Adverse Climate variations are adversely impacting the hydrological cycles which is causing abnormal flooding and drought conditions in the region, including Ethiopia. Severe environmental and socioeconomic consequences result from extreme weather occurrences like floods. Therefore, evidence-based hydrological data is essentially required for accurate estimations of extreme events (flood and drought) predictions for prudent management of available water resources. When managing and developing water resources, accurate flood predictions and peak flow estimations are crucial. Flooding is one of the major problems in Ethiopia. Over the past few decades, both frequency and magnitude have quickly grown in scope and complexity. Both changes in land use and climate change are the main drivers for the flooding scenarios in the country. The flood frequency analysis methods were used for forecasting the incoming flood of the two rivers. The result of the study shows that General Parto and General logistic distributions are the best-fitted probability distributions for the Gumera and Megech Rivers. Using these best-fit probability distributions, flood magnitudes for 10, 25, 50, 100, and 200-year return periods were forecasted. The result also shows the incoming flood increased from 310.8 (10-year return period) to 413.3 (200-year return period) in Gumara River and increased from 245.3 (10-year return period) to 323.7 (200-year return period) in Megech River.

Keywords: Peak flow, flood frequency analysis, flood, and return period