Journal articles: 'Flood frequency analysis'

1

Campbell, Katherine. "Flood Frequency Analysis." Technometrics 43, no. 2 (May 2001): 238. http://dx.doi.org/10.1198/tech.2001.s592.

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Kimber, Alan C. "Flood Frequency Analysis." Journal of the American Statistical Association 96, no. 454 (June 2001): 780–81. http://dx.doi.org/10.1198/jasa.2001.s402.

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Stedigner, Jery R., and Stephen J. Burges. "Flood frequency analysis." Eos, Transactions American Geophysical Union 66, no. 47 (1985): 1179. http://dx.doi.org/10.1029/eo066i047p01179-01.

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Baidya, S., Ajay Singh, and Sudhindra N. Panda. "Flood frequency analysis." Natural Hazards 100, no. 3 (January 6, 2020): 1137–58. http://dx.doi.org/10.1007/s11069-019-03853-4.

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Ibeje, Andy Obinna, and Ben N. Ekwueme. "Regional Flood Frequency Analysis using Dimensionless Index Flood Method." Civil Engineering Journal 6, no. 12 (December 1, 2020): 2425–36. http://dx.doi.org/10.28991/cej-2020-03091627.

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Hydrologic designs require accurate estimation of quartiles of extreme floods. But in many developing regions, records of flood data are seldom available. A model framework using the dimensionless index flood for the transfer of Flood Frequency Curve (FFC) among stream gauging sites in a hydrologically homogeneous region is proposed. Key elements of the model framework include: (1) confirmation of the homogeneity of the region; (2) estimation of index flood-basin area relation; (3) derivation of the regional flood frequency curve (RFFC) and deduction of FFC of an ungauged catchment as a product of index flood and dimensionless RFFC. As an application, 1983 to 2004 annual extreme flood from six selected gauging sites located in Anambra-Imo River basin of southeast Nigeria, were used to demonstrate that the developed index flood model: , overestimated flood quartiles in an ungauged site of the basin. It is recommended that, for wider application, the model results can be improved by the availability and use of over 100 years length of flood data spatially distributed at critical locations of the watershed. Doi: 10.28991/cej-2020-03091627 Full Text: PDF

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Kidson, R., and K. S. Richards. "Flood frequency analysis: assumptions and alternatives." Progress in Physical Geography: Earth and Environment 29, no. 3 (September 2005): 392–410. http://dx.doi.org/10.1191/0309133305pp454ra.

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Flood frequency analysis (FFA) is a form of risk analysis, yet a risk analysis of the activity of FFA itself is rarely undertaken. The recent literature of FFA has been characterized by: (1) a proliferation of mathematical models, lacking theoretical hydrologic justification, but used to extrapolate the return periods of floods beyond the gauged record; (2) official mandating of particular models, which has resulted in (3) research focused on increasingly reductionist and statistically sophisticated procedures for parameter fitting to these models from the limited gauged data. These trends have evolved to such a refined state that FFA may be approaching the ‘limits of splitting’; at the very least, the emphasis was shifted early in the history of FFA from predicting and explaining extreme flood events to the more soluble issue of fitting distributions to the bulk of the data. However, recent evidence indicates that the very modelling basis itself may be ripe for revision. Self-similar (power law) models are not only analytically simpler than conventional models, but they also offer a plausible theoretical basis in complexity theory. Of most significance, however, is the empirical evidence for self-similarity in flood behaviour. Self-similarity is difficult to detect in gauged records of limited length; however, one positive aspect of the application of statistics to FFA has been the refinement of techniques for the incorporation of historical and palaeoflood data. It is these data types, even over modest timescales such as 100 years, which offer the best promise for testing alternative models of extreme flood behaviour across a wider range of basins. At stake is the accurate estimation of flood magnitude, used widely for design purposes: the power law model produces far more conservative estimates of return period of large floods compared to conventional models, and deserves closer study.

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Leščešen, Igor, and Dragan Dolinaj. "Regional Flood Frequency Analysis of the Pannonian Basin." Water 11, no. 2 (January 23, 2019): 193. http://dx.doi.org/10.3390/w11020193.

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In this paper, we performed Regional Flood Frequency Analysis (RFFA) by using L-moments and Annual Maximum Series (AMS) methods. Time series of volumes and duration of floods were derived using the threshold level method for 22 hydrological stations in the Pannonian Basin. For flood definition, a threshold set at Q10 was used. The aim of this research is to derive best-fit regional distribution for the four major rivers within the Pannonian Basin and to provide reliable prediction of flood quantiles. The results show that the investigated area can be considered homogeneous (Vi < 1) both for flood volumes (0.097) and durations (0.074). To determine the best-fit regional distribution, the six most commonly used distributions were used. Results obtained by L-moment ratio diagram and Z statistics show that all distributions satisfy the test criteria, but because the Log-Normal distribution has the value closest to zero, it can be selected as the best-fit distribution for the volumes (0.12) and durations (0.25) of floods.

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Stamatatou, Nikoletta, Lampros Vasiliades, and Athanasios Loukas. "Bivariate Flood Frequency Analysis Using Copulas." Proceedings 2, no. 11 (August 3, 2018): 635. http://dx.doi.org/10.3390/proceedings2110635.

