<Emphasis Type="Bold">Analysis of Spatio-temporal Characteristics and Regional Frequency of Droughts in the Southern Peninsula of India</Emphasis>

A detailed regional drought study is carried out in the southern peninsula of India to characterize the spatio-temporal nature of droughts and to predict the drought magnitudes for various probabilities in the homogeneous drought regions. The method of several random initializations of the cluster centres of the K-means algorithm is suggested for the identification of the initial regions in the context of drought regionalization, which is shown to perform better than the initialization from the Ward’s algorithm and the Ward’s algorithm itself. The peninsula is classified into seven spatially well-separated homogeneous drought regions. The robust L-moment framework is used for the regional frequency analysis of drought magnitudes computed using the standardized precipitation index. The Pearson type III is found to be appropriate for regional drought frequency analysis in six of the regions, while the robust Wakeby distribution is suggested for one region. Low magnitude droughts are frequent and dominant in the northern part of west coast, the north-eastern coast and its adjoining inland region, while high magnitude droughts are less in number and are experienced in semi-arid central part, southern part of western coast, south-eastern part and north-western inland region. The spatial maps of drought magnitudes indicate that at higher return periods (100 and 200 years) the south-eastern part of the peninsula is likely to encounter high magnitude droughts, while the central region is likely to experience the same at lower return periods (10 and 50 years). Hence these regions need to be given special importance in the drought mitigation planning activities.     

Assessing the Regional Concept with Sub-Sampling Approach to Identify Probability Distribution for at-Site Hydrological Frequency Analysis

The framework of regional analysis allows superior discrimination as well as better identification of the shape of a population distribution in a hydrological frequency analysis. The aim of this study is to incorporate the better of regional concept while performing an at-site frequency analysis. The study proposes a new method in the form of sub-sampling technique with the aid of a regional distribution selection procedure to choose an appropriate probability distribution function for frequency analysis. The technique is evaluated against common distribution selection methods: a widely used goodness-of-fit method in Anderson–Darling (AD) and a popular graphical assessment tool in L-moment ratio diagram (LMRD). The performance is evaluated by applying the technique to gauged annual maximum daily precipitation data series of 24 stations located across China. It is found that the technique accomplished a better performance in discriminating among distributions which or else may not be achievable only by the AD or LMRD test. In general, all results indicate that the proposed technique can be an attractive means in discriminating as well as identifying the best distribution for at-site frequency analysis.

     

L-Moment-Based Regional Frequency Analysis of Annual Extreme Precipitation and its Uncertainty Analysis

Estimation of precipitation amounts associated with different return periods is an important task for the planning and design of many types of infrastructures. In this study, regional frequency analysis based on L-moments is proposed to estimate the annual maximum daily precipitation quantiles in the Taihu basin, China. The Generalized Extreme Value (GEV) distribution is used to describe the frequency distributions of extreme rainfall events. At-site frequency analysis results based on L-moments are compared with those obtained from regional analysis. The 95% confidence intervals of estimated precipitation quantiles are calculated using Monte Carlo simulations (MCS). Uncertainty assessment results indicate that regional analysis is more robust and more accurate than at-site analysis. Furthermore, when conducting regional frequency analysis, the estimation of precipitation quantile confidence intervals can be simplified by assuming normality for the MCS results. The variation of the precipitation quantiles’ sample statistics for different return periods is expressed as a function of the return period. The proposed methods are useful for the Taihu Basin and are recommended for other regions.     

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.     

Estimating Temporal Changes in Extreme Rainfall in Sicily Region (Italy)

An intensification of extreme rainfall events have characterized several areas of peninsular and insular Italy since the early 2000s, suggesting an upward ongoing trend likely driven by climate change. In the present study temporal changes in 1-, 3-, 6-, 12- and 24-h annual maxima rainfall series from more than 200 sites in Sicily region (Italy) are examined. A regional study is performed in order to reduce the uncertainty in change detection related to the limited length of the available records of extreme rainfall series. More specifically, annual maxima series are treated according to a regional flood index - type approach to frequency analysis, by assuming stationarity on a decadal time scale. First a cluster analysis using at-site characteristics is used to determine homogeneous rainfall regions. Then, potential changes in regional L-moment ratios are analyzed using a 10-year moving window. Furthermore, the shapes of regional growth curves, derived by splitting the records into separate decades, are compared. In addition, a jackknife procedure is used to assess uncertainty in the fitted growth curves and to identify significant trends in quantile estimates. Results reveal that L-moment ratios show a general decreasing trend and that growth curves for the last decade (2000–2009) usually do not stand above the others, with the only exception of the ones related to the outer western part of Sicily. On the other hand, rainfall quantile estimates for the same period are the highest values almost all over the region. An explanation can be found in the increase of subregional average medians, largely caused by recent severe local storms.     

