A sample reconstruction method based on a modified reservoir index for flood frequency analysis of non-stationary hydrological series

Flood extremes, affected by climate change and intense human activities, exhibit non-stationary characteristics. As a result, the stationarity assumption of traditional flood frequency analysis (FFA) cannot be satisfied. Generally, the impacts of human activities, especially water conservancy projects (i.e., reservoirs), on extreme flood series are much greater than those of climate change; therefore, new FFA methods must be developed to address the non-stationary flood extremes associated with large numbers of reservoirs. In this study, a new sample reconstruction method is proposed to convert the reservoir-influenced annual maximum flow (AMF) series from non-stationary to stationary, thus warranting the feasibility of the traditional FFA approach for non-stationary cases. To be more specifically, a modified reservoir index (MRI(t)) is proposed and the original non-stationary AMF series are converted to stationary series by multiplying by a scalar factor 1/(1 ? MRI(t)), and thus traditional FFA can be adopted. Besides, Bayesian theory was applied to analyze the effect of uncertainty on the designed reconstructed AMF. As an example, the proposed method was applied to observations from Huangzhuang station located on the Hanjiang River. The original AMF observations from Huangzhuang displayed nonstationarity for the continuous construction of reservoirs in the basin. After applying the new method of sample reconstruction, the original AMF observations became stationary, and the designed AMFs were estimated using the reconstructed series and compared with those estimated based on the original observation series. In addition, Bayesian theory is adopted to quantify the uncertainty of designed reconstructed AMF and provide the expectation of the sampling distribution.     

Climate‐informed low‐flow frequency analysis using nonstationary modelling

Stationarity is often assumed for frequency analysis of low flows in water resources management and planning. However, many studies have shown that flow characteristics, particularly the frequency spectrum of extreme hydrologic events, were modified by climate change and human activities. Thus, the conventional frequency analysis that fails to consider the nonstationary characteristics may lead to costly design. The analysis presented in this paper was based on the more than 100 years of daily flow data from the Yichang gauging station 44 km downstream of the Three Gorges Dam. The Mann–Kendall trend test under the scaling hypothesis showed that the annual low flows had a significant monotonic trend, whereas an abrupt change point was identified in 1936 by the Pettitt test. The climate‐informed low‐flow frequency analysis and the divided and combined method were employed to account for the impacts from related climate variables and nonstationarities in annual low flows. Without prior knowledge of the probability density function for the gauging station, six distribution functions including the generalized extreme values (GEV), Pearson Type III, Gumbel, Gamma, Lognormal and Weibull distributions have been tested to find the best fit, in which the local likelihood method is used to estimate the parameters. Analyses show that GEV had the best fit for the observed low flows. This study has also shown that the climate‐informed low‐flow frequency analysis is able to exploit the link between climate indices and low flows, which would account for the dynamic feature for reservoir management and provide more accurate and reliable designs for infrastructure and water supply. Copyright © 2014 John Wiley & Sons, Ltd.     

Quantifying differences between reservoir inflows and dam site floods using frequency and risk analysis methods

Reservoirs are the most important constructions for water resources management and flood control. Great concern has been paid to the effects of reservoir on downstream area and the differences between inflows and dam site floods due to the changes of upstream flow generation and concentration conditions after reservoir’s impoundment. These differences result in inconsistency between inflow quantiles and the reservoir design criteria derived by dam site flood series, which can be a potential risk and must be quantificationally evaluated. In this study, flood frequency analysis (FFA) and flood control risk analysis (FCRA) methods are used with the long reservoir inflow series derived from a multiple inputs and single output model and a copula-based inflow estimation model. The results of FFA and FCRA are compared and the influences on reservoir flood management are also discussed. The Three Gorges Reservoir (TGR) in China is selected as a case study. Results show that the differences between the TGR inflow and dam site floods are significant which result in changes on its flood control risk rates. The mean values of TGR’s annual maximum inflow peak discharge and 3 days flood volume have increased 5.58 and 3.85% than the dam site ones, while declined by 1.82 and 1.72% for the annual maximum 7 and 15 days flood volumes. The flood control risk rates of middle and small flood events are increased while extreme flood events are declined. It is shown that the TGR can satisfy the flood control task under current hydrologic regime and the results can offer references for better management of the TGR.     

