Institute of Technology
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Item FLOOD MODELING AND RISK MAPPING: (CASE OF KULFO RIVER IN SOUTHERN ETHIOPIA REGION(Hawassa University, 2024-10-22) CHALACHEW SHENKUTEFloods pose significant threats globally, causing immense damage to lives, societies, and economies. This study aimed to assess flood hazards, evaluate vulnerabilities, and determine flood risk along the Kulifo River floodplain. To achieve the objectives of a study, advanced hydrological and hydraulic modeling techniques were analyzed, using data from various sources, including rainfall from the National Meteorological Agency, stream flow data from the Ministry of Water Resources, and land use/land cover data from USGS. The HEC-HMS model accurately calibrated and validated using observed stream flow data, the result of model calibration gives Nash Sutcliffe efficiency (NSE) of 0.81, Percent Bias (PBIAS) of 1.77, coefficient of determination (R2 ) of 0.77, and Relative Mean Square Error (RMSE) of 4.28. During the validation period, the model gives (R2 ) of 0.79, NSE of 0.78, PBIAS of 1.09, and RMSE of 2.13. After model calibration and validation, flood hydrographs for different return periods were generated. These hydrographs served as inputs for the HEC-RAS hydraulic model, integrated with GIS software to map flood inundation areas. The resulting flood inundation maps revealed extensive flood-prone areas along the Kulifo River, with maximum flood depths of 15.2 meters and maximum velocities of 6.9 m/s during a 100-year flood event. Flood hazard maps classified areas into different hazard categories from low to extreme hazard, and 59% of inundated area falling under extreme, very high, and high hazard levels, 41% of inundated area falling under medium, and low hazard levels. Vulnerability analysis considered indicators such as flood depth, velocity, duration, slope, land use, and population density, highlighting 25% of the flooded area as very high and high vulnerability, 20% of the flooded area as moderate vulnerability and 55% of the flooded area as low and very low vulnerability. Combining flood hazard and vulnerability information, a comprehensive flood risk map was developed, identifying 32% of the flooded area as very high and high risk, 15% of the flooded area as moderate risk and 55% of the flooded area as low and very low risk. These high risk zones were concentrated in the Limat area of Arba Minch city, emphasizing the need for mitigation measures and emergency response plans. The flood risk map provided valuable insights for decision-making processes, guiding the implementation of structural and non-structural measures, floodplain zoning, and population relocation. This study's findings contribute to effective flood management, land-use planning, and disaster risk reduction strategies along the Kulifo RiverItem 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.