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1.
Detrending is a key step in the study of the scaling behaviors using Detrended Fluctuation Analysis (DFA) to explore the long‐range correlation of hydrological series. However, the irregular periodicity and various trends within hydrological series as a result of integrated influences of human activities such as construction of water reservoirs and human withdrawal of freshwater and climate changes such as alterations of precipitation changes in both space and time make difficult the selection of detrending methods. In this study, we attempt to address the detrending problem due to the important theoretical and practical merits of detrending in DFA‐based scaling analysis. In this case, with focus on the irregularity of the periodic trends, a modified DFA, varying parameter DFA (VPDFA), and its combination with adaptive detrending algorithm (ADA) are employed to eliminate the influences of irregular cycles on DFA‐based scaling results. The results indicate that, for streamflow series with no more than 20 cycles, VPDFA is recommended; otherwise, the combined method has to be employed. Comparison study indicates that the scaling behavior of the detrended observed streamflow series by average removed method, when compared to those by DFA, VPDFA, and ADA, is the one of the periodic residues around the averaged annual cycle for the entire series rather than that excluding all annual cycles. However, although the result by VPDFA for short observed streamflow record can well correspond to that for numerically simulated series, the scaling behavior obtained by combined method analyzing long record looks strange and is different from that by numerical analysis. We attribute this difference to the complicated hydrological structure and the possible hydrological alternation due to the increasing integrated impacts of human activities and human activities with the extending record. How to include the most of the important factors into the detrending procedure is still a challenging task for further study in the analysis of the scaling behavior of hydrological processes. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

2.
A number of studies have indicated a transition from warm-dry to warm-wet climate in Northwest China after the 1980s. This transition was characterized by an increase in temperature and precipitation, added river runoff volume, increased lake water surface elevation and area, and elevated groundwater table. However, some literatures showed that the Hotan River has presented a contrary situation, i.e. the runoff decreased, whereas temperature and precipitation increased. In order to discover the nonlinear runoff trend and its causes in the Hotan River, based on the related data from hydrological stations, ground and air sounding meteorological stations, this study applied a comprehensive method combing correlation analysis, wavelet analysis and regression analysis to investigate the runoff change in the Hotan River with its relevant climatic factors over the past decades. The main findings are: (a) the hydrological process of the Hotan River is a nonlinear system, with a periodicity of 24 year cycle, and it shows different nonlinear trends at different time scales; (b) the data from the ground meteorological stations in the Hotan area shows a false appearance that there is almost no correlation between runoff and temperature, and a little negative correlation between runoff and precipitation; (c) but the data from air sounding meteorological stations shows the truth that there is a close relation between the runoff in the Hotan River and the 0°C level height in summer on the north slope of Kunlun Mountains. The two variables present a same periodicity, i.e. 24-year cycle, having similar nonlinear trends and significant correlations at different time scales.  相似文献   

3.
Abstract

A method is introduced for probabilistic forecasting of hydrological events based on geostatistical analysis. In this method, the predictors of a hydrological variable define a virtual field such that, in this field, the observed dependent variables are considered as measurement points. Variography of the measurement points enables the use of the system of kriging equations to estimate the value of the variable at non-measured locations of the field. Non-measured points are the forecasts associated with specific predictors. Calculation of the estimation variance facilitates probabilistic analysis of the forecast variables. The method is applied to case studies of the Red River in Manitoba, Canada and Karoon River in Khoozestan, Iran. The study analyses the advantages and limitations of the proposed method in comparison with a K-nearest neighbour approach and linear and nonlinear multiple regression. The utility of the proposed method for forecasting hydrological variables with a conditional probability distribution is demonstrated.  相似文献   

4.
Scaling and multifractal properties of the hydrological processes of the Yangtze River basin were explored by using a multifractal detrended fluctuation analysis (MF‐DFA) technique. Long daily mean streamflow series from Cuntan, Yichang, Hankou and Datong stations were analyzed. Using shuffled streamflow series, the types of multifractality of streamflow series was also studied. The results indicate that the discharge series of the Yangtze River basin are non‐stationary. Different correlation properties were identified within streamflow series of the upper, the middle and the lower Yangtze River basin. The discharge series of the upper Yangtze River basin are characterized by short memory or anti‐persistence; while the streamflow series of the lower Yangtze River basin is characterized by long memory or persistence. h(q) vs q curves indicate multifractality of the hydrological processes of the Yangtze River basin. h(q) curves of shuffled streamflow series suggest that the multifractality of the streamflow series is mainly due to the correlation properties within the hydrological series. This study may be of practical and scientific importance in regional flood frequency analysis and water resource management in different parts of the Yangtze River basin. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

