Comparative Study of Flood Coincidence Risk in The Mainstream and Its Tributaries

The coincidence of floods in the mainstream and its tributaries may lead to a large flooding in the downstream confluence area, and the flood coincidence risk analysis is very important for flood prevention and disaster reduction. In this study, the multiple regression model was used to establish the functional relationship among flood magnitudes in the mainstream and its tributaries. The mixed von Mises distribution and Pearson Type III distribution were selected to fit the probability distribution of the annual maximum flood occurrence dates and magnitudes, respectively. The joint distributions of the annual maximum flood occurrence dates and magnitudes were established using copula function. Fuhe River in the Poyang Lake region was selected as a study case. The joint probability, co-occurrence probability and conditional probability of flood magnitudes were calculated and compared with the simulated results of the observed data. The results show that the selected marginal and joint distributions perform well in simulating the observed flood data. The coincidence probabilities of flood occurrence dates in the upper mainstream and its tributaries mainly occur from May to early July. Among the three coincidence probability calculation methods, the conditional probability is the most consistent with the flood coincidence risk in the mainstream and its tributaries, which is more reliable and rational in practice. The results reflect the actual flood coincidence situation in the Fuhe River basin and can provide technique support for flood control decision-making.

The Use of a Uniform Technique for Harmonization and Generalization in Assessing the Flood Discharge Frequencies of Long Return Period Floods in the Danube River Basin

The flow regime conditions of the Danube River are continually changing. These changes are the result of natural processes and anthropogenic activities. The territory of the Danube River Basin is one of the most flood-endangered regions in Europe and assessing the design discharges along the Danube channel is complicated by the different estimation methods that are applied in particular countries. For this reason, it is necessary to harmonize flood design value assessment methods. The long-term maximum annual discharge series of the Danube River and other rivers in the Danube basin were analyzed and used to estimate the flood design values. We used the Log-Pearson type III distribution, which is one of the most widely used theoretical probability distributions to estimate extremes. This distribution can be flexibly applied to extreme values depending on the skew coefficient. We also analyzed the effect of the inclusion and exclusion of the historical extremes in the processed dataset. The results show that the inclusion of historical floods and the regionalization of the Log-Pearson type III distribution skew parameter can change the design discharges.

ESTIMATION OF THE T-YEAR SPECIFIC DISCHARGE USING THE REGIONALISED SKEWNESS COEFFICIENT OF THE LOG-PEARSON TYPE III DISTRIBUTION

In this paper the results are presented of estimation of T-year specific discharge of several streams in two regions in Slovakia. The Qmax time series used in the study were observed at water gauges from lowland Slovak part of the Morava River basin, and from the mountainous Belá River basin. For estimating the design values, we have studied the use of only one type of probability distribution, namely the Log-Pearson Type III Distribution (LP3 distribution). The use of only one type of distribution brings several benefits, e.g. possibility of the regionalization of the distribution parameters (in this study skew coefficient). In the first step the design values of the specific discharge series qmax (with historical data) were estimated and regional skew coefficients Gr of the LP3 distribution were computed. Regional skewness coefficient Gr was estimated to be 0.38 in the Morava River region, and 0.73 in the Belá River region. In many cases the estimate of the 1000-year specific discharge is two times higher than the value of the 100-year specific discharge. Then we have derived the empirical relations between station skew coefficient G and the elevation of the water gauge. In the second step we have derived the empirical relationships between 1000-years specific discharge q1000 and the elevation of the water gauge for both regions separately. The derived empirical regional equations can be used to estimate the 1000-years specific discharge of other streams in the region.

