Local and regional flood frequency analysis based on hierarchical Bayesian model in Dongting Lake Basin,China

This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study area were analyzed with the HB model.The generalized extreme value(GEV)distribution was selected as the extreme flood distribution,and the GEV distribution location and scale parameters were spatially modeled through a regression approach with the drainage area as a covariate.The Markov chain Monte Carlo(MCMC)method with Gibbs sampling was employed to calculate the posterior distribution in the HB model.The results showed that the proposed HB model provided satisfactory Bayesian credible intervals for flood quantiles,while the traditional delta method could not provide reliable uncertainty estimations for large flood quantiles,due to the fact that the lower confidence bounds tended to decrease as the return periods increased.Furthermore,the HB model for regional analysis allowed for a reduction in the value of some restrictive assumptions in the traditional index flood method,such as the homogeneity region assumption and the scale invariance assumption.The HB model can also provide an uncertainty band of flood quantile prediction at a poorly gauged or ungauged site,but the index flood method with L-moments does not demonstrate this uncertainty directly.Therefore,the HB model is an effective method of implementing the flexible local and regional frequency analysis scheme,and of quantifying the associated predictive uncertainty.

Rising trends of global precipitable water vapor and its correlation with flood frequency

Using 4 global reanalysis data sets, significant upward trends of precipitable water vapor(PWV) were found in the 3 time periods of 1958-2020, 1979-2020, and 2000-2020. During 1958-2020, the global PWV trends obtained using the ERA5 and JRA55 data sets are 0.19 ± 0.01 mm per decade(1.15 ± 0.31%)and 0.23 ± 0.01 mm per decade(1.45 ± 0.32%), respectively. The PWV trends obtained using the ERA5,JRA55, NCEP-NCAR, and NCEP-DOE data sets are 0.22 ± 0.01 mm per decade(1.18 ± 0.54%),0.21 ± 0.00 mm per decade(1.76 ± 0.56%), 0.27 ± 0.01 mm per decade(2.20 ± 0.70%) and 0.28 ± 0.01 mm per decade(2.19 ± 0.70%) for the period 1979-2020. During 2000-2020, the PWV trends obtained using ERA5, JRA55, NCEP-DOE, and NCEP-NCAR data sets are 0.40 ± 0.25 mm per decade(2.66 ± 1.51%),0.37 ± 0.24 mm per decade(2.19 ± 1.54%), 0.40 ± 0.26 mm per decade(1.96 ± 1.53%) and 0.36 ± 0.25 mm per decade(2.47 ± 1.72%), respectively. Rising PWV has a positive impact on changes in precipitation,increasing the probability of extreme precipitation and then changing the frequency of flood disasters.Therefore, exploring the relationship between PWV(derived from ERA5 and JRA55) change and flood disaster frequency from 1958 to 2020 revealed a significant positive correlation between them, with correlation coefficients of 0.68 and 0.79, respectively, which explains the effect of climate change on the increase in flood disaster frequency to a certain extent. The study can provide a reference for assessing the evolution of flood disasters and predicting their frequency trends.

Accounting for the Effects of Climate Variability in Regional Flood Frequency Estimates in Western Nigeria

Extreme flood events are becoming more frequent and intense in recent times, owing to climate change and other anthropogenic factors. Nigeria, the case-study for this research experiences recurrent flooding, with the most disastrous being the 2012 flood event that resulted in unprecedented damage to infrastructure, displacement of people, socio-economic disruption, and loss of lives. To mitigate and minimize the impact of such floods now and in the future, effective planning is required, underpinned by analytics based on reliable data and information. Such data are seldom available in many developing regions, owing to financial, technical, and organizational drawbacks that result in short-length and inadequate historical data that are prone to uncertainties if directly applied for flood frequency estimation. This study applies regional Flood Frequency Analysis (FFA) to curtail deficiencies in historical data, by agglomerating data from various sites with similar hydro-geomorphological characteristics and is governed by a similar probability distribution, differing only by an “index-flood”;as well as accounting for climate variability effect. Data from 17 gauging stations within the Ogun-Osun River Basin in Western Nigeria were analysed, resulting in the delineation of 3 sub-regions, of which 2 were homogeneous and 1 heterogeneous. The Generalized Logistic distribution was fitted to the annual maximum flood series for the 2 homogeneous regions to estimate flood magnitudes and the probability of occurrence while accounting for climate variability. The influence of climate variability on flood estimates in the region was linked to the Madden-Julian Oscillation (MJO) climate indices and resulted in increased flood magnitude for regional and direct flood frequency estimates varying from 0% - 35% and demonstrate that multi-decadal changes in atmospheric conditions influence both small and large floods. The results reveal the value of considering climate variability for flood frequency analysis, especially when non-stationarity is established by homogeneity analysis.

