基于MODIS数据的2000-2013年西昆仑山玉龙喀什河流域积雪面积变化

利用两种卫星影像合成并引入冰川积雪区的方法，对西昆仑山玉龙喀什河流域2000-2013 年MOD10A2积雪数据进行去云处理，分析不同海拔高度积雪的年内和年际变化特征及趋势，结合气象要素，分析其分布变化原因。结果表明：① 低山区（1650-4000 m）积雪年内变化为单峰型，补给期为冬季，而高山区（4000~6000 m）存在“平缓型”春季补给期和“尖峰型”秋季补给期两个峰值；② 就年际变化而言，低、高山区平均、最大积雪面积呈微弱增加趋势，高山区最小积雪面积显著增加，倾向率为65.877 km²/a；③ 就季节变化而言，春、夏、冬三季低、高山区积雪面积年际变化呈“增加—减少—增加”趋势，秋季高山区积雪面积则呈“增加—减少”趋势，而低山区积雪面积在2009 和2010 年异常偏大，其他年份面积变化不大；④ 在低山区，气温是影响春、夏两季积雪面积变化的主因，气温和降水对秋季积雪面积变化的影响相当，而冬季积雪面积变化对降水更敏感；在高山区，夏季积雪面积变化对气温更敏感，而冬、春季积雪面积变化主要受降水影响。

Snow cover area changes in the Yurungkax River Basin of West Kunlun Mountains during 2000-2013 using MODIS data

The Yurungkax River is one of the two major tributaries of the Hotan River that is located at the southern edge of the Tarim River Basin. Its flow is mainly recharged by snow and ice melt water. Since these sources of river flow play an important role in the state of regional water resources, it is necessary to analyze the temporal and spatial variations of snow cover area(SCA) in this catchment for rational water resource management. In this study, we mainly used 8-day snow cover data(MOD10A2) of Moderate Resolution Imaging Spectro-radiometer to extract the SCA of the studied basin over a period of 13 years(March 2000 to February 2013). The two methods used for removing cloud contamination of the SCA images are as follows: MOD/MYD images compositing; and correction using glacier boundary extracted using nine Landsat TM, ETM+ and OLI images from 2000 to 2013. The results show that the two methods removed on average 77.23% of the cloudy pixels and effectively increased the number of images that can be used for analysis. Furthermore, we analyzed the spatial and temporal variations of the SCA in the study area using the corrected MOD10A2 snow cover data, and calculated the coefficients of the Pearson correlation between the SCA and meteorological parameters(air temperature and precipitation) from the hydrological station Tongguziluoke. Results of seasonal change analysis indicate single peak(winter season) of the SCA at low altitude (1650~4000 m asl.) and double peaks(spring and autumn respectively) at high altitude (4000~6000 m asl.), as well as no significant change of the SCA above 6000 m asl. because most areas at this altitude are covered by glaciers. Inter-annual changes of the SCA show that neither the average nor the maximum SCA at all altitude had a significant increasing trend, but the minimum SCA at high altitude increased significantly at a rate of 65.877 km² per year during the study period. The SCA time series analysis shows an increasing-decreasing-increasing trend at all altitudes in spring, summer and winter seasons respectively. But in the autumn, there was no significant fluctuation of the SCA at low altitude except in 2009 and 2010, which were the peak years of the SCA, and the SCA shows an increasing-decreasing trend at high altitude. Pearson correlation coefficients between the SCA and air temperature and precipitation in 8-day interval show that SCA changes are significantly influenced by air temperature and precipitation at low altitude, where air temperature was the dominant factor in the spring and summer, precipitation was the dominant factor in the winter, and air temperature and precipitation equally controlled the SCA regime in the autumn. At high altitude, SCA was sensitive to precipitation only in winter and spring. In the summer SCA was affected by both temperature and precipitation but air temperature was the main factor that influenced SCA.