Institute of Technology
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Item LAND USE LAND COVER CHANGE DYNAMICS AND SOIL LOSS: GIS AND REMOTE SENSING BASED ANALYISIS, IN SHASHOGO WEREDA, HADIYA ZONE, SNNPRS, ETHIOPIA(Hawassa University, 2018-10-26) YOSEPH DEBOCH HANKOREThe relationship between land use land cover change dynamics and soil loss over the last four decades (1973-2015) was investigated using GIS and Remote Sensing data at Shashogo Wereda, Hadiya Zone, SNNPRS, Ethiopia. In order to achieve these, satellite data of Landsat 1 MSS for 1973, Landsat 5 TM for 1986, Landsat 7 ETM plus for 2000, and Landsat 8 OLI for 2015 have been obtained and pre-processed using ERDAS Imagine 2014 software. The Maximum Likelihood Algorithm of Supervised Classification has been used to generate LULC maps. Ancillary data were used to validate the classified LULC maps. For the accuracy of classified LULC maps, a confusion matrix was used to derive overall accuracy and results were above the minimum and acceptable threshold level. For change detection statistics, cross-tabulation matrices method was employed to identify gains and losses between LULC classes. The study analyzed the magnitude of spatial and temporal LULC changes for three consecutive periods; 1973 to 1986, 1986 to 2000, and 2000 to 2015. Moreover, the soil loss from the watershed was estimated using USLE employing GIS tools. Results of the study revealed that the study area has undergone substantial LULC changes. Over the 42yrs, the aerial coverage of cultivated land was increased from 43.9 to 63.0% between 1973 and 2015. Similarly, water body and wetland were increased from 0.6 to 3.9% and 4.4 to 6.7% respectively. Settlement area which was not found in the first and second period of study years, satellite image result have 2.9% proportion in 2015 LULC classification. On the other hand, grass land, bush land, and bare land were decreased from 16.1 to 6.5%, 28.6 to 12.4%, and 6.4 to 4.5% between 1973 and 2015, respectively. Following the land use change pattern, soil loss values were increased in 2015. The estimated soil loss rate in the watershed was 14.31t/ha/yr in 2015. The findings of this study suggested that the rate of LULC change over the study period, particularly intensively cultivated land, bare land, and soil erosion problems need to be given due attention to maintain the stability of the ecosystemItem IMPACT OF SOIL EROSION ON CHELELEKA WETLAND AREA OF TIKURWUHA CATCHMENT, LAKE HAWASSA WATERSHED, SOUTHERN ETHIOPIA(Hawassa University, 2017-10-22) ASHAGO AGARO ALITEnvironmental depletion and loss of wetland ecosystem due to soil erosion from the nearby catchment is an alarming issue because of its adverse impact on the environment that aggravated due to human pressure. This research was carried out on Tikurwuha catchment that has faced tremendous environmental problems in the last 30 years. The objective of the research was to assess the current status of soil erosion from the catchment and to detect changes on each land use /land land cover in the catchment in 1985, 2000 and 2015 time periods. The study related to estimating soil erosion from the catchment was undertaken using Revised Universal Soil Loss Equation (RUSLE) model integrating with Geographic Information System (GIS). Change in the area detected using 1985, 2000 and 2015 year satellite images. Questionnaires and focused group discussion were employed to identify major contributed factors for soil erosion in the catchment within 30 years. The result indicated that the annual soil loss in the catchment within slope classification, ranges from 0.003 to 19,886.5 t//yr and the average soil loss ranges 0.004 t/ha/yr to 13.61 t/ha/y and about 60.8% of the study area were identified to experience very low annual soil loss, whereas 21.16% of the study area experienced low annual soil losses and 18 % of the study area experienced as its high contribution for annual soil loss in the catchment. Significant change has occurred and observed in the wetland sub- catchment by analyzing three years Land sat images in the last 30 years. The areas that were covered with marsh land in 1985 were 3609.92 ha this was changed to 2441.40ha in the 2000 and this was decreased to 1651.74 ha in the 2015 and has shown 54.22% decrease from 1985 to 2015. The area that were covered with forest in 1985 was 2950.78ha and this was changed to 4409.01ha in 2000 and this was decreased to 1261.97ha in 2015 and has shown 57.14% decrease from 1985 to 2015. The area that were covered with cultivated land in 1985 was 20932ha and this increased