地区线性矩法在太湖流域暴雨频率分析中的应用

介绍了基于水文气象途径的地区线性矩法的概念,通过基于次序统计量的线性矩进行参数估计与基于水文气象一致区的地区分析法相结合,以太湖流域1d时段的年极值降雨资料为例,进行暴雨频率分析。应用水文气象一致区的判别准则,将太湖流域划分为8个水文气象一致区;综合考虑三种拟合优度检测方法,选择1~8区的最优分布线型分别为:GEV、GLO、GEV、GEV、GNO、GNO、GEV、GNO;根据地区分析法原理,估算各雨量站的暴雨频率设计值。分析表明:太湖流域各重现期下的年极值降雨空间分布形态基本一致,西南山区是太湖流域的暴雨高风险区,应该在地区防洪规划中引起重视。结果表明:地区线性矩法具有很高的学术和实用价值,建议在全国范围内推广,作为防洪规划的顶层设计和基础工作,以满足工程防洪设计、地区防洪规划、山洪预警和城市防涝防洪规划等方面的需求。     

考虑不确定度的POT模型在洪水重现期分析中的应用研究

以淮河紫罗山子流域出口日平均流量数据为研究对象,基于超阈值(POT)模型,采用最大似然法估计广义Pareto(GP)分布参数并计算出重现期水平和相应的置信区间范围。拟合优度检验结果显示POT模型在扩大洪水样本提高使用效率的同时,对样本经验点据的适线性也较好。通过对5种时段长度的水文实测流量数据重现期计算发现:实测数据长度对重现期计算结果不确定性有重要影响,在工程水文中推荐选取恰当的置信区间上界作为设计值加以解决。     

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

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

国外区域洪水频率分析方法研究进展

总结了国际上区域洪水频率分析方法的最新研究进展。对经典的标度洪水法进行了评述,阐述了进行区域洪水频率分析时应该遵守的几个原则,总结了关于数据检查、水文分区识别及水文分区均匀性检验等几个关键问题的研究结果。     

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

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

Flood Frequency Analysis of Betwa River,Madhya Pradesh India

Flood is common phenomena worldwide since time immemorial. Recently the change in climatic parameters has drastically affected the pattern and magnitude of flood. India being one of the tropical country face flood and drought situations every year, therefore it needs accurate assessment and forecast of flood for proper management of natural resources.An attempt has been made through the present study which consists frequency analysis on maximum daily discharge data in Betwa river at Basoda, Mohana and Shahijina gauging stations in Madhya Pradesh state using Gumbel’s Extreme value distribution and Log Pearson Type-3 distribution for 20 years period (1993-2012).The result shows that Log Pearson Type-3 distribution is better suited for Betwa basin. The results can be used by civil engineers for deciding the dimensions of hydraulic structures such as spillways, dams, bridges etc. Floods are forecasted for the different return periods for Betwa river.     

Flood inundation mapping and hazard assessment of Baitarani River basin using hydrologic and hydraulic model

Frequent flood is a concern for most of the coastal regions of India. The importance of flood maps in governing strategies for flood risk management is of prime importance. Flood inundation maps are considered dependable output generated from simulation results from hydraulic models in evaluating flood risks. In the present work, a continuous hydrologic-hydraulic model has been implemented for mapping the flood, caused by the Baitarani River of Odisha, India. A rainfall time-series data were fed into the hydrologic model and the runoff generated from the model was given as an input into the hydraulic model. The study was performed using the HEC-HMS model and the FLO-2D model to map the extent of flooding in the area. Shuttle Radar Topographic Mission (SRTM) 90 m Digital Elevation Model (DEM) data, Land use/Land cover map (LULC), soil texture data of the basin area were used to compute the topographic and hydraulic parameters. Flood inundation was simulated using the FLO-2D model and based on the flow depth, hazard zones were specified using the MAPPER tool of the hydraulic model. Bhadrak District was found to be the most hazard-prone district affected by the flood of the Baitarani River. The result of the study exhibited the hydraulic model as a utile tool for generating inundation maps. An approach for assessing the risk of flooding and proper management could help in mitigating the flood. The automated procedure for mapping and the details of the study can be used for planning flood disaster preparedness in the worst affected area.