To what extent have changes in channel capacity contributed to flood hazard trends in England and Wales?

The frequency of floods has been projected to increase across Europe in the coming decades due to extreme weather events. However, our understanding of how flood frequency is affected by geomorphic changes in river channel capacity remains limited. This paper seeks to quantify the influence of trends in channel capacity on flood hazards. Measuring and predicting the effect of geomorphic changes on freshwater flooding is essential to mitigate the potential effects of major floods through informed planning and response. Hydrometric records from 41 stream gauging stations were used to measure trends in the flood stage (i.e. water surface elevation) frequency above the 1% annual exceedance threshold. The hydrologic and geomorphic components of flood hazard were quantified separately to determine their contribution to the total trend in flood stage frequency. Trends in cross‐sectional flow area and mean flow velocity were also investigated at the same flood stage threshold. Results showed that a 10% decrease (or increase) in the channel capacity would result in an increase (or decrease) in the flood frequency of approximately 1.5 days per year on average across these 41 sites. Widespread increases in the flood hazard frequency were amplified through both hydrologic and geomorphic effects. These findings suggest that overlooking the potential influence of changing channel capacity on flooding may be hazardous. Better understanding and quantifying the influence of geomorphic trends on flood hazard will provide key insight for managers and engineers into the driving mechanisms of fluvial flooding over relatively short timescales. Copyright © 2016 John Wiley & Sons, Ltd.     

Design flood estimation in ungauged catchments and statistical characterization using principal components analysis: application of Gradex method in Upper Moulouya

Design flood estimation in ungauged catchments is of great importance in hydrologic practice especially where there is no available data about streamflow. Except the watershed of Anseghmir who is equipped with a gauge station, all the other watersheds are ungauged catchments. The use of frequency analysis of series of rainfall and streamflow is very important for the characterization of the hydrologic resources of the Upper Moulouya. The region has a semiarid climate that requires a good knowledge of the watershed's potential water to assist policy makers in forecasting extreme events, managing water resources and decision making. The frequency analysis was used to determine the design flood of different return periods. The results obtained are used in Gradex method to estimate the hydrologic variables of each subcatchment of the Upper Moulouya. Once the hydrologic study is completed, a principal components analysis was made to highlight the affinities between the different subcatchments and to deduce the hydrologic and hydrographic parameters that better characterize them. Copyright © 2012 John Wiley & Sons, Ltd.     

Applicability of Wakeby distribution in flood frequency analysis: a case study for eastern Australia

Parametric method of flood frequency analysis (FFA) involves fitting of a probability distribution to the observed flood data at the site of interest. When record length at a given site is relatively longer and flood data exhibits skewness, a distribution having more than three parameters is often used in FFA such as log‐Pearson type 3 distribution. This paper examines the suitability of a five‐parameter Wakeby distribution for the annual maximum flood data in eastern Australia. We adopt a Monte Carlo simulation technique to select an appropriate plotting position formula and to derive a probability plot correlation coefficient (PPCC) test statistic for Wakeby distribution. The Weibull plotting position formula has been found to be the most appropriate for the Wakeby distribution. Regression equations for the PPCC tests statistics associated with the Wakeby distribution for different levels of significance have been derived. Furthermore, a power study to estimate the rejection rate associated with the derived PPCC test statistics has been undertaken. Finally, an application using annual maximum flood series data from 91 catchments in eastern Australia has been presented. Results show that the developed regression equations can be used with a high degree of confidence to test whether the Wakeby distribution fits the annual maximum flood series data at a given station. The methodology developed in this paper can be adapted to other probability distributions and to other study areas. Copyright © 2014 John Wiley & Sons, Ltd.     

