基于Copula函数的鄱阳湖流域极值流量遭遇频率及灾害风险

在以气温上升为主要特征的全球气候变化导致区域水循环加剧、极端气候水文事件频发的背景下,对极端水文事件,特别是水文极值遭遇频率的科学认识,对区域防洪抗旱具有重要意义.基于此,本文引入当前多变量分析中较常用的Copula函数.分析鄱阳湖流域主要支流赣江与抚河、乐安河与昌江的洪水、枯水流量联合概率特征,并对引起该流域水文极值...     

变化环境下珠江流域洪水频率变化特征、成因及影响(1951-2010年)

气候变化和人类活动导致珠江流域水文变化,变化前后洪水频率分布显著不同.运用滑动秩和(Mann-Whitney U test)结合Brown-Forsythe、滑动T、有序聚类和Mann-Kendall检验法,并用累积距平曲线法获取年最大流量序列详细信息,综合确定样本最佳变化节点,并对水文变化成因做了系统分析.在此基础上,对整体序列、变化前后序列用线性矩法推求广义极值分布参数以及不同重现期设计流量.结果表明:(1)西江大部以及北江流域最佳变化节点在1991年左右;东江流域最佳变化节点与该流域内3大控制性水库建成时间基本吻合;(2)变化后,西江、北江年最大流量持续增加,洪峰强度增大,尤其是西江干流年最大流量显著增加;东江流域年最大流量显著减小,洪峰强度降低;(3)变化后,西江与北江洪水风险增加,尤其是下游珠三角地区本身受人类活动显著影响,加之西江与北江持续增加的洪水强度,珠三角地区发生洪水的强度及频次加剧,而东江洪水风险减小.此研究对于珠江流域在变化环境下的洪水风险评估与防洪抗灾具有重要意义.     

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.     

随机结构动力可靠度估计算法的对比分析

对比分析了随机结构动力可靠度计算的三种估计算法.渐进展开法是基于Laplace算法对概率积分进行渐进估计的,此法通过计算最大被积分式值对应点,并将其代入概率积分的渐进估计表达式求解失效概率.由于概率积分的主要贡献来自于最大被积分式值对应点的周围,因此本文的重要抽样法假定重要抽样函数的最大似然值等于最大被积分式值对应点值.极值分布-泰勒展开法首先通过结构随机参数的极值分布函数给出失效概率的表达式,随后利用泰勒展开法对失效概率进行估计,其中采用中心差分法对极值分布函数的梯度进行估算.最后应用三种算法和Monte Carlo法对受高斯白噪声激励作用的单自由度随机结构进行了计算,结果表明三种方法不但运算简便,而且对比Monte Carlo法计算效率有显著提高.     

考虑降雨空间变化的随机产汇流模型

引入两个负指数型差值函数,估计降雨量的概率分布,以此描述流域降雨空间变异性问题.将降雨量空间统计分布与垂向混合产流模型耦合进行产流量计算,即对地表径流,采用超渗产流模式,根据降雨与土壤下渗能力的联合分布推求其空间分布;对地面以下径流,采用蓄满产流模式,以地表渗入量的均值作为输入,进行简化处理以提高其实用性;最终推导出总产流量概率分布函数计算公式.将流域概化成一个线性水库,并根据随机微分方程理论,推导任一计算时段洪水流量的概率分布,从而构建了一个完整的随机产汇流模型.以淮河支流黄泥庄流域为例进行应用研究,结果表明,该模型可提供洪水过程的概率预报,可用于防洪风险分析,若以概率分布的期望值作为确定性预报,亦具有较高精度.     

用极值理论对京-津-唐地区及7个主要地震带未来地震活动的分析s

本文利用历史地震资料及现代地震资料,运用改进的极值分布函数法,讨论了我国内陆7个主要地震带及京-津-唐地区地震活动的特征,对未来的地震活动性作了定量的估计,并且对运用极值理论处理历史地震资料应当注意的若干问题进行了分析.研究了历史资料起始时间后移和前期中小地震遗漏对极值分布函数的影响,并应用改进的极值分布函数探讨了未来地震的危险性.      

广义极值分布在地震危险性分析中的应用

利用广义极值分布研究地震最大发震震级的规律,给出了广义极值分布下地震危险性分析的相关公式与方法,并对台湾地区历史地震资料进行极值统计分析,发现最大震级超过7级的地震理论发震次数与实际发震次数完全一致,在此基础上预测了未来几年发震的危险性.     

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.     