     

长江流域降水极值的变化趋势

依据1960-2005年长江流域147个气象站逐日降水,ECHAM5/MPI-OM气候模式模拟的长江流域79个格点20世纪实验期(1941-2000年)以及未来3种排放情景(SRES-B1,A1B,A2)下21世纪前50年逐日降水数据,建立年最大强降水和汛期<1.27 mm/d的最长干旱持续天数序列。运用广义极值分布,广义帕雷托分布,广义逻辑分布与韦克比分布等4种分布函数定量拟合了长江流域降水极值的概率分布。研究表明:韦克比分布函数能够较好地拟合长江流域降水极值的概率分布。在3种排放情景下,未来降水极值的重现期呈现不同的空间分布特征。长江流域,尤其是中下游大部地区,1951-2000年间的50年一遇强降水和干旱事件,在2001-2050年间发展成为25年一遇降水极值事件。未来气候变暖条件下,降水极值重现期出现的这种变化趋势,将会对水资源趋势产生重大的影响。     

Bivariate frequency analysis of low flow using copula functions (case study: Dez River Basin,Iran)

Accurate estimation of low flow as a criterion for different objectives in water resource management, including drought is of crucial importance. Despite the complex nature of water deficits, univariate methods have often been used to analyze the frequency of low flows. In this study, low flows of Dez River basin were examined during period of 1956–2012 using copula functions at the upstream of headbranches’ junction. For this purpose, at first 7-day series of low flow was extracted at the studied stations, then their homogeneity was examined by Mann–Kendall test. The results indicated that 7-day low flow series of Dez basin were homogenous. In the next stage, 12 different distribution functions were fitted onto the low flow data. Finally, for Sepid Dasht Sezar (SDS), Sepid Dasht Zaz (SDZ), and Tang Panj Bakhtiyari (TPB) stations, logistic distribution had the best fit, while for Tang Panj Sezar (TPS) station, GEV distribution enjoyed the best fit. After specifying the best fitted marginal distributions, seven different copula functions including Ali–Mikhail–Haq (AMH), Frank, Clayton, Galambos, Farlie–Gumbel–Morgenstern (FGM), Gumbel–Hougaard (GH), and Plackett were used for bivariate frequency analysis of the 7-day low flow series. The results revealed that the GH copula had the best fitness on paired data of SDS and SDZ stations. For TPS and TPB stations, Frank copula has had the best correspondence with empirical copula values. Next, joint and conditional return periods were calculated for the low flow series at the upstream of branches’ junction. The results of this study indicated that the risk of incidence of severe drought is higher in upstream stations (SDZ and SDS) when compared with downstream stations (TPB and TPS) in Dez basin. Generally, application of multivariate analysis allows researchers to investigate hydrological events with a more comprehensive view by considering the simultaneous effect of the influencing factors on the phenomenon of interest. It also enables them to evaluate different combinations of required scenarios for integrated management of basin and planning to cope with the damages caused by natural phenomena.     

Timing and maximum flood level of the Early Holocene glacial lake Nedre Glomsjø outburst flood,Norway

This study discusses the timing and maximum flood level of the Nedre Glomsjø outburst flood, Norway, based on sediment records retrieved from 15 bog and lake basins located close to the purported maximum flooded level. The sediment records in 12 of the basins consist of a distinct light-coloured silty bed that is correlated to the outburst-flood-deposited ‘Romerike Silt Bed’ identified elsewhere in the region. The silt bed is recorded in basins up to a certain elevation and is absent above this level. The new maximum flood level inferred from the basin sediment records exceeds the established landform-induced palaeostage indicators by 5–10 m. The data indicate a higher maximum flood level and larger inundation area than previously suggested and highlight the importance of acquiring a wide range of geological data when reconstructing palaeofloods. Radiocarbon dates of terrestrial macrofossils found stratigraphically above and below the Romerike Silt Bed suggest that the glacial lake Nedre Glomsjø outburst flood occurred between 10.5 and 10.3 cal. ka BP. The new and well-constrained timing of the outburst flood is beneficial for reconstructing regional deglaciation and provides a precise age for the Romerike Silt Bed chronostratigraphical marker, which is of value for studies in SE Norway and adjacent regions.     