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Flood frequency estimation for the design of hydraulic structures is usually performed as a univariate analysis of flood event magnitudes. However, recent studies show that for accurate return period estimation of the flood events, the dependence and the correlation pattern among flood attribute characteristics, such as peak discharge, volume and duration should be taken into account in a multivariate framework. The primary goal of this study is to compare univariate and joint bivariate return periods of floods that all rely on different probability concepts in Yermasoyia watershed, Cyprus. Pairs of peak discharge with corresponding flood volumes are estimated and compared using annual maximum series (AMS) and peaks over threshold (POT) approaches. The Lyne-Hollick recursive digital filter is applied to separate baseflow from quick flow and to subsequently estimate flood volumes from the quick flow timeseries. Marginal distributions of flood peaks and volumes are examined and used for the estimation of typical design periods. The dependence between peak discharges and volumes is then assessed by an exploratory data analysis using K-plots and Chi-plots, and the consistency of their relationship is quantified by Kendall’s correlation coefficient. Copulas from Archimedean, Elliptical and Extreme Value families are fitted using a pseudo-likelihood estimation method, verified using both graphical approaches and a goodness-of-fit test based on the Cramér-von Mises statistic and evaluated according to the corrected Akaike Information Criterion. The selected copula functions and the corresponding joint return periods are calculated and the results are compared with the marginal univariate estimations of each variable. Results indicate the importance of the bivariate analysis in the estimation of design return period of the hydraulic structures.

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ACREMAN, M. C., and R. J. HORROCKS. "Flood Frequency Analysis for the 1988 Truro Floods." Water and Environment Journal 4, no. 1 (February 1990): 62–69. http://dx.doi.org/10.1111/j.1747-6593.1990.tb01558.x.

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10

Mangukiya, Nikunj K., Darshan J. Mehta, and Raj Jariwala. "Flood frequency analysis and inundation mapping for lower Narmada basin, India." Water Practice and Technology 17, no. 2 (January 31, 2022): 612–22. http://dx.doi.org/10.2166/wpt.2022.009.

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Abstract Floods are one of the world's most destructive natural disasters, taking more lives and causing more infrastructural damage than any other natural phenomenon. Floods have a significant economic, social, and environmental impact in developing countries like India. As a result, it is essential to address this natural disaster to mitigate its effects. The lower Narmada basin has experienced numerous floods, including severe flooding in 1970, 1973, 1984, 1990, 1994, and 2013. The objective of the present study is to use flood frequency analysis to anticipate peak floods and prepare flood inundation maps for the lower Narmada River reach. The flood frequency analysis was carried out using Gumbel's and Log-Pearson Type III Distribution methods. The hydrodynamic simulation was performed using HEC-RAS v6.0 to prepare flood inundation maps for predicted flood peaks. The result shows that the Log-Pearson Type-III distribution method gives good results for the lower return period while Gumbel's method gives good results for the higher return period. The hydrodynamic model results indicate that as the return period increases, the area of the high-risk zone increases while the area of the low-risk zone remains almost constant. The present study concludes that the existing embankment system on the banks of the Narmada River is not sufficient for significant floods. The developed maps will be helpful to government authorities and individual stakeholders to decide the flood mitigation measures.

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Caissie, Daniel, and Nassir El-Jabi. "A stochastic study of floods in Canada: frequency analysis and regionalization." Canadian Journal of Civil Engineering 18, no. 2 (April 1, 1991): 225–36. http://dx.doi.org/10.1139/l91-027.

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Peak stream discharge is a hydrologic parameter that is very important for the determination of flood risk, design of engineering works, and management of water resources. In this study, some 237 stream records across Canada were analyzed using the theory of stochastic processes applied to extreme values. This model, based on partial duration series analysis, was applied to each stream record, considering the time of occurrence of floods to be a Poisson process. In addition, exceedances (values above a given discharge level or truncation level) were considered to be independent random variables identically distributed over a one-year time interval. After this frequency analysis of each stream record, a regionalization of the flood frequency characteristics in Canada was performed using two different approaches: multiple regression analysis and index-flood method. A comparison of the two approaches was carried out by examining mean relative error and root-mean-square error. It was determined that the level of difficulty in applying the stochastic flood model was not the same across Canada. Moreover, error associated with the index-flood method is mainly due to error in estimating low return floods. Key words: flood, partial duration series, regional hydrology, index-flood method, low return flood.

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Pekárová, Pavla, Dana Halmová, Veronika Bačová Mitková, Pavol Miklánek, Ján Pekár, and Peter Škoda. "Historic flood marks and flood frequency analysis of the Danube River at Bratislava, Slovakia." Journal of Hydrology and Hydromechanics 61, no. 4 (December 1, 2013): 326–33. http://dx.doi.org/10.2478/johh-2013-0041.

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Abstract In this paper we focused on the history of floods and extreme flood frequency analysis of the upper Danube River at Bratislava. Firstly, we briefly describe the flood marks found on the Danube River in the region of Bratislava, Slovakia, and provide an account of the floods’ consequences. Secondly, we analyzed the annual maximum discharge series for the period 1876-2012, including the most recent flood of June 2013. Thirdly, we compare the values of T-year design discharge computed with and without incorporating the historic floods (floods of the years 1501, 1682, and 1787 into the 138-year series of annual discharge peaks). There are unfortunately only a few historic flood marks preserved in Bratislava, but there are very important and old marks in neighbouring Hainburg and other Austrian cities upstream to Passau. The calculated T-year maximum discharge of the Danube at Bratislava for the period 1876-2010 without and with historic flood values have been compared. Our analysis showed that without incorporating the historic floods from the years 1501, 1682, and 1787 the 1000-year discharge calculated only with data from the instrumented period 1876- 2013 is 14,188 m3 s-1, and it is lower compared to the 1000-year discharge of 14,803 m3 s-1 when the three historic floods are included. In general, the T-year discharge is higher throughout the whole spectrum of T-year discharges (10, 20, 50, 100, 200, 500-year discharge) when the three historic floods are included. Incorporating historic floods into a time series of maximum annual discharge seems to exert a significant effect on the estimates of low probability floods. This has important implications for flood managements and estimation of flood design discharge.

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Zhang, Min, and Juanle Wang. "Global Flood Disaster Research Graph Analysis Based on Literature Mining." Applied Sciences 12, no. 6 (March 17, 2022): 3066. http://dx.doi.org/10.3390/app12063066.

