Rainfall flood hazard at nuclear power plants in India

Flood hazard evaluation is an important input for Nuclear Power Plants external events safety studies. In the present study, flood hazard at various nuclear sites in India due to rainfall has been evaluated. Hazard estimation is a statistical procedure by which rainfall intensity versus occurrence frequency is estimated from historical records of rainfall data and extrapolated with asymptotic extreme value distribution. Rainfall data needed for flood hazard assessment are daily annual maximum rainfall (24?h data). The observed data points have been fitted using Gumbel, power law and exponential distribution, and return period has been estimated. To study the stationarity of rainfall data, a moving window estimate of the parameters has been performed. The rainfall pattern is stationary in both coastal and inland regions over the period of observation. The coastal regions show intense rainfall and higher variability than inland regions. Based on the plant layout, catchment area and drainage capacity, the prototype fast breeder reactor (PFBR) site is unlikely to be flooded.     

20世纪暴雨和洪水极值的年代际变化

利用20世纪100年(特别是后50年)2万多个雨量站和175个大中河流水文站的实测和调查雨量和流量资料,分析了中国大陆(外流区)暴雨和洪水极值的年代际变化,其中包括长期站暴雨的年代均值变化、20世纪50年点雨量极值的前后期平均值对比、最大点雨量发生年代分布和特大洪峰流量的年代分布。分别就5种历时、不同地区的暴雨洪水极值随年代的变化作了分析,揭示了变化的事实,计算了多项年代比率,探讨了影响因子。     

Comparison of probability distributions in extreme value analysis of rainfall and temperature data

Estimation of rainfall and temperature for a desired return period is a prerequisite for planning, design and operation of various hydraulic structures and for evaluation of technical and engineering appraisal of large infrastructure projects. This can be computed through Extreme Value Analysis (EVA) by fitting probability distributions to the annual series of 1-day maximum rainfall, maximum and minimum temperature. This paper details the study on adoption of Extreme Value Type-1, Extreme Value Type-2, 2-parameter Log Normal and Log Pearson Type-3 (LP3) probability distributions in EVA of rainfall and temperature for Hissar. Based on the applicability, standard parameter estimation procedures such as method of moments, maximum likelihood method (MLM) and order statistics approach are used for determination of parameters of distributions. The adequacy on fitting of probability distributions used in EVA of rainfall and temperature is evaluated by goodness-of-fit (GoF) tests, viz. Anderson–Darling and Kolmogorov–Smirnov and diagnostic test using D-index. The GoF and diagnostic tests results suggest the LP3 (MLM) is better suited amongst four probability distributions adopted in EVA of rainfall and temperature for Hissar.     

Regional Rainfall Depth–Duration–Frequency Equations for an Alpine Region

In this paper the scaling hypotheses are applied to annual maximum series of rainfall depth for different rainfall duration to derive the depth–duration–frequency (DDF) curve. It is shown that, based on the empirically observed scaling properties of rainfall and some general assumptions about the cumulative distribution function for the annual maximum of the rainfall depth, it is possible to derive a simple DDF relationship. This general framework provides a basis for the generation of maps that can be used to infer DDF curves at any point of a particular area. Data from a dense raingauge network in a mountainous region in north-eastern Italy (the Trentino Province) are used to clarify the methodology for the construction and regionalization of the DDF relationship. The geographical variation of short-duration (i.e., less than 60 xmin) rainfall extremes is also evaluated by using the same framework. It is found that depth–duration ratios, defined as the ratios of the t-min to the 60-min rainfall depths of the same return period, may be considered independent of return period and geographical location for any storm duration less than 60 min.     

Statistical analysis of the largest possible earthquake magnitudes on the Ecuadorian coast for selected return periods

ABSTRACT

In this work, we have studied the largest earthquake magnitudes on the Ecuadorian coast by using the principles of Extreme Value Analysis based on its two approaches: Block Maxima and Peaks-over-Threshold. First, before modelling the recorded earthquakes, the K-means clustering technique was applied to determine a classification according to the level of magnitude of the earthquakes. Then, models based on the Extreme Value theory of earthquake magnitudes were developed for each of the four clusters that were found, and finally, the best-fitted models were those known as Fréchet and Gumbel ones. The zone with the greatest earthquake magnitudes on the Ecuadorian coast is located between the north of the province of Manabí and the south of the province of Esmeraldas, with a return period of 50 years for an earthquake with magnitude greater than 7.7 M_W.     