ASSESSMENT HARMONIZATION PROBLEMS OF THE LONG RETURN PERIOD FLOODS ON THE DANUBE RIVER

One of the basic problems of the flood hydrology was (and still is) the solution of the relationship between peak discharges of the flood waves and probability of their return period. The assessment of the design values along the Danube channel is more complicated due to application of different estimation methods of design values in particular countries downstream the Danube. Therefore, it is necessary to commence the harmonization of the flood design values assessment methods. All methods of estimating floods with a very long return period are associated with great uncertainties. Determining of the specific value of the 500- or 1000-year floods for engineering practice is extremely complex. Nowadays hydrologists are required to determine not only the specific design value of the flood, but it is also necessary to specify confidence intervals in which the flow of a given 100-, 500-, or 1000-year flood may occur with probability, for example, 90 %. The assessment of the design values Qmax can be done by several methods. In this study we have applied the statistical methods based on the assessment of the distribution function of measured time series of the maximum annual discharge. In order to apply regionalization methods for the estimation of the distribution function in this study we used only one distribution - the Pearson Type III distribution with logarithmic transformation of the data (log Pearson Type III distribution - LP3 distribution). To estimate regional skew coefficient for the Danube River we use 20 Qmax measured time series from water gauges along the Danube River from Germany to Ukraine. We firstly analyzed the occurrence of historic floods in several stations along the Danube River. Then we search relationship between the parameter of skewness of the log Pearson type III distribution function and runoff depth, altitude, or basin area in all 20 water gauge. Skewness coefficients of the LP3 distribution in the stations along the Danube River vary between –0.4 and 0.86.

Flood Frequency Analysis for Burhi Gandak River Basin

The study is aimed at finding the best distribution to match the steam flow and calculation of magnitude and frequency of flow. In the current study, we have used several statistical distributions to find the best fit distribution for stream flow and used flood frequency analysis techniques to find the magnitude and frequency of stream flow and non-exceedance probability of peak discharge. The study has been performed at Sikandarpur and Rosera gauging sites of BurhiGandak River. Historical (50 years) maximum annual peak discharge data of each station are used for statistical analysis for estimating maximum peak discharge in 5, 10, 25, 50, 100 year return period. In this study, Lognormal distribution, Galton distribution, Gamma distribution, Log Pearson Type III distribution, Gumbell distribution, Generalised extreme values distribution have been considered to describe the annual maximum stream flow. Flood frequency analysis methods were used for estimating the magnitude of the extreme flow events and their associated return periods. For both Sikandarpur and Rosera stations, Log Pearson type III distributions showed the lowest value of K–S and Chi-square test statistic. The annual probable peak discharge for 5, 10, 25, 50, and 100 years return period is calculated for each distribution. The most suitable distribution for both the stations is found to be the log-Pearson type III distribution.

Probability Distribution and Characterization of Daily Precipitation Related to Tropical Cyclones over the Korean Peninsula

Rainfall events are known to be driven by various synoptic disturbances or dominant processes in the atmosphere. In spite of the diverse atmospheric contributions, the assumption of homogeneity is commonly adopted when a hydrological frequency analysis is conducted. This study examines how the dominant processes, particularly the landfalling tropical cyclones (TCs) and non-TC events, have various effects to the characteristics of rainfall in South Korea. With rainfall data from the fifty-nine weather stations spread across the country, the multiple contributions of the TC and non-TC rainfall to the relative amount of rainfall, duration, intensity and maximum rainfall, on a seasonal and monthly scale, are first explored in this study. For the second objective, suitable probability distributions for the TC and non-TC time series are identified potentially for a synthetic analysis. Our results indicate that TCs cause a heterogeneous spatial distribution in the rainfall characteristics over the gauge networks particularly in the southern and eastern coastal areas. Some gauges in these areas attribute a significant portion of their amount and annual maximum rainfall to landfalling TCs. The results also show that the Pearson Type III distribution best represents the non-TC wet-day series, while the TC wet-day series can be represented by various distributions including the Weibull and Gamma distributions. From the analysis, we present how the characteristics of TCs differ from non-TCs with the emphasis on the need to consider their individual effects when conducting synthetic analyses.

Rainstorm Intensity–Duration–Frequency Model for Tarkwa, Ghana

Rainstorm intensity–duration–frequency relationship is a tool required for appropriate planning and designing of drainage systems. In this study, 22 years of annual peak daily rainstorm data distribution was tested to verify if it followed Lognormal, Gumbel, or Log Pearson Type III distribution. The distribution to which it belonged was used to build rainstorm intensity model of 0.5, 2, 5, 8, 10, 12, 15, 18, and 24 h durations. The findings revealed that the observed peak annual rainstorm followed Gumbel and Log Pearson Type III distributions at 0.05 significant level. Sherman rainstorm intensity model was also adopted and the parameters determined. Data generated with the Gumbel distribution function best fitted the Sherman model followed by those by log Pearson Type III. The rainstorm models developed with Sherman’s equation were recommended for use in the Tarkwa area. Keywords: Flood, Gumbel Distribution, Water Resources, Rainstorm