[Simulation of temporal-spatial variation characteristics of surface runoff in Changbai Mountain based on process model for landscape scale].

The seasonal dynamics and spatial distribution characteristics of surface runoff in Changbai Mountain simulated by the process model (EPPML), and the relationships between surface runoff and environmental conditions were analyzed. The results showed that the seasonal variation of surface runoff in Changbai Mountain presented obvious three-peak pattern, i.e., the lowest values in June and September, peak values in August (2.58 mm.d-1), similar to that of soil water content. Total trend of surface runoff for different vegetations in the growing season was in order of grass and shrub > coniferous forest > broad-leaved forest > mixed broad-leaved and Korean pine forest, highly correlated to LAI. Annual surface runoff in 1995 was estimated to be 0.203 m.yr.-1, mostly ranging from 0.0 to 0.246.m.yr.-1, accounting for 69.3%. The trend of spatially increasing annual surface runoff along with increasing altitude was obvious. The maximum annual surface runoff appeared in alpine grass (0.619 m.yr.-1), minimum in mixed broad-leaved and Korean pine (Pinus koraiensis) forest (0.081 m.yr.-1), others being alpine tundra, Betula ermanii forest, meadow, shrub, mixed spruce (Picea asperata) and fir (Abies nephrolepis) forest, Changbai larch (Larix olgensis) forest and broad-leaved forest. Vegetation and environmental conditions controlled the main trend of the spatial distribution of annual surface runoff in Changbai Mountain. There was very strong negative exponential correlativity between annual surface runoff and LAI (R2 = 0.857). The more LAI, the more literfall, the more precipitation intercepted by litter, thus, the less surface runoff. Annual surface runoff was highly negatively correlated with air temperature and total solar radiation (R2 being 0.965 and 0.836 respectively), however, it was highly positively correlated with precipitation, relative humidity and wind speed (R2 being more than 0.950). And annual surface runoff was also strongly correlated to soil characteristics.