Assessing the influence of land use and land cover datasets with different points in time and levels of detail on watershed modeling in the North River Watershed, China.

Land use and land cover (LULC) information is an important component influencing watershed modeling with regards to hydrology and water quality in the river basin. In this study, the sensitivity of the Soil and Water Assessment Tool (SWAT) model to LULC datasets with three points in time and three levels of detail was assessed in a coastal subtropical watershed located in Southeast China. The results showed good agreement between observed and simulated values for both monthly and daily streamflow and monthly NH(4)+-N and TP loads. Three LULC datasets in 2002, 2007 and 2010 had relatively little influence on simulated monthly and daily streamflow, whereas they exhibited greater effects on simulated monthly NH(4)+-N and TP loads. When using the two LULC datasets in 2007 and 2010 compared with that in 2002, the relative differences in predicted monthly NH(4)+-N and TP loads were -11.0 to -7.8% and -4.8 to -9.0%, respectively. There were no significant differences in simulated monthly and daily streamflow when using the three LULC datasets with ten, five and three categories. When using LULC datasets from ten categories compared to five and three categories, the relative differences in predicted monthly NH(4)+-N and TP loads were -6.6 to -6.5% and -13.3 to -7.3%, respectively. Overall, the sensitivity of the SWAT model to LULC datasets with different points in time and levels of detail was lower in monthly and daily streamflow simulation than in monthly NH(4)+-N and TP loads prediction. This research provided helpful insights into the influence of LULC datasets on watershed modeling.