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1.
Variations and statistical probability characteristic analysis of extreme precipitation events under climate change in Haihe River Basin,China
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The magnitude and frequency of regional extreme precipitation events may have variability under climate change. This study investigates the time–space variability and statistical probability characteristics of extreme precipitation under climate change in the Haihe River Basin. Hydrological alteration diagnosis methods are implemented to detect the occurrence time, style and degree of alteration such as trend and jump in the extreme precipitation series, and stationarity and serial independence are tested prior to frequency analysis. Then, the historical extreme precipitation frequency and spatio‐temporal variations analyses are conducted via generalized extreme value and generalized Pareto distributions. Furthermore, the occurrence frequency of extreme precipitation events in future is analysed on the basis of the Fourth Assessment Report of the Intergovermental Panel on Climate Change multi‐mode climate models under different greenhouse gases emission scenarios (SRES‐A2, A1B and B1). Results indicate that (1) in the past, alteration of extreme precipitation mainly occurred in the area north of 38°N. Decreasing trends of extreme precipitation are detected at most stations, whereas jump alteration is not obvious at most stations. (2) Spatial variation of estimated extreme precipitation under different return periods shows similarity. Bounded by the Taihang Mountain–Yan Mountain, extreme rainfall in the Haihe River Basin gradually reduces from the southeast to the northwest, which is consistent with the geographical features of the Haihe River Basin. (3) In the future, extreme precipitation with return period 5–20 years accounts for a significant portion of the total occurrence times. The frequency of extreme precipitation events has an increase trend under A1B and A2 scenarios. The total occurrence times of extreme precipitation under A1B senario are not more than that under B1 senario until the 2030s. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
2.
Yu Zhong Yonghong Hao Xueli Huo Mingkun Zhang Qingyun Duan Yonghui Fan 《水文科学杂志》2013,58(11):2011-2023
ABSTRACTTo acquire better understanding of spring discharge under extreme climate change and extensive groundwater pumping, this study proposed an extreme value statistical decomposition model, in which the spring discharge was decomposed into three items: a long-term trend; periodic variation; and random fluctuation. The long-term trend was fitted by an exponential function, and the periodic variation was fitted by an exponential function whose index was the sum of two sine functions. A general extreme value (GEV) model was used to obtain the return level of extreme random fluctuation. Parameters of the non-linear long-term trend and periodic variation were estimated by the Levenberg-Marquardt algorithm, and the GEV model was estimated by the maximum likelihood method. The extreme value statistical decomposition model was applied to Niangziguan Springs, China to forecast spring discharge. We showed that the modelled spring discharge fitted the observed data very well. Niangziguan Springs discharge is likely to continue declining with fluctuation, and the risk of cessation by August 2046 is 1%. The extreme value decomposition model is a robust method for analysing the nonstationary karst spring discharge under conditions of extensive groundwater development/pumping, and extreme climate changes.
Editor D. Koutsoyiannis; Associate editor J. Ward 相似文献
3.
Maochuan Hu Takahiro Sayama Weili Duan Kaoru Takara Bin He Pingping Luo 《水文科学杂志》2017,62(8):1255-1265
A suite of extreme indices derived from daily precipitation and streamflow was analysed to assess changes in the hydrological extremes from 1951 to 2012 in the Kamo River Basin. The evaluated indices included annual maximum 1-day and 5-day precipitation (RX1day, RX5day), consecutive dry days (CDD), annual maximum 1-day and 5-day streamflow (SX1day, SX5day), and consecutive low-flow days (CDS). Sen’s slope estimator and two versions of the Mann-Kendall test were used to detect trends in the indices. Also, frequency distributions of the indices were analysed separately for two periods: 1951–1981 and 1982–2012. The results indicate that quantiles of the rainfall indices corresponding to the 100-year return period have decreased in recent years, and the streamflow indices had similar patterns. Although consecutive no rainfall days represented by 100-year CDD decreased, continuous low-flow days represented by 100-year CDS increased. This pattern change is likely associated with the increase in temperature during this period.
EDITOR D. KoutsoyiannisASSOCIATE EDITOR E. Gargouri 相似文献
4.