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Floods are the most frequent and highest-impact among the natural disasters caused by global climate change. A large number of flood disaster knowledge were buried in the scientific literature. This study mines research trends and hotspots on flood disasters and identifies their quantitative and spatial distribution features using natural language process technology. The abstracts of 14,076 studies related to flood disasters from 1990 to 2020 were used for text mining. The study used logistic regression to classify themes, adopted the dictionary matching method to analyze flood disaster subcategories, analyzed the spatial distribution characteristics of research institutions, and used Stanford named entity recognition to identify hot research areas. Finally, the disaster information was integrated and visualized as a knowledge graph. The main findings are as follows. (1) The research hotspots are concentrated on flood disaster risks and prediction. Rainfall, coastal floods, and flash floods are the most-studied flood disaster sub-categories. (2) There are some connections and differences between the physical occurrence and research frequency of flood disasters. Occurrence frequency and research frequency of flood disasters are correlated. However, the spatial distribution at the global and intercontinental scales is geographically imbalanced. (3) The study’s flood disaster knowledge graph contains 39,679 nodes and 64,908 edges, reflecting the literature distribution and field information on the research themes. Future research will extract more disaster information from the full texts of the studies to enrich the flood disaster knowledge graph and obtain more knowledge on flood disaster risk and reduction.

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Wang, Yang, Shuhui Zhang, Ziyi Zhang, Caichao Su, Peng Ding, and Guangtian Cao. "Frequency analysis of representative flood control water level stations in Puyang River." E3S Web of Conferences 329 (2021): 01002. http://dx.doi.org/10.1051/e3sconf/202132901002.

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Puyang river basin is located in the north central part of Zhejiang Province, which is one of the most important river basins in Zhejiang Province. The lower reaches of Puyang River are easily influenced by tide in Hangzhou Bay and flood in Qiantang River. When Puyang river floods, it often meets Fuchun River and floods occur at the same time. The flood discharge of Puyang river is blocked and the water level rises and rises, which makes the Puyang River vulnerable to disaster. Water level frequency analysis is the basis of Puyang river planning and flood control plan. The representative flood control water level stations of Puyang River include Zhuji station and wenjiayan station. The frequency analysis of these representative stations is helpful to determine the water level of these key nodes under different frequencies, and to provide basic data for accurate flood control of Puyang River and ensure the safety of flood control.

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Machado, M. J., B. A. Botero, J. López, F. Francés, A. Díez-Herrero, and G. Benito. "Flood frequency analysis of historical flood data under stationary and non-stationary modelling." Hydrology and Earth System Sciences 19, no. 6 (June 2, 2015): 2561–76. http://dx.doi.org/10.5194/hess-19-2561-2015.

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Abstract. Historical records are an important source of information on extreme and rare floods and fundamental to establish a reliable flood return frequency. The use of long historical records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 yr flood record from the Tagus River in Aranjuez (central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their contribution within hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations in flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation (NAO) index. Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators, and (b) a time-varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, which incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged records) improved the estimates of the probabilities of rare floods (return intervals of 100 yr and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 yr) has changed over the last 500 yr due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful in providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

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Strupczewski, W. G., K. Kochanek, and E. Bogdanowicz. "Flood frequency analysis supported by the largest historical flood." Natural Hazards and Earth System Sciences 14, no. 6 (June 20, 2014): 1543–51. http://dx.doi.org/10.5194/nhess-14-1543-2014.

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Abstract. The use of non-systematic flood data for statistical purposes depends on the reliability of the assessment of both flood magnitudes and their return period. The earliest known extreme flood year is usually the beginning of the historical record. Even if one properly assesses the magnitudes of historic floods, the problem of their return periods remains unsolved. The matter at hand is that only the largest flood (XM) is known during whole historical period and its occurrence marks the beginning of the historical period and defines its length (L). It is common practice to use the earliest known flood year as the beginning of the record. It means that the L value selected is an empirical estimate of the lower bound on the effective historical length M. The estimation of the return period of XM based on its occurrence (L), i.e. ^M = L, gives a severe upward bias. The problem arises that to estimate the time period (M) representative of the largest observed flood XM. From the discrete uniform distribution with support 1, 2, ... , M of the probability of the L position of XM, one gets ^L = M/2. Therefore ^M = 2L has been taken as the return period of XM and as the effective historical record length as well this time. As in the systematic period (N) all its elements are smaller than XM, one can get ^M = 2t( L+N). The efficiency of using the largest historical flood (XM) for large quantile estimation (i.e. one with return period T = 100 years) has been assessed using the maximum likelihood (ML) method with various length of systematic record (N) and various estimates of the historical period length ^M comparing accuracy with the case when systematic records alone (N) are used only. The simulation procedure used for the purpose incorporates N systematic record and the largest historic flood (XMi) in the period M, which appeared in the Li year of the historical period. The simulation results for selected two-parameter distributions, values of their parameters, different N and M values are presented in terms of bias and root mean square error RMSEs of the quantile of interest are more widely discussed.

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Strupczewski, W. G., K. Kochanek, and E. Bogdanowicz. "Flood Frequency Analysis supported by the largest historical flood." Natural Hazards and Earth System Sciences Discussions 1, no. 6 (November 5, 2013): 6133–53. http://dx.doi.org/10.5194/nhessd-1-6133-2013.