矿山地震能量极值分布的研究及其应用

将冈贝尔I型极值分布应用于矿山地震能量分布规律的研究，结合前人的研究成果，推导了能量极值分布函数的表达式，给出了其参数确定方法。在简要介绍老虎台矿矿山地震活动的构造及物理背景后，结合老虎台矿矿震实际，介绍了如何将能量极值分布用于强矿山地震事件的预测。结果表明，用这种方法预测的月最大矿震能量的概率分布与实际记录的矿震月最大能量分布一致。最后应用该法预测了老虎台矿未来几年内强矿震事件发生的概率。     

中国大陆活动地块边界带最大震级分布特征研究

中国大陆活动地块边界带是强震活动的集中带,也是地震预测研究与防灾减灾的主要目标区,而最大地震震级是描述区域地震活动性的一个基本参数,被广泛应用于地震危险性分析研究中,因此有必要开展各活动地块边界带最大震级分布特征研究.本文利用广义极值(GEV)分布对各边界带作极值统计分析,对于分布参数进行估计,比较极值分布99％分位数和b值截距法最大震级、历史最大震级,并计算各震级水平下地震平均复发周期与发震次数,探讨活动地块各边界带未来强震活动的危险性.     

A framework to estimate sediment loads using distributions with covariates: Beaurivage River watershed (Québec,Canada)

A framework to estimate sediment loads based on the statistical distribution of sediment concentrations and various functional forms relating distribution characteristics (e.g. mean and variance) to covariates is developed. The covariates are used as surrogates to represent the main processes involved in sediment generation and transport. Statistical models of increasing complexity are built and compared to assess their relative performance using available sediment concentration and covariate data. Application to the Beaurivage River watershed (Québec, Canada) is conducted using data for the 1989–2004 period. The covariates considered in this application are streamflow and calendar day. A comparison of different statistical models shows that, in this case, the log‐normal distribution with a mean value depending on streamflow (power law with an additive term) and calendar day (sinusoidal), a constant coefficient of variation for streamflow dependence and a constant standard deviation for calendar day dependence provide the best result. Model parameters are estimated using the maximum likelihood estimation technique. The selected model is then used to estimate the distribution of annual sediment loads for the Beaurivage River watershed for a selected period. A bootstrap parametric method is implemented to account for uncertainties in parameter values and to build the distributions of annual loads. Comparison of model results with estimates obtained using the empirical ratio estimator shows that the latter were rarely within the 0·1–0·9 quantile interval of the distributions obtained with the proposed approach. Copyright © 2008 John Wiley & Sons, Ltd.     

Rainfall and streamflow response to El Niño Southern Oscillation: a case study in a semiarid catchment,Australia

Abstract

This paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0–3 month lead time, compared to rainfall distribution.     

Estimating minimum streamflow from measurements at ungauged sites in regions with streamflow‐gauging networks

Estimation of low flows in rivers continues to be a vexing problem despite advances in statistical and process‐based hydrological models. We develop a method to estimate minimum streamflow at seasonal to annual timescales from measured streamflow based on regional similarity in the deviations of daily streamflow from minimum streamflow for a period of interest. The method is applied to 1,019 gauged sites in the Western United States for June to December 2015. The gauges were clustered into six regions with distinct timing and magnitude of low flows. A gamma distribution was fit each day to the deviations in specific discharge (daily streamflow divided by drainage area) from minimum specific discharge for gauges in each region. The Kolmogorov–Smirnov test identified days when the gamma distribution was adequate to represent the distribution of deviations in a region. The performance of the gamma distribution was evaluated at gauges by comparing daily estimates of minimum streamflow with estimates from area‐based regression relations for minimum streamflow. Each region had at least 8 days during the period when streamflow measurements would provide better estimates than the regional regression equation, but the number of such days varied by region depending on aridity and homogeneity of streamflow within the region. Synoptic streamflow measurements at ungauged sites have value for estimating minimum streamflow and improving the spatial resolution of hydrological model in regions with streamflow‐gauging networks.     

Disaggregation modelling of monthly streamflows using a new approach of the method of fragments

Abstract

The method of fragments is applied to the generation of synthetic monthly streamflow series using streamflow data from 34 gauging stations in mainland Portugal. A generation model based on the random sampling of the log-Pearson Type III distribution was applied to each sample to generate 1200 synthetic series of annual streamflow with an equal length to that of the sample. The synthetic annual streamflow series were then disaggregated into monthly streamflows using the method of fragments, by three approaches that differed in terms of the establishment of classes and the selection of fragments. The results of the application of such approaches were compared in terms of the capacity of the method to preserve the main monthly statistical parameters of the historical samples.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Silva, A.T. and Portela, M.M., 2012. Disaggregation modelling of monthly streamflows using a new approach of the method of fragments. Hydrological Sciences Journal, 57 (5), 942–955.     

