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Arnold, J.G., Moriasi, D.N., Gassman, P.W., Abbaspour, K.C., White, M.J., Srinivasan, R., Santhi, C., Harmel, R.D., van Griensven, A., Van Liew, M.W. and Kannan, M.K. (2012) Model Use, Calibration, and Validation. American Society of Agricultural and Biological Engineers, 55, 1491-1508.

has been cited by the following article:

• TITLE: Assessing the Impacts of Land Use and Land Cover Changes on Hydrology of the Mbarali River Sub-Catchment. The Case of Upper Great Ruaha Sub-Basin, Tanzania

  AUTHORS: Edmund Mutayoba, Japhet J. Kashaigili, Frederick C. Kahimba, Winfred Mbungu, Nyemo A. Chilagane

  KEYWORDS: Geographic Information System (GIS), Mbarali River Sub-Catchment, Land Use and Cover Change, Soil and Water Assessment Tool (SWAT), Water Balance, Stream Flow

  JOURNAL NAME: Engineering, Vol.10 No.9, September 29, 2018

  ABSTRACT: Intensification of agricultural land use and population growth from 1990-2017 has caused changes in land cover and land use of the Mbarali River sub-catchment which is located in the Upper Great Ruaha Sub basin, Tanzania. This has affected the magnitude of the surface runoff, total water yield and the groundwater flow. This study assesses the impacts of the land cover and land use changes on the stream flows and hydrological water balance components (surface runoff, water yield, percolation and actual evapotranspiration). The land use and land cover (LULC) maps for three window period snapshots, 1990, 2006 and 2017 were created from Landsat TM and OLI_TIRS with the help of QGIS version 2.6. Supervised classification was used to generate LULC maps using the Maximum Likelihood Algorithm and Kappa statistics for assessment of accuracy. SWAT was set up and run to simulate stream flows and hydrological water balance components. The assessment of the impacts of land use and land cover changes on stream flows and hydrological water balance component was performed by comparing hydrological parameters simulated by SWAT using land use scenarios of 2006 and 2017 against the baseline land use scenario of 1990. Accuracy of LULC classification was good with Kappa statistics ranging between 0.9 and 0.99. There was a drastic increase in areal coverage of cultivated land, for periods 1990-2006 (5.84%) and 2006-2017 (12.05%) compared to other LULC. During 2006 and 2017 surface runoff increased by 4% and 9% respectively; however, water yield increased by only 0.5% compared to 1990 baseline period. This was attributed to increased proportion of cultivated land in the sub-catchment which has a high curve number (59.60) that indicates a higher runoff response and low infiltration rate.