《水文科学杂志》2013,58(3):550-567
Abstract The multivariate extension of the logistic model with generalized extreme value (GEV) marginals is applied to provide a regional at-site flood estimate. The maximum likelihood estimators of the parameters were obtained numerically by using a multivariable constrained optimization algorithm. The asymptotic results were checked by distribution sampling techniques in order to establish whether or not those results can be utilized for small samples. A region in northern Mexico with 21 gauging stations was selected to apply the model. Results were compared with those obtained by the most popular univariate distributions, the bivariate approach of the logistic model and three regional methods: station-year, index flood and L-moments. These show that there is a reduction in the standard error of fit when estimating the parameters of the marginal distribution with the trivariate distribution instead of its univariate and bivariate counterpart, and differences between at-site and regional at-site design events can be significant as return period increases. 相似文献
5.
Abdullah Gokhan Yilmaz 《水文科学杂志》2013,58(12):2148-2162
AbstractThere is increasing concern that flood risk will be exacerbated in Antalya, Turkey as a result of global-warming-induced, more frequent and intensive, heavy rainfalls. In this paper, first, trends in extreme rainfall indices in the Antalya region were analysed using daily rainfall data. All stations in the study area showed statistically significant increasing trends for at least one extreme rainfall index. Extreme rainfall datasets for current (1970–1989) and future periods (2080–2099) were then constructed for frequency analysis using the peaks-over-threshold method. Frequency analysis of extreme rainfall data was performed using generalized Pareto distribution for current and future periods in order to estimate rainfall intensities for various return periods. Rainfall intensities for the future period were found to increase by up to 23% more than the current period. This study contributed to better understanding of climate change effects on extreme rainfalls in Antalya, Turkey. 相似文献
6.
7.
Spatiotemporal characteristics of precipitation and extreme events on the Loess Plateau of China between 1957 and 2009 总被引:1,自引:0,他引:1
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Spatiotemporal trends in precipitation may influence vegetation restoration, and extreme precipitation events profoundly affect soil erosion processes on the Loess Plateau. Daily data collected at 89 meteorological stations in the area between 1957 and 2009 were used to analyze the spatiotemporal trends of precipitation on the Loess Plateau and the return periods of different types of precipitation events classified in the study. Nonparametric methods were employed for temporal analysis, and the Kriging interpolation method was employed for spatial analysis. The results indicate a small decrease in precipitation over the Loess Plateau in last 53 years (although a Mann–Kendall test did not show this decrease to be significant), a southward shift in precipitation isohyets, a slightly delayed rainy season, and prolonged return periods, especially for rainstorm and heavy rainstorm events. Regional responses to global climate change have varied greatly. A slightly increasing trend in precipitation in annual and sub‐annual series, with no obvious shift of isohyets, and an evident decreasing trend in extreme precipitation events were detected in the northwest. In the southeast, correspondingly, a more seriously decreasing trend occurred, with clear shifts of isohyets and a slightly decreasing trend in extreme precipitation events. The result suggests that a negative trend in annual precipitation may have led to decreased soil erosion but an increase in sediment yield during several extreme events. These changes in the precipitation over the Loess Plateau should be noted, and countermeasures should be taken to reduce their adverse impacts on the sustainable development of the region. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
8.
The identification of homogeneous precipitation regions has value in many water resources engineering applications (infrastructure planning, design, operations; climate forecasting, modelling). The objective of this paper is to assess the sensitivity of precipitation regions to the temporal resolution (monthly, seasonal, annual and the annual maximum series) of the data. The presented method uses the fuzzy c-means clustering algorithm to partition climate sites into statistically homogeneous precipitation regions. The regions are validated using an approach based on L-moment statistics. The method is conducted in two climatically different study areas in western and eastern Canada. There does not appear to be a relationship between the spatial distributions of the regions formed using different temporal resolutions of the precipitation data. It is recommended to delineate precipitation regions that are specific to the task at hand, and to select a temporal resolution that is consistent with the final application of the regional precipitation dataset.
EDITOR A. Castellarin; ASSOCIATE EDITOR T. Kjeldsen 相似文献
9.
