Estimation of Surface Runoff in Gebel Watershed Using SCS-CN Model and Correlation Analysis with Watershed Characteristics

Estimating surface runoff is a key factor in water resources management, especially in arid and semi-arid environments. This research aims to analyze the hydrological characteristics of the Gebel watershed, which has an area of 404.65 km², using the SCS-CN model. Three soil groups (B, C, D) are identified based on soil samples taken from the study area, and the land cover is classified into eight classes. Daily rainfall data for the year (2023-2024) are analyzed for three meteorological stations located within the study area (Akre, Dinarta, and Bajil). The Thiessen polygon method is used for spatial rainfall distribution, which contributes to improving the accuracy of the estimates. The amount of rainfall in Dinarata was (1761.8 mm), in Akre (994.9 mm), and in Bajil (1502 mm), while the surface runoff was (549.46 mm) in Dinarata, (145.11 mm) in Akre, and (442.89 mm) in Bajil; therefore, the volume of total runoff in Gebel watershed was (132851245.8 m³). The Bajil station portion is (57270105.9 m³), Dinarata has (48415096.8 m³), and Akre has (27166043.1 m³), with runoff percentages of (31.18%), (29.48%), and (14.60%), respectively. The study demonstrates that runoff has a positive correlation with precipitation (P), initial abstraction (Ia), elevation (E), slope (LS), and soil type (S). The strongest correlation is observed with precipitation (r = 0.931). In contrast, negative correlations are found with both the Curve Number (CN) and Land Cover and Land Use (LCLU), with correlation coefficients of -0.56 and -0.46, respectively. The results confirm that the SCS-CN model is an effective tool for accurately estimating surface runoff.