Regional frequency analysis of autumnal floods in the province of Quebec, Canada

A large number of models have been proposed over the last years for regional flood frequency analysis in northern regions. However, these models dealt generally with snowmelt-caused spring floods. This paper deals with the adaptation, application, and comparison of two regional frequency analysis methods, canonical correlation analysis (CCA) and universal canonical kriging (UCK), on autumnal floods of 29 stations from the C?te-Nord region (QC, Canada). Three possible periods during which autumnal floods can take place are tested. The absolute and specific flood peak and volume quantiles are also studied. A jack-knife resampling procedure is applied to compare the performance of each model according to the selected period and the type of quantile. The period of September 1st to December 15th is found to be optimal to represent autumnal floods and specific quantiles were shown to lead to better results than absolute quantiles. Variables that explain best the autumnal floods are the basin area, the fraction of the area covered with lakes, and the average of mean July, August, and September maximal temperatures. The CCA model performs slightly better than UCK.     

Joint pattern of seasonal hydrological droughts and floods alternation in China’s Huai River Basin using the multivariate L-moments

Under the current condition of climate change, droughts and floods occur more frequently, and events in which flooding occurs after a prolonged drought or a drought occurs after an extreme flood may have a more severe impact on natural systems and human lives. This challenges the traditional approach wherein droughts and floods are considered separately, which may largely underestimate the risk of the disasters. In our study, the sudden alternation of droughts and flood events (ADFEs) between adjacent seasons is studied using the multivariate L-moments theory and the bivariate copula functions in the Huai River Basin (HRB) of China with monthly streamflow data at 32 hydrological stations from 1956 to 2012. The dry and wet conditions are characterized by the standardized streamflow index (SSI) at a 3-month time scale. The results show that: (1) The summer streamflow makes the largest contribution to the annual streamflow, followed by the autumn streamflow and spring streamflow. (2) The entire study area can be divided into five homogeneous sub-regions using the multivariate regional homogeneity test. The generalized logistic distribution (GLO) and log-normal distribution (LN3) are acceptable to be the optimal marginal distributions under most conditions, and the Frank copula is more appropriate for spring-summer and summer-autumn SSI series. Continuous flood events dominate at most sites both in spring-summer and summer-autumn (with an average frequency of 13.78% and 17.06%, respectively), while continuous drought events come second (with an average frequency of 11.27% and 13.79%, respectively). Moreover, seasonal ADFEs most probably occurred near the mainstream of HRB, and drought and flood events are more likely to occur in summer-autumn than in spring-summer.     

Optimal design of flood-control multi-reservoir system on a watershed scale

Flood events have the highest damage costs and losses among natural hazards. There are different types of measures to mitigate flood damage costs and their negative consequences. Application of flood-control reservoirs or detention dams, as one of the main measures, may decrease devastating flood effects or even may cause to intensify flood damages in the watershed by a poor design with tremendous construction costs. Optimal design of a flood-control multi-reservoir system can simultaneously minimize investment costs of constructions and potential flood damage costs. This study proposes a simulation-based optimization approach to optimize the design of multi-reservoirs for flood control in the watershed by coupling the MIKE-11 hydrodynamic model and the NSGA-II multi-objective optimization model. The present approach provides the Pareto optimal solutions between two conflict objectives of minimizing total investment costs and the expected flood damage costs in the watershed. Application of the proposed model for a small watershed in central part of Iran as a case study shows that optimal designs of multi-reservoir systems can efficiently reduce construction costs, flood peaks and their corresponding damage costs at the downstream reaches of the basin.     

