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The use of the exponent K(q) function to delimit homogeneous regions in regional frequency analysis of extreme annual daily rainfall 
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下载免费PDF全文 A. P. García‐Marín J. Estévez C. Sangüesa‐Pool R. Pizarro‐Tapia J. L. Ayuso‐Muñoz F. J. Jimenez‐Hornero 《水文研究》2015,29(1):139-151
The regional frequency analysis of extreme annual rainfall data is a useful methodology in hydrology to obtain certain quantile values when no long data series are available. The most crucial step in the analysis is the grouping of sites into homogeneous regions. This work presents a new grouping criterion based on some multifractal properties of rainfall data. For this purpose, a regional frequency analysis of extreme annual rainfall data from the Maule Region (Chile) has been performed. Daily rainfall data series of 53 available stations have been studied, and their empirical moments scaling exponent functions K(q) have been obtained. Two characteristics parameters of the K(q) functions (γmax and K(0)) have been used to group the stations into three homogeneous regions. Only five sites have not been possible to include into any homogenous regions, being the local frequency analysis of extreme daily rainfall the most appropriate method to be used at these locations. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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A multifractal analysis was carried out in order to validate the simulation of hourly rainfall records of a local climate model for the Iberian Peninsula. Observed and simulated hourly rainfall data from four locations in Andalusia (southern Spain) were used to carry out the study. In order to detect the influence of the length of the data series on the results, two different sizes were used for the real data: 4 years, and 20 years. The results show that algebraic tails are required to fit the probability distribution of extreme rain event sizes, and rain and dry event durations for both kinds of rainfall data. Similar results are found for the extreme rain event sizes and dry event durations fits when the real and synthetic data are considered. Nevertheless, some differences appear in the cases of rain event durations. The detection of the presence of a first‐order multifractal phase transition associated with a critical moment in the empirical moment scaling exponent function and the results of the extreme rain event sizes fits, reveal that real rainfall is a self‐organized criticality (SOC) process. That behaviour is less evident in the simulated rainfall series. The same ‘synoptic maximum’ value was found for each place with both types of rainfall data. A time clustering analysis was carried out applying the count‐based periodogram and the Fano factor methods. Some periodicities have been detected in the periodograms, especially for the longest real rainfall data series. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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In this work, the multifractal properties of hourly rainfall data recorded at a location in Southern Spain have been related to the scale properties of the corresponding intensity–duration–frequency (IDF) curves. Four parametric models for the IDF curves have been fitted to the quantiles of rainfall obtained using the generalized Pareto frequency distribution function with the extreme data series obtained for the same place. The scaling of the rainfall intensity moments has been analysed, and the empirical moments scaling exponent function has been obtained. The corresponding values of q1 and γ1 have been empirical and theoretically calculated and compared with some characteristics of the different IDF models. Thus, the scaling behaviour of IDF curves has been analysed, and the best model has been selected. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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The multifractality of energy and thermal dissipation of fully developed intermittent turbulence is investigated in the urban canopy layer under unstable conditions by the singularity spectrum for the fractal dimensions of sets of singularities characterizing multifractals. In order to obtain high-order moment properties of smallscale turbulent dissipation in the inertial range, an ultrasonic anemometer with a high sampling frequency of 100 Hz was used. The authors found that the turbulent signal could be singular everywhere. Moreover, the singular exponents of energy and thermal dissipation rates are most frequently encountered at around 0.2, which is significantly smaller than the singular exponents for a wind tunnel at a moderate Reynolds number. The evidence indicates a higher intermittency of turbulence in the urban canopy layer at a high Reynolds number, which is demonstrated by the data with high temporal resolution. Furthermore, the temperature field is more intermittent than the velocity field. In addition, a large amount of samples could be used for verification of the results. 相似文献
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A multifractal analysis of hourly and daily rainfall data recorded at four locations of Andalusia (southern Spain) was carried out in order to study the temporal structure of rainfall and to find differences between both time resolutions. The results show that an algebraic tail is required to fit the probability distribution of the extreme rain events for all the cases. The presence of a multifractal phase transition associated with a critical moment in the empirical moments scaling exponent function was also detected. Both facts indicate that the rainfall process is a case of self‐organized criticality (SOC) dynamics, although the results differ for each place according to the time resolution and the nature of the rainfall, either convective or frontal. This SOC behaviour is related to a statistically steady state that implies the presence of clusterization in the time‐occurrence sequence of rain events. Such fluctuations have been shown by performing the analysis of the Fano and Allan factors and the count‐based periodogram. The values for the “synoptic maximum”, the typical lifetime of planetary scale atmospheric structures, have been obtained for each place and some important periodicities have been detected when dealing with extremes. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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The identification of an appropriate Minimum Inter‐event Time (MIT) based on multifractal characterization of rainfall data series 下载免费PDF全文
下载免费PDF全文 Different hydrological models of sediment entrainment, infiltration, overland flow production, soil loss, landslide occurrence, among others, need rainfall events data. The Minimum Inter‐event Time (MIT) used to separate rainfall events affects their properties. Therefore, it is highly important their correct definition. Various event definitions are commonly used in hydrology, and a high variety of MIT is applied. In this work, an easy method is proposed for deciding the proper MIT in a certain place when dealing with hourly rainfall data series. This new methodology is based on the scale invariance properties of rainfall, analysed with both multifractal and Self‐Organized Criticality theories. The similarity between some parameters from both analyses allows picking out the more appropriate MIT for the hourly rainfall data sets analysed, in Malaga (Southern Spain) and Bullileo (Central Chile). The method can be applied for different rainfall time resolutions according to the purpose of the model that needs the rain event information. Copyright © 2016 John Wiley & Sons, Ltd. 相似文献
