Observed Peak Discharge Research Articles

Derivation of unit hydrograph from GIUH analysis for a Himalayan river

Unit Hydrograph (UH) is the most popular and widely used method for predicting flood hydrograph resulting from a known storm in a basin area. However, the non-availability of UH due to poor network of raingauge stations in flood prone Indian river basins is a major concern. The computation of Horton's ratios and their application in generating the Geomorphological Instantaneous Unit Hydrograph (GIUH) can provide a solution for ungauged rivers. A detailed drainage network analysis was carried out for a 5th order flood- prone Himalayan river system in order to highlight its significance in flood management program. The equations for GIUH of 5th order stream were derived through Markov Chain analysis. The GIUH model for the 5th order stream was used to derive the first ever analytical UH of the river. Further, it was applied to determine the 50-yr return period flood. The 50-yr return period flood matches with the result of flood frequency analysis based on observed peak discharge data. This drainage network analysis and application of GIUH can provide a significant contribution towards flood management program.

Bayesian flood frequency analysis with paleohydrologic bound data

It is valuable to construct likelihood functions that rigorously incorporate measurement errors and annual peak discharge, historical, and paleohydrologic bound information in Bayesian flood frequency analyses. Estimates of primary posterior modes for common three‐parameter frequency distributions are constructed using simulated annealing and the simplex method. Parameter and flood frequency probability intervals are calculated directly by systematic parameter space integration. Bayesian flood frequency analyses with annual peak discharge, historical, and paleohydrologic bound data for the Santa Ynez River, California, and the Big Lost River, Idaho, demonstrate that paleohydrologic bounds reduce quantile biases by placing large observed peak discharges in their proper long‐term contexts and substantially narrow peak discharge confidence intervals when estimating floods with low exceedance probabilities.

Probablistic analysis of runoff simulations in a small urban catchment

In Urban Hydrology, a basic question is whether or not the common methods involving the use of design storms bring to the the some results obtained by those methods that make use of real storms. In general, one can say that different design storms give good results when used with the appropriate model, or, conversely, that good results can be achieved through careful model calibration. On the basis of 51 rainfall-runoff recordings obtained from the experimental catchment of Luzzi (Cosenza, Italy), the frequency distribution of the observed peak discharges was initially computed. Then the runoff events were simulated using Wallrus, a well known simulation model, taking as input the observed precipitations. The frequency distribution of the simulated peak discharges was compared to that of the observed ones, with the aim of calibrating the model on a statistical basis. After that, the rainfall events were analysed, obtaining the frequency distributions of the observed intensities over several durations and developing IDF curves of given frequencies and, then, the Chicago design storms. The plotting positions of the peak discharges simulated by this way show a good agreement with the distribution of both the observed peak discharges and the peak discharges simulated through the real storms.

Probablistic analysis of runoff simulations in a small urban catchment

In Urban Hydrology, a basic question is whether or not the common methods involving the use of design storms bring to the the some results obtained by those methods that make use of real storms. In general, one can say that different design storms give good results when used with the appropriate model, or, conversely, that good results can be achieved through careful model calibration.On the basis of 51 rainfall-runoff recordings obtained from the experimental catchment of Luzzi (Cosenza, Italy), the frequency distribution of the observed peak discharges was initially computed. Then the runoff events were simulated using Wallrus, a well known simulation model, taking as input the observed precipitations. The frequency distribution of the simulated peak discharges was compared to that of the observed ones, with the aim of calibrating the model on a statistical basis. After that, the rainfall events were analysed, obtaining the frequency distributions of the observed intensities over several durations and developing IDF curves of given frequencies and, then, the Chicago design storms.The plotting positions of the peak disharges simulated by this way show a good agreement with the distribution of both the observed peak discharges and the peak discharges simulated through the real storms.

Extreme Historical UK Floods and Maximum Flood Estimation

ABSTRACTHistorical flood events recorded as flood marks on bridges and houses or reported in newspapers and journals provide valuable information on the maximum size of floods which are likely to occur in the UK. For hydrological analysis peak water level must be converted to peak discharge, which is problematic even when the flood has been recorded at a flow gauging station. This paper describes some of the methods used to calculate the magnitude of extreme floods. Sixty‐nine historical UK floods are plotted on a graph of discharge versus drainage area and compared with curves published in 1933 and 1960 which were used to estimate the Normal Maximum Flood required for dam spillway design before 1975. From that date the design standard became the Probable Maximum Flood. PMF is calculated for 17 sites where extreme floods have occurred. For six events the observed peak discharge exceeded PMF. Possible reasons for these findings are discussed.

An Empirical Study of Flood Measurement Error

At a gaging station, very large peak discharges are usually estimated by extending the rating curve or by making an indirect measurement; hence these discharges are subject to much larger errors than are directly measured discharges. A crude measure of the uncertainty of the largest observed peak discharge at a gaging station is the ratio of the largest directly measured discharge to the largest observed peak discharge. For 46 gaging stations in the State of Wisconsin this ratio ranges from 0.16 to 0.99, with a median of 0.72. For the annual flood series from the half of the gaging stations with the lowest ratios, the coefficients of skewness have considerably higher mean and standard deviation than do those of the remaining flood series. These results are consistent with the impact of measurement error, though they can also be explained by the occurrence of single extremely large floods in several of the annual flood series.

Envelope curves for extreme flood events in northwestern and western Greece

Abstract Maximum flood experience in the northwestern and western regions of Greece can be depicted in graphs on which the maximum observed peak discharges are plotted against drainage areas. The peak discharges are found to be power functions of the drainage areas, and the curves enveloping the plotted points differ from region to region according to the climatic regime. The exponents of the Greek envelope curves are in the range of values of the exponents of yearly floodflow-drainage area envelope curves developed in conterminous U.S. basins, but the former curves' constants are much lower than the latter. When the peak discharges are plotted against a morphoclimatic index, which is the product of the expected storm duration by the maximum observed average storm intensity for this duration by the area of the drainage basin, a single linear envelope curve is drawn for both regions that explains 95% of the regional variation in the dependent variable. This curve is free from several drawbacks of floodflow-drainage area envelope curves, i.e. it does not need the determination of region boundaries, etc. The developed envelope curves can predict peak discharges at certain probability levels for ungauged basins of the area and can be used in specific engineering applications.