Regional Flood Frequency Analysis of Mahi-Sabarmati Basin (Subzone 3-a) using Index Flood Procedure with L-Moments

With the objective of investigating the hydrological homogeneity of India's hydrometeorological subzone 3-a and identification of a suitable frequency distribution for it, a regional flood frequency analysis has been carried out using the index flood procedure and the L-moments. Based on analysis of flood data at 12 gauged sites, the Mahi-Sabarmati basin is shown to be hydrologically homogeneous and follows the generalized normal distribution. Regional curve developed based on the analysis has been recommended for carrying out flood frequency analysis at both gauged and ungauged sites in this region.     

Regional Flood Frequency Analysis of North-Bank of the River Brahmaputra by Using LH-Moments

In this study LH-moment proposed by Wang (Water Resour Res 33(12):2841–2848, 1997) has been used for regional flood frequency analysis of the North-Bank region of the river Brahmaputra, India. Three probability distributions i.e. generalized extreme value (GEV), generalized logistic (GLO) and generalized Pareto (GPA) has been used for each level of LH-moments i.e. L, L₁, L₂, L₃ and L₄. The regional frequency analysis procedure proposed by Hosking and Wallis (Water Resour Res 29(2):271–281, 1993) for L-moments i.e. discordancy measure for screening the data, heterogeneity measure for formation of homogeneous region and goodness-of-fit test have been used for each level of LH-moments. Based on the LH-moment ratio diagram and ∣Z∣-statistic criteria, GEV distribution for level one LH-moment is identified as the robust distribution for the study area. For estimation of floods of various return periods for both gauged and ungauged catchments of the study area, regional flood frequency relationships have been developed by using the level one LH-moment based on GEV distribution. A comparative study has been performed between L-moments and LH-moments for the study area. It is observed from comparative study that the regional flood frequency analysis based on the GEV distribution by using level one LH-moment (L₁) is superior to the use of L-moments.     

Use of L-Moments Approach for Regional Flood Frequency Analysis in Sicily, Italy

Extremely great floods are among environmental events with the most disastrous consequences for the entire world. Estimates of their return periods and design values are of great importance in hydrologic modeling, engineering practice for water resources and reservoirs design and management, planning for weather-related emergencies, etc. Regional flood frequency analysis resolves the problem of estimating the extreme flood events for catchments having short data records or ungauged catchments. This paper analyzes annual maximum peak flood discharge data recorded from more than 50 stream flow gauging sites in Sicily, Italy, in order to derive regional flood frequency curves. First these data are analyzed to point out some problems concerning the homogeneity of the single time series. On the basis of the L-moments and using cluster analysis techniques, the entire region is subdivided in five subregions whose homogeneity is tested using the L-moments based heterogeneity measure. Comparative regional flood frequency analysis studies are carried out employing the L-moments based commonly used frequency distributions. Based on the L-moment ratio diagram and other statistic criteria, generalized extreme value (GEV) distribution is identified as the robust distribution for the study area. Regional flood frequency relationships are developed to estimate floods at various return periods for gauged and ungauged catchments in different subregions of the Sicily. These relationships have been implemented using the L-moment based GEV distribution and a regional relation between mean annual peak flood and some geomorphologic and climatic parameters of catchments.     

Classification of Drainage Basins Based on Readily Available Information

Classification of drainage basins into groups with similar response to meteorological forcing can be very helpful in cases of transfer of hydrological information in space such as in streamflow prediction in ungauged basins. It is also critical for the implementation of the Water Framework Directive and related legislative tools of the EU such as the Flood Directive. The focus is testing the ability to classify drainage basins using climate-based variables and geomorphometric characteristics as predictors. Precipitation is selected as the climate-based variable, since this is commonly measured in the majority of basins. Geomorphometric characteristics include, among others, the average ground slope and drainage density; these are derived from a Digital Terrain Model. The employed methodology involves two steps. In the first step we perform unsupervised classification through using the fuzzy c-means method to identify basin classes that serve as the reference classes in the second step of analysis. A set of hydrological signatures is used in the first step, which includes the runoff ratio, the baseflow index, the slope of the flow duration curve, and the snow day ratio. In the second step we perform supervised classification through using the k-Nearest Neighbour method which maps predictors to basin classes. Last, the success rate of the obtained classification is assessed through using jack-knife re-sampling. Twenty-four gauged basins in mainland Greece are used, which are classified into four classes. The employed methodology proved to be successful in more than 95 % of cases of recognition of the class for an ungauged basin.     