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To quantify the spatial distribution of geochemical elements, the multifractality indices for Zn, Cu, Pt, Pd, Cr, Ni, Co, Pb, and As in lake-sediment samples in the Shining Tree area in the Abitibi area of Ontario are determined. The characterization of multifractal distribution patterns is based on the box-counting moment method and involves three functions: a mass exponent function (q); Coarse Hölder Exponent (q); and fractal dimension spectrum f( (q)). Properties of these functions at different values of q, characterize the spatial distribution of the variable under study. It is shown that the degree of multifractality defined by (1) can be used as a measure of irregularity of geochemical spatial dispersion patterns. The variations of Zn and Cu in the study area are characterized by relatively low degree of multifractality, whereas those for Pt, Pd, Cr, Ni, and Co; and particularly for As and Pb are characterized by higher multifractality indices.In the case of Zn and Cu, singularity spectra are close to a monofractal compared to the ones for As an Pb. The determination of multifractality indices allows us, in a quantitative way, to study the pattern of metal dispersions and link them to different physical processes, such as metal adsorption by organic material or glaciogenic processes. 相似文献
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Apparent multifractality and scale‐dependent distribution of data sampled from self‐affine processes
Shlomo P. Neuman 《水文研究》2011,25(11):1837-1840
It has been previously demonstrated theoretically and numerically by the author that square or absolute increments of data sampled from fractional Brownian/Lévy motion (fBm/fLm), or of incremental data sampled from fractional Gaussian/Lévy noise (fGn/fLn), exhibit apparent/spurious multifractality. Here, we generalize these previous development in a way that (a) rigorously subordinates (truncated) fLn to fGn or, in a statistically equivalent manner, (truncated) fLm to fBm; (b) extends the analysis to a wider class of subordinated self‐affine processes; (c) provides a simple way to generate such processes and (d) explains why the distribution of corresponding increments tends to evolve from heavy tailed at small lags (separation distances or scales) to Gaussian at larger lags. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
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The Baker River is the largest free-flowing river in Chilean Patagonia. Long-range dependence (LRD), a recognised hydrological property of river runoff worldwide, was detected for the Baker River runoff time series. Analyses were conducted on a monthly scale between 1961 and 2015 using the fractal and multifractal detrended fluctuation analysis methodology. A long-range-dependent Hurst coefficient (H) equal to 0.94 was obtained. A scaling range, which is the signature of LRD, was detected for the Baker River runoff time series between 1 and 5.25 years. Baker River runoff showed a strong correlation (r?=?0.96) with the Antarctic Oscillation (AAO) Index during the 2007–2015 period. The high storage capacity of Lake General Carrera, the size of the Baker River basin area and the dynamics of AAO are proposed as main factors that contribute to the emergence of LRD in the Baker River runoff time series. 相似文献
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In this article, the Multi-Fractal Detrended Fluctuation Analysis (MF-DFA) method is adopted to study the temperature, i. e., the maximum temperature (Tmax), mean temperature (Tavg) and minimum (Tmin) air temperature, multifractal characteristics and their formation mechanism, in the typical temperature zones in the coastal regions in Guangdong, Jiangsu and Liaoning Provinces. Following are some terms and concepts used in the present study. Multifractality is defined as a term that characterizes the complexity and self-similarity of objects, and fractal characteristics depict the distribution of probability over the whole set caused by different local conditions or different levels in the process of evolution. Fractality strength denotes the fluctuation range of the data set, and long-range correlation (LRC) measures the stability of the climate system and the trend of climate change in the future. In this research, it is found that the internal stability and feedback mechanism of climate systems in different regions show regional differences. Furthermore, the research also proves that the Tavg, Tmax and Tmin of the above three provinces are highly multifractal. The temperature series multifractality of each province decreases in the order of temperature series multifractality of Liaoning > temperature series multifractality of Guangdong > temperature series multifractality of Jiangsu, and the corresponding long-range correlations follow the same order. It reveals that the most stable temperature series is that of Liaoning, followed by the temperature series of Guangdong, and the most unstable one is that of Jiangsu. Liaoning has the most stable climate system, and it will thus be less responsive to the future climate warming. The stability of the climate system in Jiangsu is the weakest, and its temperature fluctuation will continue to increase in the future, which will probably result in the meteorological disasters of high temperature and heat wave there. Guangdong possesses the strongest degree of multifractal strength, which indicates that its internal temperature series fluctuation is the largest among the three regions. The Tmax multifractal strength of Jiangsu is stronger than that of Liaoning, while the Tavg and Tmin multifractal strength of Jiangsu is weaker than that of Liaoning, showing that Jiangsu has a larger internal Tmax fluctuation than Liaoning does, while it has a smaller fluctuation of Tavg and Tmin than Liaoning does. Guangdong and Liaoning both show the strongest Tmin multifractal strength, followed by Tavg multifractal strength, and the weakest Tmax multifractal strength. However, Jiangsu has the strongest Tmax, followed by Tavg, and the weakest Tmin. The research findings show that these phenomena are closely related to solar radiation, monsoon strength, topography and some other factors. In addition, the multifractality of the temperature time series results from the negative power-law distribution and long-range correlation, in which the long-range correlation influence of temperature series itself plays the dominant role. With the backdrop of global climate change, this research can provide a theoretical basis for the prediction of the spatial-temporal air temperature variation in the eastern coastal areas of China and help us understand its characteristics and causes, and thus the present study will be significant for the environmental protection of coastal areas. 相似文献
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