A THESIS SUBMITTED TO THE FACULTY OF HYDRAULIC AND WATER RESOURCES ENGINEERING ARBA MINCH WATER TECHNOLOGY INSTITUTE SCHOOL OF GRADUATE STUDIES ARBA MINCH UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENT FOR THE DEGREE OF MASTER OF SCIENCE INHYDRAULIC ENGINEERING

Abstract

Land use and land cover change is one of the responsible factors for changing hydrological process of watershed, for that reason, study aimed at assessing the effects of land use land cover changes on stream flow of Woibo catchment to be importance to hydrologists, land use planners, watershed management and decision makers for sustainable water resource projects and planet ecosystems. Arc GIS10.2.1 and ERDAS IMAGINE 2014 were used to process soil raster data set and prepare land use/cover maps from land sat images acquired in 1993, 2005 and 2017 years respectively. Land use classification was performed using supervised classification system and accuracy assessment was done using confusion matrix. Classification results showed expansion of agricultural lands from 58 % in 1993 to 77.95 % in 2005 LULC and from 77.95 % in 2005 LULC to 86.65 % in 2017 LULC. Moreover, increments of bare, rural and urban settlement lands under expenses of forest, bush and grass lands. The catchment is undergoing land use changes due to intensive cultivation and urbanization as a result of population growth which has an impact on hydrologic response of the basin. Geographic Information system (GIS) was integrated with SWAT model to quantify basin runoff volume and evaluated the effects of land use/land cover change on the stream flow. After sensitivity analysis, the model calibration was done from 1993 to 2008 and validation from 2009 to 2015. The calibration and validation results shows very good agreement between simulated and observed data with Nash-Sutcliff efficiency of 0.78 and 0.75, coefficient of determination (R2) 0.79 and 0.76 for calibration and validation respectively. The result of land use dynamics impact specified that land use land cover changes have significant effects on stream flow, surface runoff, ground water etc. The result shows the wettest monthly flow increased by 5.54 m3/s from 1993 to 2005, 9.09 m3/s from 2005 to 2017, 14.63 m3/s from 1993 to 2017 m3/s) and the driest monthly flow decreased by1.96 m3/s from 1993-2005, 0.5 m3/s from 2005 to 2017 and 3.46 m3/s 1993 to 2017).