As a result of the increased availability of spatial information in watershed modeling, several easy to use and widely accessible spatial datasets have been developed. Yet, it is not easy to decide which source of data is better and how data from different sources affect model outcomes. | Turkish Journal of Agriculture and Forestry Research Article Turk J Agric For (2014) 38: 515-530 © TÜBİTAK doi: Evaluating the impact of land use uncertainty on the simulated streamflow and sediment yield of the Seyhan River basin using the SWAT model 1, 2 Ashraf EL-SADEK *, Ahmet İRVEM Desert Research Center, Ecology and Dryland Agriculture Division, Cairo, Egypt 2 Biosystem Engineering Department, Faculty of Agriculture, Mustafa Kemal University, Antakya, Turkey 1 Received: Accepted: Published Online: Printed: Abstract: As a result of the increased availability of spatial information in watershed modeling, several easy to use and widely accessible spatial datasets have been developed. Yet, it is not easy to decide which source of data is better and how data from different sources affect model outcomes. In this study, the results of simulating the stream flow and sediment yield from the Seyhan River basin in Turkey using 3 different types of land cover datasets through the soil and water assessment tool (SWAT) model are discussed and compared to the observed data. The 3 land cover datasets used include the coordination of information on the environment dataset (CORINE; CLC2006), the global land cover characterization (GLCC) dataset, and the GlobCover dataset. Streamflow and sediment calibration was done at monthly intervals for the period of 2001–2007 at gauge number 1818 (30 km upstream of the Çatalan dam). The model simulation of monthly streamflow resulted in good Nash–Sutcliffe efficiency (NSE) values of , , and for the GLCC, GlobCover, and CORINE datasets, respectively, for the calibration period. Furthermore, the model simulated the monthly sediment yield with satisfactory NSE values of , , and for the GLCC, GlobCover, and CORINE land cover datasets, respectively. The results suggest that the sensitivity of the SWAT .
