Assessment of uncertainty of error in design flood estimates using 2-parameter log normal distribution

Abstract

Estimation of design flood is formed as a basis for planning and management of civil engineering construction especially hydraulic structures such as water use and flood control structures. The dimensions and capacity of the buildings depend on flood magnitude for a given return period that may have some uncertainty due to model error. This can be achieved through Flood Frequency Analysis (FFA) that involves fitting probability distribution to the series of Annual Maximum Discharge (AMD) data. In this paper, a study on assessment of uncertainty of error in design flood estimates was carried out by fitting Method of Moments (MoM), Maximum Likelihood Method (MLM) and method of L- Moments (LMO) of 2- parameter Log Normal (LN2) distribution to the series of AMD data for river Tapi at Prakasha barrage. The selection of best fit method of LN2 was made through Goodness-of-Fit (GoF) tests viz., Chi-Square and Kolmogorov-Smirnov, and Model Performance Indicators (MPIs) such as correlation coefficient, root mean absolute error and root mean squared error. GoF tests results confirmed the suitability of all three methods of LN2 for estimation of Peak Flood Discharge (PFD). The results indicated that the predicted PFD by MLM is closer to the observed data. From FFA results, it was witnessed that the standard error on the estimated PFD by MoM is minimum than those values of MLM and LMO. The outcomes of FFA results were weighed with MPIs and found that MLM is better suited amongst three methods of LN2 for estimation of PFD at Prakasha barrage.