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Abstract. The use of non-systematic flood data for statistical purposes depends on reliability of assessment both flood magnitudes and their return period. The earliest known extreme flood year is usually the beginning of the historical record. Even if one properly assess the magnitudes of historic floods, the problem of their return periods remains unsolved. The matter in hand is that the only largest flood (XM) is known during whole historical period and its occurrence marks the beginning of the historical period and defines its length (L). It is the common practice of using the earliest known flood year as the beginning of the record. It means that the L value selected is an empirical estimate of the lower bound on the effective historical length M. The estimation of the return period of XM based on its occurrence (L), i.e. ∧ M = L, gives the severe upward bias. Problem arises to estimate the time period (M) representative of the largest observed flood XM. From the discrete uniform distribution with support 1,2, ... , M of the probability of the L position of XM one gets ∧ L = M/2. Therefore ∧ M = 2L has been taken as the return period of XM and as the effective historical record length as well this time. As in the systematic period (N) all its elements are smaller than XM, one can get ∧ M =2(L+N). The efficiency of using the largest historical flood (XM) for large quantile estimation (i.e. one with return period T = 100 yr has been assessed using ML method with various length of systematic record (N) and various estimates of historical period length ∧ M comparing accuracy with the case when systematic records alone (N) are used only. The simulation procedure used for the purpose incorporates N systematic record and one largest historic flood (XMi) in the period M which appeared in the Li year backward from the end of historical period. The simulation result for selected distributions, values of their parameters, different N and M values are presented in terms of bias and RMSE of the quantile of interest and widely discussed.

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Jakob, Matthias, and Peter Jordan. "Design flood estimates in mountain streams the need for a geomorphic approach." Canadian Journal of Civil Engineering 28, no. 3 (June 1, 2001): 425–39. http://dx.doi.org/10.1139/l01-010.

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Estimates of design flood frequencies are routinely required for engineering purposes on ungauged streams and streams with a limited period of streamflow record. In these cases, the design flood is determined either by rainfall frequencyduration analysis, regional analysis of streamflow data, or by extrapolation of a short record from a gauged stream. Although these types of analyses are valuable in a first approximation of peak discharges for different return periods, there is increasing evidence that geomorphic processes such as debris flows, landslide dam failures, glacial outburst floods, and even snow avalanches in the watershed can significantly exceed these estimates. This paper highlights the problem of a purely hydrologic approach for design flood estimates using several case studies, and suggests procedures to routinely include geomorphic processes in standard flood frequency studies.Key words: debris flows, debris floods, landslide dams, flood hazards, outburst floods, frequency analysis.

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Dong, N. Dang, V. Agilan, and K. V. Jayakumar. "Bivariate Flood Frequency Analysis of Nonstationary Flood Characteristics." Journal of Hydrologic Engineering 24, no. 4 (April 2019): 04019007. http://dx.doi.org/10.1061/(asce)he.1943-5584.0001770.

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20

Machado, M. J., B. A. Botero, J. López, F. Francés, A. Díez-Herrero, and G. Benito. "Flood frequency analysis of historical flood data under stationary and non-stationary modelling." Hydrology and Earth System Sciences Discussions 12, no. 1 (January 14, 2015): 525–68. http://dx.doi.org/10.5194/hessd-12-525-2015.

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Abstract. Historical records are an important source of information about extreme and rare floods with a great value to establish a reliable flood return frequency. The use of long historic records for flood frequency analysis brings in the question of flood stationarity, since climatic and land-use conditions can affect the relevance of past flooding as a predictor of future flooding. In this paper, a detailed 400 year flood record from the Tagus River in Aranjuez (Central Spain) was analysed under stationary and non-stationary flood frequency approaches, to assess their implications on hazard studies. Historical flood records in Aranjuez were obtained from documents (Proceedings of the City Council, diaries, chronicles, memoirs, etc.), epigraphic marks, and indirect historical sources and reports. The water levels associated with different floods (derived from descriptions or epigraphic marks) were computed into discharge values using a one-dimensional hydraulic model. Secular variations on flood magnitude and frequency, found to respond to climate and environmental drivers, showed a good correlation between high values of historical flood discharges and a negative mode of the North Atlantic Oscillation index (NAO index). Over the systematic gauge record (1913–2008), an abrupt change on flood magnitude was produced in 1957 due to constructions of three major reservoirs in the Tagus headwaters (Bolarque, Entrepeñas and Buendia) controlling 80% of the watershed surface draining to Aranjuez. Two different models were used for the flood frequency analysis: (a) a stationary model estimating statistical distributions incorporating imprecise and categorical data based on maximum likelihood estimators; (b) a time–varying model based on "generalized additive models for location, scale and shape" (GAMLSS) modelling, that incorporates external covariates related to climate variability (NAO index) and catchment hydrology factors (in this paper a reservoir index; RI). Flood frequency analysis using documentary data (plus gauged record) improved the estimates of the probabilities of rare floods (return intervals of 100 year and higher). Under non-stationary modelling flood occurrence associated with an exceedance probability of 0.01 (i.e. return period of 100 year) has changed over the last 500 year due to decadal and multi-decadal variability of the NAO. Yet, frequency analysis under stationary models was successful on providing an average discharge around which value flood quantiles estimated by non-stationary models fluctuate through time.

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VIJAYALAKSHMI, D. P., and K. S. JINESH BABU. "Flood Frequency Analysis - A Comparative Study of ANN and ANFIS." International Journal of Earth Sciences and Engineering 10, no. 01 (March 6, 2017): 116–20. http://dx.doi.org/10.21276/ijee.2017.10.0118.

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Bhattarai, Tek Narayan, and Swastik Ghimire. "Flood Susceptibility Analysis in West Rapti River Basin Using Frequency Ratio Model." Jalawaayu 3, no. 1 (February 14, 2023): 1–24. http://dx.doi.org/10.3126/jalawaayu.v3i1.52053.