Frequency analysis of climate extreme events in Zanjan, Iran 总被引:2,自引:1,他引:1
Saeed Jahanbaksh Asl Ali Mohammad Khorshiddoust Yagob Dinpashoh Fatemeh Sarafrouzeh 《Stochastic Environmental Research and Risk Assessment (SERRA)》2013,27(7):1637-1650
In this study, generalized extreme value distribution (GEV) and generalized Pareto distribution (GPD) were fitted to the maximum and minimum temperature, maximum wind speed, and maximum precipitation series of Zanjan. Maximum (minimum) daily and absolute annual observations of Zanjan station from 1961 to 2011 were used. The parameters of the distributions were estimated using the maximum likelihood estimation method. Quantiles corresponding to 2, 5, 10, 25, 50, and 100 years return periods were calculated. It was found that both candidate distributions fitted to extreme events series, were statistically reasonable. Most of the observations from 1961 to 2011 were found to fall within 1–10 years return period. Low extremal index (θ) values were found for excess maximum and minimum temperatures over a high threshold, indicating the occurrence of consecutively high peaks. For the purpose of filtering the dependent observations to obtain a set of approximately independent threshold excesses, a declustering method was performed, which separated the excesses into clusters, then the de-clustered peaks were fitted to the GPD. In both models, values of the shape parameters of extreme precipitation and extreme wind speed were close to zero. The shape parameter was less negative in the GPD than the GEV. This leads to significantly lower return period estimates for high extremes with the GPD model. 相似文献
10.
ABSTRACTNumerous statistical downscaling models have been applied to impact studies, but none clearly recommended the most appropriate one for a particular application. This study uses the geographically weighted regression (GWR) method, based on local implications from physical geographical variables, to downscale climate change impacts to a small-scale catchment. The ensembles of daily precipitation time series from 15 different regional climate models (RCMs) driven by five different general circulation models (GCMs), obtained through the European Union (EU)-ENSEMBLES project for reference (1960–1990) and future (2071–2100) scenarios are generated for the Omerli catchment, in the east of Istanbul city, Turkey, under scenario A1B climate change projections. Special focus is given to changes in extreme precipitation, since such information is needed to assess the changes in the frequency and intensity of flooding for future climate. The mean daily precipitation from all RCMs is under-represented in the summer, autumn and early winter, but it is overestimated in late winter and spring. The results point to an increase in extreme precipitation in winter, spring and summer, and a decrease in autumn in the future, compared to the current period. The GWR method provides significant modifications (up to 35%) to these changes and agrees on the direction of change from RCMs. The GWR method improves the representation of mean and extreme precipitation compared to RCM outputs and this is more significant, particularly for extreme cases of each season. The return period of extreme events decreases in the future, resulting in higher precipitation depths for a given return period from most of the RCMs. This feature is more significant with downscaling. According to the analysis presented, a new adaption for regulating excessive water under climate change in the Omerli basin may be recommended. 相似文献
11.
Abstract The aim of this paper is to quantify meteorological droughts and assign return periods to these droughts. Moreover, the relation between meteorological and hydrological droughts is explored. This has been done for the River Meuse basin in Western Europe at different spatial and temporal scales to enable comparison between different data sources (e.g. stations and climate models). Meteorological drought is assessed in two ways: using annual minimum precipitation amounts as a function of return period, and using troughs under threshold as a function of return period. The Weibull extreme value type 3 distribution has been fitted to both sources of information. Results show that the trough-under-threshold precipitation is larger than the annual minimum precipitation for a specific return period. Annual minimum precipitation values increase with spatial scale, being most pronounced for small temporal scales. The uncertainty in annual minimum point precipitation varies between 68% for the 30-day precipitation with a return period of 100 years, and 8% for the 120-day precipitation with a return period of 10 years. For spatially-averaged values, these numbers are slightly lower. The annual discharge deficit is significantly related to the annual minimum precipitation. Citation Booij, M. J. & de Wit, M. J. M. (2010) Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales. Hydrol. Sci. J. 55(8), 1289–1301. 相似文献
12.
Probable maximum flood (PMF) event estimation has challenged the scientific community for many years. Although the concept of the PMF is often applied, there is no consensus on the methods that should be applied to estimate it. In PMF estimation, the spatio-temporal representation of the probable maximum precipitation (PMP) as well as the choice of modelling approach is often not theoretically founded. Moreover, it is not clear how these choices influence PMF estimation itself. In this study, combinations of three different spatio-temporal PMP representations and three different modelling approaches are applied to determine the PMF of a mesoscale basin keeping the antecedent catchment conditions and the total precipitation amount constant. The nine resulting PMF estimations are used to evaluate each combination of methods. The results show that basic methods allow for a rough estimation of the PMF. In cases where a physically plausible and reliable estimation is required, sophisticated PMP and PMF estimation approaches are recommended.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Viglione 相似文献
13.