Regional frequency analysis of extreme precipitation and its spatio-temporal characteristics in the Huai River Basin, China

With the increasing exposure of populations and economy to natural hazards, the spatio-temporal characteristics of extreme rainfall remain a key subject of study. Based on annual maximum rainfall (AM) and peaks over threshold rainfall series at 30 meteorological stations during 1960–2011 in the Huai River Basin (HRB), spatio-temporal characteristics of extreme rainfall are analyzed through regional frequency analysis method using L-moments. The accuracy and uncertainty analysis of quantile estimations are also carried out, and the regional and at-site frequency analyses are compared. Results indicate the following: (1) During 1960–2011, AM precipitation at 20 stations in the HRB shows an increasing trend, while at the other 10 stations, it shows a decreasing trend. And both the increased and decreased trends are not significant. (2) The HRB can be categorized into three homogeneous regions via cluster analysis. For both at-site and regional frequency analyses, the root mean square error values increase with the increase in return periods. The estimations are reliable enough for the return periods of less than 100 years. The quantile estimates of large return period from regional frequency analysis are more accurate and have smaller uncertainty than those from at-site frequency analysis. (3) Extreme precipitation in the HRB concentrates in the upstream of the Huai River and YiShuSi water system in the east of the HRB. Generally, the area with extreme precipitation, especially the upper reaches of the Huai River and Yimeng Mountain areas, also has large standard variations of extreme precipitation, which will increase the risk of natural hazards.     

降雨重现期及其用于滑坡概率分析的探讨

极端气候条件往往会诱发各种地质灾害,而降雨型滑坡的发生则与极值降雨关系密切。为了有效预防和控制汛期滑坡灾害的发生,定量评估滑坡灾害造成的人员与经济风险,讨论了汛期极值降雨条件下滑坡概率的分析方法。利用Gumbel极值分布理论,以三峡库区巴东县1990~2006年日降雨量为基础资料,采用统计分析方法,求取研究区在汛期(6月中旬至9月)最大一次连续降雨量、多日累积最大降雨量的极值及其分布曲线; 在此基础上,以研究区一个滑坡实例为对象,综合采用渗流模拟、稳定性分析和基于蒙特卡罗的滑坡概率分析方法,讨论了降雨极值及其重现期成果分别在降雨新生型滑坡和降雨复活型滑坡概率分析中的应用思路与方法。结果表明,随着重现期的增加,一次降雨过程的降雨量也增加; 随着降雨日数的增加,具有不同重现期降雨事件的累积降雨量均会增加,且重现期越长,累积降雨量值会越大; 降雨极值曲线分别应用于降雨新生型和降雨复活型滑坡概率分析的思路是可行并有效的。     

中国点暴雨量极值的分布

暴雨极值是大型水利工程设计洪水重要依据之一。本文根据中国暴雨资料讨论了点暴雨量极值的主要内容,包括最大24小时点暴雨量、各历时最大点雨量、暴雨极值的季节变化;给出了大量最大点雨量记录图表;探讨了全国暴雨极值的地域分布规律及其影响因素。     

Impact of climate change on extreme rainfall events and flood risk in India

The occurrence of exceptionally heavy rainfall events and associated flash floods in many areas during recent years motivate us to study long-term changes in extreme rainfall over India. The analysis of the frequency of rainy days, rain days and heavy rainfall days as well as one-day extreme rainfall and return period has been carried out in this study to observe the impact of climate change on extreme rainfall events and flood risk in India. The frequency of heavy rainfall events are decreasing in major parts of central and north India while they are increasing in peninsular, east and north east India. The study tries to bring out some of the interesting findings which are very useful for hydrological planning and disaster managements. Extreme rainfall and flood risk are increasing significantly in the country except some parts of central India.     