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Floods are recognized as lethal natural events, which result in devastating natural and human losses. So, identifying flood susceptible zones is crucial to adopt necessary mitigation strategies beforehand. With the advent of GIS tools and modelling techniques, mapping of such zones has become easier and more precise; yet, flood prone countries like Nepal have not been able to embrace such tools for flood risk management. With a compelling need to address this situation, this paper employs Frequency Ratio model to analyze flood susceptibility in the West Rapti River Basin. The model, created with the help of 77 flood points and tested with 30 points to obtain 80.7% accuracy, maps the flood hazard zones in the area and identifies the lower Terai and settlement regions as high-risk areas. With the increasing threat of changing climate in the future, this study also propounds better preparation of flood inventory maps in the future for more precise susceptibility analysis models and better flood risk management.

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Jung, I. W., H. Chang, and H. Moradkhani. "Quantifying uncertainty in urban flooding analysis considering hydro-climatic projection and urban development effects." Hydrology and Earth System Sciences 15, no. 2 (February 22, 2011): 617–33. http://dx.doi.org/10.5194/hess-15-617-2011.

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Abstract. How will the combined impacts of land use change, climate change, and hydrologic modeling influence changes in urban flood frequency and what is the main uncertainty source of the results? Will such changes differ by catchment with different degrees of current and future urban development? We attempt to answer these questions in two catchments with different degrees of urbanization, the Fanno catchment with 84% urban land use and the Johnson catchment with 36% urban land use, both located in the Pacific Northwest of the US. Five uncertainty sources – general circulation model (GCM) structures, future greenhouse gas (GHG) emission scenarios, land use change scenarios, natural variability, and hydrologic model parameters – are considered to compare the relative source of uncertainty in flood frequency projections. Two land use change scenarios, conservation and development, representing possible future land use changes are used for analysis. Results show the highest increase in flood frequency under the combination of medium high GHG emission (A1B) and development scenarios, and the lowest increase under the combination of low GHG emission (B1) and conservation scenarios. Although the combined impact is more significant to flood frequency change than individual scenarios, it does not linearly increase flood frequency. Changes in flood frequency are more sensitive to climate change than land use change in the two catchments for 2050s (2040–2069). Shorter term flood frequency change, 2 and 5 year floods, is highly affected by GCM structure, while longer term flood frequency change above 25 year floods is dominated by natural variability. Projected flood frequency changes more significantly in Johnson creek than Fanno creek. This result indicates that, under expected climate change conditions, adaptive urban planning based on the conservation scenario could be more effective in less developed Johnson catchment than in the already developed Fanno catchment.

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Rao, A. R. "Flood frequency and risk analysis." Eos, Transactions American Geophysical Union 68, no. 15 (1987): 212. http://dx.doi.org/10.1029/eo068i015p00212-02.

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Ahmad, M. I., C. D. Sinclair, and A. Werritty. "Log-logistic flood frequency analysis." Journal of Hydrology 98, no. 3-4 (April 1988): 205–24. http://dx.doi.org/10.1016/0022-1694(88)90015-7.

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Zhang, L., and Vijay P. Singh. "Frequency Analysis of Flood Damage." Journal of Hydrologic Engineering 10, no. 2 (March 2005): 100–109. http://dx.doi.org/10.1061/(asce)1084-0699(2005)10:2(100).

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Serago, Jake M., and Richard M. Vogel. "Parsimonious nonstationary flood frequency analysis." Advances in Water Resources 112 (February 2018): 1–16. http://dx.doi.org/10.1016/j.advwatres.2017.11.026.

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Yu, Guo, Daniel B. Wright, Zhihua Zhu, Cassia Smith, and Kathleen D. Holman. "Process-based flood frequency analysis in an agricultural watershed exhibiting nonstationary flood seasonality." Hydrology and Earth System Sciences 23, no. 5 (May 7, 2019): 2225–43. http://dx.doi.org/10.5194/hess-23-2225-2019.

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Abstract. Floods are the product of complex interactions among processes including precipitation, soil moisture, and watershed morphology. Conventional flood frequency analysis (FFA) methods such as design storms and discharge-based statistical methods offer few insights into these process interactions and how they “shape” the probability distributions of floods. Understanding and projecting flood frequency in conditions of nonstationary hydroclimate and land use require deeper understanding of these processes, some or all of which may be changing in ways that will be undersampled in observational records. This study presents an alternative “process-based” FFA approach that uses stochastic storm transposition to generate large numbers of realistic rainstorm “scenarios” based on relatively short rainfall remote sensing records. Long-term continuous hydrologic model simulations are used to derive seasonally varying distributions of watershed antecedent conditions. We couple rainstorm scenarios with seasonally appropriate antecedent conditions to simulate flood frequency. The methodology is applied to the 4002 km2 Turkey River watershed in the Midwestern United States, which is undergoing significant climatic and hydrologic change. We show that, using only 15 years of rainfall records, our methodology can produce accurate estimates of “present-day” flood frequency. We found that shifts in the seasonality of soil moisture, snow, and extreme rainfall in the Turkey River exert important controls on flood frequency. We also demonstrate that process-based techniques may be prone to errors due to inadequate representation of specific seasonal processes within hydrologic models. If such mistakes are avoided, however, process-based approaches can provide a useful pathway toward understanding current and future flood frequency in nonstationary conditions and thus be valuable for supplementing existing FFA practices.

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Najibi, Nasser, and Naresh Devineni. "Recent trends in the frequency and duration of global floods." Earth System Dynamics 9, no. 2 (June 8, 2018): 757–83. http://dx.doi.org/10.5194/esd-9-757-2018.