A study on selection of probability distributions for at-site flood frequency analysis in Australia

The most direct method of design flood estimation is at-site flood frequency analysis, which relies on a relatively long period of recorded streamflow data at a given site. Selection of an appropriate probability distribution and associated parameter estimation procedure is of prime importance in at-site flood frequency analysis. The choice of the probability distribution for a given application is generally made arbitrarily as there is no sound physical basis to justify the selection. In this study, an attempt is made to investigate the suitability of as many as fifteen different probability distributions and three parameter estimation methods based on a large Australian annual maximum flood data set. A total of four goodness-of-fit tests are adopted, i.e., the Akaike information criterion, the Bayesian information criterion, Anderson–Darling test, and Kolmogorov–Smirnov test, to identify the best-fit probability distributions. Furthermore, the L-moments ratio diagram is used to make a visual assessment of the alternative distributions. It has been found that a single distribution cannot be specified as the best-fit distribution for all the Australian states as it was recommended in the Australian rainfall and runoff 1987. The log-Pearson 3, generalized extreme value, and generalized Pareto distributions have been identified as the top three best-fit distributions. It is thus recommended that these three distributions should be compared as a minimum in practical applications when making the final selection of the best-fit probability distribution in a given application in Australia.     

极值分布和P-III型分布线性矩法在区域洪水频率分析中的检验

以江西省和福建省的86个水文站的年最大洪水资料为样本,在成因水文分区———模糊聚类法的基础上,采用线性矩区域综合方法进行区域洪水频率分析,并选用两种区域洪水分布线型:通用极值分布(GEV)、P-III型分布来检验这两省的洪水特性。结果表明,P-III型分布优于GEV分布。     

新疆塔里木河流域洪水过程集聚性及低频气候影响

运用Cox回归模型、月频率法以及离散指数法,研究了新疆塔里木河（塔河）流域8个水文站点POT抽样和5个区域洪水序列时间集聚性特征以及受低频气候变化的影响。结果表明:受气候变化的影响,塔河流域洪水序列呈现显著集聚性特征,洪水发生频率高的时期往往也是大量级洪峰集中发生的时期,这是塔河流域洪灾损失居高不下的主要原因;Cox回归模型拟合的气候指标系数值为正值的站点和区域,气候指标正相位导致相同超过概率的洪水发生时间提前,而相同发生时间的洪水发生超过概率降低,气候指标值为负值时则相反;塔河流域大部分水文站点和区域洪水发生的超过概率均对气候指标变化有较好响应,这一现象有利于塔河流域洪水风险控制与洪灾管理;塔河流域站点洪水序列多无年际集聚性现象,而区域洪水序列的年际集聚性特征显著。     

Comparison of the performance of power law and probability distributions in the frequency analysis of flood in Dez Basin,Iran

Determination of the return period of design flood depends on the nature of the project and the consequences of the flood and is based on economic criteria, human casualties, and hydrological factors. Underestimation of flood might result in casualties and economic damages, while the overestimation leads to capital waste. Therefore, in this research, the flood frequency analysis of Dez Basin, Iran was conducted within the period of 1956–2012 using power law approach together with ordinary distributions, including normal, log normal, Pearson type III, exponential, gamma, generalized extreme value, Nakagami, Rayleigh, logistic, generalized logistic, generalized Pareto, and Weibull distributions. The power law comes from the fractal nature of earth science phenomena such as precipitation and runoff. Accordingly, in this research the partial duration flood series of five hydrometric stations in Dez Basin were extracted using power law with the intervals of 7, 14, 30, and 60 days and then compared with the annual maxima. The results indicated that the annual maxima were not suitable for frequency analysis of the flood in Dez Basin, and the 30-day partial duration series obtained from the power law has a better correspondence with the flow and properties of the Dez Basin. The independence and stationarity of the 30-day partial duration series were examined by Wald–Wolfowitz test, confirming the independence of the considered series. Next, the power distribution and the typical statistical distributions were fitted onto the data of the flood in Dez Basin, with the performance of each distribution being investigated using normalized root-mean-square error and Nash–Sutcliffe criteria. The results revealed that in the SDZ and TPB stations, power distribution had a better performance than other considered distributions. Moreover, in the SDS, TPS, and TZ stations the power distribution stood in the second rank in terms of the best distribution. As the performance of power distribution in the estimation of the flood in Dez Basin has been very satisfactory and calculation of its parameters and its application is easier than ordinary probability distributions, thus it can be suggested as the superior distribution for flood frequency analysis in Dez Basin.     

