Nonparametric streamflow simulation by wavelet or Fourier analysis

Abstract

Wavelet or Fourier analysis is proposed as an alternative nonparametric method to simulate streamflows. An observed series is decomposed into its components at various resolutions and then recombined randomly to generate synthetic series. The mean and standard deviation are perfectly reproduced and coefficient of skewness tends to zero as the number of simulations increases. Normalizing transforms can be used for skewed series. Autocorrelation coefficients and the dependence structure are better preserved when Fourier analysis is used, but the mean and variance remain constant when the simulated and observed series have the same length. Monthly as well as annual flows can be simulated by this technique as illustrated on some examples. Wavelet analysis should be preferred as it generates flow series that exhibit a wider range of required reservoir capacities.     

Forecasting streamflow by combination of a genetic input selection algorithm and wavelet transforms using ANFIS models

ABSTRACT

In this study, a data-driven streamflow forecasting model is developed, in which appropriate model inputs are selected using a binary genetic algorithm (GA). The process involves using a combination of a GA input selection method and two adaptive neuro-fuzzy inference systems (ANFIS): subtractive (Sub)-ANFIS and fuzzy C-means (FCM)-ANFIS. Moreover, the application of wavelet transforms coupled with these models is tested. Long-term data for the Lighvan and Ajichai basins in Iran are used to develop the models. The results indicate considerable improvements when GA selection and wavelet methods are used in both models. For example, the Nash-Sutcliffe efficiency (NSE) coefficient for Lighvan using FCM-ANFIS is 0.74. However, when GA selection is applied, the NSE is improved to 0.85. Moreover, when the wavelet method is added, the performance of new hybrid models shows noticeable enhancements. The NSE value of wavelet-FCM-ANFIS is improved to 0.97 for Lighvan basin.

Editor D. Koutsoyiannis Associate editor E. Toth     

Simulation of streamflow with statistically downscaled daily rainfall using a hybrid of wavelet and GAMLSS models

ABSTRACT

A rainfall–streamflow model is proposed, in which a downscaled rainfall series and its wavelet-based decomposed sub-series at optimum lags were used as covariates in GAMLSS (Generalized Additive Model in Location, Scale and Shape). GAMLSS is applied in climate change impact assessment using CMIP5 general climate model to simulate daily streamflow in three sub-catchments of the Onkaparinga catchment, South Australia. The Spearman correlation and Nash-Sutcliffe efficiency between the observed and median simulated streamflow values were high and comparable for both the calibration and validation periods for each sub-catchment. We show that the GAMLSS has the capability to capture non-stationarity in the rainfall–streamflow process. It was also observed that the use of wavelet-based decomposed rainfall sub-series with optimum lags as covariates in the GAMLSS model captures the underlying physics of the rainfall–streamflow process. The development and application of an empirical rainfall–streamflow model that can be used to assess the impact of catchment-scale climate change on streamflow is demonstrated.     

Threshold level approach for streamflow drought analysis in the Central Andes of Argentina: a climatological assessment

A streamflow drought climatology was developed over the Central Andes of Argentina, a semi-arid region highly vulnerable to climatic variations, based on the analysis of daily historical streamflow records. A threshold level approach was applied on a daily basis for three different severity levels in order to depict the main characteristics of droughts – number of drought events, mean duration and mean severity – over the period 1957–2014. Based on three annual indices that summarize the frequency of drought events, their duration and severity, we identified the main regional dry periods and the main modes of variability through an empirical decomposition. These modes are linked to La Niña conditions on inter-annual time scales and the Pacific Decadal Oscillation for the decadal variations, showing the influence of the tropical Pacific Ocean in the development of streamflow drought conditions and its relevance for potential predictability of hydroclimatic variations over the region.     

Identification and quantification of streamflow trends on the Canadian Prairies

Abstract

Trend analysis was performed on streamflow data for a collection of stations on the Canadian Prairies, in terms of spring and summer runoff volumes, peak flow rates and peak flow occurrences, as well as an annual volume measure, for analysis periods of 1966–2005, 1971–2005, and 1976–2005. The Mann-Kendall statistical test for trend and bootstrap resampling were used to identify the trends and to determine the field significance of the trends. Partial correlation analysis was used to identify relationships between hydrological variables that exhibit a significant trend and meteorological variables that exhibit a significant trend. Noteworthy results include decreasing trends in the spring snowmelt runoff event volume and peak flow, decreasing trends (earlier occurrence) in the spring snowmelt runoff event peak date and decreasing trends in the seasonal (1 March–31 October) runoff volume. These trends can be attributed to a combination of reductions in snowfall and increases in temperatures during the winter months.     

