摘要
积雪是塔什库尔干河流域宝贵的资源,了解流域融雪时空变化规律及其与气象、地形因素的相关关系具有重要意义。基于不同高程带、坡度和坡向的ArcGIS解译积雪覆盖数据和CMADS数据,采用方差分析和Pearson相关性分析等方法,研究不同高程带、坡度和坡向雪盖时空变化规律及其与气象因子的相关关系。结果表明:平均气温、太阳辐射和降水是影响塔什库尔干河流域积雪的主导气象因子,同时还受地形(高程、坡度、坡向)的限制;积雪覆盖率在各地形上存在明显季节差异性及月差异性,积雪覆盖率与气象因子相关度从高到低依次排序为:平均气温>太阳辐射>降水>风速>相对湿度,积雪覆盖率与前3个因素存在显著负相关关系,风速次之,与相对湿度的相关性最小。
Snow accumulation is a valuable resource in the Tashkurgan River Basin.Exploring the temporal and spatial changes of snowmelt in the basin and their correlations with meteorology and topography is conducive to improve the development and utilization of its water resources.This study used ArcGIS based on different elevation zones,slopes and aspect directions to interpret snow cover data and CMADS data,and used analysis of variance and Pearson correlation to study the temporal and spatial variation of different elevation zones,slopes and slope snow cover and their correlation with meteorological factors.The results showed that the average temperature,solar radiation and precipitation are the dominant meteorological factors affecting the snow in the Tashkurgan river basin,which are also limited by the topography(elevation,slope,aspect).Snow cover coverage has obvious seasonal differences and monthly differences in various forms.The correlation between snow coverage and meteorological factors is ranked from high to low:average temperature>solar radiation>precipitation>wind speed>relative humidity.There is a significant negative correlation between snow cover and the first three factors above,followed by wind speed and minimum correlation with relative humidity.
作者
彭亮
郑淑文
何英
穆振侠
李晓庆
PENG Liang;ZHENG Shuwen;HE Ying;MU Zhenxia;LI Xiaoqing(College of Water Resources and Civil Engineering,Xinjiang Agricultural University,Urumqi 830052,China;Xinjing Laboratory of Lake Environment&Resources in Arid Zone,Urumqi 830054,China)
出处
《水资源与水工程学报》
CSCD
2019年第4期53-62,共10页
Journal of Water Resources and Water Engineering
基金
国家自然科学基金项目(51569031)
新疆干旱区湖泊环境与资源实验室基金项目(XJDX0909-2012-02)
关键词
气象因子
积雪时空变化
Pearson相关性
MODIS
CMADS
meteorological factor
temporal and spatial changes of snow cover
Pearson correlation
MODIS
CMADS(The China meteorological assimilation driving datasets for SWAT model)