to 31912.55 ha in 2000 and this has increased to 33080.75 ha in 2015 and it has shown 58.02% increase from 1985 to 2015. Farmers’ attitudes were also analyzed and they replied that forest degradation, agricultural land expansion and unwise use of catchments are the main causes for the decrease of wetland areas and for the soil loss in the catchmenItem GIS BASED SOIL LOSS ESTIMATION USING USLE MODEL FOR SOIL CONSERVATION PLANNING: IN KARESA WATERSHED, LOMA WOREDA, SOUTH WEST ETHIO(Hawassa University, 2017-10-10) BAGEGNEHU BEKELE MENGISTUSoil erosion is the most challenging and continuous environmental problems resulting in both on-site and off-site effects in the world particularly in Ethiopia. Karesa watershed is one of the most erosion-prone watersheds which received little attention. Managing the on site erosion is to reduce the negative impacts of downstream water resources and requires an understanding of the rates of soil loss as well as identification of the major controlling factors that enhance or retard these processes. This study was conducted to estimate average annual soil loss rate using Geographic Information System and Universal Soil Loss Equation Model adapted to Ethiopian condition. The following datasets were obtained from different sources for estimating annual soil loss such as 15 years mean annual rainfall data for estimating Erosivity factor, digital soil map for estimating soil Erodibility factor, 30m x 30m resolution Digital Elevation Model for estimating slope length and slope steepness (LS) factor, Landsat6ETM+ images with 30mx30m resolution for detecting Vegetation cover and Conservation practice factor. Raster calculator was used to interactively multiply and produce annual soil loss. The result reveals that 42,413.72 ton per year soil loss from 9939 ha entire watershed and 4.27 tons per hectare per year average annual soil loss rate. The mean annual soil loss rate was classified in to four erosion severity classes as very less, less, moderate and High . The result also implies, two slope classes (0-15% and 15-30%) were categorized under very less to less soil loss (0-6.25 tons ha-1 yr-1 ) which accounts an area of 9383.07 ha (94.4%) of the watershed areas and representing 81.13% of the total soil loss. On the other hand, the watershed slope classes (>30%) fell under moderate to High soil loss (6.25-25 tons ha-1 yr-1 ) together covers 555.93ha (5.6%) of the watershed areas contributing 18.82% of the total soil loss mainly due to cultivation of marginal land,Intensive cultivation, poor vegetation cover during critical rainfall period. Moreover, about 2,184.93 ha of the watershed area was highly affected by erosion which contributes 18,182.25 tones yr-1 (42.87%) total soil loss and requires integrated soil and water conservation measuresItem Land use/land cover change and soil erosion risk mapping in Shebedino woreda, Sidama zone, southern Ethiopia(Hawassa University, 2017-10-12) ADDISU AMARE HABTESoil erosion is one of the major environmental problems that threaten sustainable agricultural production. Estimates of soil erosion risks and changes in the land use land cover will assist effective and sustainable land management and soil and water conservation (SWC) measures implementations. This study reported assessments of Land use/land cover changes between periods of 1973 and 2014 using GIS and Remote Sensing technique of Shebedino woreda. The study also attempted to map soil erosion risk by water and estimated the rate of soil erosion using Universal Soil Loss Equation in combination with GIS and Remote Sensing applications. Two satellite imageries (Landsat MSS 1973 and Landsat ETM+2014) have been used for change detection. Ethiopia soil map and soil survey data, 23 years rainfall data, a digital elevation model image, and land cover map for the year of 2014 have been used to estimate rate of soil erosion. Subsequently, land use/land cover map of the year 1973 and 2014, and soil erosion risk map of the study area have been produced. The study revealed that in the last four decades significant changes have been detected on LULCC. Forest cover and grazing land significantly decreased at a rate of 184.22 ha/yr and 38.08 ha/yr respectively; on the other hand cultivated land has shown increment in area at a rate of 179.91 ha/yr; and settlement has shown increment as well. The soil erosion risk analysis result shows that the woreda exhibited soil erosion rate of between 0 to 50 tonnes per hectare per year. The total annual soil loss in the study area was about 77200.50 tonnes, with 3.92 tonnes per hectare