小波分析在地球物理及大地测量中的应用

小波分析是重要的时—领域分析工具，在地球物理和大地测量相关问题研究中逐渐显示出其独特的作用。本文较全面地介绍了现阶段小波分析在重力异常分解、固体潮、地球自转变化、ENSO和重力场展开等地球物理及大地到量领域的研究进展，并在此基础上对地球物理及大地测量领域小波分析的应用前景做了进一步分析。     

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.     

Stochastic simulation of regionalized ground motions using wavelet packets and cokriging analysis

Performance‐based earthquake engineering often requires ground‐motion time‐history analyses to be performed, but very often, ground motions are not recorded at the location being analyzed. The present study is among the first attempt to stochastically simulate spatially distributed ground motions over a region using wavelet packets and cokriging analysis. First, we characterize the time and frequency properties of ground motions using the wavelet packet analysis. The spatial cross‐correlations of wavelet packet parameters are determined through geostatistical analysis of regionalized ground‐motion data from the Northridge and Chi‐Chi earthquakes. It is observed that the spatial cross‐correlations of wavelet packet parameters are closely related to regional site conditions. Furthermore, using the developed spatial cross‐correlation model and the cokriging technique, wavelet packet parameters at unmeasured locations can be best estimated, and regionalized ground‐motion time histories can be synthesized. Case studies and blind tests using data from the Northridge and Chi‐Chi earthquakes demonstrate that the simulated ground motions generally agree well with the actual recorded data. The proposed method can be used to stochastically simulate regionalized ground motions for time‐history analyses of distributed infrastructure and has important applications in regional‐scale hazard analysis and loss estimation. Copyright © 2014 John Wiley & Sons, Ltd.     

利用EMD和子波振幅谱与相位谱关系的时变子波提取方法

本文首先分析了地震波在黏弹介质的传播规律,基于黏弹介质地震波动方程总结了时变子波振幅谱和相位谱的关系,从而得出结论,准确估计子波相位谱初值和不同时刻的子波振幅谱是实现时变子波准确提取的必要条件.在此基础上,针对传统方法限制子波振幅谱形态且受限于分段平稳假设的问题,提出了一种利用EMD（Empirical Mode Decomposition）和子波振幅谱与相位谱关系的时变子波提取方法,根据子波对数振幅谱光滑连续而反射系数对数振幅谱振荡剧烈的特点,采用EMD方法将不同时刻地震记录的对数振幅谱分解为一组具有不同振荡尺度的模态分量,通过滤除振荡剧烈分量、重构光滑连续分量提取时变子波振幅谱;再应用子波振幅谱和相位谱的关系提取时变子波相位谱,将分别提取的振幅谱和相位谱逐点进行合成,最终实现时变子波的准确提取.本文方法不需要求取Q值,适用于变Q值的情况,具有良好的抗噪性能.数值仿真和叠后实际资料处理结果表明,相比传统的分段提取方法,利用本文方法提取的时变子波准确度更高,研究成果对提高地震资料分辨率具有重要意义.

     

A process-based approach to attribution of historical streamflow decline in a data-scarce and human-dominated watershed

Human activities have resulted in rapid hydrological change around the world, in many cases producing shifts in the dominant hydrological processes, confounding predictions, and complicating effective management and planning. Identifying and characterizing such changes in hydrological processes is therefore a globally relevant problem, one that is particularly challenging in sparsely monitored environments. We develop a novel, process-based approach for attribution of hydrological change in such scenarios and apply the approach to the TG Halli watershed outside Bangalore, India, where streamflow has declined considerably over the last 50 years. The approach consists of (a) employing a range of field instrumentation and experiments to identify contemporary streamflow generation mechanisms, (b) using these observations to constrain our understanding and generate hypotheses pertaining to historical changes, and (c) evaluating these hypotheses with a range of evidence including proxies for historical hydrological processes. The body of evidence in the TG Halli watershed indicates the historical presence and subsequent loss of a shallow groundwater table that previously discharged to the stream, meaning that groundwater depletion is the most likely driver of streamflow decline. These findings present a viable path towards improved predictions of future water resources and sustainable water management within the watershed. Our process-based approach to attribution has the potential to improve understanding of human-driven hydrological change in regions with poor monitoring of hydrological systems.     

Hiibert-Huang transform and wavelet analysis of time history signal

The brief theories of wavelet analysis and Hilbert-Huang transform (HHT) are introduced firstly in the present paper. Then several signal data were analyzed by using wavelet and HHT methods, respectively. The comparison shows that HHT is not only an effective method for analyzing non-stationary data, but also is a useful tool for examining detailed characters of time history signal.     

