Project Abstract

Abstract
Flood frequency analysis is a crucial component of hydrological studies aimed at understanding the potential impact of floods on a particular region. One common approach to conducting flood frequency analysis is by using annual peak rainfall data collected over a period of time. This study focuses on comparing flood frequency analysis results obtained using different methods applied to annual peak rainfall data. The research project involves the collection of annual peak rainfall data from various monitoring stations located in a specific watershed. The data is then analyzed using two different methods commonly used in flood frequency analysis the Gumbel distribution and the Log-Pearson Type III distribution. These methods are chosen for their widespread application and well-established mathematical foundations in hydrology. The Gumbel distribution is a commonly used statistical model for analyzing extreme events such as floods. It is based on the assumption that the distribution of extreme values can be approximated by the Gumbel distribution function. On the other hand, the Log-Pearson Type III distribution is another widely used model that takes into account the skewness and kurtosis of the data, providing a more flexible approach to flood frequency analysis. By comparing the results obtained from these two methods, this study aims to evaluate the impact of using different distribution models on flood frequency analysis outcomes. The analysis includes determining the return periods for various flood magnitudes as well as assessing the associated uncertainties in the results. The findings of this research project will contribute to the understanding of the strengths and limitations of different methods used in flood frequency analysis. By comparing the outcomes of the Gumbel distribution and the Log-Pearson Type III distribution, insights can be gained into how the choice of distribution model influences the estimation of flood frequencies and associated risks. Overall, this study provides valuable information for hydrologists, engineers, and policymakers involved in flood risk management and mitigation efforts. By improving our understanding of flood frequency analysis using annual peak rainfall data, better-informed decisions can be made to enhance the resilience of communities and infrastructure to potential flood events.

Project Overview

 Flood is a basic phenomenon of nature, it occurs during or immediately after an intensive rainfall or large and sudden snow-melt due to increase in temperature (in the glacial/temperate countries). Also, flood is a high water stage in which overflows its natural or artificial banks onto normally dry land such as a river inundated its flood pain. When flood spreads to area of steep slope, it accelerate the runoff, the potential energy immediately takes on an additional and high kinetic energy due to increased velocity. The effects of flood on human well being range from unqualified blessings to catastrophes. The regular seasonal spring flood of the Nile River prior to construction of the Aswan high dam, for example were depends upon to provide moisture for the fertile flood pains of its delta. The uncontrolled flood of the Yantze River and the Huang Ho, have however, repeatedly wrought disaster when these rivers habitually re-chart their courses. Uncontrollable floods likely to cause considerable damage commonly result from excessive rainfall over brief period of time, as, for example the Omiyale flood of the Ogunpa river in Ibadan, Nigeria (1958, 1973 and 1980), the flood of Paris, France (1658 and 1910), of wars haw, England (1861 and1964), potentially disastrous floods may, however, also result from ice jams during the spring rise, as with the Danube, Switzerland (1342, 1402, 1501 and 1830), from storm tides such as those of 1099 and 1953 that the coast of England, Belgium, and the Netherlands; and from tsunamis, the mountainous sea waves cause by earthquakes, as in Lisbon (1755) and Hawaii, U.S.A (Hilo, 1946). Flood can be measured by height, peak discharge, area inundated, and volume of  flow, these factors are important to judicious land use, construction of protective levees and storage reservoirs, and, indirectly, the implementation of programs of soil and forest conservation to retard and absorb runoff from storm and more recently monitoring of river flow by computers using specifically designed software. The discharge volume of an individual storm is often highly variable from month to month and year to year. A particularly striking example of this variability is the flash flood, sudden unexpected torrent of muddy and sporadic rainfall: it is uncommon, of relatively brief duration and generally the result of summer thunderstorms in mountains. A flash flood can take place in a singles tributary while the rest of the drainage basin remains dry. The suddenness of its occurrences causes a flash flood to be extremely dangerous.