On the relationship between hydrographs and chemographs

The spatial representativeness of gauging stations was investigated in two low‐mountainous river basins near the city of Trier, southwest Germany. Longitudinal profiles during low and high flow conditions were sampled in order to identify sources of solutes and to characterize the alteration of flood wave properties during its travel downstream. Numerous hydrographs and chemographs of natural flood events were analysed in detail. Additionally, artificial flood events were investigated to study in‐channel transport processes. During dry weather conditions the gauging station was only representative for a short river segment upstream, owing to discharge and solute concentrations of sources contiguous to the measurement site. During artificial flood events the kinematic wave velocity was considerably faster than the movement of water body and solutes, refuting the idea of a simple mixing process of individual runoff components. Depending on hydrological boundary conditions, the wave at a specific gauge could be entirely composed of old in‐channel water, which notably reduces the spatial representativeness of a sampling site. Natural flood events were characterized by a superimposition of local overland flow, riparian water and the kinematic wave process comprising the downstream conveyance of solutes. Summer floods in particular were marked by a chronological occurrence of distinct individual runoff components originating only from a few contributing areas adjacent to the stream and gauge. Thus, the representativeness of a gauge for processes in the whole basin depends on the distance of the nearest significant source to the station. The consequence of our study is that the assumptions of mixing models are not satisfied in river basins larger than 3 km². Copyright © 2006 John Wiley & Sons, Ltd.     

Regional flood frequency analysis using residual kriging in physiographical space

In this article, an approach using residual kriging (RK) in physiographical space is proposed for regional flood frequency analysis. The physiographical space is constructed using physiographical/climatic characteristics of gauging basins by means of canonical correlation analysis (CCA). This approach is a modified version of the original method, based on ordinary kriging (OK). It is intended to handle effectively any possible spatial trends within the hydrological variables over the physiographical space. In this approach, the trend is first quantified and removed from the hydrological variable by a quadratic spatial regression. OK is therefore applied to the regression residual values. The final estimated value of a specific quantile at an ungauged station is the sum of the spatial regression estimate and the kriged residual. To evaluate the performance of the proposed method, a cross‐validation procedure is applied. Results of the proposed method indicate that RK in CCA physiographical space leads to more efficient estimates of regional flood quantiles when compared to the original approach and to a straightforward regression‐based estimator. Copyright © 2010 John Wiley & Sons, Ltd.     

Interaction between suspended sediment and tidal amplification in the Guadalquivir Estuary

Water level records at two stations in the Guadalquivir Estuary (Spain), one near the estuary mouth (Bonanza) and one about 77 km upstream (Sevilla), have been analysed to study the amplification of the tide in the estuary. The tidal amplification factor shows interesting temporal variation, including a spring-neap variation, some extreme low values, and especially the anomalous behaviour that the amplification factor is larger during a number of periods. These variations are explained by data analysis combined with numerical and analytical modelling. The spring-neap variation is due to the quadratic relation between the bottom friction and the tidal flow velocity. The river flood events are the direct causes of the extreme low values of the amplification factor, and they trigger the non-linear interaction between the tidal flow and suspended sediment transport. The fluvial sediment input during a river flood causes high sediment concentration in the estuary, up to more than 10 g/l. This causes a reduction of the effective hydraulic drag, resulting in stronger tidal amplification in the estuary for a period after a river flood. After such an event the tidal amplification in the estuary does not always fall back to the same level as before the event, indicating that river flood events have significant influence on the long-term development of this estuary.     

An improved time series model for monthly stream flows

This study aims to develop an improved time series model to overcome difficulties in modeling monthly short term stream flows. The periodic, serial dependent and independent components of the classical time series models are improved separately by information transfer from a surrounding long term gauging station to the considered flow section having short term records. Eventually, an improved model preserving the mathematical model structure of the classical time series model, while improving general and monthly statistics of the monthly stream flows, is derived by using the improved components instead of the short term model components in the time series modeling. The correlative relationships between the current short term and surrounding long term stations are used to improve periodic and serial dependent behaviors of monthly flows. Independent components (residuals) are improved via the parameters defining their theoretical probability distribution. The improved model approach is tested by using 50 year records of Göksu-Himmetli (1801) and Göksu-Gökdere (1805) flow monitoring stations located on the Ceyhan river basin, in south of Turkey. After 50 year records of the station 1801 are separated into five 10 year sub series, their improved and classical time series models are computed and compared with the real long-term (50 year) time series model of this station to reveal efficiencies of the improved models for each subseries (sub terms with 10 year observation). The comparisons are realized based on the model components, model estimates and general/monthly statistics of model estimates. Finally, some evaluations are made on the results compared to the regression method classically applied in the literature.     