地球同步轨道高能电子变化

结合小波分析及交叉小波分析方法,研究了地球同步轨道高能电子动态变化的多时间尺度结构,分析了电子通量在不同周期随着太阳风速、地磁指数D_st变化的具体特点.结果发现：（1）电子通量的长期变化受控于太阳风速,在太阳活动低值年,电子通量值高,具有明显的13.4天,27.4天及187天周期;交叉小波分析表明,电子通量的13.4天及27.4天周期受太阳风速周期变化信号的影响,187天周期变化受D_st指数周期变化信号的影响.（2）电子通量半年变化主要归因于太阳风的驱动作用,在每年的第100天及270左右达到两次峰值,峰值大小不对称,与D_st指数的谷值大小呈反比.（3）由于冕洞形成过程中的太阳风高速流影响,电子通量具有13.4及27.4天的周期,峰值水平受控于太阳风速结构.     

基于双谱幅值和相位重构的地震子波提取

利用地震记录双谱中包含子波的幅值和相位信息,以及其超强的抗噪声干扰能力,采用一种基于双谱幅值和相位重构的地震子波提取方法,首先提取出子波幅值及相位信息,进而通过傅立叶反变换,使子波得以完全恢复.本文针对双谱相位重构递推公式,提出一种新的初值选取方法,使地震子波估计的稳定性得到了提高.仿真实验证实了该方法的可行性.     

Assessment of drought trend and variability in India using wavelet transform

ABSTRACT

This paper presents an analysis of trends in six drought variables at 566 stations across India over the period 1901–2002. Six drought variables were computed using standardized precipitation index (SPI). The Mann-Kendall (MK) trend test and Sen’s slope estimator were used for trend analysis of drought variables. Discrete wavelet transform (DWT) was used to identify the dominant periodic components in trends, whereas the significance of periodic components was examined using continuous wavelet transform (CWT) based global wavelet spectrum (GWS). Our results show an increasing trend in droughts in eastern, northeastern and extreme southern regions, and a decreasing trend in the northern and southern regions of the country. The periodic component influencing the trend was 2–4 years in south, 4–8 years in west, east and northeast, 8–64 years in central parts and 32–128 years in the north; however, most of the periodic components were not statistically significant.     

基于小波分析的结构损伤检测研究进展

近10几年来,在土木和机械领域结构损伤识别方法已引起不同领域的相关学者的极大研究兴趣。小波分析是一种新的数学分析和信号处理工具,可以对非稳态信号进行详细的时频分析,是传统傅里叶分析所不能及的,已广泛应用于土木、机械和航空工程领域中,特别是在结构损伤识别和健康监测中的应用尤为突出。本文回顾和总结了小波分析理论及其在结构损伤识别、损伤定位和损伤程度确定中的应用,对今后的研究进行了讨论和展望。     

前兆观测资料与地震活动时间序列的Morlet小波变换及相关性分析

Morlet小波在时、频两域都具有良好的局部性,是对时间序列进行多尺度分析和局部特性研究常用的小波变换方法。本文运用Morlet小波变换分析了云南省大理市下关水化站1990~2013年期间水氡、水汞、流量、气压和固体CO2月均值时间序列的变化特征,并与同时期大理市附近50km以内ML2.0~2.9、100km以内ML3.0~3.9、200km以内ML4.0~4.9和600km以内MS≥5.0地震活动月频度的Morlet小波变换特征进行了对比研究,分别计算了5项前兆资料月均值与4个震级范围地震活动月频度的小波平方模之间的相关系数,并对其相关性进行了探讨。     

Changes in seasonality and timing of peak streamflow in snow and semi‐arid climates of the north‐central United States, 1910–2012

Changes in the seasonality and timing of annual peak streamflow in the north‐central USA are likely because of changes in precipitation and temperature regimes. A source of long‐term information about flood events across the study area is the U.S. Geological Survey peak streamflow database. However, one challenge of answering climate‐related questions with this dataset is that even in snowmelt‐dominated areas, it is a mixed population of snowmelt/spring rain generated peaks and summer/fall rain generated peaks. Therefore, a process was developed to divide the annual peaks into two populations, or seasons, snowmelt/spring, and summer/fall. The two series were then tested for the hypotheses that because of changes in precipitation regimes, the odds of summer/fall peaks have increased and, because of temperature changes, snowmelt/spring peaks happen earlier. Over climatologically and geographically similar regions in the north‐central USA, logistic regression was used to model the odds of getting a summer/fall peak. When controlling for antecedent wet and dry conditions and geographical differences, the odds of summer/fall peaks occurring have increased across the study area. With respect to timing within the seasons, trend analysis showed that in northern portions of the study region, snowmelt/spring peaks are occurring earlier. The timing of snowmelt/spring peaks in three regions in the northern part of the study area is earlier by 8.7– 14.3 days. These changes have implications for water interests, such as potential changes in lead‐time for flood forecasting or changes in the operation of flood‐control dams. Copyright © 2015 John Wiley & Sons, Ltd.     