基于聚类分析的水文相似流域研究

在洪水预警预报中,一些中小流域常常由于水文资料短缺造成分析计算困难。随着流域下垫面地形、植被、土壤等数据的大量获取和数据挖掘技术的不断发展,应用聚类分析等无指导学习方法对流域下垫面大量数据进行分析,根据对象之间距离最近的原则对流域进行分组,得到水文相似流域,从而将有水文资料流域的水文参数应用于水文资料短缺的相似流域,使洪水预报得以实现。选取浙江省118个具有20年以上雨水情资料的流域进行研究,采用流域长度、流域宽度、河长、河流比降、流域平均坡度、流域形状系数、多年平均1,3,6和12 h面最大降水等10个指标,应用主成分分析对数据进行降维,进而对流域进行聚类分析,将浙江省流域分为23个相似组。在分组基础上,选取其中两组中径流资料大于20年的站点进行多年平均最大洪峰、洪量比对,验证水文相似流域分类合理性。结果表明相似流域组内年最大洪峰、年最大平均1,3,6和12 h洪量具有较大相似性,分类较为合理,从统计学角度为浙江省的洪水预警预报提供新的理论与思路。     

Regional flood frequency analysis in the central‐western river basins of Argentina

Knowing the probability of occurrence of a flood event is an important issue for water resources planning. At‐site probability models require a long extension of hydrological data for robust estimation of low‐frequency events. As the mean record length of 25 gauge stations in western river basins of Argentina is 49 years (until 2010), regional models are an interesting tool to determine mountain rivers system dynamics. This study aims to estimate low‐frequency quantiles of annual maximum flow in Argentinean western river basins (28°S–37°S) applying regional frequency analysis based on the L‐moments method. Besides, mean annual maximum flow of 75 gauge stations (22°S–52°S) was analysed. First, an exploratory data analysis was performed; normality, independence, and randomness were accepted in the 27%, 87%, and 91% of cases, respectively. Increasing trends in annual maximum flows in the north‐western and central‐western rivers of Argentina were detected, whereas decreasing trends in annual maximum flow in the Patagonian Andes were identified. Base on at‐site characteristics and at‐site statistics, a homogeneous region of 12 stations with a record period of 568 years was formed. General extreme value was the most appropriate distribution for this homogeneous study region. Estimation accuracy using Monte Carlo simulations was performed. The error bounds were set at 90%, the mean square error was 9.23%, and the relative bias was 1.6%. The regional method performed better than the at‐site estimation.     

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.     

Quantification of Expected Changes in Peak Flow Quantiles in Climate Change by Combining Continuous Hydrological Modelling with the Modified Curve Number Method

Climate projections point to modifications in the magnitude, frequency and timing of floods in the future. However, robust methodologies to quantify how climate change will modify the catchment response in flood events are required. Continuous hydrological modelling usually smooth magnitudes of extreme events. This paper proposes a methodology to improve the assessment of flood changes in the future driven by climate change. Climate change projections of the EURO-CORDEX programme obtained under the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC) supplied are used. Four catchments located on the Douro River Basin have been considered as case studies. Precipitation and temperature projections have been bias corrected to reduce errors with observations in the control period (1971–2004). The HBV continuous hydrological simulation model has been used to simulate the soil moisture content on the day of occurrence of the maximum annual rainfalls in the four catchments. The modified curve number method has been utilized to obtain the changes expected in the future in flood magnitudes, considering the initial soil moisture contents estimated with the HBV model and the expected changes in annual maximum rainfalls. The methodology has been applied to the control period (1971–2004) to check the validity of the process. Then, the methodology has been applied to the future period (2011–2095), to quantify the changes expected in the future in flood magnitudes under climate change conditions. The combined use of the HBV continuous hydrological simulation with the modified curve number method improves the results provided by the HBV model. The proposed methodology allows a better characterization of the response of catchments in flood events. It also considers the expected variation in the antecedent moisture content in catchments in the future, driven by increasing temperatures and decreasing mean annual precipitations in the future. The results show that flood quantiles will increase in three of the four catchments considered.