per year of mean annual rate of soil loss. A significant increment (159 %) in total annual soil loss has been observed. The total annual soil loss amount increased to 77200.50 tonnes in 2014 compared to 31076.05 tonnes 1973 situation. Based on the finding of this study, it was concluded that there were significant land use/ land cover change happened in the woreda. Part of the worda is prone to soil erosion risks. Therefore, all woreda level actors should give emphases to the situation and devise appropriate interventions measures for better and effective management of land recoursesItem HYDRAULIC MODELING AND FLOOD MAPPING OF HAROSHA RIVER WITH HEC-RAS AND HEC-GeoRAS MODELS IN TIGRAY, ETHIOPIA(Hawassa University, 2017-10-27) MULUGETA TAREKE ABEBEThe Harosha river catchment is found in Tigray region in Raya Valley. This study area is surrounded by Waja and Tumuga catchment in the south and Harosha, Limeat and Harle catchment in the North and also it is the upper south part of the Raya valley catchment. The area is also dominated by undulating terrain with relatively steep to moderately steep and flatter slopes in the downstream of the catchment. Harosha flood plain has been vulnerable to high flooding from rainfall during rainy season. Also the main causes of these damages are land use changes from years to years and the main objective of this study is to estimate peak flood for various return period and prepare flood inundation mapping that can be used as decision support system for future intervention. The data used for this study was annual daily maximum rainfall, DEM, land use land cover map, and soil map and the flood frequency analysis of annual maximum daily rainfall was analyzed. The SCS rain fall-runoff method, HEC-RAS, HEC-GeoRAS and ArcGIS environment are used to determine the peak flood for different return periods. The simulation result for return period of 5, 10, 25, 50 and 100 year floods magnitude are 347.4, 383.7, 420.8, 443.6 and 463.1m 3 /s respectively. The maximum flood hazard and flow depth maps for a return periods of 5, 10, 25, 50 and 100 year are 84.6 and 3.36; 86.1 and 3.84; 86.9 and 4.35; 87.1 and 4.91; and 87.7 hectare and 5.89 m respectively with a maximum velocity of 4.6 m/s.Item IDENTIFICATION OF GROUNDWATER POTENTIAL ZONE BY USING GIS AND REMOTESENSING IN SUTEN TO TORA SUB-CATCHMENT, RIFT VALLEY LAKES BASIN, SOUTHERN ETHIOPIA(Hawassa Unversity, 2019-10-21) ASCHALEW GURMUThis study was aimed to mapping of Groundwater potential investigation of Suten-Tora sub catchment in the Rift Valley Lakes basin, Southern Ethiopia. Climate, hydro-geological, land use/land cover, soil, lithology, geomorphology and stratigraphic data were collected, analyzed and inferred. The aquifer characteristics from the well completion reports were used to map the Groundwater flow direction. A Groundwater level contour map; which developed from well completion report is revealed that the Groundwater flows from western towards the center and eastern part of the sub-catchment. The results also inferred from the geological formations show that the Suten-Tora Sub-catchment are mainly covered by partially welded pyroclastic flow, Gash Megal rhyolitic lava flows, Guraghe-Anchor basalt, Nazret welded pyroclastic, Lacustrine sediment, Mesozoic sediment, porphyritic rhyolitic lava domes, Wonji basalts, Precambrian basement complex and recent basalt flows. Moreover, there is also a Geological structure in the study area. The linear feature of these structures are characterized by three distinct interconnected fault trends systems are called in NW-SE, NE-SW and N-S which are more or less affect the availability of Groundwater potential. Among the above listed lithological formations lacustrine sediments, Wonji basalt with scoria deposit and pyroclastic are coincide with high Groundwater potential zone. Similarly a moderate Groundwater potential zone is covered by Geological formations; e.g. Chefe Donsa, un-welded to poorly weld pyroclastic and others small formations. In the other way low and very low potential zones are covered by depositions of Nazret pyroclastic, Gash Megal rhyolite and other similar lithological formations. For the delineation of Groundwater potential zones, the weight over analysis of different factors namely: lineament density, lithology, geomorphology, slope, soil texture, drainage density, rainfall and elevation have been analyzed through the Analytical Hierarchal process (AHP) and ArcGIS 10.3 software. The delineated Groundwater potential zone was categories into four classes namely high, moderate, low and