Evaluating Performance of Community-based Irrigation Schemes Using Remote-sensing Technologies to Enhance Sustainable Irrigation Water Management

An accurate estimate of the amount of water used in an irrigation scheme is vital to conserve water resources, although a reliable scheme-level estimate is difficult. The study used remote-sensing technologies to assess the Koga irrigation scheme’s performance in the Blue Nile River Basin, Ethiopia. Surface Energy Balance Algorithm for Land (SEBAL) and Landsat 8 images were used to estimate actual evapotranspiration (ETa). Additionally, the FAO-Penman-Monteith method was applied to estimate the crop’s evapotranspiration (ETc) and used as a crop water need in assessing performance parameters. The result shows that seasonal relative irrigation supply (RIS) was 6 to 77% higher than the demand. Depletion fraction (DF) varied from 0.4 to 0.5, while relative evapotranspiration deficit values ranged from 0.3 to 0.6, and the crop water use estimate was only about 50% of its need. The lower crop water use is attributed to the excessive application of water for plowing, pre-plant irrigation, and during the early stage of the crop. While the amount of water applied at the mid and late-season stages is less than the crop water need due to water mismanagement because of a lack of coordination among the water users. The study concludes that the use of remote sensing created a good potential to evaluate community-managed scheme irrigation performance. Performing under potential is an implication of low irrigation water productivity that affects environmental sustainability. Therefore, re-thinking better water management ways in community-managed schemes can help to improve water productivity and food security in the changing environment.