5.
Annual and monthly rainfall data generation schemes   总被引：2，自引：2，他引：0  
Synthetic annual and monthly rainfall data series are generated by using autoregressive (AR) processes, Thomas-Fiering (TF) model, method of fragments (F) and its modified version (MF), two-tier (TT) model, and a newly developed wavelet (W) approach. It is seen that the W approach is as well in preserving the statistical behavior of the observed data series as the classical annual and monthly hydrological data generation schemes used in this study. The W approach is found even better in replacing some particular characteristics such as the mean of the sequence and correlation between the successive months in the series. It is, therefore, proposed as a new annual and monthly hydrological data generation scheme.  相似文献   

6.
何孟奇  闪锟  王兰  杨柳  李哲  尚明生 《湖泊科学》2023,35(2):507-518
水华的频发已成为当前三峡水库最为突出的生态环境问题之一。尽管水动力调控叠加上温度变暖和营养负荷增加会诱导水华暴发强度和频率增加,但仍缺乏有效的方法框架去利用野外观测数据评估环境因子与浮游植物间的因果关联。本研究以三峡水库澎溪河监测数据为例,采用非线性时序分析的建模框架来量化浮游植物的因果响应规律。数据来自于2007年6月至2018年9月澎溪河流域的高阳平湖和汉丰湖两个观测点,其中包含了水文、气象和水质及叶绿素a等11种变量。首先,利用奇异谱分析(SSA)分离了叶绿素a和环境因子的低维确定性动力学信号;其次,采用收敛交叉映射(CCM)方法检验了叶绿素a与环境因子间的因果关联。结果显示:(1)气象因子、支流流量、水温、三峡大坝水位和上游调节坝水位是影响高阳平湖叶绿素a时序变化的重要因素;(2)总氮、总磷为代表的营养盐只在汉丰湖观测点中表现出与叶绿素a的因果关系,且总氮较之于总磷对叶绿素a变化影响更为显著;(3)CCM结果与传统的皮尔森相关性分析及格兰杰因果检验比较,证实非线性时序分析方法在分析浮游植物的因果响应上更具优势。本研究为水生态系统的因果建模提供了研究范例,也为推动利用长期观测数据...  相似文献   

7.
The coherence method is always used to describe the discontinuity and heterogeneity of seismic data. In traditional coherence methods, a linear correlation coefficient is always used to measure the relationship between two random variables (i.e., between two seismic traces). However, mathematically speaking, a linear correlation coefficient cannot be applied to describe nonlinear relationships between variables. In order to overcome this limitation of liner correlation coefficient. We proposed an improved concordance measurement algorithm based on Kendall’s tau. That mainly concern the sensitivity of the liner correlation coefficient and concordance measurements on the waveform. Using two designed numerical models tests sensitivity of waveform similarity affected by these two factors. The analysis of both the numerical model results and real seismic data processing suggest that the proposed method, combining information divergence measurement, can not only precisely characterize the variations of waveform and the heterogeneity of an underground geological body, but also does so with high resolution. In addition, we verified its effectiveness by the actual application of real seismic data from the north of China.  相似文献   

8.
In this study, we investigated the temporal variability of dissolved oxygen and water temperature in conjunction with water level fluctuations and river discharge in the Narew lowland river reach. For this purpose, high resolution hydrologic and water quality time series have been used. Spectral analyses of time series using continuous wavelet transform scheme have been applied in order to identify characteristic scales, its duration, and localisation in time. The results of wavelet analysis have shown a great number of periodicities in time series at the inter-annual time scale when compared to the classical Fourier analysis. Additionally, wavelet coherence revealed the complex nature of the relationship between dissolved oxygen and hydrological variables dependent on the scale and localisation in time. Hence, the results presented in this paper may provide an alternative representation to a frequency analysis of time series.  相似文献   

9.
Many studies have analysed the nonstationarity in single hydrological variables due to changing environments. Yet, few researches have been done to investigate how the dependence structure between different individual hydrological variables is affected by changing environments. To investigate how the reservoirs have altered the dependence structure between river flows at different locations on the Hanjiang River, a time‐varying copula model, which takes the nonstationarity in the marginal distribution and/or the time variation in dependence structure between different hydrological series into consideration, is presented in this paper to perform a bivariate frequency analysis for the low‐flow series from two neighbouring hydrological gauges. The time‐varying moments model with either time or reservoir index as explanatory variables is applied to build the time‐varying marginal distributions of the two low‐flow series. It's found that both marginal distributions are nonstationary, and the reservoir index yields better performance than the time index in describing the nonstationarities in the marginal distributions. Then, the copula with the dependence parameter expressed as a function of either time or reservoir index is applied to model the variable dependence between the two low‐flow series. The copula with reservoir index as the explanatory variable of the dependence parameter has a better fitting performance than the copula with the constant or the time‐trend dependence parameter. Finally, the effect of the time variation in the joint distribution on three different types of joint return periods (i.e. AND, OR and Kendall) of low flows at two neighbouring hydrological gauges is presented. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   

