Modeling Land-use Land-cover Change And Assessment Of Its Impacts On Hydrology Using Gis And Remote Sensing Techniques A Case Of Muger Catchment Ethiopia
Geodesy And Geomatics Project Topics
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Assessing the impacts of LULC change on hydrology plays a great role in the effective planningrnand management of hydrological resources of the catchment. The change of LULC has a directrneffects on the different hydrological processes that occur during and after rainfall, such asrnsurface discharge, evaporation, evapotranspiration, groundwater infiltration, and surfacernrunoff. Therefore, modeling the land-use land-cover change and assessment of its impacts onrnhydrology is critically an important issue at the current time. This study deals on modeling thernland-use land-cover change and assessment of its effects on the hydrology for Muger catchmentrnby using GIS and remote sensing techniques through integrating with the SWAT hydrologicalrnmodel. It was conducted using the spatio-temporal data such as slope, land-use land-cover, soil,rnmeteorological and hydrological data from the different sources. The maximum likelihoodrnclassification, change detection, and SWAT hydrological model was deployed to perform thisrnanalysis. Finally, the sensitivity analysis, model calibration, and validation were beingrnconducted. There is a strong relationship between the measured and simulated monthly flowsrnbased on the calibration results with the NSE of 0.81 and R2 of 0.86 for Aleltu River; NSE ofrn0.63 and R2 of 0.84 for Muger River and NSE of 0.66 and R2 of 0.79 for Sibilu River. In addition,rnthe validation result reveals that the measured and simulated flow are in good agreement withrnthe NSE of 0.73 and R2 of 0.89 for Aleltu River; NSE of 0.66 and R2 of 0.88 for Muger River andrnNSE of 0.87 and R2 of 0.89 for Sibilu River. The change of the LULC is the driving force tornchange an ecosystem and environmental processes in different ways. Therefore, this studyrnfacilitates the society within Muger catchment for conducting proper land management practicesrnas well as proper utilization of the water resources.
Subsurface Intelligence & Critical Mineral Exploration
Modern Geology projects now focus on Machine Learning in Mineral Targeting, Carbon Capture & Storage (CCS) Geologic Modeling, and Critical Mineral Systems (Lithium, REEs). If your research involves Hydrogeological Connectivity, Seismic Inversion, or Geotechnical Site Characterization, ensure your analysis follows the JORC or NI 43-101 reporting standards and utilizes robust 3D Subsurface Visualization and Geochemical Fingerprinting frameworks.
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