Extreme hydrological events,palaeo-information and climate change

Abstract

Extreme flood events have been and continue to be one of the most important natural hazards responsible for deaths and economic losses. Extreme floods result in direct destructive effects during the time of the event, and they also may be followed by a related chain of indirect calamities such as famines and epidemics that produce additional damages and suffering. Extreme hydrological events that have occurred in the historical past may also occur in the future. Knowledge about magnitudes and recurrence frequencies of past extreme hydrological events in most regions are too short to adequately evaluate potential magnitudes and recurrence frequencies of extreme hydrological events. Stationary climate in which the mean and variance do not change over time is a basic underlying assumption of standard methodological procedures for estimating recurrence probabilities of extreme hydrological events. Palaeo-archives contained in river and lake sediments, fossil plant and animal matter, ice layers, and other natural archives show that the assumption of stationary climate is not valid when the time scale is extended beyond centuries and millennia. Records of past extreme floods that occurred long before the period of instrumentation can be reconstructed from the distribution of slackwater flood deposits or from derivation of water depths competent to transport the largest rocks found in flood deposited sediment. Palaeoflood records reconstructed from the Upper Mississippi and Lower Colorado River systems in the United States confirm nonstationary behaviour of the mean and variance in hydrological time series. These stratigraphic records have shown that even very modest climatic changes have resulted in very important changes in the magnitudes and recurrence frequencies of extreme floods. A close relationship was found between the palaeo-flood record of extreme floods in the Upper Mississippi River system and a palaeo-record of stable isotopes of oxygen and carbon preserved in speleothem calcite from a local cave. The relationship suggests that isotopic records elsewhere might be calibrated to provide insight about how future potential climate changes might impact extreme flood magnitudes and recurrence frequencies there. Atmospheric global circulation models (GCMs) mainly simulate average climatic conditions and are presently inadequate sources of information about how future climate changes might be represented at the extreme event scale. Palaeo-flood archives, however, provide basic information about how magnitudes and recurrence frequencies of extreme hydrological events responded to past climate changes and they also provide a reference base against which GCM simulations can be calibrated regionally and be better interpreted to decipher hydrological information at the extreme event scale.     

Regional frequency analysis of rainfall extremes in Southern Malawi using the index rainfall and L-moments approaches

Rainfall extremes often result in the occurrence of flood events with associated loss of life and infrastructure in Malawi. However, an understanding of the frequency of occurrence of such extreme events either for design or disaster planning purposes is often limited by data availability at the desired temporal and spatial scales. Regionalisation, which involves “trading time for space” by pooling together observations for stations with similar behavior, is an alternative approach for more accurate determination of extreme events even at ungauged areas or sites with short records. In this study, regional frequency analysis of rainfall extremes in Southern Malawi, large parts of which are flood prone, was undertaken. Observed 1-, 3-, 5- and 7-day annual maximum rainfall series for the period 1978–2007 at 23 selected rainfall stations in Southern Malawi were analysed. Cluster analysis using scaled at-site characteristics was used to determine homogeneous rainfall regions. L-moments were applied to derive regional index rainfall quantiles. The procedure also validated the three rainfall regions identified through homogeneity and heterogeneity tests based on Monte Carlo simulations with regional average L-moment ratios fitted to the Kappa distribution. Based on assessments of the accuracy of the derived index rainfall quantiles, it was concluded that the performance of this regional approach was satisfactory when validated for sites not included in the sample data. The study provides an estimate of the regional characteristics of rainfall extremes that can be useful in among others flood mitigation and engineering design.     

The chronology and the hydrometeorology of catastrophic floods on Dartmoor,South West England

Extreme floods are the most widespread and often the most fatal type of natural hazard experienced in Europe, particularly in upland and mountainous areas. These ‘flash flood’ type events are particularly dangerous because extreme rainfall totals in a short space of time can lead to very high flow velocities and little or no time for flood warning. Given the danger posed by extreme floods, there are concerns that catastrophic hydrometeorological events could become more frequent in a warming world. However, analysis of longer term flood frequency is often limited by the use of short instrumental flow records (last 30–40 years) that do not adequately cover alternating flood‐rich and flood‐poor periods over the last 2 to 3 centuries. In contrast, this research extends the upland flood series of South West England (Dartmoor) back to ca AD 1800 using lichenometry. Results show that the period 1820 to mid‐1940s was characterized by widespread flooding, with particularly large and frequent events in the mid‐to‐late 19th and early 20th centuries. Since ca 1850 to 1900, there has been a general decline in flood magnitude that was particularly marked after the 1930s/mid‐1940s. Local meteorological records show that: (1) historical flood‐rich periods on Dartmoor were associated with high annual, seasonal and daily rainfall totals in the last quarter of the 19th century and between 1910 and 1946, related to sub‐decadal variability of the North Atlantic Oscillation and receipt of cyclonic and southerly weather types over the southwest peninsula; and (2) the incidence of heavy daily rainfall declined notably after 1946, similar to sedimentary archives of flooding. The peak period of flooding on Dartmoor predates the beginning of gauged flow records, which has practical implications for understanding and managing flood risk on rivers that drain Dartmoor. Copyright © 2013 John Wiley & Sons, Ltd.     

