Identification of Critical Sub-Watersheds Prone to Soil Erosion using Remote Sensing Data and Geospatial Techniques in Thiririka Watershed, Kenya

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dc.contributor.authorInyele, Juliet
dc.contributor.authorMurimi, Shadrack
dc.contributor.authorKweyu, Raphael
dc.date.accessioned2023-09-04T12:14:23Z
dc.date.available2023-09-04T12:14:23Z
dc.date.issued2023
dc.descriptionArticleen_US
dc.description.abstractMorphometric Studies And Land Use/Land Cover Analysis Play A Key Role In Integrated Watershed Management. Sustainable Resource Utilization At A Watershed Level Requires An In-Depth Understanding Of Land Use, Drainage, And Hydrological Patterns Of The Watershed. In Developing Countries, Poverty Has Led To Unsuitable Land Management Practices (E.G. Deforestation, Continuous Tillage), Contributing To Increased Soil Erosion In Watersheds. To Reduce Soil Erosion At The Watershed Level, Watershed Managers Need To Make Informed Decisions Such As Developing Vegetative Cover And Agroforestry. However, This Is Limited Due To A Lack Of Readily Available Data To Guide The Process. This Study Explores The Potential Use Of Basin Morphometry And Land Use /Land Cover Parameters With Geographic Information Systems (GIS) And Remote Sensing (RS) Tools To Identify Areas Susceptible To Soil Erosion In Thiririka Watershed In Kenya. Five SubWatersheds Were Delineated And Assigned A Code From SW1 To SW5 Using The Shuttle Radar Topographic Mission (SRTM) 30-Meter Resolution Digital Elevation Model (DEM) In Arcgis Software, Followed By Morphometric Analysis Of Linear, Aerial, And Relief Aspects Of The Watershed. Land Use/Land Cover Classes Were Generated From A Median Composite Of Sentinel-2 2020 Image. A Supervised Classification Scheme Was Used To Develop A Random Forest Classifier To Perform The Classification. Finally, The Effects Of Each Morphometric And Land Use/Land Cover Parameters On Soil Erosion Were Assessed And Assigned Ranks 1 To 5. These Ranks Were Averaged To Get The Compound Priority (CP) In GIS Tabular Database. Results Showed That Sub-Watershed 5 Is Highly Susceptible To Soil Erosion Needing Immediate Management Actions, While Sub-Watershed 4 (SW4) Shows Less Susceptibility To Soil Erosion. The Study Recommends The Use Of Remote Sensing And GIS In Watershed Prioritization Managementen_US
dc.identifier.citationInyele, J., Murimi, S., & Kweyu, R. Identification Of Critical Sub-Watersheds Prone To Soil Erosion Using Remote Sensing Data And Geospatial Techniques In Thiririka Watershed, Kenya.en_US
dc.identifier.otherDOI: 10.9790/0990-1104011323
dc.identifier.urihttp://ir-library.ku.ac.ke/handle/123456789/26883
dc.language.isoenen_US
dc.publisherIOSRen_US
dc.subjectSoil Erosionen_US
dc.subject, Land Use / Land Coveren_US
dc.subjectMorphometric Analysisen_US
dc.subjectGISen_US
dc.subjectWatershedsen_US
dc.subjectPrioritizationen_US
dc.titleIdentification of Critical Sub-Watersheds Prone to Soil Erosion using Remote Sensing Data and Geospatial Techniques in Thiririka Watershed, Kenyaen_US
dc.typeArticleen_US
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