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dc.contributor.authorKimeli, Noah
dc.date.accessioned2017-11-16T05:14:08Z
dc.date.available2017-11-16T05:14:08Z
dc.date.issued2017-08
dc.identifier.urihttp://hdl.handle.net/11295/101213
dc.description.abstractSurface runoff isasinglemost significanthydrological variablethat isutilizedin many civil works, planning for optimal usageof reservoirs, shapingrivers and floodcontrol.Predictionand quantification of catchment runoffis a basic challenge in hydrology.In this study, estimationof floodwatersby Soil Conservation Services-Curve Number(SCS-CN) methodusing GISwasconducted.The important parametersincludeland use map, hydrologic soil groups, daily rainfall dataandDigital Elevation Model (DEM). The landusedatawasderivedfrom Landsat satellite images. Hydrological Soil Group(HSG)thematic map wasalsopreparedbased on the soil type, infiltration rate and percentage slope. A spatial union between theland use and HSG datasetswas created to obtain Soil-Vegetation-Land use (SVL) complexwhich wasthen assigned the Antecedent Moisture Condition II (AMC II) Curve Numbers (CN)valuesbased on respective classes. Weighted-CN wascalculated as the product of CN-values and percentage areal coverage of respective classes hence resulting in arunoff potential map.Using daily precipitation data recorded in a weather station, sum of five-dayprior precipitation wascomputed to give the AMC for each day.Revision of weighted AMC II wasdone based on AMC results.Direct daily runoffdepthin the watershedwasthen computed using SCS-CN equation.The depth was laterconverted to runoff volume. It was revealed thatrunoff potential of the watershed is increasing at a very slow rate due to insignificant changes in land use. The annual runoff volume was found to range between 7,120,686.458M3during the period of low rains to95,632,370.51 M3during heavy rains.When dailyrunoff wascomputed from theseresults, the daily floodwaters volume was found to becomparable with the NCT valuethat was used to validate the results.Keywords: Surface runoff,SCS-CN,GIS, HSG,SVL complex.
dc.language.isoenen_US
dc.publisherUniversity of Nairobien_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.titleApplication of GIS estimation water runoff volume in water collection sites: case study of northern collector water tunnelen_US
dc.typeThesisen_US


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Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivs 3.0 United States