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1.
Abstract

Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area.

Editor Z.W. Kundzewicz; Associate editor K. Hamed

Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294.  相似文献   

2.
Widespread major flood events in both the UK and Europe over the last decade have focussed attention on perceived increases in rainfall intensities. The changing magnitude of such events may have significant impacts upon many sectors, particularly those associated with flooding, water resources and the insurance industry. Here, two methods are used to assess the performance of the HadRM3H model in the simulation of UK extreme rainfall: regional frequency analysis and individual grid box analysis. Both methods use L-moments to derive extreme value distributions of rainfall for 1-, 2-, 5- and 10-day events for both observed data from 204 sites across the UK (1961–1990) and gridded 50 km by 50 km data from the control climate integration of HadRM3H. Despite differences in spatial resolution between the observed and modelled data, HadRM3H provides a good representation of extreme rainfall at return periods of up to 50 years in most parts of the UK. Although the east–west rainfall gradient tends to be exaggerated, leading to some overestimation of extremes in high elevation western areas and an underestimation in eastern ‘rain shadowed’ regions, this suggests that the regional climate model will also have skill in predicting how rainfall extremes might change under enhanced greenhouse conditions.  相似文献   

3.
Abstract

Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding events that have exceeded existing historical estimates of infrastructure design rainfall intensity–duration–frequency (IDF) values. These recent events and the limited number of short-duration recording raingauges have prompted the need to research the climatology of heavy rainfall events within the study area, review the existing design IDF methodologies, and evaluate alternative approaches to traditional point-based heavy rainfall IDF curves, such as regional IDF design values. The use of additional data and the regional frequency analysis methodology were explored for the study area, with the objective of validating identified clusters or homogeneous regions of extreme rainfall amounts through Ward's method. As the results illustrate, nine homogeneous regions were identified in Southern Ontario using the annual maximum series (AMS) for daily and 24-h rainfall data from climate and rate-of-rainfall or tipping bucket raingauge (TBRG) stations, respectively. In most cases, the generalized extreme value and logistic distributions were identified as the statistical distributions that provide the best fit for the 24-h and sub-daily rainfall data in the study area. A connection was observed between extreme rainfall variability, temporal scale of heavy rainfall events and location of each homogeneous region. Moreover, the analysis indicated that scaling factors cannot be used reliably to estimate sub-daily and sub-hourly values from 24- and 1-h data in Southern Ontario.

Citation Paixao, E., Auld, H., Mirza, M.M.Q., Klaassen, J. & Shephard, M.W. (2011) Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada. Hydrol. Sci. J. 56(7), 1067–1089.  相似文献   

4.
Using a rainfall stochastic generator to detect trends in extreme rainfall   总被引：4，自引：3，他引：1  
An original approach is proposed to estimate the impacts of climate change on extreme events using an hourly rainfall stochastic generator. The considered generator relies on three parameters. These parameters are estimated by average, not by extreme, values of daily climatic characteristics. Since climate changes should result in parameters instability in time, the paper focuses on testing the presence of linear trends in the generator parameters. Maximum likelihood tests are used under a Poisson–Pareto-Peak-Over-Threshold model. A general regionalization procedure is also proposed which offers the possibility to work on both local and regional scales. From the daily information of 139 rain gauge stations between 1960 and 2003, changes in heavy precipitations in France and their impacts on quantile predictions are investigated. It appears that significant changes occur mainly between December and May for the rainfall occurrence which increased during the four last decades, except in the Mediterranean area. Using the trend estimates, one can deduced that these changes, up to now, do not affect quantile estimations.  相似文献   