Bivariate flood frequency analysis using the copula function: a case study of the Litija station on the Sava River

As an alternative to the commonly used univariate flood frequency analysis, copula frequency analysis can be used. In this study, 58 flood events at the Litija gauging station on the Sava River in Slovenia were analysed, selected based on annual maximum discharge values. Corresponding hydrograph volumes and durations were considered. Different bivariate copulas from three families were applied and compared using different statistical, graphical and upper tail dependence tests. The parameters of the copulas were estimated using the method of moments with the inversion of Kendall's tau. The Gumbel–Hougaard copula was selected as the most appropriate for the pair of peak discharge and hydrograph volume (Q‐V). The same copula was also selected for the pair hydrograph volume and duration (V‐D), and the Student‐t copula was selected for the pair of peak discharge and hydrograph duration (Q‐D). The differences among most of the applied copulas were not significant. Different primary, secondary and conditional return periods were calculated and compared, and some relationships among them were obtained. Copyright © 2014 John Wiley & Sons, Ltd.     

Characteristics of intense rainfall over Gujarat State (India) based on percentile criteria

The study focuses on the spatial and temporal variations of intense/extreme rainfall events over Gujarat State (India) during the period 1970–2014. Average monsoon rainfall for the state shows a significant increasing trend, with an increase of 48 mm/decade. Some of the stations in the Saurashtra region show a statistically significant increasing trend but none of the stations in the state show a decreasing trend. The increasing trend in monsoon rainfall is very significant for the past three decades, with an increase of 167 mm/decade. Instead of fixed absolute threshold values, relative threshold values of rainfall corresponding to the 95th, 98th, 99th and 99.5th percentiles for each station have been proposed to represent heavy, very heavy, intense and extreme rainfall, which varied between 70–120, 105–160, 130–210 and 165–280 mm, respectively. Significant increasing trends are observed for the frequency of heavy and very heavy rainfall events over the state.     

Trivariate generalized extreme value distribution in flood frequency analysis

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.     

Detection of trends in hydrological extremes for Canadian watersheds

The potential impacts of climate change can alter the risk to critical infrastructure resulting from changes to the frequency and magnitude of extreme events. As well, the natural environment is affected by the hydrologic regime, and changes in high flows or low flows can have negative impacts on ecosystems. This article examines the detection of trends in extreme hydrological events, both high and low flow events, for streamflow gauging stations in Canada. The trend analysis involves the application of the Mann–Kendall non‐parametric test. A bootstrap resampling process has been used to determine the field significance of the trend results. A total of 68 gauging stations having a nominal record length of at least 50 years are analysed for two analysis periods of 50 and 40 years. The database of Canadian rivers investigated represents a diversity of hydrological conditions encompassing different extreme flow generating processes and reflects a national scale analysis of trends. The results reveal more trends than would be expected to occur by chance for most of the measures of extreme flow characteristics. Annual and spring maximum flows show decreasing trends in flow magnitude and decreasing trends in event timing (earlier events). Low flow magnitudes exhibit both decreasing and increasing trends. Copyright © 2010 John Wiley & Sons, Ltd.     