An integrated 1D–2D hydraulic modelling approach to assess the sensitivity of a coastal region to compound flooding hazard under climate change

Coastal regions are dynamic areas that often lie at the junction of different natural hazards. Extreme events such as storm surges and high precipitation are significant sources of concern for flood management. As climatic changes and sea-level rise put further pressure on these vulnerable systems, there is a need for a better understanding of the implications of compounding hazards. Recent computational advances in hydraulic modelling offer new opportunities to support decision-making and adaptation. Our research makes use of recently released features in the HEC-RAS version 5.0 software to develop an integrated 1D–2D hydrodynamic model. Using extreme value analysis with the Peaks-Over-Threshold method to define extreme scenarios, the model was applied to the eastern coast of the UK. The sensitivity of the protected wetland known as the Broads to a combination of fluvial, tidal and coastal sources of flooding was assessed, accounting for different rates of twenty-first century sea-level rise up to the year 2100. The 1D–2D approach led to a more detailed representation of inundation in coastal urban areas, while allowing for interactions with more fluvially dominated inland areas to be captured. While flooding was primarily driven by increased sea levels, combined events exacerbated flooded area by 5–40% and average depth by 10–32%, affecting different locations depending on the scenario. The results emphasise the importance of catchment-scale strategies that account for potentially interacting sources of flooding.

     

Risk analysis and influencing factors of drought and flood disasters in China

The risk analysis of flood and drought disasters and the study of their influencing factors enhance our understanding of the temporal and spatial variation law of disasters and help identify the main factors affecting disasters. This paper uses the provincial administrative region of China as the research area. The proportion of the disaster area represents the degree of the disaster. The statistical distribution of the proportions was optimized from 10 alternative distributions based on a KS test, and the disaster risk was analyzed. Thirty-five indicators were selected from nature, agriculture and the social economy as alternative factors. The main factors affecting flood and drought disasters were selected by Pearson, Spearman and Kendall correlation coefficient test. The results demonstrated that the distribution of floods and drought is right-skewed, and the gamma distribution is the best statistical distribution for fitting disasters. In terms of time, the risk of flood and drought disasters in all regions showed a downward trend. Economic development and the enhancement of the ability to resist disasters were the main reasons for the change in disasters. Spatially, the areas with high drought risk were mainly distributed in Northeast and North China, and the areas with high flood risk were mainly distributed in the south, especially in Hubei, Hunan, Jiangxi and Anhui. The distribution of floods and drought disasters was consistent with the distribution characteristics of precipitation and water resources in China. Among the natural factors, precipitation was the main factor causing changes in floods and drought disasters. Among the agricultural and socioeconomic factors, the indicators reflecting the disaster resistance ability and regional economic development level were closely related to flood and drought disasters. The research results have reference significance for disaster classification, disaster formation mechanisms and flood and drought resistance.

     

Regional rating curve models of suspended sediment transport for Turkey

Estimations of annual suspended sediment loads are required for various types of water resources studies. Often estimation of the sediment load is needed for ungauged watersheds. Regionalization methods provide a practical solution to solve such problems. The purpose of this study is to classify suspended sediment yields in watersheds into homogeneous regions in order to identify their regional sediment rating curves. This study has been carried out for suspended sediment stations on 26 main basins of Turkey. Long term-scale suspended sediment rating curves of 115 gauging stations in Turkey were classified using cluster analysis on the basis of hydrological homogeneity. An agglomerative hierarchical clustering algorithm is used so that stations from different geographical locations are considered in the same cluster independently of their geographical location. 115 gauging stations were clustered into 4 different homogenous regions and the regional suspended sediment rating curve was developed for each region. The performance efficiencies of the developed regional rating curves were evaluated for 8 test stations and compared to the performances of rating curves in test sites. A regionalization model is developed for estimating suspended sediment rating curves for ungauged sites in Turkey. The developed regional rating curve models result in very close performances to those of their corresponding site rating curves.