Abstract
Extreme hydrological situations constantly disturb the earth activities and life, to envisage such extreme activities we need a system that alarms well on time and recognized the expected danger; to prepare such systems one must have knowledge of the significant factors that are actively responsible for such extreme situations and we should have a reliable statistical technique that helps to prepare a useful model for such systems. In this paper we investigate the historical data of peak flood from several gauging stations of river Jhelum in Kashmir, India. A reliable estimation technique (L-moment) is applied for parametric estimation of the probability distributions and a reliable testing techniques are used to check the accuracy of fitting of the distribution, in additional to that L-moment ratio diagram (LMRD) is used to impart information about fitting of distribution. Log Pearsons-III distribution shows better results and satisfies tests of distribution fitting, same probability distribution is globally accepted for flood forecasting.
Highlights
The probability distributions that are used in flood frequency distributions are extreme value Type –I, Generalized Pareto distribution, Log Pearson-III, Generalized extreme value distribution and normal distribution [3]
2.1 Generalized Extreme Values (GEV) Generalized extreme value distribution is the combination of Weibull, Gumbel and Frechet probability distributions, it has three parameters: location parameter (z), scale parameter (α) and shape parameter (k)
An additional mode to check the fitting of distributions is the (LMRD), it the diagram which represents the relationship between L-Skewness and L-Kurtosis (τ3,τ4) of data plotted against points and constant lines
Summary
To identify the trend and the movements of such situations we should have good knowledge of the significant factors involving in system and the reliable statistical techniques, in order to save the human and economic losses, we should build such a system that provides the warning before the extreme situation and support and remain effective in those conditions. As far as the hydrologic forecast and allied constructional/managemental scrutiny is considered one must have the adequate knowledge about the concerning factors that plays vital role and latest statistical techniques that is used to frame better models.
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