Flood Frequency Analysis at Oshun River in Asejire Dam Site, Nigeria

Flood frequency analysis procedure was performed on annual maximum discharge data of River Oshun at Iwo in Osun State, Nigeria for the period 1985 to 2002 utilizing three probability distribution models namely： Extreme EVI （value Type-l）, LN （Log normal） and LPIII （Log Pearson Type III）. The models were used to predict and compare corresponding flood discharge estimates at 2, 5, 10, 25, 50, 100 and 200 years return periods. The results indicated that Extreme Value Type 1 distribution predicted discharge values ranging from 26.6 m3/s for two years to 431.8 m3/s for 200 years return periods; the Log Pearson Type III distribution predicted discharge values ranging from 127.2 m3/s for two years to 399.54 m3/s for 200 years return periods and the Log normal distribution predicted discharge values ranging from 116.2 m3/s for two years to 643.9 m3/s for 200 years return periods. From the results~ it was concluded that for lower return periods （T_〈 50 yrs） Extreme Value Type 1 and Log Pearson Type III could be used to estimate flood quantile values at the station while for higher return periods （T 〉 50 yrs） Log Normal probability distribution model which gives higher estimates could be utilized for safe design in view of the short length of discharge records used for the analysis.

Impacts of water surface area of watershed on design flood

In order to analyze the impact of the water surface area of a watershed on the design flood, the watershed was classified into a land watershed and a water surface watershed for flood flow calculation at the same time interval. Then, the design flood of the whole watershed was obtained by adding the two flood flows together. Using this method, we calculated design floods with different water surface areas of three reservoirs and analyzed the impact of water surface area on the flood volume and peak flow. The results indicate that larger water surface areas lead to greater impacts on the flood volume and peak flow. For the same watershed area, the impact of water surface area on the flood volume and peak flow is positively proportional to the flood frequency, i.e., the higher the frequency, the greater the impact becomes.

Floodplain Hazard Mitigations, Solutions and Recommendations for Wadi Asia in Jeddah-Saudi Arabia

No simple solution to flood prevention is accessible. This research provides a brief summary of the hydrologic and hydraulic methodology that can be used to develop specific details that integrated the flood information tool. It permits rapid analysis of a wide variety of stream discharge data and topographic mapping to avoid the flood hazard over entire floodplain boundaries. This paper focuses on the water floodplain hazard in Wadi Asla-Jaddah-Saudi Arabia. The most common type of rainfall in the study area is that accompanied by thunderstorms, which usually fall during the winter season as well as in the spring. The primarily evaluation of this problem and the solution is contemplate. The more essential and ＂doable＂ elements of a solutions and recommendations are discussed in this research.

A 249-Year Record of Floods at Appleby in Westmorland, UK

An analysis of nearly 250 years of flood records on the river Eden at Appleby-in-Westmorland has enabled a flood frequency relationship to be established. The most severe floods were in the late 18th and early 19th century. With such a long history of flooding, some remedial measures would have been expected but the local people have, to some extent, adapted to the flood hazard by means of temporary and permanent flood proofing methods such as a cemented board across a doorway and removable flood boards. These measures were overwhelmed during the 2015 flood, as were the flood gates installed by the Environment Agency in 1998. A higher level of protection from floods at Appleby is called for.

Flood Risk for Embanked Rivers

Flood frequency analysis (FFA) concentrates on peak flows of flood hydrographs. However, floods that last years devastated large parts of Poland lead us to revision of the views on the assessment of flood risk in Poland. It turned out that it is the prolonged exposure to high water on levees that causes floods, not only the water overflowing the levee crest. This is because, the levees are weakened by water and their disruption occurs when it seems that the danger is over, i.e. after passing culmination. Two main causes of inundation of embanked rivers, namely over-crest flow and wash out of the levees, are combined to assess the total risk of inundation. Therefore the risk of inundation is the total of risk of exceeding embankment crest by flood peak and risk of washout of levees. Hence, while modeling the flood events in addition to the maximum flow one should consider also the duration of high water in a river channel, Analysis of the frequency of annual peak flows based on annual maxima and peaks over threshold is the subject of countless publications. Therefore we will here mainly modeling the duration of high water levels. In the paper the two-component model of flood hydrograph shape i.e. “duration of flooding-discharge- probability of nonexceedance” (DqF), with the methodology of its parameters estimation for stationary case was developed as a completion to the classical FFA with possible extension to non stationary flood regime. The model combined with the technical evaluation of probability of levees breach due to the d-days duration of flow above alarm stage gives the annual probability of inundation caused by the embankment breaking. The results of theoretical research were supplemented by a practical example of the model application to the series for daily flow in the Vistula River in Szczucin. Regardless promising results, this method is still in its infancy despite its great cognitive potential and practical importance. Therefore, we would like to point to the usefulness and necessity of the DqF models to the one-dimensional analysis of the peak flood hydrographs and to flood risk analysis. This approach constitutes a new direction in FFA for embanked rivers.