     

Slackwater Sediments Record the Increase in Sub-daily Rain Flood due to Climate Change in a European Mediterranean Catchment

In this work we propose an original method to determine the magnitude of the discharge, the intensity of the precipitation and the duration of short-rain floods in small torrential basins (<?2000 km²), extending our earlier approach for long-rain floods in larger basins (Water 2016, 8, 526; Remote Sens. 2017, 9, 727). The studied areas are located in ungauged catchments with high erosion rates where torrents deposit slackwater sediments near the outlet of the basins. Such deposits and erosive morphologies allow us to analyse sub-daily extreme hydrological events by combining standard techniques in paleohydrology, the kinematic wave method and remote-sensed paleostage indicators. The formulation was correctly verified in extreme events through reliable gauge measurements and a high-resolution distributed hydrological model showing the accuracy of our calculations (10% ≤relative error ≤?22%). In catchments of the European Mediterranean region where the frequency and magnitude of short-rain floods are increasing (e.g. the Guadalquivir Basin), the main hydrological variables can thus be quantified post-event using the proposed approach. The outputs may serve to construct a new database for this kind of events complementary to the existing daily database for long-rain floods (>?24 h). The need is evident for safety designs of civil infrastructures and flood risk mitigation strategies in the current climate change scenario.

     

Development of Regional Flood Frequency Relationships Using L-moments for Middle Ganga Plains Subzone 1(f) of India

In this study, screening of the data has been carried out basedon the discordancy measure (D _i) in terms of the L-moments. Homogeneity of the region has been tested using the L-moments based heterogeneity measure, H. For computing the heterogeneity measure H, 500 simulations were carried out using the four parameter Kappa distribution. Based on this test, it has been observed that the data of 8 out of 11 bridge sites constitute ahomogeneous region. Hence, the data of these 8 sites have been used in this study. Catchment areas of these 8 sites vary from 32.89 to 447.76 km² and their mean annual peak floods varyfrom 24.29 to 555.21 m³ s^-1. Comparative regional floodfrequency analysis studies have been carried out using the various L-moments based frequency distributions viz. Extreme value (EV1), General extreme value (GEV), Logistic (LOS), Generalized logistic (GLO), Normal (NOR), Generalized normal (GNO), Uniform (UNF), Pearson Type-III (PE3), Exponential (EXP),Generalized Pareto (GPA), Kappa (KAP), and five parameter Wakeby(WAK). Based on the L-moment ratio diagram and Z _i ^dist –statistic criteria, GEV distribution has been identified as the robust distribution for the study area. For estimation of floods of various return periods for gauged catchments of the study area, regional flood frequency relationship has been developed using the L-moments based GEV distribution. Also, for estimation of floods of desiredreturn periods for ungauged catchments, regional flood frequencyrelationship has been developed by coupling the regional flood frequency relationship with the regional relationship between mean annual maximum peak flood and catchment area.     

Regional Flood Frequency Analysis Using L-Moments for the West Mediterranean Region of Turkey

The aim of this study is to investigate and determine hydrologically homogeneous regions and to derive regional flood frequency estimates for 47 gauged sites in the West Mediterranean River Basins in Turkey, using an index flood method with L-moments parameter estimation. Screening of the data of the gauged site is carried out based on a discordancy measure in terms of the L-moments. Initial candidate regions are established by the cluster analysis of first five L-moment statistics, using k-means method. Homogeneity of the basins is tested using simulation with a four-parameter Kappa distribution and an L-moments based heterogeneity measure. Three subregions are defined, namely the Antalya subregion, the Lower West Mediterranean subregion, and the Upper West Mediterranean subregion. Comparative regional flood frequency estimates are made for each subregion using various distributions, namely the generalized logistic, general extreme value, generalized normal, Pearson type III, generalized Pareto, kappa, and Wakeby distributions. Based on an L-moments goodness-of-fit statistic, the Pearson type III distribution is identified as the best-fit distribution for the Antalya and Lower-West Mediterranean subregions, and the Generalized Logistic for the Upper-West Mediterranean subregion. Monte Carlo simulation is used to evaluate the accuracy of the quantile estimates on the basis of the relative root-mean-square error and relative bias.     

Design Flood Estimation Using GIS Supported GIUHApproach

Quantitative understanding and prediction of theprocesses of runoff generation and its transmission to theoutlet represent one of the most basic and challenging areasof hydrology. Traditional techniques for design floodestimation use historical rainfall-runoff data for unithydrograph derivation. Such techniques have been widelyapplied for the estimation of design flood hydrograph at thesites of gauged catchment. For ungauged catchments, unithydrograph may be derived using either regional unithydrograph approach or alternatively GeomorhologicalInstantaneous Unit Hydrograph (GIUH) approach. The unithydrograph thus derived may be used for the simulation offlood events for the ungauged catchments. In this study Gambhiri dam catchment located inRajasthan, India is selected for applying this approach. Gambhiri river is a small tributary of the Berach/Banasriver of the Chambal basin in Rajasthan, India. Theobjective of the present study is to apply GeographicalInformation System (GIS) supported GIUH approach for theestimation of design flood. A mathematical model has beendeveloped at the National Institute of Hydrology, whichenables the evaluation of the Clark Model parameters usinggeomorphological characteristics of the basin. This modelhas been applied for the present study.From this study it is observed that the peakcharacteristics of the design flood are more sensitive tothe various storm pattern as well as method of criticalsequencing followed for the computation of design stormpatterns. Earlier estimates for the peak and time to peakhydrograph was 9143.74 cumec and 18 hrs. respectively.However, the estimates for the peak characteristics ofdesign flood hydrograph obtained from the GIUH basedapproach are 11870.6 cumec and 19 hrs. respectivelyconsidering the same design storm pattern.     