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Abstract. Frequency and duration of floods are analyzed using the global flood database of the Dartmouth Flood Observatory (DFO) to explore evidence of trends during 1985–2015 at global and latitudinal scales. Three classes of flood duration (i.e., short: 1–7, moderate: 8–20, and long: 21 days and above) are also considered for this analysis. The nonparametric Mann–Kendall trend analysis is used to evaluate three hypotheses addressing potential monotonic trends in the frequency of flood, moments of duration, and frequency of specific flood duration types. We also evaluated if trends could be related to large-scale atmospheric teleconnections using a generalized linear model framework. Results show that flood frequency and the tails of the flood duration (long duration) have increased at both the global and the latitudinal scales. In the tropics, floods have increased 4-fold since the 2000s. This increase is 2.5-fold in the north midlatitudes. However, much of the trend in frequency and duration of the floods can be placed within the long-term climate variability context since the Atlantic Multidecadal Oscillation, North Atlantic Oscillation, and Pacific Decadal Oscillation were the main atmospheric teleconnections explaining this trend. There is no monotonic trend in the frequency of short-duration floods across all the global and latitudinal scales. There is a significant increasing trend in the annual median of flood durations globally and each latitudinal belt, and this trend is not related to these teleconnections. While the DFO data come with a certain level of epistemic uncertainty due to imprecision in the estimation of floods, overall, the analysis provides insights for understanding the frequency and persistence in hydrologic extremes and how they relate to changes in the climate, organization of global and local dynamical systems, and country-scale socioeconomic factors.

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Jung, I. W., H. Chang, and H. Moradkhani. "Quantifying uncertainty in urban flooding analysis caused by the combined effect of climate and land use change scenarios." Hydrology and Earth System Sciences Discussions 7, no. 4 (August 5, 2010): 5369–412. http://dx.doi.org/10.5194/hessd-7-5369-2010.

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Abstract. How will the combined impacts of land use change and climate change influence changes in urban flood frequency and what is the main uncertainty source of the results? We attempt to answer to these questions in two catchments with different degrees of urbanization, the Fanno catchment with 84% urban land use and the Johnson catchment with 36% urban land use, both located in the Pacific Northwest of the US. Five uncertainty sources – general circulation model (GCM) structures, future greenhouse gas (GHG) emission scenarios, land use change scenarios, natural variability, and hydrologic model parameters – are considered to compare the relative source of uncertainty in flood frequency projections. Two land use change scenarios conservation and development, representing possible future land use changes are used for analysis. Results show the highest increase in flood frequency under the combination of medium high GHG emission (A1B) and development scenarios, and the lowest increase under the combination of low GHG emission (B1) and conservation scenarios. Although the combined impact is more significant to flood frequency change than individual scenarios, it does not linearly increase flood frequency. Changes in flood frequency are more sensitive to climate change than land use change in the two catchments for 2050s (2040–2069). Shorter term flood frequency change, 2 and 5 year floods, is highly affected by GCM structure, while longer term flood frequency change above 25 year floods is dominated by natural variability. Projected flood frequency changes more significantly in Johnson creek than Fanno creek. This result indicates that, under expected climate change conditions, an adaptive urban planning based on the conservation scenario could be more effective in less developed Johnson catchment than in the already developed Fanno catchment.

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KOMATSU, Yosuke, Yasuhisa KUZUHA, Kunio TOMOSUGI, and Tokuo KISHII. "RERIONAL FLOOD FREQUENCY ANALYSIS IN SNOW-MELT FLOOD AREA." PROCEEDINGS OF HYDRAULIC ENGINEERING 48 (2004): 115–20. http://dx.doi.org/10.2208/prohe.48.115.

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Nka, B. N., L. Oudin, H. Karambiri, J. E. Paturel, and P. Ribstein. "Trends in West African floods: a comparative analysis with rainfall and vegetation indices." Hydrology and Earth System Sciences Discussions 12, no. 5 (May 29, 2015): 5083–121. http://dx.doi.org/10.5194/hessd-12-5083-2015.

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Abstract. After the drought of the 1970s in West Africa, the variability of rainfall and land use changes affected mostly flow, and recently flooding has been said to be an increasingly common occurrence throughout the whole of West Africa. These changes raised many questions about the impact of climate change on the flood regimes in West African countries. This paper investigates whether floods are becoming more frequent or more severe, and to what extent climate patterns have been responsible for these changes. We analyzed the trends in the floods occurring in 14 catchments within West Africa's main climate zone. The methodology includes two methods for sampling flood events, namely the AM (annual maximum) method and the POT (peak over threshold), and two perspectives of analysis are presented: long-term analysis based on two long flood time series, and a regional perspective involving 14 catchments with shorter series. The Mann–Kendall trend test and the Pettitt break test were used to assess time series stationarity. The trends detected in flood time series were compared to the rainfall index trends and vegetation indices using contingency tables, in order to identify the main driver of change in flood magnitude and flood frequency. The relation between the flood index and the physiographic index was evaluated through a success criterion and the Cramer criterion calculated from the contingency tables. The results point out the existence of trends in flood magnitude and flood frequency time series with two main patterns. Sahelian floods show increasing flood trends and some Sudanian catchments present decreasing flood trends. For the overall catchments studied, the maximum 5 day consecutive rainfall index (Rx5d) seems to follow the flood trend, while the NDVI indices do not show a significant link with the flood trends, meaning that this index has no impact in the behavior of floods in the region.

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Liang, Yulian, Yongli Wang, Yinjun Zhao, Yuan Lu, and Xiaoying Liu. "Analysis and Projection of Flood Hazards over China." Water 11, no. 5 (May 16, 2019): 1022. http://dx.doi.org/10.3390/w11051022.