5.
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   

6.
Heavy rainfall events during the fall season are causing extended damages in Mediterranean catchments. A peaks‐over‐threshold model is developed for the extreme daily areal rainfall occurrence and magnitude in fall over six catchments in Southern France. The main driver of the heavy rainfall events observed in this region is the humidity flux (FHUM) from the Mediterranean Sea. Reanalysis data are used to compute the daily FHUM during the period 1958–2008, to be included as a covariate in the model parameters. Results indicate that the introduction of FHUM as a covariate can improve the modelling of extreme areal precipitation. The seasonal average of FHUM can improve the modelling of the seasonal occurrences of heavy rainfall events, whereas daily FHUM values can improve the modelling of the events magnitudes. In addition, an ensemble of simulations produced by five different general circulation models are considered to compute FHUM in future climate with the emission scenario A1B and hence to evaluate the effect of climate change on the heavy rainfall distribution in the selected catchments. This ensemble of climate models allows the evaluation of the uncertainties in climate projections. By comparison to the reference period 1960–1990, all models project an amplification of the mean seasonal FHUM from the Mediterranean Sea for the projection period 2070–2099, on average by +22%. This increase in FHUM leads to an increase in the number of heavy rainfall events, from an average of 2.55 events during the fall season in present climate to 3.57 events projected for the period 2070–2099. However, the projected changes have limited effects on the magnitude of extreme events, with only a 5% increase in the median of the 100‐year quantiles. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

7.
Analyses of the spatio-temporal variability of precipitation extremes defined by eleven extreme precipitation indices in Shandong were conducted by utilizing the methods of linear regression, ensemble empirical mode decomposition (EEMD) and Mann–Kendall test. The results revealed that statistically significant decreasing trends existed for almost all extreme precipitation indices except for the consecutive dry days (CDD) and simple daily intensity index. A periodicity of 10–15 years for precipitation extremes is detected by EEMD analysis. Greatest 5-day total rainfall (RX5day), very wet days (R95p) and annual total wet-day precipitation (PRCPTOT) experienced decreasing trends in the region stretching from the southeast coast to the west, while the spatial distribution of the decreasing trends for other indices was more complicated. Moreover, the frequency of occurrence in precipitation extremes at Changdao station, surrounded by the sea in the northeast region, increased in contrast to surrounding stations. This may suggest a possible effect from the local marine environment on extreme precipitation. In addition, the stations with statistically significant positive trends for CDD were mainly located in mid-west Shandong and along the southeast coast, where the extreme precipitation and total rainfall were, on the contrary, characterized by decreasing trends. These results indicate that drought or severe drought events have become more frequent in those regions. Analysis of large-scale atmospheric circulation changes indicates that a strengthening anticyclonic circulation and increasing geopotential height as well as decreasing strength of monsoonal flow in recent decades may have contributed to the variations in extreme precipitation in Shandong.  相似文献   

8.
Extreme rainfall events are of particular importance due to their severe impacts on the economy, the environment and the society. Characterization and quantification of extremes and their spatial dependence structure may lead to a better understanding of extreme events. An important concept in statistical modeling is the tail dependence coefficient (TDC) that describes the degree of association between concurrent rainfall extremes at different locations. Accurate knowledge of the spatial characteristics of the TDC can help improve on the existing models of the occurrence probability of extreme storms. In this study, efficient estimation of the TDC in rainfall is investigated using a dense network of rain gauges located in south Louisiana, USA. The inter-gauge distances in this network range from about 1 km to 9 km. Four different nonparametric TDC estimators are implemented on samples of the rain gauge data and their advantages and disadvantages are discussed. Three averaging time-scales are considered: 1 h, 2 h and 3 h. The results indicate that a significant tail dependency may exist that cannot be ignored for realistic modeling of multivariate rainfall fields. Presence of a strong dependence among extremes contradicts with the assumption of joint normality, commonly used in hydrologic applications.  相似文献   

9.
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10.
The correct identification of homogeneous areas in regional rainfall frequency analysis is fundamental to ensure the best selection of the probability distribution and the regional model which produce low bias and low root mean square error of quantiles estimation. In an attempt at rainfall spatial homogeneity, the paper explores a new approach that is based on meteo-climatic information. The results are verified ex-post using standard homogeneity tests applied to the annual maximum daily rainfall series. The first step of the proposed procedure selects two different types of homogeneous large regions: convective macro-regions, which contain high values of the Convective Available Potential Energy index, normally associated with convective rainfall events, and stratiform macro-regions, which are characterized by low values of the Q vector Divergence index, associated with dynamic instability and stratiform precipitation. These macro-regions are identified using Hot Spot Analysis to emphasize clusters of extreme values of the indexes. In the second step, inside each identified macro-region, homogeneous sub-regions are found using kriging interpolation on the mean direction of the Vertically Integrated Moisture Flux. To check the proposed procedure, two detailed examples of homogeneous sub-regions are examined.  相似文献   

