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<p>Flooding represents a major natural disaster that poses threats to infrastructure, human safety, and private property. In this context, the current study focuses on Flood Forecasting, Inundation Mapping, and Risk Analysis Mapping for the Phase-I Ribb Irrigation Area located in the Amhara Region of Ethiopia. The analysis began with the collection and examination of rainfall data obtained from nearby meteorological stations. This data was crucial in calculating flood peaks, which are critical for understanding potential flooding events. To accurately map the watershed, a Thiessen polygon map was created. This method helps delineate areas that influence water flow within the watershed. Additionally, the inverse distance weighting method was employed to interpolate any missing rainfall data, ensuring a comprehensive dataset for analysis. For statistical assessment, the study identified the Log-Pearson Type 3 distribution as the most appropriate model for the data collected from the Ribb River. This study created flood inundation depth maps for various return periods (2, 5, 10, 25, 50, and 100&#xa0;years) by overlaying flood grid depths in the study region. The categories include flooded but safe (0–0.25&#xa0;m), unsafe for children (0.25–0.5&#xa0;m), unsafe for adults (0.5–0.75&#xa0;m), unsafe for sportsmen (0.75–1&#xa0;m), unsafe for inside structures (0.75–1&#xa0;m), and High-risk zone (&gt; 1.5&#xa0;m). In contrast, the Generalized Extreme Value distribution was more suitable for analyzing data from other rivers in the region. The study evaluated two flood risks for before and after the construction of dykes and one after their completion.</p>

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Flood forecasting, inundation mapping, and risk analysis mapping for Phase-I Ribb irrigation area in Amhara Region, Ethiopia

  • 期刊论文

  • 发表日期：

    2025年3月24日

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  • Otoma Orkaido Garo,
  • Shawol H/slassie Mamecha,
  • Mihiretu Shale Sasa,
  • Yohannes Mehari Andiye

摘要

Flooding represents a major natural disaster that poses threats to infrastructure, human safety, and private property. In this context, the current study focuses on Flood Forecasting, Inundation Mapping, and Risk Analysis Mapping for the Phase-I Ribb Irrigation Area located in the Amhara Region of Ethiopia. The analysis began with the collection and examination of rainfall data obtained from nearby meteorological stations. This data was crucial in calculating flood peaks, which are critical for understanding potential flooding events. To accurately map the watershed, a Thiessen polygon map was created. This method helps delineate areas that influence water flow within the watershed. Additionally, the inverse distance weighting method was employed to interpolate any missing rainfall data, ensuring a comprehensive dataset for analysis. For statistical assessment, the study identified the Log-Pearson Type 3 distribution as the most appropriate model for the data collected from the Ribb River. This study created flood inundation depth maps for various return periods (2, 5, 10, 25, 50, and 100 years) by overlaying flood grid depths in the study region. The categories include flooded but safe (0–0.25 m), unsafe for children (0.25–0.5 m), unsafe for adults (0.5–0.75 m), unsafe for sportsmen (0.75–1 m), unsafe for inside structures (0.75–1 m), and High-risk zone (> 1.5 m). In contrast, the Generalized Extreme Value distribution was more suitable for analyzing data from other rivers in the region. The study evaluated two flood risks for before and after the construction of dykes and one after their completion.