A probabilistic approach for estimating return period of extreme annual rainfall in different cities of Punjab

Multi-day rainfall events are an important cause of recent severe flooding in Pakistan, and any change in the magnitude of such events may have severe impact upon urban structures such as dams, urban drainage systems, and flood. This article uses statistical distributions to define extremes of annual rainfall of different cities of Punjab (Lahore, Murree, Sialkot, and Jhelum) with given return periods. Our calculations suggest that general extreme value is the best-fitted distribution for the extreme annual rainfall of different cities of Punjab. Our calculations show that different cities of Punjab have 5 years return period for receiving more than 100 mm daily rainfall. While they have 30 years return period for receiving more than 200 mm daily rainfall. This asks for construction of new dams in Pakistan.     

Maximum daily rainfall in South Korea

Annual maxima of daily rainfall for the years 1961–2001 are modeled for five locations in South Korea (chosen to give a good geographical representation of the country). The generalized extreme value distribution is fitted to data from each location to describe the extremes of rainfall and to predict its future behavior. We find evidence to suggest that the Gumbel distribution provides the most reasonable model for four of the five locations considered. We explore the possibility of trends in the data but find no evidence suggesting trends. We derive estimates of 10, 50, 100, 1000, 5000, 10,000, 50,000 and 100,000 year return levels for daily rainfall and describe how they vary with the locations. This paper provides the first application of extreme value distributions to rainfall data from South Korea.     

Rainfall variability and indices of extreme rainfall-analysis and perception study for two stations over Central Himalaya,India

The analysis of rainfall pattern and indices of extreme rainfall events is performed for two meteorological stations located in the Central Himalayan Region which is highly vulnerable to rain-induced hazards. The records of these rain-induced disasters suggest that such events are generally observed in later part of monsoon season, when soil is saturated after monsoon rains. An attempt is made here to test trends of 19 different extreme rainfall indices that have been widely used in the literature, using daily rainfall data for two urban centres (Nainital and Almora) over the period 1992–2005. We have used statistical tools such as Sen’s method and Mann–Kendall test for detection of trend in annual rainfall, monsoon rainfall, number of rainy days and 1-day extreme rainfall. Principal component analysis gives the correlation between different extreme rainfall indices. Time series of principal components are representing the trends of extreme indices, their variation and interrelation between different indices. The perception study conducted in the same sites indicates that extreme rainfall events and change in rainfall amount and timing are well perceived by the local people.     

Variability and trends of extreme dry and wet seasonal precipitation in Argentina. A retrospective analysis

The variability in seasonal mean and extreme precipitation is analyzed for several regions of Argentina to the north of 39º S, using long-term monthly time series data which expand from 1860 to 2006. The selected locations can be considered as representative of different climatic regions. This work focuses on the analysis of monthly rainfall distribution, significant seasonal trends, changes in variance and extreme monthly values, in order to establish the magnitude of the seasonal climatic rainfall variability through time for central Argentina. A 40-yr moving window was employed in order to analyze seasonal variability of rainfall extremes. Extremes were computed for different probability levels of a theoretical distribution function over/below the 80th/20th percentile. The gamma distribution was selected among five other theoretical distributions, and the scale and shape parameters were computed using the maximum likelihood estimation (MLE) and the bootstrap method for 1000 resample data sets, as well. Trend analysis was performed for each window on winter and summer means and tested for significance. The use of a moving window allowed detecting the window of maximum absolute values for the trends. Research results show significant temporal shifts in seasonal rainfall distribution and return values (RV) that were computed for different frequencies (once every five, 10 and 20 years). Generally, summer precipitation extremes have become wetter for the whole region. Rainfall amounts for summer wet/dry extremes (W/D) corresponding to the 90th (for W) and 10th (for D) percentiles were subjected to significant increase, but depending on the geographical area this effect spreads slightly differently over records of years. A common-for-all-stations period of such summer increase trend in extreme values spans from the window 1921-1960 to the last window analyzed: 1967-2006. This behavior was not observed for north and west Argentina during winter, except for the region represented by Bahía Blanca, where the 10% D extreme has increased throughout the study period.     

