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<p>Excessive runoff in floodplain areas, intensified by climate change and urbanization, poses a significant challenge, particularly during the rainy season. Accurate estimation of rainfall-induced runoff is crucial for effective watershed management and sustainable water resource utilization. This study applies the Soil Conservation Service-Curve Number (SCS-CN) method, integrated with Geographic Information Systems (GIS), to estimate runoff in the Wuseta Watershed, Upper Blue Nile Basin, Ethiopia. The SCS-CN method’s simplicity and reliability make it an effective tool for assessing runoff dynamics. Various datasets including rainfall, land use/land cover, soil characteristics, and Hydrologic Soil Group (HSG) data were utilized, with Antecedent Moisture Conditions (AMC) incorporated to capture runoff variability. Weighted Curve Numbers (C.N.) were computed for dry, normal, and wet conditions over a 20-year period, revealing significant runoff variability. The highest annual rainfall of 1,458.00&#xa0;mm occurred in 2009, while the lowest (1,256.21&#xa0;mm) was recorded in 2005, with an average of 1,358.84&#xa0;mm. Correspondingly, peak runoff reached 458.6&#xa0;mm in 2009, while the lowest was 261.43&#xa0;mm in 2015. Over the study period, total rainfall amounted to 28,487.79&#xa0;mm, generating 7,364.59&#xa0;mm of runoff, accounting for 25.90% of total precipitation. The average runoff depth was 358.76&#xa0;mm, exhibiting a strong correlation with rainfall (R<sup>2</sup> = 0.81). Flood frequency analysis using the Gumbel method indicated an increasing trend in peak discharge with return periods, ranging from 11.35 m<sup>3</sup>/s for a 5-year return period to 19.90 m<sup>3</sup>/s for a 100-year return period. These findings are essential for flood risk management, watershed planning, and the development of effective flood mitigation strategies. This study underscores the importance of accurate runoff estimation and rainfall-runoff analysis for sustainable water resource management and flood risk reduction.</p>

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Runoff estimation using the SCS-CN method and GIS: a case study in the Wuseta watershed, upper blue Nile Basin, Ethiopia

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年4月24日

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  • Arega Mulu,
  • Samuel Berihun Kassa,
  • Mindesilew Lakew Wossene,
  • Taye Minichil Meshesha,
  • Ayele Almaw Fenta,
  • Yoseph Buta Hailu

摘要

Excessive runoff in floodplain areas, intensified by climate change and urbanization, poses a significant challenge, particularly during the rainy season. Accurate estimation of rainfall-induced runoff is crucial for effective watershed management and sustainable water resource utilization. This study applies the Soil Conservation Service-Curve Number (SCS-CN) method, integrated with Geographic Information Systems (GIS), to estimate runoff in the Wuseta Watershed, Upper Blue Nile Basin, Ethiopia. The SCS-CN method’s simplicity and reliability make it an effective tool for assessing runoff dynamics. Various datasets including rainfall, land use/land cover, soil characteristics, and Hydrologic Soil Group (HSG) data were utilized, with Antecedent Moisture Conditions (AMC) incorporated to capture runoff variability. Weighted Curve Numbers (C.N.) were computed for dry, normal, and wet conditions over a 20-year period, revealing significant runoff variability. The highest annual rainfall of 1,458.00 mm occurred in 2009, while the lowest (1,256.21 mm) was recorded in 2005, with an average of 1,358.84 mm. Correspondingly, peak runoff reached 458.6 mm in 2009, while the lowest was 261.43 mm in 2015. Over the study period, total rainfall amounted to 28,487.79 mm, generating 7,364.59 mm of runoff, accounting for 25.90% of total precipitation. The average runoff depth was 358.76 mm, exhibiting a strong correlation with rainfall (R2 = 0.81). Flood frequency analysis using the Gumbel method indicated an increasing trend in peak discharge with return periods, ranging from 11.35 m3/s for a 5-year return period to 19.90 m3/s for a 100-year return period. These findings are essential for flood risk management, watershed planning, and the development of effective flood mitigation strategies. This study underscores the importance of accurate runoff estimation and rainfall-runoff analysis for sustainable water resource management and flood risk reduction.