Hydraulic Engineering
Permanent URI for this collectionhttps://etd.hu.edu.et/handle/123456789/69
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Item FLOOD RISK MAPPING USING HEC-RAS MODEL: CASE STUDY ON WAJA WATERSHED IN RIFT VALLEY BASIN CENTRAL ETHIOPIA REGION, ETHIOPIA(Hawassa University, 2024-04-22) ATEREFE TAMIRAT DEBOCHFlood is among the most devastating natural disasters worldwide, significantly affecting human lives and property. The current study conducted on the Waja River floodplain aimed to model and maps the flood inundation, flood hazard, flood vulnerability, and flood risk associated with flooding in the area. To achieve this objective, various data sources were utilized, including meteorological, hydrologic, and topographic data collected from different organizations. The study employed several tools and materials, including the HEC HMS and HEC-RAS models, GIS software, GPS devices, and metering tape. The HEC HMS model was used to analyze flood hazard and risk by developing inflow design floods for different return periods. The model was calibrated and validated using actual stream flow data. During model calibration the NSE value was 0.75, Percent Bias (PBIAS) was 2.02, coefficient of determination (R2 ) was 0.78, and Relative Mean Square Error (RMSE) was 2.03. During the validation period, the model achieved an R2 of 0.77, NSE of 0.76, PBIAS of 1.64, and RMSE of 1.3. After calibration and validation, the annual maximum precipitation from rainfall data was extracted to develop frequency storms for different return periods. These storms were then used as input for the HEC HMS model to generate flood hydrographs. The HEC-RAS model, combined with the flood hydrographs, was used to produce flood inundation maps, which were visualized in ARC-GIS software for detailed analysis. The results of the study indicated that for return periods of 10, 25, 50, and 100 years, the areas inundated by floods were 3030 ha, 3364 ha, 3520 ha, and 3683 ha, respectively. Additionally, the maximum flood depths were found to be 6.3m, 9.2m, 12.6m, and 14.45m for the respective return periods. The maximum flood velocities were 3.8 m/s, 4.7 m/s, 5.5 m/s, and 6.8 m/s for the same return periods. Flood hazard maps were derived from the depth, velocity, and duration of floodwaters, revealing that 35% of the flooded area was categorized as having very high and high hazard, while approximately 65% was classified as medium and low hazard. The flood vulnerability map classified approximately 17% of the flooded area as having high and very high vulnerability. About 18% of the flooded area fell into the moderate vulnerability class. The majority of the flooded area, approximately 65%, had low and very low vulnerability. By combining the flood hazard and vulnerability information, the study developed a flood risk map. The results showed that 24% of the area fell into the high and very high-risk categoriesItem FLOOD HAZARD MODELING AND RISK MAPPING: CASE STUDY ON LOWER WEITO RIVER RIFT VALLEY BASIN SNNPR, ETHIOPIA(Hawassa University, 2025-08-12) GELMA BORUThis study focuses on the modeling and mapping of flood inundation and associated risks in the Lower Weito River, a tributary of Lake Abaya by means of coupled hydrological and hydraulic models with different return periods. Meteorological, hydrologic, and topographic data were collected from various sources. Rainfall data from 1990 to 2015 were collected from the National Meteorological Agency and the stream flow data from 1990 to 2007 were collected from the Ministry of Water and Energy. DEM 12 * 12m resolution was downloaded from Alaska satellite facility, soil data was taken from FAO and LULC data were collected from the Ministry of Water and Energy. These data were integrated using modeling tools such as HEC-HMS and HEC-RAS, along with GIS software. To examine the accuracy of the HEC-HMS model, calibration and validation is performed using observed stream flow data. The results showed a strong relationship between simulated and observed data, with R2 and NSE values of 0.82 and 0.77, for calibration periods and 0.78 and 0.75 for validation period respectively which indicating a very good agreement between observed and simulated flow . The calibrated and validated model was then used to develop flood hydrographs for different return periods based on frequency storm analysis. The result of flood frequency analysis showed minimum peak flow of 77.9m 3 /s for a 2-year return period with 24-hour storm duration and, the maximum peak flow 606.2 m3 /s occurs with a 100-year frequency storm for the same duration. The HEC-RAS model was used to generate flood inundation maps, which revealed the extent of flooded areas and the maximum flood depths and velocities for various return periods. The results indicated that the areas inundated by floods ranged from 1711.2 hectares for a 10-year return period to 2763.3 hectares for a 100-year return period. The maximum flood depths varied from 5.2 meters for a 10-year return period to 7.5 meters for a 100-year return period. The maximum flood velocities ranged from 3.15 meters per second for a 10-year return period to 7.01 meters per second for a 100-year return period. Flood hazard maps were derived by considering the depth, velocity, and duration of floodwaters. The results showed that about 0.01% of the total flooded area was under extreme hazard, 14% under very high hazard, 29% under high hazard, 35% under medium hazard, and 21% under low hazard. The flood vulnerability map classified the flooded areas into five vulnerability classes. Approximately 44% of the flooded area was classified as high and very high vulnerability, 19% as moderate vulnerability, and 37% as low or very low vulnerability. The flood risk map was developed by combining the flood hazard and vulnerability information. The results showed that 16% of the area was classified as very high to high risk, 46% as medium risk, and 38% from low to very low risk.