10.
The role of lithology in influencing basin form and function is explored empirically by investigating correlations between a range of catchment variables, where the spatial unit of analysis is not surface catchments but lithologically coherent groundwater units. Using the Thames basin, UK, as a case study, nine groundwater units have been identified. Values for 11 hydrological and geomorphological variables, including rainfall, drainage density, Baseflow Index, aquifer porosity, storage coefficient and log‐hydraulic conductivity, aquifer and drainage elevation, river incision, and hypsometric integral have been estimated for each of the groundwater units in the basin, and Pearson correlation coefficients calculated for all pairs of variables. Seven of the correlation coefficients are found to be significant at a confidence level of > 99%. Negative correlations between drainage density and log aquifer hydraulic conductivity, and between drainage density and river incision, and positive correlations between log‐hydraulic conductivity and river incision, log‐hydraulic conductivity and Baseflow Index, and between Baseflow Index and river incision are inferred to have consistent causal explanations. For example, incision of rivers into aquifers leads to relative increases in hydraulic gradients in the vicinity of rivers which, in turn, promotes the development of secondary porosity increasing both aquifer hydraulic conductivity and, hence, Baseflow Index. The implication of this interpretation is that the geomorphological evolution of basins is intimately linked to the evolution of hydraulic conductivity of the underlying aquifers. This is consistent with, and supports the notion of a coupled complexly evolving surface water‐groundwater system. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

11.
In this paper, we analyzed the high/low water levels of eight stations along the Pearl River estuary and the high/low tidal levels of Sanzao station, and streamflow series of Sanshui and Makou stations using wavelet transform technique and correlation analysis method. The behaviors of high/low water levels of the Pearl River estuary, possible impacts of hydrological processes of the upper Pearl River Delta and astronomical tidal fluctuations were investigated. The results indicate that: (1) the streamflow variability of Sanshui and Makou stations is characterized by 1-year period; 1-, 0.5- and 0.25-year periods can be detected in the high tidal level series of Sanzao station, which reflect the fluctuations of astronomical tidal levels. The low tidal level series of Sanzao station has two periodicity elements, i.e. 0.5- and 0.25-year periods; (2) different periodicity properties have been revealed: the periods of high water levels of the Pearl River estuary are characterized by 1-, 0.5- and 0.25-year periods; and 1-year period is the major period in the low water levels of the Pearl River estuary; (3) periodicity properties indicate that behaviors of low water levels are mainly influenced by hydrological processes of the upper Pearl River Delta. High water levels of the Pearl River estuary seem to be affected by both hydrological processes and fluctuations of astronomical tidal levels represented by tidal level changes of Sanzao station. Correlation analysis results further corroborate this conclusion; (4) slight differences can be observed in wavelet transform patterns and properties of relationships between high/low water levels and streamflow changes. This can be formulated by altered hydrodynamic and morphodynamic processes due to intensifying human activities such as construction of engineering infrastructures and land reclamation.  相似文献   

12.
The ordinary least square method (OLS) has been the most frequently used least square method in hydrological data analysis. Its computational algorithm is simple, and the error analysis is also simple and clear. However, the primary assumption of the OLS method, which states that the dependent variable is the only error‐contaminated variable and all other variables are error free, is often violated in hydrological data analyses. Recently, a matrix algorithm using the singular value decomposition for the total least square (TLS) method has been developed and used in data analyses as errors‐in‐variables model where several variables could be contaminated with observational errors. In our study, the algorithm of the TLS is introduced in the evaluation of rating curves between the flow discharge and the water level. Then, the TLS algorithm is applied to real data set for rating curves. The evaluated TLS rating curves are compared with the OLS rating curves, and the result indicates that the TLS rating curve and the OLS rating curve are in good agreement. The TLS and OLS rating curves are discussed about their algorithms and error terms in the study. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