11.
ABSTRACT

A rainfall–runoff model was employed to identify four major flood-generating processes corresponding to flood events identified from daily discharge data from 614 stations across Europe in the period 1961–2010: long-rain, short-rain, snowmelt, and rain-on-dry-soil flood events. Trend analyses were performed on the frequency of occurrence of each of the flood types continentally and in five geographical regions of Europe. Continentally, the annual frequency of flood events did not show a significant change over the investigation period. However, the frequency of both winter and summer long-rain events increased significantly, while that of summer snowmelt events decreased significantly. Regionally, the frequency of winter short and long-rain events increased significantly in Western Europe, while the frequency of summer snowmelt and short-rain events decreased in Northern Europe. The frequency of summer snowmelt events in Eastern Europe and winter short-rain events in Southern Europe showed a declining trend.  相似文献   

12.
The dependence between variables plays a central role in multivariate extremes. In this paper, spatial dependence of Madeira Island's rainfall data is addressed within an extreme value copula approach through an analysis of maximum annual data. The impact of altitude, slope orientation, distance between rain gauge stations and distance from the stations to the sea are investigated for two different periods of time. The results obtained highlight the influence of the island's complex topography on the spatial distribution of extreme rainfall in Madeira Island.  相似文献   

13.
《水文科学杂志》2013,58(3):456-473
Abstract

The main objective of this study is to compare the seasonality of selected precipitation and runoff characteristics in Austria and Slovakia. Monthly seasonality indices are analysed to interpret the long-term climatic behaviour, while the seasonality of extremes is analysed to understand flood occurrence. The analysis is based on mean monthly precipitation data at 555 (Austria) and 202 (Slovakia) stations, annual maximum daily precipitation at 520 (Austria) and 56 (Slovakia) stations, and mean monthly runoff and annual maximum floods at 258 (Austria) and 85 (Slovakia) gauging stations. The results suggest that the seasonality of the selected hydrological characteristics is an important indicator of flood processes, but varies considerably in space. The seasonality of extreme flood events and, hence flood processes, tends to change with the flood magnitude. This change is more pronounced in the lowland and hilly regions than it is in the mountains. Both in Austria and Slovakia, decades of flood seasonality exist.  相似文献   

14.
ABSTRACT

Following 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   

15.
Abstract

There 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   

16.
Abstract

A new technique is developed for identifying groups for regional flood frequency analysis. The technique uses a clustering algorithm as a starting point for partitioning the collection of catchments. The groups formed using the clustering algorithm are subsequently revised to improve the regional characteristics based on three requirements that are defined for effective groups. The result is overlapping groups that can be used to estimate extreme flow quantiles for gauged or ungauged catchments. The technique is applied to a collection of catchments from India and the results indicate that regions with the desired characteristics can be identified using the technique. The use of the groups for estimating extreme flow quantiles is demonstrated for three example sites.  相似文献   

17.
ABSTRACT

Discharge observations and reliable rainfall forecasts are essential for flood prediction but their availability and accuracy are often limited. However, even scarce data may still allow adequate flood forecasts to be made. Here, we explored how far using limited discharge calibration data and uncertain forcing data would affect the performance of a bucket-type hydrological model for simulating floods in a tropical basin. Three events above thresholds with a high and a low frequency of occurrence were used in calibration and 81 rainfall scenarios with different degrees of uncertainty were used as input to assess their effects on flood predictions. Relatively similar model performance was found when using calibrated parameters based on a few events above different thresholds. Flood predictions were sensitive to rainfall errors, but those related to volume had a larger impact. The results of this study indicate that a limited number of events can be useful for predicting floods given uncertain rainfall forecasts.  相似文献   