very low potential zone. These delineated Groundwater potential zones class called high, Moderate, Low and very low potential zones are covers an area of around 50%, 20%, 16% and 14% of the total sub catchment area respectively. To conclude that; the center and southeastern parts of the sub catchment have high amounts of Groundwater potential. However the western part has les Groundwater potential. Depend on the validation of output accuracy level; the delineation of Groundwater potential zones by using GIS and remote sensing techniques is important method. Finally it has been recommend that ; the well drillers in this study area suggested to use this Groundwater potential zone map as informationItem ASSESSMENT OF SURFACE IRRIGATION POTENTIAL: THE CASE OF GIDABO WATERSHED, RIFT VALLEY LAKES BASIN, ETHIOPIA(Hawassa University, 2019-03-07) AZEMERAW ALEMUEthiopia has immense potential in expanding irrigated agriculture. Irrigable land assessment is essential for the development of irrigated agriculture. The study was aimed at assessing land potential of Gidado watershed. Land suitable for irrigation development was determined with a GIS-based multi-criteria evaluation, which considers the interaction of various factors such as slope, soil, LULC, proximity to river and road. The Analytical Hierarchal Process (AHP) and ArcSWAT were used for analyzing the different factors by assigning weights and mapping of suitable potential irrigable areas and surface water potential of the study area was estimated using SWAT model respectively. The model was calibrated and validated from observed stream flow data at three monitoring sites within the watershed using the periods of 1993-2004 and 2005-2012 respectively by using SWAT-CUP program and Global Sensitivity Analysis (GSA) was used for identifying important model parameters. The irrigable land of the area was identified using weighted overlay analysis of the suitability parameters, thus the result indicated that 1138.31 km2 areas was classified suitable and 2042.19 km2 area was classified as not suitable for surface irrigation. During calibration and validation, the results of model performance indicators were in the acceptable range (R 2= 0.68, 0.73, 0.72), (NSE = 0.60, 0.63, 0.71) and (PBIAS=12.2, -9.0 and -14.0) for Gidabo, Kola and Bedessa rivers respectively which indicated that a good to very good agreement between observed and simulated values. And average surface water resource potential of the catchment estimated to be 86.36m3 /s or 223.86 MCM. However after analyzing 25 years river discharge and determined the water demand of the crop, 74390.89ha (23.39%) of the potential irrigable area was estimated and could be irrigated consistently with runoff from the river systems. For sustainable irrigation development, other suitability factors such as soil chemical properties, socio-economic, environmental issues, and distance from markets and town should be consideredItem HYDRAULIC MODELING AND FLOOD MAPPING OF HAROSHA RIVER WITH HEC-RAS AND HEC-GeoRAS MODELS IN TIGRAY, ETHIOPIA(Hawassa University, 2017-03-10) MULUGETA TAREKE ABEBEThe Harosha river catchment is found in Tigray region in Raya Valley. This study area is surrounded by Waja and Tumuga catchment in the south and Harosha, Limeat and Harle catchment in the North and also it is the upper south part of the Raya valley catchment. The area is also dominated by undulating terrain with relatively steep to moderately steep and flatter slopes in the downstream of the catchment. Harosha flood plain has been vulnerable to high flooding from rainfall during rainy season. Also the main causes of these damages are land use changes from years to years and the main objective of this study is to estimate peak flood for various return period and prepare flood inundation mapping that can be used as decision support system for future intervention. The data used for this study was annual daily maximum rainfall, DEM, land use land cover map, and soil map and the flood frequency analysis of annual maximum daily rainfall was analyzed. The SCS rain fall-runoff method, HEC-RAS, HEC-GeoRAS and ArcGIS environment are used to determine the peak flood for different return periods. The simulation result for return period of 5, 10, 25, 50 and 100 year floods magnitude are 347.4, 383.7, 420.8, 443.6 and 463.1m 3 /s respectively. The maximum flood hazard and flow depth maps for a return periods of 5, 10, 25, 50 and 100 year are 84.6 and 3.36; 86.1 and 3.84; 86.9 and 4.35; 87.1 and 4.91; and 87.7 hectare and 5.89 m respectively with a maximum velocity of 4.6 m/s.