《水文科学杂志》2013,58(1):236-252
Abstract Suspended sediments are a natural component of aquatic ecosystems, but when present in high concentrations they can become a threat to aquatic life and can carry large amounts of pollutants. Suspended sediment concentration (SSC) is therefore an important abiotic variable used to quantify water quality and habitat availability for some species of fish and invertebrates. This study is an attempt to quantify and predict annual extreme events of SSC using frequency analysis methods. Time series of daily suspended sediment concentrations in 208 rivers in North America were analysed to provide a large-scale frequency analysis study of annual maximum concentrations. Seasonality and the correlation of discharges and annual peak of suspended sediment concentration were also analysed. Peak concentrations usually occur in spring and summer. A significant correlation between extreme SSC and associated discharge was detected only in half of the stations. Probability distributions were fitted to station data recorded at the stations to estimate the return period for a specific concentration, or the concentration for a given return period. Selection criteria such as the Akaike and Bayesian information criterion were used to select the best statistical distribution in each case. For each selected distribution, the most appropriate parameter estimation method was used. The most commonly used distributions were exponential, lognormal, Weibull and Gamma. These four distributions were used for 90% of stations. 相似文献
14.
José J. Hernández Ayala David Keellings Peter R. Waylen Corene J. Matyas 《水文科学杂志》2017,62(13):2103-2119
An extreme value analysis (EVA) point process approach has been implemented to examine the flood characteristics of Puerto Rico when tropical cyclones (TCs) are present in the discharge series and when they are removed from it. Mean daily discharge values that exceeded the 99th percentile thresholds were used in both the TC and non-TC data series. In nine of the 12 stations the maximum discharge was associated with a TC, with hurricanes Hortense (1996), Georges (1998) and Eloise (1975) responsible for most of the maximum peaks at each site. Percentage changes in the generalized extreme value parameters, which include location (central tendency), scale (variance) and shape (skewness), between the TC and non-TC data exhibited a decrease in the majority of stations. Stations in the eastern interior and central region of the island showed the largest decrease in all parameters, in flood occurrences and in return periods when TCs were removed from the series. 相似文献
15.
Modelling bivariate extreme precipitation distribution for data‐scarce regions using Gumbel–Hougaard copula with maximum entropy estimation
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A new method of parameter estimation in data scarce regions is valuable for bivariate hydrological extreme frequency analysis. This paper proposes a new method of parameter estimation (maximum entropy estimation, MEE) for both Gumbel and Gumbel–Hougaard copula in situations when insufficient data are available. MEE requires only the lower and upper bounds of two hydrological variables. To test our new method, two experiments to model the joint distribution of the maximum daily precipitation at two pairs of stations on the tributaries of Heihe and Jinghe River, respectively, were performed and compared with the method of moments, correlation index estimation, and maximum likelihood estimation, which require a large amount of data. Both experiments show that for the Ye Niugou and Qilian stations, the performance of MEE is nearly identical to those of the conventional methods. For the Xifeng and Huanxian stations, MEE can capture information indicating that the maximum daily precipitation at the Xifeng and Huanxian stations has an upper tail dependence, whereas the results generated by correlation index estimation and maximum likelihood estimation are unreasonable. Moreover, MEE is proved to be generally reliable and robust by many simulations under three different situations. The Gumbel–Hougaard copula with MEE can also be applied to the bivariate frequency analysis of other extreme events in data‐scarce regions. 相似文献
16.
Based on daily precipitation data of more than 2000 Chinese stations and more than 50 yr, we constructed time series of extreme precipitation based on six different indices for each station: annual and summer maximum(top-1) precipitation,accumulated amount of 10 precipitation maxima(annual, summer; top-10), and total annual and summer precipitation.Furthermore, we constructed the time series of the total number of stations based on the total number of stations with top-1 and top-10 annual extreme precipitation for the whole data period, the whole country, and six subregions, respectively. Analysis of these time series indicate three regions with distinct trends of extreme precipitation:(1) a positive trend region in Southeast China,(2) a positive trend region in Northwest China, and(3) a negative trend region in North China. Increasing(decreasing)ratios of 10–30% or even 30% were observed in these three regions. The national total number of stations with top-1 and top-10 precipitation extremes increased respectively by 2.4 and 15 stations per decade on average but with great inter-annual variations.There have been three periods with highly frequent precipitation extremes since 1960:(1) early 1960 s,(2) middle and late 1990 s,and(3) early 21 st century. There are significant regional differences in trends of regional total number of stations with top-1 and top-10 precipitation. The most significant increase was observed over Northwest China. During the same period, there are significant changes in the atmospheric variables that favor the decrease of extreme precipitation over North China: an increase in the geopotential height over North China and its upstream regions, a decrease in the low-level meridional wind from South China coast to North China, and the corresponding low moisture content in North China. The extreme precipitation values with a50-year empirical return period are 400–600 mm at the South China coastal regions and gradually decrease to less than 50 mm in Northwest China. The mean increase rate in comparison with 20-year empirical return levels is 6.8%. The historical maximum precipitation is more than twice the 50-year return levels. 相似文献
17.