The Influence of the North Atlantic Oscillation on Rainfall Triggering of Landslides near Lisbon

The majority of landsliding episodes in the area north of Lisbon are associated with rainfall events of short (less than 5 days) medium (5–20 days) or long duration (more than 20 days). The precipitation regime in Portugal is highly irregular, with large differences between wet and dry years. We have assessed the impact of the North Atlantic Oscillation (NAO) on both the winter precipitation and the timing and magnitude of associated landslide events. Results show that the large inter-annual variability of winter precipitation is largely modulated by the NAO mode. The precipitation composite corresponding to high NAO index presents a considerable lower median value (47 mm/month) than the corresponding low NAO index class (134 mm/month). The entire precipitation distribution associated with the low NAO index composite encompasses a wider range of values than the corresponding high NAO index composite. This non-linear behavior is reflected in the probability of occurrence of a very wet month (precipitation above the 90% percentile) that is just 1% for the positive NAO class and 23% for low NAO index months. Results for the low NAO class are crucial because these months are more likely associated with long-lasting rainfall episodes responsible for large landslide events. This is confirmed by the application of a 3-month moving average to both NAO index and precipitation time series. This procedure allowed the identification of many months with landslide activity as being characterized by negative average values of the NAO index and high values of average precipitation (above 100 mm/month). Finally, using daily data we have computed the return periods associated with the entire set of landslide episodes and, based on these results, obtained a strong linear relationship between critical cumulative rainfall and the corresponding critical rainfall event duration.     

Hydrologic behavior and flood probability for selected arid basins in Makkah area, western Saudi Arabia

In arid regions, flash floods often occur as a consequence of excessive rainfall. Occasionally causing major loss of property and life, floods are large events of relatively short duration. Makkah area in western Saudi Arabia is characterized by high rainfall intensity that leads to flash floods. This study quantifies the hydrological characteristics and flood probability of some major wadis in western Saudi Arabia, including Na’man, Fatimah, and Usfan. Flood responses in these wadis vary due to the nature and rainfall distribution within these wadis. Rainfall frequency analysis was performed using selected annual maximums of 24-h rainfall from eight stations located in the area. Two of the most applied methods of statistical distribution, Gumbel’s extreme value distribution and log Pearson type III distribution, were applied to maximum daily rainfall data over 26 to 40 years. The Gumbel’s model was found to be the best fitting model for identifying and predicting future rainfall occurrence. Rainfall estimations from different return periods were identified. Probable maximum floods of the major wadis studied were also estimated for different return periods, which were extrapolated from the probable maximum precipitation.     

Flood frequency analysis of river swat using Log Pearson type 3, Generalized Extreme Value,Normal, and Gumbel Max distribution methods

In Pakistan, floods are among the most devastating and recurring natural hazards. Flood hazard assessment requires flood event magnitude and probability of occurrence. Flood frequency analysis is the most common technique used for the at-site estimation of flood recurrence magnitude. This paper evaluates four most commonly used distribution methods, i.e., Generalized Extreme Value (GEV), Log Pearson 3 (LP3), Gumbel Max, and Normal for the flood frequency and estimation of flood recurrence. Different hydrological stations data namely Khwazakhela, Chakdarra, Panjkora, and Munda Headwork located at Swat river was taken from Provincial Irrigation Department, Khyber Pakhtunkhwa. The analysis is done for 5-, 10-, 25-, 50-, and 100-year return periods by using annual maximum discharge data from 1980 to 2016 (37 yr). Three goodness-of-fit tests were applied to the fitted distributions, i.e., Kolmogorov–Smirnov, Anderson–Darling, and Chi-squared at 5% significance level. Results indicate that LP3 and GEV were ranked top two distributions at all locations while Gumbel Max and Normal were the least fitted having rank 3 and 4, respectively. Based on the goodness-of-fit ranking, LP3 was selected for the estimation of flood magnitude and return periods at Khwazakhela. Designed hydrographs based on probabilistic approach and flood 2010 hydrograph are presented for flood simulation.     