13.
Ali Subyani  Zekai en 《水文研究》2006,20(20):4373-4380
The rainfall and infiltration elements of the hydrological cycle in arid regions are characterized by temporal and spatial variations that are random and sporadic. Consequently, the chloride concentration in rainfall has a similar behaviour. Despite this, the classical chloride mass balance (CMB) approach only employs arithmetic and weighted averages for recharge estimation. In this paper, the classical CMB method is modified by taking into account some perceived deficiencies in the methodology. The modified CMB method takes into consideration additional statistical parameters, namely variances and the correlation coefficient between variables concerned based on the application of the perturbation method. Strategic aquifer planning in the Kingdom of Saudi Arabia requires a quick method for estimating groundwater recharge in order to determine the temporal management of available water resources. To demonstrate the difference between the classical and the refined CMB methods, both were applied to a representative basin, i.e. Wadi Yalamlam, in the western part of Saudi Arabia. Based on the refined calculations, recharge to groundwater is found to be 11% of the effective annual rainfall. This refined method provides higher recharge rates because it takes into account the actual variability in the variables concerned and can, thus, improve the accuracy of future groundwater recharge estimation studies. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

14.
Non-linear canonical correlation analysis in regional frequency analysis   总被引：2，自引：2，他引：0  
Hydrological processes are complex non-linear phenomena. Canonical correlation analysis (CCA) is frequently used in regional frequency analysis (RFA) to delineate hydrological neighborhoods. Although non-linear CCA (NL-CCA) is widely used in several fields, it has not been used in hydrology, particularly in RFA. This paper presents an overview of techniques used to reproduce non-linear relationships between two sets of variables. The approaches considered in this work are based on NL-CCA using neural networks (CCA-NN), coupled to a log-linear regression model for flood quantile estimation. In order to demonstrate the usefulness of these approaches in RFA, a comparative study between the latter and linear CCA is performed using three different databases from North America. Results show that CCA-NN is more robust and can better reproduce the non-linear relationship structures between physiographical and hydrological variables. This reflects the high flexibility of this approach. Results indicate that for all three databases, it is more advantageous to proceed with the non-linear CCA approach.  相似文献   

15.
Hydrological system analyses are challenged by complexities of irregular nonlinearities, data uncertainties, and multivariate dependencies. Among them, the irregular nonlinearities mainly represent inexistence of regular functions for robustly simulating highly complicated relationships between variables. Few existing studies can enable reliable simulation of hydrological processes under these complexities. This may lead to decreased robustness of the constructed models, unfeasibility of suggestions for human activities, and damages to socio‐economy and eco‐environment. In the first of two companion papers, a discrete principal‐monotonicity inference (DPMI) method is proposed for hydrological systems analysis under these complexities. Normalization of non‐normally distributed samples and invertible restoration of modelling results are enabled through a discrete distribution transformation approach. To mitigate data uncertainties, statistical inference is employed to assess the significance of differences among samples. The irregular nonlinearity between the influencing factors (i.e. predictors) and the hydrological variable of interest (i.e. the predictand) is interpreted as piecewise monotonicity. Monotonicity is further represented as principal monotonicity under multivariate dependencies. Based on stepwise classification and cluster analyses, all paired samples representing the responsive relationship between the predictors and the predictand are discretized as a series of end nodes. A prediction approach is advanced for estimating the predictand value given any combination of predictors. The DPMI method can reveal evolvement rules of hydrological systems under these complexities. Reliance of existing hydro‐system analysis methods on predefined functional forms is removed, avoiding artificial disturbances, e.g. empiricism in selecting model functions under irregular nonlinearities, on the modelling process. Both local and global significances of predictors in driving the evolution of hydrological variables are identified. An analysis of interactions among these complexities is also achieved. The understanding obtained from the DPMI process and associated results can facilitate hydrological prediction, guide water resources management, improve hydro‐system analysis methods, or support hydrological systems analysis in other cases. The effectiveness and advantages of DPMI will be demonstrated through a case study of streamflow simulation in Xingshan Watershed, China, in another paper. Copyright © 2016 John Wiley & Sons, Ltd.  相似文献   

16.
  Mutual information is a generalised measure of dependence between any two variables. It can be used to quantify non-linear as well as linear dependence between any two variables. This makes mutual information an attractive alternative to the use of the correlation coefficient, which can only quantify the linear dependence pattern. Mutual information is especially suited for application to hydrological problems, because the dependence between any two hydrologic variables is seldom linear in nature. Calculation of the mutual information score involves estimation of the marginal and joint probability density functions of the two variables. This paper uses nonparametric kernel density estimation methods to estimate the probability density functions. Accurate estimation of the mutual information score using kernel methods requires selection of appropriate smoothing parameters (bandwidths) for use with the kernels. The aim of this paper is to obtain a practical method for bandwidth selection for calculation of the mutual information score. In this paper, the lag-one dependence structures of several autocorrelated time series are analysed using mutual information (note that this produces the lag-one auto-MI score, the analog of the lag-one autocorrelation). Empirical trials are used to select appropriate bandwidths for a range of underlying autoregressive and autoregressive-moving average models with normal or near-normal parent distributions. Expressions for reasonable bandwidth choices under these conditions are proposed.  相似文献   