利用三峡库区35个台站1961-2010年汛期(5-9月)的逐日降水量资料,首先定义不同台站的极端降水量阈值,统计各站近50 a逐年汛期极端降水事件的发生频次,进而分析其时空变化特征.结果表明:三峡库区汛期极端降水事件发生频次的最主要空间模态是主体一致性,同时存在东西和南北相反变化的差异.三峡库区汛期极端降水事件发生频次具有较大的空间差异,可分为具有不同变化特点的5个主要异常区.滑动t检验表明,三峡库区西南部区代表站巴南的极端降水事件在1974年后发生了一次由偏多转为偏少的突变,北部区代表站北碚在1981年后和1993年后分别发生了由偏少转为偏多和由偏多到偏少的突变,中部区代表站武隆在1984年后发生了一次由偏多转为偏少的突变.结合最大熵谱和功率谱分析表明,近50 a来各分区汛期极端降水事件发生频次的周期振荡不太一致,三峡库区东北部区代表站宜昌、北部区代表站北碚和中部区代表站武隆分别存在5、2.4和8.3 a的显著周期. 相似文献
18.
J. T. Shiau 《Stochastic Environmental Research and Risk Assessment (SERRA)》2003,17(1-2):42-57
Extreme hydrological events are inevitable and stochastic in nature. Characterized by multiple properties, the multivariate
distribution is a better approach to represent this complex phenomenon than the univariate frequency analysis. However, it
requires considerably more data and more sophisticated mathematical analysis. Therefore, a bivariate distribution is the most
common method for modeling these extreme events. The return periods for a bivariate distribution can be defined using either
separate single random variables or two joint random variables. In the latter case, the return periods can be defined using
one random variable equaling or exceeding a certain magnitude and/or another random variable equaling or exceeding another
magnitude or the conditional return periods of one random variable given another random variable equaling or exceeding a certain
magnitude. In this study, the bivariate extreme value distribution with the Gumbel marginal distributions is used to model
extreme flood events characterized by flood volume and flood peak. The proposed methodology is applied to the recorded daily
streamflow from Ichu of the Pachang River located in Southern Taiwan. The results show a good agreement between the theoretical
models and observed flood data.
The author wishes to thank the two anonymous reviewers for their constructive comments that improving the quality of this
work. 相似文献
19.
ABSTRACTFollowing the June 2013 disaster in the Uttarakhand Himalayas, many discussions are ongoing with regard to how climate change is seeking revenge on mankind by endowing us with disasters! The event was mostly linked with the occurrence of an extreme event due to climate change. In view of this, an attempt has been made in this paper to analyse the extreme rainfall events experienced by the Uttarakhand during 1901–2013 using more than 100 stations’ daily rainfall data. The study revealed that during the 113-year period, the highest numbers of extreme events were recorded during the decade 1961–1970, and to some extent in the decade 1981–1990. Thereafter, there is a decrease in extreme rainfall events. The comparative study of extreme events prior to 1901 showed that on 17–18 September 1880, a rainstorm which occurred in close vicinity to Uttarakhand caused serious floods and damage to lives and properties. The extreme rainfall recorded by some stations during this unprecedented rainstorm has not been surpassed to date. 相似文献
20.
AbstractThis paper focuses on a regionalization attempt to partly solve data limitation problems in statistical analysis of high flows to derive discharge–duration–frequency (QDF) relationships. The analysis is based on 24 selected catchments in the Lake Victoria Basin (LVB) in East Africa. Characteristics of the theoretical QDF relationships were parameterized to capture their slopes of extreme value distributions (evd), tail behaviour and scaling measures. To enable QDF estimates to be obtained for ungauged catchments, interdependence relationships between the QDF parameters were identified, and regional regression models were developed to explain the regional difference in these parameters from physiographic characteristics. In validation of the regression models, from the lowest (5 years) to the highest (25 years) return periods considered, the percentage bias in the QDF estimates ranged from –2% for the 5-year return period to 27% for 25-year return period.
Editor D. Koutsoyiannis 相似文献