基于地下水埋深的区域干旱频率分析研究

以地下水埋深为水文干旱指标，在分析研究区实际旱情发生频率的基础上，采用相邻时段地下水埋深变化的累积频率法，识别由地下水干旱历时和干旱烈度组成的干旱特征变量值，并从降水的角度，分析了用相邻时段地下水埋深变化表征干旱的合理性。在采用适线法确定单个干旱特征变量累积分布的基础上，利用Copula函数构建了干旱历时与干旱烈度间的联合分布，并计算了相应的干旱重现期。对淮北平原砀山县的地下水干旱频率分析结果表明：基于相邻时段地下水埋深变化的累积频率法，识别的干旱历时和干旱烈度及其对应的干旱重现期与砀山县实际受旱情况相符。提出的基于地下水埋深的区域干旱频率分析法，概念清晰，在其它类似的平原区域具有推广价值。     

Identification of Homogeneous Rainfall Regimes in Northeast Region of India using Fuzzy Cluster Analysis

Regionalization methods are often used in hydrology for frequency analysis of floods. The hydrologically homogeneous regions should be determined using cluster analysis instead of the geographically close stations. In view of the ongoing environmental and climate changes in the Northeastern of India, regionalization of homogeneous rainfall region is essential to lay out an effective flood frequency analysis of this region. The choice of appropriate cluster approach used according to the data of the basin is also significant. In the context of this study, total precipitation data of stations operated by Indian Meteorological Department (IMD) in Northeastern of India basins for cluster analysis are used. Further, five cluster validity indices, namely Partition Coefficient, Partition Entropy, Extended Xie-Beni index, Fukuyama-Sugeno index and Kwon index have been tested to determine the effectiveness in identifying optimal partition provided by the fuzzy c mean clustering algorithm (FCM). A comparison is also performed using K- Mean clustering algorithm. Additionally, regional homogeneity tests based on l-moments approach are used to check homogeneity of regions identified by both cluster analysis approaches. It was concluded that regional homogeneity test results show that regions defined by FCM method are sufficiently homogeneous for regional frequency analysis.     

Streamflow Drought Severity Analysis of Betwa River System (India)

Streamflow appraisal in time and space particularly in semi arid and dry sub humid regions has vital importance in the formulation of round the year plan of water uses comprising domestic & industrial water supply, irrigation scheduling, reservoir operation, in-stream flow maintenance etc. Drought severity analysis including the estimation of flow availability, drought duration, and deficit volume etc. was carried out using the 20–42 years (1960–2001) 10-daily streamflow data of five sites on the Betwa River system and. independent streamflow drought events were described by pooling the data, and severity of an independent drought event classified using a new drought severity index (DSIe) defined as a function of (1) the ratio of deficit flow volume to corresponding volume at the truncation level and (2) the ratio of duration of deficit flow to the maximum possible duration of the independent streamflow drought event. The study found that the upper reaches of river course were more prone to severe droughts than were the lower reaches. The drought events starting during August−November were more likely to be severe drought events than those in the other months.     

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.     