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Floods have been experienced with greater frequency and more severity under global climate change. To understand the flood hazard and its variation in the future, the current and future flood hazards in the 21st century in China are discussed. Floods and their trends are assessed using the accumulation precipitation during heavy rainfall process (AP_HRP), which are calculated based on historical meteorological observations and the outputs of a global climate model (GCM) under three Representative Concentration Pathway (RCP) scenarios. The flood-causing HRPs counted by the flood-causing critical precipitation (the 60% fractile of AP_HRP) capture more than 70% of historical flood events. The projection results indicate that the flood hazards could increase under RCP4.5 and RCP8.5 and increase slightly under RCP2.6 during the 21st century (2011–2099). The spatial characteristics of flood hazards and their increasing trends under the three RCPs are similar in most areas of China. More floods could occur in southern China, including Guangdong, Hainan, Guangxi and Fujian provinces, which could become more serious in southeastern China and the northern Yunnan province. Construction of water conservancy projects, reservoir dredging, improvement of drainage and irrigation equipment and enhancement of flood control and storage capacity can mitigate the impacts of floods and waterlogging on agriculture.

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Bian, Guodong, Jinkang Du, Mingming Song, Xueliang Zhang, Xingqi Zhang, Runjie Li, Sengyao Wu, Zheng Duan, and Chong-Yu Xu. "Detection and attribution of flood responses to precipitation change and urbanization: a case study in Qinhuai River Basin, Southeast China." Hydrology Research 51, no. 2 (March 26, 2020): 351–65. http://dx.doi.org/10.2166/nh.2020.063.

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Abstract Both flood magnitude and frequency might change under the changing environment. In this study, a procedure combining statistical methods, flood frequency analysis and attribution analysis was proposed to investigate the response of floods to urbanization and precipitation change in the Qinhuai River Basin, an urbanized basin located in Southeast China, over the period from 1986 to 2013. The Mann–Kendall test was employed to detect the gradual trend of the annual maximum streamflow and the peaks over threshold series. The frequency analysis was applied to estimate the changes in the magnitude and frequency of floods between the baseline period (1986–2001) and urbanization period (2002–2013). An attribution analysis was proposed to separate the effects of precipitation change and urbanization on flood sizes between the two periods. Results showed that: (1) there are significant increasing trends in medium and small flood series according to the Mann–Kendall test; (2) the mean and threshold values of flood series in the urbanization period were larger than those in the baseline period, while the standard deviation, coefficient of variation and coefficient of skewness of flood series were both higher during the baseline period than those during the urbanization period; (3) the flood magnitude was higher during the urbanization period than that during the baseline period at the same return period. The relative changes in magnitude were larger for small floods than for big floods from the baseline period to the urbanization period; (4) the contributions of urbanization on floods appeared to amplify with the decreasing return period, while the effects of precipitation diminish. The procedure presented in this study could be useful to detect the changes of floods in the changing environment and conduct the attribution analysis of flood series. The findings of this study are beneficial to further understanding interactions between flood behavior and the drivers, thereby improving flood management in urbanized basins.

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Spekkers, M. H., M. Kok, F. H. L. R. Clemens, and J. A. E. ten Veldhuis. "Decision tree analysis of factors influencing rainfall-related building damage." Natural Hazards and Earth System Sciences Discussions 2, no. 4 (April 1, 2014): 2263–305. http://dx.doi.org/10.5194/nhessd-2-2263-2014.

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Abstract. Flood damage prediction models are essential building blocks in flood risk assessments. Little research has been dedicated so far to damage of small-scale urban floods caused by heavy rainfall, while there is a need for reliable damage models for this flood type among insurers and water authorities. The aim of this paper is to investigate a wide range of damage-influencing factors and their relationships with rainfall-related damage, using decision tree analysis. For this, district-aggregated claim data from private property insurance companies in the Netherlands were analysed, for the period of 1998–2011. The databases include claims of water-related damage, for example, damages related to rainwater intrusion through roofs and pluvial flood water entering buildings at ground floor. Response variables being modelled are average claim size and claim frequency, per district per day. The set of predictors include rainfall-related variables derived from weather radar images, topographic variables from a digital terrain model, building-related variables and socioeconomic indicators of households. Analyses were made separately for property and content damage claim data. Results of decision tree analysis show that claim frequency is most strongly associated with maximum hourly rainfall intensity, followed by real estate value, ground floor area, household income, season (property data only), buildings age (property data only), ownership structure (content data only) and fraction of low-rise buildings (content data only). It was not possible to develop statistically acceptable trees for average claim size, which suggest that variability in average claim size is related to explanatory variables that cannot be defined at the district scale. Cross-validation results show that decision trees were able to predict 22–26% of variance in claim frequency, which is considerably better compared to results from global multiple regression models (11–18% of variance explained). Still, a large part of the variance in claim frequency is left unexplained, which is likely to be caused by variations in data at subdistrict scale and missing explanatory variables.

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Li, Jianzhu, Kun Lei, Ting Zhang, Wei Zhong, Aiqing Kang, Qiushuang Ma, and Ping Feng. "A framework for event-based flood scaling analysis by hydrological modeling in data-scarce regions." Hydrology Research 51, no. 5 (September 11, 2020): 1091–103. http://dx.doi.org/10.2166/nh.2020.042.

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Abstract Flood scaling theory is important for flood predictions in data-scarce regions but is often applied to quantile-based floods that have no physical mechanisms. In this study, we propose a framework for flood prediction in data-scarce regions by event-based flood scaling. After analyzing the factors controlling the flood scaling, flood events are first simulated by a hydrological model with different areally averaged rainfall events and curve number (CN) values as inputs, and the peak discharge of each subcatchment is obtained. Then, the flood scaling is analyzed according to the simulated peak discharge and subcatchment area. Accordingly, the relationship curves between the scaling exponent and the two explanatory factors (rainfall intensity and CN) can be drawn. Assuming that the flood and the corresponding rainfall event have the same frequency, the scaling exponent with a specific flood frequency can be interpolated from these curves.

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Blahušiaková, Andrea, and Milada Matoušková. "Analysis of floods in the upper course of the Hron River in 1930–2010." Geografie 117, no. 4 (2012): 415–33. http://dx.doi.org/10.37040/geografie2012117040415.