Analysis of dry/wet conditions using the standardized precipitation index and its potential usefulness for drought/flood monitoring in Hunan Province, China

Local dry/wet conditions and extreme rainfall events are of great concern in regional water resource and disaster risk management. Extensive studies have been carried out to investigate the change of dry/wet conditions and the adaptive responses to extreme rainfall events within the context of climate change. However, applicable tools and their usefulness are still not sufficiently studied, and in Hunan Province, a major grain-producing area in China that has been frequently hit by flood and drought, relevant research is even more limited. This paper investigates the spatiotemporal variation of dry/wet conditions and their annual/seasonal trends in Hunan with the standardized precipitation index (SPI) at various time scales. Furthermore, to verify the potential usefulness of SPI for drought/flood monitoring, the correlation between river discharge and SPI at multiple time scales was examined, and the relation between extreme SPI and the occurrence of historical drought/flood events is explored. The results indicate that the upper reaches of the major rivers in Hunan Province have experienced more dry years than the middle and lower reaches over the past 57 years, and the region shows a trend of becoming drier in the spring and autumn seasons and wetter in the summer and winter seasons. We also found a strong correlation between river discharge and SPI series, with the maximum correlation coefficient occurred at the time scale of 2 months. SPI at different time scales may vary in its usefulness in drought/flood monitoring, and this highlights the need for a comprehensive consideration of various time scales when SPI is employed to monitor droughts and floods.     

Morphological records of storm floods exemplified by the impact of the 1872 Baltic storm on a sandy spit system in south‐eastern Denmark

Beach‐ridge systems are important geo‐archives providing evidence for past wave climate including catastrophic storm flood events. This study investigates the morphological impacts of the 1872 Baltic storm flood on a beach‐ridge system (sandy spit) in south‐eastern Denmark and evaluates the frequency of extreme storm flood events in the area over a longer time perspective. This paper combines field studies of morphology and sedimentary deposits, studies of historical maps, digital terrain model, ground‐penetrating radar profiles, and luminescence dating. Sea water reached 2.8 m above mean sea level (amsl) during peak inundation and, based on studies of the morphological impacts of the 1872 storm flood, the event can be divided into four phases. Phase 1: increasing mean water levels and wave activity at the beach brought sediments from the beach (intertidal bars and normal berm) higher up in the profile and led to the formation of a storm‐berm. Phase 2: water levels further increased and sediment in the upper part of the profile continued to build up the storm‐berm. Phase 3: water levels now reached the top of the dune ridge and were well above the storm‐berm level. Sea water was breaching the dune ridge at several sites and wash‐over fans were generated until a level where the mean water level had dropped too much. Phase 4: the non‐vegetated wash‐over fans functioned as pathways for aeolian sand transport and relatively high dunes were formed in particular along the margins of the fan where aeolian sand was trapped by existing vegetation. The studied beach‐ridge system records about 4500 years of accumulation; the storm flood sediments described are unique suggesting that the 1872 Baltic storm flood event was an extreme event. Thus studies of beach‐ridge systems form a new source for understanding storm surge risk. Copyright © 2013 John Wiley & Sons, Ltd.     

Frequency analysis for predicting 1% annual maximum water levels along Florida coast,US

In the Coastal Flood Insurance Study by the Federal Emergency Management Agency (FEMA, 2005), 1% annual maximum coastal water levels are used in coastal flood hazard mitigation and engineering design in coastal areas of USA. In this study, a frequency analysis method has been developed to provide more accurate predictions of 1% annual maximum water levels for the Florida coast waters. Using 82 and 94 years of annual maximum water level data at Pensacola and Fernandina, performances of traditional frequency analysis methods, including advanced method of Generalized Extreme Value distribution method, have been evaluated. Comparison with observations of annual maximum water levels with 83 and 95 years of return periods indicate that traditional methods are unable to provide satisfactory predictions of 1% annual maximum water levels to account for hurricane‐induced extreme water levels. Based on the characteristics of annual maximum water level distribution of Pensacola and Fernandina stations, a new probability distribution method has been developed in this study. Comparison with observations indicates that the method presented in this study significantly improves the accuracy of predictions of 1% annual maximum water levels. For Fernandina station, predictions of extreme water level match well with the general trend of observations. With a correlation coefficient of 0·98, the error for the maximum observed extreme water level of 3·11 m (National Geodetic Vertical Datum) with 95 years of return period is 0·92%. For Pensacola station, the prediction error for the maximum observed extreme water level with a return period of 83 years is 5·5%, with a correlation value of 0·98. The frequency analysis has also been reasonably compared to the more costly Monte Carlo simulation method. Copyright © 2008 John Wiley & Sons, Ltd.