18.
The fact that rainfall data are usually more abundant and more readily regionalized than streamflow data has motivated hydrologists to conceive methods that incorporate the hydrometeorologial information into flood frequency analyses. Some of them, particularly those derived from the French GRADEX method, involve assumptions concerning the relationship between extreme rainfall and flood volumes, under some distributional restrictions. In particular, for rainfall probability distributions exhibiting exponential-like upper tails, it is possible to derive the shape and scale of the probability distribution of flood volumes by hypothesizing the basic properties of such a relationship, under rare and/or extreme conditions. This paper focuses on a parametric mathematical model for the relationship between rare and extreme rainfall and flood volumes under exponentially-tailed distributions. The model is analyzed and fitted to rare and extreme events derived from hydrological simulation of long stochastically-generated synthetic series of rainfall and evaporation for the Indaiá River basin, located in south-central Brazil. The paper also provides a sensitivity analysis of the model parameters in order to better understand flood events under rare and extreme conditions. By working with hydrologically plausible hypothetical events, the modeling approach proved to be a useful way to explore extraordinary rainfall and flood events. The results from this exploratory analysis provide grounds to derive some conclusions regarding the relative positions of the upper tails of the probability distributions of rainfall and flood volumes.  相似文献   

19.
In Australia, multidecadal periods of floods and droughts have major economic consequences. Due to the short duration of Australian instrumental precipitation records, it is difficult to determine the patterns of these multidecadal periods. Proxy records can be used to create long‐term rainfall reconstructions for regions that are lacking instrumental data. However, the spatial extent over which single‐site proxy records can be applied is poorly understood. Southeast Queensland (SEQ) is an area where tree rings can be used to reconstruct long‐term rainfall patterns, but their regional representation is unknown. In this study, the spatial variability in rainfall across SEQ is investigated from 1908 to 2007 using 140 instrumental rainfall stations. Pearson correlation analysis between stations is used to create groups at the r = 0.80, 0.85, and 0.90 correlation levels, and then annual deviations from the mean are determined. These patterns indicate that rainfall is not uniform across SEQ but can be broken into 2 main spatially consistent groups. Each of these groups is broken down into several subgroups with higher correlation levels. Long‐term streamflow records are found to be correlated to rainfall patterns local to the streamflow stations, indicating that analysis of extreme events should consider spatial precipitation variability. Finally, the only currently available proxy rainfall reconstruction for the region, a 140‐year Toona ciliata tree ring width record from Lamington National Park, is compared to rainfall groups at different correlation levels across all of SEQ. The correlation between the reconstruction and the rainfall station groupings is best for the groups within which the tree‐ring record is spatially located, and this correlation improves as rainfall group correlation increases. Correlation is nearly nonexistent for groupings located at a distance from the tree‐ring site. These results demonstrate the importance of assessing the spatial variability of precipitation so that the spatial applicability of proxy records can be assessed.  相似文献   

20.
Regional models of extreme rainfall must address the spatial variability induced by orographic obstacles. However, the proper detection of orographic effects often depends on the availability of a well‐designed rain gauge network. The aim of this study is to investigate a new method for identifying and characterizing the effects of orography on the spatial structure of extreme rainfall at the regional scale, including where rainfall data are lacking or fail to describe rainfall features thoroughly. We analyse the annual maxima of daily rainfall data in the Campania region, an orographically complex region in Southern Italy, and introduce a statistical procedure to identify spatial outliers in a low order statistic (namely the mean). The locations of these outliers are then compared with a pattern of orographic objects that has been a priori identified through the application of an automatic geomorphological procedure. The results show a direct and clear link between a particular set of orographic objects and a local increase in the spatial variability of extreme rainfall. This analysis allowed us to objectively identify areas where orography produces enhanced variability in extreme rainfall. It has direct implications for rain gauge network design criteria and has led to promising developments in the regional analysis of extreme rainfall. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

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