17.
Abstract

The degree of relationship between hydrological variables being independent of time series properties is especially related to the distance between gauging stations of these variables. The linear character of these variables without extreme deviation in time makes possible the use of a new method of interpolation. Following is an explanation of a method which generalizes methods of linear interpolation of two points. Computing the variable values at each point, automatic drawing of isoplets and the water height in a basin can be easily computed by this method.  相似文献   

18.
Climate change and human activities are two major driving forces affecting the hydrologic cycle, which further influence the stationarity of the hydrologic regime. Hydrological drought is a substantial negative deviation from the normal hydrologic conditions affected by these two phenomena. In this study, we propose a framework for quantifying the effects of climate change and human activities on hydrological drought. First, trend analysis and change‐point test are performed to determine variations of hydrological variables. After that, the fixed runoff threshold level method (TLM) and the standardized runoff index (SRI) are used to verify whether the traditional assessment methods for hydrological drought are applicable in a changing environment. Finally, two improved drought assessment methods, the variable TLM and the SRI based on parameter transplantation are employed to quantify the impacts of climate change and human activities on hydrological drought based on the reconstructed natural runoff series obtained using the variable infiltration capacity hydrologic model. The results of a case study on the typical semiarid Laohahe basin in North China show that the stationarity of the hydrological processes in the basin is destroyed by human activities (an obvious change‐point for runoff series is identified in 1979). The traditional hydrological drought assessment methods can no longer be applied to the period of 1980–2015. In contrast, the proposed separation framework is able to quantify the contributions of climate change and human activities to hydrological drought during the above period. Their ranges of contributions to hydrological drought calculated by the variable TLM method are 20.6–41.2% and 58.8–79.4%, and the results determined by the SRI based on parameter transplantation method are 15.3–45.3% and 54.7–84.7%, respectively. It is concluded that human activities have a dominant effect on hydrological drought in the study region. The novelty of the study is twofold. First, the proposed method is demonstrated to be efficient in quantifying the effects of climate change and human activities on hydrological drought. Second, the findings of this study can be used for hydrological drought assessment and water resource management in water‐stressed regions under nonstationary conditions.  相似文献   

19.
Abstract

A new method is presented to generate stationary multi-site hydrological time series. The proposed method can handle flexible time-step length, and it can be applied to both continuous and intermittent input series. The algorithm is a departure from standard decomposition models and the Box-Jenkins approach. It relies instead on the recent advances in statistical science that deal with generation of correlated random variables with arbitrary statistical distribution functions. The proposed method has been tested on 11 historic weekly input series, of which the first seven contain flow data and the last four have precipitation data. The article contains an extensive review of the results.

Editor D. Koutsoyiannis

Citation Ilich, N., 2014. An effective three-step algorithm for multi-site generation of stochastic weekly hydrological time series. Hydrological Sciences Journal, 59 (1), 85–98.  相似文献   

20.
Abstract

This paper develops an algorithm for computing spatially-distributed monthly potential evaporation (PE) over a mountainous region, the Lhasa River basin in China. To develop the algorithm, first, correlation analysis of different meteorological variables was conducted. It was observed that PE is significantly correlated with vapour pressure and temperature differences between the land surface and the atmosphere. Second, the Dalton model, which was developed based on the mass transfer mechanism, was modified by including the influence of the related meteorological variables. Third, the influence of elevation on monthly temperature, vapour pressure and wind velocity was analysed, and functions for extending these meteorological variables to any given altitude were developed. Fourth, the inverse distance weighting method was applied to integrate the extended meteorological variables from five stations adjacent to and within the Lhasa River basin. Finally, using the modified Dalton model and the integrated meteorological variables, we computed the spatially-distributed monthly PE. This study indicated that spatially-distributed PE can be obtained using data from sparse meteorological stations, even if only one station is available; the results show that in the Lhasa River basin PE decreases when elevation increases. The new algorithm, including the modified model and the method for spatially extending meteorological variables can provide the basic inputs for distributed hydrological models.
Editor Z.W. Kundzewicz  相似文献   

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