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Flood Frequency Analysis (flood + frequency_analysis)
Selected AbstractsEvidence for Changing Flood Risk in New England Since the Late 20th Century,JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, Issue 2 2009Mathias J. Collins Abstract:, Long-term flow records for watersheds with minimal human influence have shown trends in recent decades toward increasing streamflow at regional and national scales, especially for low flow quantiles like the annual minimum and annual median flows. Trends for high flow quantiles are less clear, despite recent research showing increased precipitation in the conterminous United States over the last century that has been brought about primarily by an increased frequency and intensity of events in the upper 10th percentile of the daily precipitation distribution , particularly in the Northeast. This study investigates trends in 28 long-term annual flood series for New England watersheds with dominantly natural streamflow. The flood series are an average of 75 years in length and are continuous through 2006. Twenty-five series show upward trends via the nonparametric Mann-Kendall test, 40% (10) of which are statistically significant (p < 0.1). Moreover, an average standardized departures series for 23 of the study gages indicates that increasing flood magnitudes in New England occurred as a step change around 1970. The timing of this is broadly synchronous with a phase change in the low frequency variability of the North Atlantic Oscillation, a prominent upper atmospheric circulation pattern that is known to effect climate variability along the United States east coast. Identifiable hydroclimatic shifts should be considered when the affected flow records are used for flood frequency analyses. Special treatment of the flood series can improve the analyses and provide better estimates of flood magnitudes and frequencies under the prevailing hydroclimatic condition. [source] Multifractal detrended fluctuation analysis of streamflow series of the Yangtze River basin, ChinaHYDROLOGICAL PROCESSES, Issue 26 2008Qiang Zhang Abstract 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. [source] Downscaling of global climate models for flood frequency analysis: where are we now?HYDROLOGICAL PROCESSES, Issue 6 2002Christel Prudhomme Abstract The issues of downscaling the results from global climate models (GCMs) to a scale relevant for hydrological impact studies are examined. GCM outputs, typically at a spatial resolution of around 3° latitude and 4° longitude, are currently not considered reliable at time scales shorter than 1 month. Continuous rainfall-runoff modelling for flood regime assessment requires input at the daily or even hourly time-step. A review of the different methodologies suggested in the literature to downscale GCM results at smaller spatial and temporal resolutions is presented. The methods, from simple interpolation to more sophisticated dynamical modelling, through multiple regression and weather generators, are, however, mostly based directly on GCM outputs, sometimes at daily time-step. The approach adopted is a simple, empirical methodology based on modelled monthly changes from the HadCM2 greenhouse gases experiment for the time horizon 2050s. Three daily rainfall scenarios are derived from the same set of monthly changes, representing different possible changes in the rainfall regime. The first scenario represents an increase of the occurrence of frontal systems, corresponding to a decrease in the rainfall intensity; the second corresponds to an increase in convective storm-type rainfall, characterized by extreme events with higher intensity; the third one assumes an increase in the monthly rainfall without any change in rainfall variability. A continuous daily rainfall-runoff model, calibrated for the Severn catchment, was used to generate daily flow series for the 1961,90 baseline period and the 2050s, and a peaks-over-threshold analysis was undertaken to produce flood frequency distributions for the two time horizons. Though the three scenarios lead to an increase in the magnitude and the frequency of the extreme flood events, the impact is strongly influenced by the type of daily rainfall scenario applied. We conclude that if the next generation of GCMs produce more reliable rainfall variance estimates, then more appropriate ways of deriving rainfall scenarios could be developed using weather generators rather than empirical methods. Copyright © 2002 John Wiley & Sons, Ltd. [source] Bivariate flood frequency analysis: Part 1.JOURNAL OF FLOOD RISK MANAGEMENT, Issue 4 2008Determination of marginals by parametric, nonparametric techniques Abstract In flood frequency analysis, a flood event is mainly characterized by peak flow, volume and duration. These three variables or characteristics of floods are random in nature and mutually correlated. In this article, an effort is made to find out appropriate marginal distribution of the flood characteristics considering a set of parametric and nonparametric distributions, and further mathematically model the correlated nature among them. A set of parametric distribution functions and nonparametric methods based on kernel density estimation and orthonormal series are used to determine the marginal distribution functions for peak flow, volume and duration. In conventional methods of flood frequency analysis, the marginal distribution functions of peak flow, volume and duration are assumed to follow some specific parametric distribution function. The present work performs a better selection of marginal distribution functions for flood characteristics as both parametric and nonparametric estimation procedures are extensively followed. The methodology is demonstrated with 70-year stream flow data of Red River at Grand Forks of North Dakota, USA. [source] | ||||||||||