Uncertainties of snow cover extraction caused by the nature of topography and underlying surface

Manas River,the largest inland river to the north of the Tianshan Mountains,provides important water resources for human production and living.The seasonal snow cover and snowmelt play essential roles in the regulation of spring runoff in the Manas River Basin（MRB）.Snow cover is one of the most significant input parameters for obtaining accurate simulations and predictions of spring runoff.Therefore,it is especially important to extract snow-covered area correctly in the MRB.In this study,we qualitatively and quantitatively analyzed the uncertainties of snow cover extraction caused by the terrain factors and land cover types using TM and DEM data,along with the Per（the ratio of the difference between snow-covered area extracted by the Normalized Difference Snow Index（NDSI） method and visual interpretation method to the actual snow-covered area） and roughness.The results indicated that the difference of snow-covered area extracted by the two methods was primarily reflected in the snow boundary and shadowy areas.The value of Per varied significantly in different elevation zones.That is,the value generally presented a normal distribution with the increase of elevation.The peak value of Per occurred in the elevation zone of 3,700–4,200 m.Aspects caused the uncertainties of snow cover extraction with the order of sunny slope〉semi-shady and semi-sunny slope〉shady slope,due to the differences in solar radiation received by each aspect.Regarding the influences of various land cover types on snow cover extraction in the study area,bare rock was more influential on snow cover extraction than grassland.Moreover,shrub had the weakest impact on snow cover extraction.

Spatiotemporal variation of surface albedo and its influencing factors in northern Xinjiang, China

Surface albedo is a quantitative indicator for land surface processes and climate modeling,and plays an important role in surface radiation balance and climate change.In this study,by means of the MCD43A3 surface albedo product developed on the basis of Moderate Resolution Imaging Spectroradiometer(MODIS),we analyzed the spatiotemporal variation,persistence status,land cover type differences,and annual and seasonal differences of surface albedo,as well as the relationship between surface albedo and various influencing factors(including Normalized Difference Snow Index(NDSI),precipitation,Normalized Difference Vegetation Index(NDVI),land surface temperature,soil moisture,air temperature,and digital elevation model(DEM))in the north of Xinjiang Uygur Autonomous Region(northern Xinjiang)of Northwest China from 2010 to 2020 based on the unary linear regression,Hurst index,and Pearson's correlation coefficient analyses.Combined with the random forest(RF)model and geographical detector(Geodetector),the importance of the above-mentioned influencing factors as well as their interactions on surface albedo were quantitatively evaluated.The results showed that the seasonal average surface albedo in northern Xinjiang was the highest in winter and the lowest in summer.The annual average surface albedo from 2010 to 2020 was high in the west and north and low in the east and south,showing a weak decreasing trend and a small and stable overall variation.Land cover types had a significant impact on the variation of surface albedo.The annual average surface albedo in most regions of northern Xinjiang was positively correlated with NDSI and precipitation,and negatively correlated with NDVI,land surface temperature,soil moisture,and air temperature.In addition,the correlations between surface albedo and various influencing factors showed significant differences for different land cover types and in different seasons.To be specific,NDSI had the largest influence on surface albedo,followed by precipitation,land surface temperature,and soil moisture;whereas NDVI,air temperature,and DEM showed relatively weak influences.However,the interactions of any two influencing factors on surface albedo were enhanced,especially the interaction of air temperature and DEM.NDVI showed a nonlinear enhancement of influence on surface albedo when interacted with land surface temperature or precipitation,with an explanatory power greater than 92.00%.This study has a guiding significance in correctly understanding the land-atmosphere interactions in northern Xinjiang and improving the regional land-surface process simulation and climate prediction.