Estimation of Runoff Using CN Method and Arc GIS for Irrigation Water Accessibility at Kulumsa Watershed, Arsi Zone of Ethiopia

Abstract

Rainfall and runoff are essential components in water resources assessment. Rainfall serves various purposes, including agriculture, hydropower, industries, climate, and the environment, being the primary source of runoff. Rainfall-runoff models estimate surface runoff from watersheds. This study aimed to locate potential water harvesting sites and estimate runoff for irrigation at the Kulumsa Agricultural Research Center. The Curve Number (CN) model predicted runoff based on empirical equations for ungauged Kulumsa watersheds. Rainfall, land use/land cover, and soil data were used for runoff estimation. Landsat 8 imagery from the USGS aided land use/land cover preparation and underwent accuracy assessment. Data on land use and soil types were inputted into a GIS to determine the composite curve number, resulting in a watershed CN of 85, with AMC I dry and AMC III wet seasons having values of 71 and 93, respectively. The Kulumsa watershed has 4.66 km² and receives an average annual rainfall of 821mm. The estimated average annual surface runoff depth was 78.9mm, with a computed volume of approximately 3,673,024m³ generated during the same period. This runoff volume represents 9.61% of the total annual rainfall, signifying the portion that contributed to runoff instead of infiltrating the soil. This study demonstrates the practicality and efficiency of using empirical models integrated with GIS for water resource management. Findings not only highlight potential water harvesting and irrigation but also provide insights for policymakers and water resource managers. Moreover, it presents a scalable framework applicable to diverse areas, contributing to enhanced water management practices and bolstering agricultural sustainability in Ethiopia.