推求无资料地区设计洪水的一种方法

在地貌单位线、菲利浦下渗公式和暴雨特征频率分布的基础上,引用产流开始时刻和净雨量的概念,推求不同净雨情况下不产流暴雨事件的概率,从而求得洪峰流量小于和等于给定Q_p值的理论频率分布及其相应的重现期。在贵州和山西应用结果表明,该方法更适用于半干旱地区。由模型验证实例分析了这种理论洪水频率分布模型的应用前景。     

Regional frequency analysis of daily rainfall extremes using L-moments approach

Daily extreme precipitation values are among environmental events with the most disastrous consequences for human society. Information on the magnitudes and frequencies of extreme precipitations is essential for sustainable water resources management, planning for weather-related emergencies, and design of hydraulic structures. In the present study, regional frequency analysis of maximum daily rainfalls was investigated for Golestan province located in the northeastern Iran. This study aimed to find appropriate regional frequency distributions for maximum daily rainfalls and predict the return values of extreme rainfall events (design rainfall depths) for the future. L-moment regionalization procedures coupled with an index rainfall method were applied to maximum rainfall records of 47 stations across the study area. Due to complex geographic and hydro-climatological characteristics of the region, an important research issue focused on breaking down the large area into homogeneous and coherent sub-regions. The study area was divided into five homogeneous regions, based on the cluster analysis of site characteristics and tests for the regional homogeneity. The goodness-of-fit results indicated that the best fitting distribution is different for individual homogeneous regions. The difference may be a result of the distinctive climatic and geographic conditions. The estimated regional quantiles and their accuracy measures produced by Monte Carlo simulations demonstrate that the estimation uncertainty as measured by the RMSE values and 90% error bounds is relatively low when return periods are less than 100 years. But, for higher return periods, rainfall estimates should be treated with caution. More station years, either from longer records or more stations in the regions, would be required for rainfall estimates above T=100 years. It was found from the analyses that, the index rainfall (at-site average maximum rainfall) can be estimated reasonably well as a function of mean annual precipitation in Golestan province. Index rainfalls combined with the regional growth curves, can be used to estimate design rainfalls at ungauged sites. Overall, it was found that cluster analysis together with the L-moments based regional frequency analysis technique could be applied successfully in deriving design rainfall estimates for northeastern Iran. The approach utilized in this study and the findings are of great scientific and practical merit, particularly for the purpose of planning for weather-related emergencies and design of hydraulic engineering structures.     

太湖流域应对特大洪水防洪工程效益模拟

防洪效益评估对防洪工程投资决策与减灾对策制定具有重要意义。建立集成了与太湖流域防洪效益评估相关的系列模型和方法,包括含降雨产流与平原净雨计算的水文分析方法、由河网水动力学模型和平原区域洪水分析模型组成的大尺度水力学模型、综合流域社会经济和淹没因素的洪灾损失评估模型。模拟了太湖流域遇特大洪水的灾害损失,开展了不同防洪工程应对流域性特大洪水减灾效益的预测分析。结果表明：1999年型200年一遇降雨将会给太湖流域造成高达568.29亿元的直接经济损失,外排动力增强30%至100%的防洪效益介于26.69亿元到45.70亿元之间,新建圩区、太浦河拓宽的防洪效益依次减小,而圩区泵排能力增加30%的防洪效益仅为0.65亿元。基于研究成果提出了增设外排泵站、加强圩区科学调度、通过保险分担风险等应对特大洪水的对策措施建议,为太湖流域特大洪水的防治提供支撑和参考。     

Extreme surface and near-bottom currents in the northwest Atlantic

This study presents a methodology for estimating extreme current speeds from numerical model results using extremal analysis techniques. This method is used to estimate the extreme near-surface and near-bottom current speeds of the northwest Atlantic Ocean with 50-year return periods from 17?years of model output. The non-tidal currents produced by a three-dimensional ocean circulation model for the 1988?C2004 period were first used to estimate and map the 17-year return period extreme current speeds at the surface and near the bottom. Extremal analysis techniques (i.e., fitting the annual maxima to the Type I probability distribution) are used to estimate and map the 50-year extreme current speeds. Tidal currents are dominant in some parts of the northwest Atlantic, and a Monte Carlo-based methodology is developed to take into account the fact that large non-tidal extrema may occur at different tidal phases. The inclusion of tidal currents in this way modifies the estimated 50-year extreme current speeds, and this is illustrated along several representative transects and depth profiles. Seasonal variations are examined by calculating the extreme current speeds for fall-winter and spring?Csummer. Finally, the distribution of extreme currents is interpreted taking into account (1) variability about the time-mean current speeds, (2) wind-driven Ekman currents, and (3) flow along isobaths.