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The main focus of this research is concentrated on the flood analyses in the upper course of the Hron River in the period 1930–2010. The study includes an evaluation of the flood seasonality, frequency and extremity in two periods 1930–1991 and 1992–2009. The year 2010 has been added because of a very high amount of precipitation between May–September 2010 which caused extreme flooding. The most extreme flood in the 20th century occurred in October 1974. At the gauging station Banská Bystrica, discharge values reached 560 m3.s−1 which corresponds to the 100-year flood. In the last decade, extreme floods occurred in years 2002 and 2010. The main reason for the flooding was an intense rainfall and local storms with high amount of precipitation. The frequency analysis (in equally long periods 1950–1979 and 1980–2009) proved that there is a higher frequency of floods since 1980 (17 in the period 1950–1979 and 27 between 1980–2009). Higher water levels during floods were reached in the period 1950–1979. The summer floods dominate in both observed periods, but winter floods also occurred very often (7 floods in the period 1950–1979 and 12 in 1980–2009). This is due to the hollow relief of the upper course of the Hron River.

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Fontanazza, C. M., G. Freni, G. La Loggia, and V. Notaro. "Uncertainty evaluation of design rainfall for urban flood risk analysis." Water Science and Technology 63, no. 11 (June 1, 2011): 2641–50. http://dx.doi.org/10.2166/wst.2011.169.

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A reliable and long dataset describing urban flood locations, volumes and depths would be an ideal prerequisite for assessing flood frequency distributions. However, data are often piecemeal and long-term hydraulic modelling is often adopted to estimate floods from historical rainfall series. Long-term modelling approaches are time- and resource-consuming, and synthetically designed rainfalls are often used to estimate flood frequencies. The present paper aims to assess the uncertainty of such an approach and for suggesting improvements in the definition of synthetic rainfall data for flooding frequency analysis. According to this aim, a multivariate statistical analysis based on a copula method was applied to rainfall features (total depth, duration and maximum intensity) to generate synthetic rainfalls that are more consistent with historical events. The procedure was applied to a real case study, and the results were compared with those obtained by simulating other typical synthetic rainfall events linked to intensity–duration–frequency (IDF) curves. The copula-based multi-variate analysis is more robust and adapts well to experimental flood locations even if it is more complex and time-consuming. This study demonstrates that statistical correlations amongst rainfall frequency, duration, volume and peak intensity can partially explain the weak reliability of flood-frequency analyses based on synthetic rainfall events.

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Cerneagă, C., and C. Maftei. "Flood frequency analysis of Casimcea river." IOP Conference Series: Materials Science and Engineering 1138, no. 1 (April 1, 2021): 012014. http://dx.doi.org/10.1088/1757-899x/1138/1/012014.

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Orsini-Zegada, Luis, and Carlos Agustín Escalante-Sandoval. "Flood frequency analysis using synthetic samples." Atmósfera 29, no. 4 (October 1, 2016): 299–309. http://dx.doi.org/10.20937/atm.2016.29.04.02.

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Hosking, J. R. M., and J. R. Wallis. "Paleoflood Hydrology and Flood Frequency Analysis." Water Resources Research 22, no. 4 (April 1986): 543–50. http://dx.doi.org/10.1029/wr022i004p00543.

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He, Jianxun, Axel Anderson, and Caterina Valeo. "Bias compensation in flood frequency analysis." Hydrological Sciences Journal 60, no. 3 (January 19, 2015): 381–401. http://dx.doi.org/10.1080/02626667.2014.885651.

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Bobée, Bernard, and Peter F. Rasmussen. "Recent advances in flood frequency analysis." Reviews of Geophysics 33, S2 (July 1995): 1111–16. http://dx.doi.org/10.1029/95rg00287.

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Markiewicz, Iwona, and Witold G. Strupczewski. "Dispersion measures for flood frequency analysis." Physics and Chemistry of the Earth, Parts A/B/C 34, no. 10-12 (2009): 670–78. http://dx.doi.org/10.1016/j.pce.2009.04.003.

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Cunderlik, Juraj M., and Donald H. Burn. "Non-stationary pooled flood frequency analysis." Journal of Hydrology 276, no. 1-4 (May 2003): 210–23. http://dx.doi.org/10.1016/s0022-1694(03)00062-3.

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Bradley, A. Allen, and Kenneth W. Potter. "Flood frequency analysis of simulated flows." Water Resources Research 28, no. 9 (September 1992): 2375–85. http://dx.doi.org/10.1029/92wr01207.

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Bobée, Bernard, and Fahim Ashkar. "Log-logistic flood frequency analysis — Comment." Journal of Hydrology 107, no. 1-4 (May 1989): 367–70. http://dx.doi.org/10.1016/0022-1694(89)90067-x.

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Ahmad, M. I., C. D. Sinclair, and A. Werritty. "Log-logistic flood frequency analysis — Reply." Journal of Hydrology 107, no. 1-4 (May 1989): 370–72. http://dx.doi.org/10.1016/0022-1694(89)90068-1.

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Durrans, S. R., M. A. Eiffe, W. O. Thomas, and H. M. Goranflo. "Joint Seasonal /Annual Flood Frequency Analysis." Journal of Hydrologic Engineering 8, no. 4 (July 2003): 181–89. http://dx.doi.org/10.1061/(asce)1084-0699(2003)8:4(181).

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Ferro, Vito, and Paolo Porto. "Flood Frequency Analysis for Sicily, Italy." Journal of Hydrologic Engineering 11, no. 2 (March 2006): 110–22. http://dx.doi.org/10.1061/(asce)1084-0699(2006)11:2(110).

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Journal articles on the topic 'Flood frequency analysis'

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