Spatial Pattern Characterization and Multivariate Hydrological Frequency Analysis of Extreme Precipitation in the Pearl River Basin, China

Consecutive extreme rainfall events, especially those having unfavourable spatio-temporal patterns, always trigger large floods. This paper aims to examine, through the multivariate hydrological frequency analysis, the probability of the synchronous occurrence of rainfall extremes in the Pearl River basin. The copula method together with the stationarity and independence tests, which are crucial to the valid use of statistical methods in regional frequency analyses, were applied in the study. The obtained results indicate that: (1) major precipitation events of the annual maximum 1-, 3-, 5- and 7-day rainfall recorded at 42 stations are the flat looking series and variables are independent, (2) the marginal distribution of all extreme rainfall variables in four homogeneous hydrologic regions fits the log-normal probability distribution and most of their joint distribution fits the Gumbel-Hougaard distribution, (3) on that basis the contour maps of the joint distribution of annual maximum 1-, 3-, 5- and 7-day rainfall between different regions are drawn and the probability of the synchronous occurrence of the extreme rainfalls in different regions are estimated. These findings have great practical value for the regional water resources and flood risk management and are important in exploration of the spatial patterns of rainfall extremes in the Pearl River basin in order to reveal the underlying linkages between precipitation and floods from a broader geographical perspective.     

Comparing Three Hydrological Models for Flash Flood Simulations in 13 Humid and Semi-humid Mountainous Catchments

Flash flood disaster ranks top among all the natural hazards across the world due to its high frequency, severity and fatality. However, flash flood simulation is still challenging in small and medium-sized catchments with complex orography, flashy hydrological responses and poor observations. Three distributed hydrological models, i.e., TOPModel, HEC and CNFF, are selected to simulate flash floods in seven humid and six semi-humid catchments in China, with consideration of water balance (RER), peak flow rate (REQ) and its occurrence time (TP), hydrograph variation (SNSE) and model uncertainty. Influences of five catchment attributes are further investigated on individual model performances. All three models perform satisfactorily in humid catchments, but less satisfactorily in semi-humid catchments. Water balance is well obtained by CNFF, followed by HEC and TOPModel. Peak flow rate and its occurrence time are most accurately captured by CNFF and HEC, respectively. Hydrograph variations are well reproduced by HEC and CNFF. TOPModel performs well for picking peak flow and hydrograph variation in humid catchments. Uncertainty interval is narrowest for HEC with average relative interval length at 95% confidence level being 0.78?~?2.53. Most observations are bracketed by uncertainty intervals for TOPModel (64.79%?~?91.91% of total). Three model performance indices (i.e., RER, REQ, and SNSE) are mainly affected by drainage area and forest ratio across humid and semi-humid catchments, while TP performance is mainly affected by mean slope in humid catchments.

     

Regionalizing Flood Magnitudes using Landscape Structural Patterns of Catchments

Emerging as an important issue in the disciplines of landscape ecology and landscape hydrology which inspired it, defining the concept of landscape metrics in a hydrological context has become a challenge to both landscape planners and engineers. Accordingly, the present study addresses the relationships existing between flooding phenomena and landscape metrics (shape index, fractal dimension index, perimeter-area ratio, related circumscribing circle, and contiguity index) of land use/land cover, hydrological soil groups and geological permeability classes. A regionalization approach was adopted employing 39 select catchments (33—4800 km² in area, 0.47—21 m³ s^?1 in mean discharge), located within the southern basin of the Caspian Sea. These catchments were predominantly covered by forest (57.4%), while rangeland, farmland and urban areas accounted for 25.9%, 11.7%, and 1.6%, respectively. Class-level landscape structural metrics of land use/land cover, hydrological soil groups and geological permeability classes have then been served as inputs to stepwise multiple linear regression analysis in an attempt to explain the flood magnitudes. The regression models (0.69?≤?r² ≤?0.84) suggested that the catchments’ flood magnitude could explicitly be predicted using average measure of the shape and related circumscribing circle indices for the land use/land cover classes and those of hydrologic soil groups and geological permeability classes of the catchments. This indicated that regularity (vs. irregularity) of the landscape, pedoscape, and lithoscape, as represented by the shape index as well as the circumscribing circle index (for elongation and convolution), explained 69–84% of the variation in the flood magnitudes in the catchment.     

