Optimization of Flood Flows at Makurdi Hydrological Basin

Abstract

The menace of flooding is overwhelmingly cruel ranging from the loss of lives, valuables, corruption of the ecosystem, destruction of livestock, shortage of food, poverty, at lots more. The ultimate intent of this research is to choose the best-fitted probability distribution function that optimally approximates the historical time series of the Makurdi hydrological station in the Niger/Benue River Basin in Nigeria. The flood data was collected from the National Inland Waterways Authority (NIWA) at Lokoja. The observed data were fitted into eight (8) probability distribution models, involving Normal (N2), Gumbel (EV1), two-parameter log-Normal (LN2), Gamma, Pearson type III (P3), log-Pearson type III (LP3), Exponential and the Generalized Extreme Value (GEV). The chi-square (χ²), Kolmogorov-Smirnov (K-S), Nash–Sutcliffe efficiency coefficient (NSE), root mean square error (RMSE), and coefficient of determination (R²) goodness of fit tests were performed at the 5-percent level of significance on the predicted data to determine the best distribution approximation from the 8 frequency distributions. From the results obtained, it was found that the Gumbel (EV1) distribution is the best approximation of flood estimation at Makurdi hydrological station with K-S, , NSE, RMSE, and  tests statistics values of 1.000, 5.12e4, 0.959, 334.8 and 0.968 respectively.