The dynamics of snow cover differs greatly from basin to basin in the Songhua River of Northeast China, which is attributable to the differences in the topographic shift as well as changes in the vegetation and climat...The dynamics of snow cover differs greatly from basin to basin in the Songhua River of Northeast China, which is attributable to the differences in the topographic shift as well as changes in the vegetation and climate since the hydrological year(HY) 2003. Daily and flexible multi-day combinations from the HY 2003 to 2014 were produced using Moderate Resolution Imaging Spectroradiometer(MODIS) from Terra and Aqua remote sensing satellites for the snow cover products in the three basins including the Nenjiang River Basin(NJ), Downstream Songhua River Basin(SD) and Upstream Songhua River Basin(SU). Snow cover duration(SCD) was derived from flexible multiday combination each year. The results showed that SCD was significantly associated with elevation, and higher SCD values were found out in the mountainous areas. Further, the average SCDs of NJ, SU and SD basins were 69.43, 98.14 and 88.84 d with an annual growth of 1.36, 2.04 and 2.71 d, respectively. Binary decision tree was used to analyze the nonlinear relationships between SCD and six impact factors, which were successfully applied to simulate the spatial distribution of depth and water equivalent of snow. The impact factors included three topographic factors(elevation, aspect and slope), two climatic factors(precipitation and air temperature) and one vegetation index(Normalized Difference Vegetation Index, NDVI). By treating yearly SCD values as dependent variables and six climatic factors as independent variables, six binary decision trees were built through the combination classification and regression tree(CART) with and without the consideration of climate effect. The results from the model show that elevation, precipitation and air temperature are the three most influential factors, among which air temperature is the most important and ranks first in two of the three studied basins. It is suggested that SCD in the mountainous areas might be more sensitive to climate warming, since precipitation and air temperature are the major factors controlling the persistence of snow cover in the mountainous areas.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41471291,41801283,41070104)Startup Foundation for Doctors of Jilin Jianzhu University(No.861111)13th Five-Year Plan of Technical and Social Research Project for Jilin Colleges(No.JJKH20170257KJ)
文摘The dynamics of snow cover differs greatly from basin to basin in the Songhua River of Northeast China, which is attributable to the differences in the topographic shift as well as changes in the vegetation and climate since the hydrological year(HY) 2003. Daily and flexible multi-day combinations from the HY 2003 to 2014 were produced using Moderate Resolution Imaging Spectroradiometer(MODIS) from Terra and Aqua remote sensing satellites for the snow cover products in the three basins including the Nenjiang River Basin(NJ), Downstream Songhua River Basin(SD) and Upstream Songhua River Basin(SU). Snow cover duration(SCD) was derived from flexible multiday combination each year. The results showed that SCD was significantly associated with elevation, and higher SCD values were found out in the mountainous areas. Further, the average SCDs of NJ, SU and SD basins were 69.43, 98.14 and 88.84 d with an annual growth of 1.36, 2.04 and 2.71 d, respectively. Binary decision tree was used to analyze the nonlinear relationships between SCD and six impact factors, which were successfully applied to simulate the spatial distribution of depth and water equivalent of snow. The impact factors included three topographic factors(elevation, aspect and slope), two climatic factors(precipitation and air temperature) and one vegetation index(Normalized Difference Vegetation Index, NDVI). By treating yearly SCD values as dependent variables and six climatic factors as independent variables, six binary decision trees were built through the combination classification and regression tree(CART) with and without the consideration of climate effect. The results from the model show that elevation, precipitation and air temperature are the three most influential factors, among which air temperature is the most important and ranks first in two of the three studied basins. It is suggested that SCD in the mountainous areas might be more sensitive to climate warming, since precipitation and air temperature are the major factors controlling the persistence of snow cover in the mountainous areas.