Using Climate-Flood Links and CMIP5 Projections to Assess Flood Design Levels Under Climate Change Scenarios: A Case Study in Southern Brazil

The Intergovernmental Panel on Climate Change (IPCC) assessed with medium confidence that there has been an anthropogenic influence in the intensification of heavy rainfall at the global scale. Nevertheless, when taking into account gauge-based evidence, no clear climate-driven global change in the magnitude or frequency of floods has been identified in recent decades. This paper follows up on a previous nonstationary flood frequency analysis in the Itajaí River, which is located in the Southeastern South America region, where evidence of significant and complex relationships between El Niño-Southern Oscillation (ENSO) and hydrometeorological extremes has been found. The identified climate-flood link is further explored using sea surface temperature (SST) output from CMIP5 models under different representative concentration pathway (RCP) scenarios. Results are inconclusive as to whether it is possible to make a statement on scenario-forced climate change impacts on the flood regime of the Itajaí river basin. The overall outcome of the analysis is that, given that sample sizes are adequate, stationary models seem to be sufficiently robust for engineering design as they describe the variability of the hydrological processes over a large period, even if annual flood probabilities exhibit a strong year-to-year dependence on ENSO.     

Impact of Climate Change on the Hydrology of Upper Tiber River Basin Using Bias Corrected Regional Climate Model

The use of regional climate model (RCM) outputs has been getting due attention in most European River basins because of the availability of large number of the models and modelling institutes in the continent; and the relative robustness the models to represent local climate. This paper presents the hydrological responses to climate change in the Upper Tiber River basin (Central Italy) using bias corrected daily regional climate model outputs. The hydrological analysis include both control (1961–1990) and future (2071–2100) climate scenarios. Three RCMs (RegCM, RCAO, and PROMES) that were forced by the same lateral boundary condition under A2 and B2 emission scenarios were used in this study. The projected climate variables from bias corrected models have shown that the precipitation and temperature tends to decrease and increase in summer season, respectively. The impact of climate change on the hydrology of the river basin was predicted using physically based Soil and Water Assessment Tool (SWAT). The SWAT model was first calibrated and validated using observed datasets at the sub-basin outlet. A total of six simulations were performed under each scenario and RCM combinations. The simulated result indicated that there is a significant annual and seasonal change in the hydrological water balance components. The annual water balance of the study area showed a decrease in surface runoff, aquifer recharge and total basin water yield under A2 scenario for RegCM and RCAO RCMs and an increase in PROMES RCM under B2 scenario. The overall hydrological behaviour of the basin indicated that there will be a reduction of water yield in the basin due to projected changes in temperature and precipitation. The changes in all other hydrological components are in agreement with the change in projected precipitation and temperature.     

基于动态权重系数法的区域综合干旱指标研究

为揭示区域总体干旱程度及其变化特征,以长株潭地区为研究区,在标准化降水指数(SPI)、标准化水位指数(SZI)、标准化区域水资源短缺指数(SSDI)基础上,利用动态权重系数法构建区域干旱综合指标MIDI,结合历史受旱面积率、因旱减少供水量等旱情统计资料,对MIDI的适用性进行分析验证。以长株潭地区11个气象站、12个水文站近几十年实测资料为例,分别采用游程理论和Copula函数法识别干旱事件,并计算其发生频率,采用多尺度统计分析法,对区域综合干旱的演变特征进行分析。研究结果表明:SPI、SZI、SSDI对于不同水源、行业类型干旱评价各具优势,SPI、SSDI年干旱累积烈度与长株潭地区农业受旱面积率相关性相对较高;SZI年干旱累积烈度与城镇因旱减少供水量相关性较高,更适用于依靠地表径流为主要供水水源的城镇干旱地区评价。本研究提出的动态权重系数法,综合考虑了区域产业结构的年际变化、产业需水规律的季节性变化等因素,可反映不同阶段各单项指标干旱对于旱情的主导作用,适用于多种水源和产业类型的区域旱情综合评价;从月、季和年3种时间尺度,分析了长株潭地区MIDI综合干旱的变化特征,结果表明长株潭地区近20 a来极端干旱发生频次呈现波动增加趋势。