Regional Frequency Analysis of Droughts in Portugal

This study investigated the frequency of droughts for the period September 1910 to October 2004 in mainland Portugal, based on monthly precipitation data from 144 rain gauges distributed across the country. The drought events were characterized using the standardized precipitation index (SPI) applied to time scales of 1, 3, 6 and 12 consecutive months. Based on the SPI time scale series a regional frequency analysis of drought magnitudes was undertaken using two approaches: annual maximum series (AMS) and partial duration series (PDS). Three spatially defined regions (north, central and south) were identified by cluster analysis and analyzed for homogeneity. Maps of drought magnitude were developed using a kriging technique for several return periods. Similar uniform spatial patterns were found throughout the country using the AMS and PDS approaches. For several SPI time scales a comparison of the observed and estimated maximum magnitude (269-year empirical return period) showed that the AMS combined with the selected probability distribution models (Pearson type III, general Pareto and Kappa) provided better results than the PDS approach combined with the same models. A general and simplified characterization of drought duration revealed a relatively uniform pattern of droughts events across the country.     

Using the Meteorological Information for the Regional Rainfall Frequency Analysis: An Application to Sicily

Regional frequency analysis is a useful tool for accurate estimation of precipitation quantiles than at-site frequency analysis, especially in the case of regions with a short rainfall time series. The use of meteorological information, combined with rainfall data analysis, could improve the selection of homogeneous regions. Starting from 1958, 198 meteorological configurations, related to extreme events, have been identified throughout the national territory of Italy. The reanalyzed meteorological data of the 40 Year Re-analysis Archive (ERA-40) of the European Centre for Medium-Range Weather Forecast (ECMWF) have been analyzed to identify homogeneous regions with respect to the Convective Available Potential Energy (CAPE), the Q vector Divergence (QD) and the Vertically Integrated Moisture Flux (VIMF). The latter index appears to be the better candidate for finding regional homogeneity inside areas where high frequency values of CAPE or QD are present. The paper presents an application based on the delimitation of homogeneous regions using climatic indexes for the island of Sicily. By applying the proposed methodology, seven homogeneous areas over Sicily were found. The consistency of the final results has been validated by using a coupled approach based on the Valuation of Floods in Italy procedure (VAPI) and on the heterogeneity test of Hosking and Wallis (Water Resour Res 29:271–281, 1993, 1997).     

Assessment of Regional Floods Using L-Moments Approach: The Case of The River Nile

In this study, a regional flood frequency analysis has been carried out, using the index flood L-moments approach. Annual maximum stream flood data observed at 14 gauged sites on the Nile River tributaries (Blue Nile, White Nile, and Atbara River) are investigated. The aim of the study is to investigate and derive hydrologically homogeneous region or regions and to identify and establish the regional statistical distribution. To this end, five distribution functions are used, namely: generalized pareto, generalized extreme-value, generalized logistic, generalized normal, and Pearson type-3 distributions. Analyses have shown that 8 sites form a hydrologically homogeneous region, and this region follows a generalized logistic (GLO) distribution. Furthermore, the other remaining two regions (possibly heterogeneous and definitely heterogeneous) are also defined. Regional dimensionless growth curves for the identified three regions are derived. Results are assessed on the basis of relative RMSE% and relative BIAS% through the use of Monte Carlo simulation.     

近500年黄淮海地区洪旱事件时空变化特征

依据近500年洪旱等级数据,采用滑动平均、累积距平、频率统计、小波分析和Mann-Kendall突变检验和空间分析方法,评估了研究区近500年洪旱灾害时空变化特征。结果表明:黄淮海地区洪旱灾害具有明显的年际和年代际变化,近年来趋向干旱发展。各子区域的年际变化存在一定的差异,突变时段差别较大。洪旱灾害发生周期的空间分布差异性显著,19世纪后半叶以来洪旱灾害频繁。研究结果对于防灾减灾、灾害预测、工程建设以及相关研究等有重要的价值。     

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.     

北江流域枯季降水径流分析

通过对北江枯季降水径流的空间变化、年际变化和年内分配规律以及降水径流相关关系等分析,探索了北江枯水期降水径流分布特点及地区差异,以及在时间和空间上的变化和影响枯季径流的因素,为实现枯季水资源管理提供一定的技术支撑。     

Regional Drought Modes in Iran Using the SPI: The Effect of Time Scale and Spatial Resolution