On Return Periodof the Largest Historical Flood

The use of nonsystematic 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 though the magnitudes of historic floods are properly assessed, a problem of their retun periods remains unsolved. Only largest flood (XM) is known during whole historical period and its occurrence carves the mark of the beginning of the historical period and defines its length (L). So, it is a 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, i.e. , gives the severe upward bias. Problem is to estimate the time period (M) representative of the largest observed flood XM. From the discrete uniform distribution with support of the probability of the L position of XM one gets ?which has been taken as the return period of XM and as the effective historical record length. 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 maximum likelihood (ML) method with various length of systematic record (N) and various estimates of historical period length ?com- paring accuracy with the case when only systematic records alone (N) are used. The i-th simula- tion procedure incorporates 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 (B) and root mean square error (RMSE) of the quantile of interest and widely discussed.

Using Copula functions to predict climatic change impacts on floods in river source regions

Flood frequency in river source regions is significantly affected by rainfall and snowmelt as part of climatic changes.A traditional univariate flood frequency analysis cannot reflect the complexity of floods,and when used in isolation,it can only underestimate flood risk.For effective flood prevention and mitigation,it is essential to consider the combined effects of precipitation and snowmelt.Copula functions can effectively quantify the joint distribution relationship between floods and their associated variables without restrictions on their distribution characteristics.This study uses copula functions to consider a multivariate probability distribution model of flood peak flow(Q)with cumulative snowmelt(CSm)and cumulative precipitation(CPr)for the Hutubi River basin located in northern Xinjiang,China.The joint frequencies of rainfall and snowmelt floods are predicted using copula models based on the Coupled Model Intercomparison Project Phase 6 data.The results show that Q has a significant positive correlation with 24-d CSm(r=0.559,p=0.002)and 23-d CPr(r=0.965,p<0.05).Flood frequency will increase in the future,and mid-(2050e2074)and long-term(2075e2099)floods will be more severe than those in the near-term(2025e2049).The probability of flood occurrence is higher under the SSP2-4.5 and SSP1-2.6 scenarios than under SSP5-8.5.Precipitation during the historical period(1990e2014)led to extreme floods,and increasing future precipitation trends are found to be insignificant.Snowmelt increases with rising temperatures and occurs earlier than estimated,leading to an earlier flood period in the basin and more frequent snowmelt floods.The Q under the joint return period is larger than that during the same univariate return period.This difference indicates that neglecting the interaction between precipitation and snowmelt for floods leads to an underestimation of the flood risk(with underestimations ranging from 0.3%to 22%).The underestimations decrease with an increase in the return period.The joint risks of rainfall or snowmelt according to various flood periods should be considered for rivers with multi-source runoff recharge in flood control design.This study reveals the joint impact of precipitation and snowmelt on extreme floods under climate change in river source regions.This study also provides a scientific basis for regional flood prevention and mitigation strategies,as well as for the rational allocation of water resources.

Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Gorges Reservoir Area in China

This study develops a multivariate eco-hydrological risk-assessment framework based on the multivari-ate copula method in order to evaluate the occurrence of extreme eco-hydrological events for the Xiangxi River within the Three Gorges Reservoir （TGR） area in China. Parameter uncertainties in marginal distri-butions and dependence structure are quantified by a Markov chain Monte Carlo （MCMC） algorithm. Uncertainties in the joint return periods are evaluated based on the posterior distributions. The proba- bilistic features of bivariate and multivariate hydrological risk are also characterized. The results show that the obtained predictive intervals bracketed the observations well, especially for flood duration. The uncertainty for the joint return period in ＂AND＂ case increases with an increase in the return period for univariate flood variables. Furthermore, a low design discharge and high service time may lead to high bivariate hydrological risk with great uncertainty.

THE TRANSFORMED NONPARAMETRIC FLOOD FREQUENCY ANALYSIS

The nonparametric kernel estimation of probability density function (PDF) pro-vides a uniform and accurate estimate of flood frequency-magnitude relationship.However, the kernel estimate has the disadvantage that the smoothing factor h is estimate empirically and is not locally adjusted, thus possibly resulting in deteri oration of density estimate when PDF is not smooth and is heavy-tailed. Such a problem can be alleviate by estimating the density of a transformed random vari able, and then taking the inverse transform. A new and efficient circular transform is proposed and investigated in this paper

EXPERIMENTAL STUDY ON PREVENTING FLOOD OF 1% FREQUENCY IN HUAIHE RIVER

After having completed river regulation work in recent years, the dike distance up the reach of Lutaizi has been extended to 1.5 2.0 km in the Huaihe river. When the middle flood happened,such as those in 1956, 1982 and 1991, flood can pass through safely. If the flood of 1% frequency happens, the flood discharge at Lutaizi will be larger than safe flood discharge 10000 m 3/s in downstream Lutaizi. By storing flood with the Linhuaigang sluice, the discharge of Lutaizi will not be over 10000 m 3/s. Cities in downstream Lutaizi will be free from flood.