时程分析中设计地震动调整的小波分析方法

本文应用小波分析核心内容之一的多分辨率分析和Mallat算法，提出一种全新的设计地震动调整方法。调整后的地震动既能满足频谱组成的要求，又能反映频谱组成随时间的变化。     

Combining the SWAT model with sequential uncertainty fitting algorithm for streamflow prediction and uncertainty analysis for the Lake Dianchi Basin,China

Streams play an important role in linking the land with lakes. Nutrients released from agricultural or urban sources flow via streams to lakes, causing water quality deterioration and eutrophication. Therefore, accurate simulation of streamflow is helpful for water quality improvement in lake basins. Lake Dianchi has been listed in the ‘Three Important Lakes Restoration Act’ in China, and the degradation of its water quality has been of great concern since the 1980s. To assist environmental decision making, it is important to assess and predict hydrological processes at the basin scale. This study evaluated the performance of the soil and water assessment tool (SWAT) and the feasibility of using this model as a decision support tool for predicting streamflow in the Lake Dianchi Basin. The model was calibrated and validated using monthly observed streamflow values at three flow stations within the Lake Dianchi Basin through application of the sequential uncertainty fitting algorithm (SUFI‐2). The results of the autocalibration method for calibrating and the prediction uncertainty from different sources were also examined. Together, the p‐factor (the percentage of measured data bracketed by 95% prediction of uncertainty, or 95PPU) and the r‐factor (the average thickness of the 95PPU band divided by the standard deviation of the measured data) indicated the strength of the calibration and uncertainty analysis. The results showed that the SUFI‐2 algorithm performed better than the autocalibration method. Comparison of the SUFI‐2 algorithm and autocalibration results showed that some snowmelt factors were sensitive to model output upstream at the Panlongjiang flow station. The 95PPU captured more than 70% of the observed streamflow at the three flow stations. The corresponding p‐factors and r‐factors suggested that some flow stations had relatively large uncertainty, especially in the prediction of some peak flows. Although uncertainty existed, statistical criteria including R² and Nash–Sutcliffe efficiency were reasonably determined. The model produced a useful result and can be used for further applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Spatio-temporal variability of streamflow in the Yellow River: possible causes and implications

Abstract

The water shortage in the Yellow River, China, has been aggravated by rapid population growth and global climate changes. To identify the characteristics of streamflow change in the Yellow River, approximately 50 years of natural and observed streamflow data from 23 hydrological stations were examined. The Mann-Kendall and Pettitt tests were used to detect trends and abrupt change points. The results show that both the natural and the observed streamflow in the Yellow River basin present downward trends from 1956 to 2008, and the decreasing rate of observed streamflow is generally faster than that of the natural streamflow. Larger drainage areas have higher declining rates, and the declining trends are intensified downstream within the mainstream. The possibility of abrupt changes in observed streamflow is higher than in natural streamflow, and streamflow series in the mainstream are more likely to change abruptly than those in the tributaries. In the mainstream, all the significant abrupt changes appear in the middle and latter half of the 1980s, but the abrupt changes occur somewhat earlier for observed streamflow than for natural streamflow. The significant abrupt change for the observed streamflow in the tributaries is almost isochronous with the natural streamflow and occurs from the 1970s to 1990s. It is implied that the slight reduction in precipitation is not the only direct reason for the streamflow variation. Other than the effects of climate change, land-use and land-cover changes are the main reasons for the natural streamflow change. Therefore, the increasing net water diversion by humans is responsible for the observed streamflow change. It is estimated that the influence of human activity on the declining streamflow is enhanced over time.

Editor Z.W. Kundzewicz

Citation Miao, C.Y., Shi, W., Chen, X.H., and Yang, L., 2012 Miao, C.Y., Yang, L. and Chen, X.H. 2012. The vegetation cover dynamics (1982–2006) in different erosion regions of the Yellow River basin, China. Land Degradation and Development, 23(1): 62–71. [Crossref], [Web of Science ®] , [Google Scholar]. Spatio-temporal variability of streamflow in the Yellow River: possible causes and implications. Hydrological Sciences Journal, 57 (7), 1355–1367.