Floods are one of the leading causes of destruction from natural disasters. Flooding causes majorrnstresses on the economic, social and environmental regimes. Structural and non-structuralrnmeasures are applied to prevent flood hazard destruction. Meanwhile, the flooding of August 5rn2006 in Dire Dawa town demonstrated that structural measures undertaken so far are notrnadequate to withstand flood threats. Non-structural techniques for preventing flood damage arernbased on acceptance of flooding as a natural process that cannot be completely controlled. Thisrnapproaches focus on altering human behavior and awareness. In this study, flood hazardrnforecasting and early warning system in Dire Dawa was developed using SCS-CN method, i.e.rnone of the techniques under non-structural approaches. The developed system has sevenrnincorporated applications namely, initial abstraction analysis, maximum retention analysis, floodrnanalysis, antecedent moisture content calculator, curve number conversion, flood prone areasrnanalysis and messaging, and developed using C# object oriented programming language. Thernstudy was carried out by using Landsat 7 ETM+ and Landsat 8 OLI satellite imageries of thernyears 2005 and 2015, respectively, 15 m Ã— 15 m digital elevation model and harmonized worldrnsoil data for hydrologic soil group classification. Images were classified into classes usingrnsupervised image classification. The results showed that 74.53% area of Dire Dawa town hasrnhigh value of CN, 10.21% is moderate and 16.07% of the town has low CN value, this impliesrnmost part of the area has low maximum retention and initial abstraction value. A reliabilityrnassessment of the system was conducted on the produced flood map of the first week of Augustrn2006. The assessment result revealed that the system is fully functional for the intendedrnapplication.rnKeywords: SCS-CN method, flood forecasting, early warning system, Dire Dawa.