Trend,periodicity and abrupt change in streamflow of the East River,the Pearl River basin

The East River in the Pearl River basin, China, plays a vital role in the water supply for mega‐cities within and in the vicinity of the Pearl River Delta. Knowledge of statistical variability of streamflow is therefore important for water resources management in the basin. This study analyzed streamflow from four hydrological stations on the East River for a period of 1951–2009, using ensemble empirical mode decomposition (EEMD), continuous wavelet transform (CWT) technique, scanning t and F tests. Results indicated increasing/decreasing streamflow in the East River basin before/after the 1980s. After the early 1970s, the high/low flow components were decreasing/increasing. CWT‐based analysis demonstrates a significant impact of water reservoirs on the periodicity of streamflow. Scanning t and F test indicates that significantly abrupt changes in streamflow are largely influenced by both water reservoirs construction and precipitation changes. Thus, changes of streamflow, which are reflected by variations of trend, periodicity and abrupt change, are due to both water reservoir construction and precipitation changes. Further, the changes of volume of streamflow in the East River are in good agreement with precipitation changes. Copyright © 2012 John Wiley & Sons, Ltd.     

Changes in streamflow regime following vegetation changes from paired catchments

Vegetation changes can significantly affect catchment water balance. It is important to evaluate the effects of vegetation cover change on streamflow as changes in streamflow relate to water security. This study focuses on the use of statistical methods to determine responses in streamflow at seven paired catchments in Australia, New Zealand, and South Africa to vegetation change. The non‐parametric Mann–Kendall test and Pettitt's test were used to identify trends and change points in the annual streamflow records. Statistically significant trends in annual streamflow were detected for most of the treated catchments. It took between 3 and 10 years for a change in vegetation cover to result in significant change in annual streamflow. Presence of the change points in streamflow was associated with changes in the mean, variance, and distribution of annual streamflow. The streamflow in the deforestation catchments increased after the change points, whereas reduction in streamflow was observed in the afforestation catchments. The streamflow response is mainly affected by the climate and underlying vegetation change. Daily flow duration curves (FDCs) for the whole period and pre‐change and post‐change point periods also were analysed to investigate the changes in flow regime. Three types of vegetation change effects on the flow regime have been identified. The relative reductions in most percentile flows are constant in the afforestation catchments. The comparison of trend, change point, and FDC in the annual streamflow from the paired experiments reflects the important role of the vegetation change. Copyright © 2011 John Wiley & Sons, Ltd.     

Kernel distributed residual function in a revised multiple order autoregressive model and its applications in hydrology

ABSTRACT

This paper describes a new approach to fill missing data in hydrologic series. Based on a multiple-order autoregressive model, our algorithm represents the random term with an empirical distribution function that includes different parameters for the low, medium and high ranges of the modelled hydrologic variable. The algorithm involves a corrective mechanism that preserves the original statistical distribution of the series that are filled, while also eliminating the possibility of obtaining negative values for low flows. The algorithm requires multiple correlated hydrologic time series with sufficient data to permit accurate calculation of their statistical properties. It ensures that both the original statistical dependence among the data series and the statistical distribution functions will be preserved after the missing data had been filled. The model has been tested using 15 streamflow series in the Upper Bow River watershed in Alberta, Canada.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

Large-scale climate teleconnections with South Korean streamflow variability

ABSTRACT

Leading patterns of observed seasonal extreme and mean streamflow on the Korean peninsula were estimated using an empirical orthogonal teleconnection (EOT) technique. In addition, statistical correlations on a seasonal basis were calculated using correlation and regression analyses between the leading streamflow patterns and various climate indices based on atmospheric–ocean circulation. The spatio-temporal patterns of the leading EOT modes for extreme and mean streamflow indicate an upstream mode for the Han River, with increasing trends in summer, and a downstream mode for the Nakdong River, with oscillations mainly on inter-decadal time scales in winter. The tropical ENSO (El Niño Southern Oscillation) forcing for both extreme and mean streamflow is coherently associated with summer to winter streamflow patterns. The western North Pacific monsoon has a negative correlation with winter streamflow variability, and tropical cyclone indices also exhibit significant positive correlation with autumn streamflow. Leading patterns of autumn and winter streamflow time series show predictability up to two seasons in advance from the Pacific sea-surface temperatures.