In the present paper, regional drought modes in Iran are identified applying the Principal Component Analysis (PCA) and Varimax rotation to the Standardized Precipitation Index (SPI) computed on different time scales. Data used include gridded monthly precipitation covering the period 1951–2007 retrieved from the Global Precipitation Climatology Centre (GPCC) archive with different spatial resolutions (2.5, 1 and 0.5° resolution). The objective of the study is twofold: (i) Investigate the stability of drought spatial modes as a function of the SPI time scales used for monitoring the different kinds of drought, (ii) Evaluate the impact of the spatial resolution of gridded data on drought regionalization. For the coarse spatial resolution of 2.5°, results show four drought modes of distinct variability, which remain quite stable when the SPI time scale is varied from 1- to 24-month. Differently, for higher spatial resolutions drought modes appear more sensitive to the index time scale and become less spatially homogeneous as the time scale is increased. Moreover, the number of identified modes (sub-regions) may reduce to three or two, but in all cases the most well defined sub-region appears to be the southern one. This suggests that both the spatial resolution of precipitation data and the time scale may affect drought regionalization, i.e. the number of drought modes and their spatial homogeneity.     

Flood Frequency Analysis Using L Moments: a Comparison between At-Site and Regional Approach

Water Resources Management - Regional flood frequency analysis has been carried out for estimating peak discharge at regional level over the Kerala State, India, along with at-site flood frequency...     

Regional Flood Frequency Analysis in Tunisia: Identification of Regional Distributions

Best-fit distributions of floods in Tunisia are determined based on L-moment diagram and statistical tests. GEV and GLO distributions provided the best fit to seven and three regions of Tunisia respectively. In each homogeneous region, hierarchical approaches and regression models were developed for gauged and ungauged watersheds. The first two parameters of the distributions (GEV and GLO) were estimated from measured data while the third parameter was represented by the regional average value weighted by the record length of all stations in the region. The obtained parameters were correlated to the catchment size. Quantiles obtained by the proposed models were compared with those obtained using local conventional models. Statistical tests showed that the proposed models provided a much better agreement with observed floods than any of the conventional methods generally used in Tunisia.     

基于SPI和SPEI的淮河中上游流域气象干旱时空分布特征对比研究

基于淮河流域1960-2017年逐月降水、气温资料,采用SPI、SPEI等干旱指数和线性趋势法、Mann-Kendall、小波分析等数学统计方法对年和四季气象干旱的趋势性、周期性及干旱频次进行时空分布特征的对比研究。结果表明:流域年、夏冬两季两种干旱指数呈微弱增加趋势,SPEI较SPI上升幅度略大,春秋两季均呈微弱减少趋势,SPEI较SPI下降幅度略大;研究时段内同一区域的两种干旱指数反映的干湿变化周期性基本一致;年尺度淮河以北SPEI显示中旱频次较多而SPI显示轻旱频次较多,其他时间尺度南北区域接近一致;两种干旱指数的空间变化趋势除夏季较为一致外,年、春秋两季在同一区域上SPEI显示的干旱化趋势较SPI略强,冬季SPI显示绝大部分区域呈湿润化趋势而SPEI呈干旱化趋势;两种指数在空间分布上存在一定程度的差异性,四季SPEI显示的干旱频次普遍比SPI统计的干旱频次高。研究结果对于干旱客观性评估和水旱灾害防治管理具有重要参考价值。     

Analysis of Drought from Humid,Semi-Arid and Arid Regions of India Using DrinC Model with Different Drought Indices

The study aims at evaluating the various drought indices for the humid, semi-arid and arid regions of India using conventional indices, such as rainfall anomaly index, departure analysis of rainfall and other indices such as Standard Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) that were analyzed using the DrinC software. In SPI, arid region has seven drought years, whereas humid and semi-arid regions have four. In case of RDI, the humid and semi-arid regions have 11 drought years, whereas arid regions have 10 years. The difference in SPI and RDI was due to the fact that RDI considered potential evapotranspiration, and hence, correlation with plants would be better in case of RDI. Humid region showed a decreasing trend in initial value of RDI during the drought as compared to semiarid and arid regions and indicated possible climate change impact in these regions. Among all the indices, RDI was considered as an effective indicator because of implicit severity and high prediction matches with the actual drought years. SPI and RDI were found to be well correlated with respect to 3 months rainfall data and SPI values led to prediction of annual RDI. The results of our study established that this correlation could be used for developing disaster management plan well in advance to combat the drought consequences.