour algorithm. The weather generator, linked with the output of GCMs in the last step of the proposed methodology, allows for the creation of an ensemble of scenarios and easy updating when improved GCM outputs become available. Two main conclusions were drawn from the application of the inverse approach to the Seyhan River basin. First, floods of 100-, 200- and 300-year return periods under present conditions will have 102-, 293- and 1370-year return periods under the future conditions; that is, critical flood events will occur much less frequently under the changing climate conditions. Second, the drought return period will change from 5.3 years under present conditions to 2.0 years under the future conditions; that is, critical drought events will occur much more frequently under the changing climate conditions.     

Precipitation patterns and associated hydrological extremes in the Yangtze River basin,China, using TRMM/PR data and EOF analysis

Abstract

A decadal-scale study to retrieve the spatio-temporal precipitation patterns of the Yangtze River basin, China, using the Tropical Rain Mapping Mission, Precipitation Radar (TRMM/PR) data is presented. The empirical orthogonal function (EOF) based on monthly TRMM/PR data extracts several leading precipitation patterns, which are largely connected with physical implications at the basin scale. With the aid of gauge station data, the amplitudes of major principal components (PCs) were used to examine the generic relationships between precipitation variations and hydrological extremes (e.g. floods and droughts) during summer seasons over the past decade. The emergence of such major precipitation patterns clearly reveals the possible linkages with hydrological processes, and the oscillations in relation to the amplitude of major PCs are consistent with these observed hydrological extremes. Although the floods in some sections of the Yangtze River were, to some extent, tied to human activities, such as the removal of wetlands, the variations in major precipitation patterns are recognized as the primary driving force of the flow extremes associated with floods and droughts. The research findings indicate that long-distance hydro-meteorological signals of large-scale precipitation variations over such a large river basin can be successfully identified with the aid of EOF analysis. The retrieved precipitation patterns and their low-frequency jumps of amplitude in relation to PCs are valuable tools to help understand the association between the precipitation variations and the occurrence of hydrological extremes. Such a study can certainly aid in disaster mitigation and decision-making in water resource management.

Editor Z.W. Kundzewicz; Associate editor A. Montanari

Citation Sun, Z., Chang, N.-B., Huang, Q., and Opp, C., 2013. Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis. Hydrological Sciences Journal, 57 (7), 1315–1324.