毛乌素沙地海流兔河流域植被净初级生产力估算

采用CASA(Carnegie-Ames-Stanford Approach)模型,结合TERRA MODIS卫星数据和气象数据,对毛乌素沙地海流兔河流域2015年各月的植被净初级生产力(NPP)进行估算,并对植被NPP月平均值的时空分布规律及其与气象因子和地下水位埋深的关系进行了分析.结果表明:毛乌素沙地海流兔河流域2015年植被NPP总量为2.88×1011 g,生长季(4月份至10月份)的植被NPP总量达2.81×1011 g,占全年植被NPP总量的97.57%.随着时间推移,植被NPP月平均值和归一化差分植被指数(NDVI)月平均值呈"缓慢增加—急剧增加—急剧下降"的变化趋势.植被NPP月平均值季节变化明显,春季、夏季、秋季和冬季植被NPP月平均值之和分别为20.55、69.39、20.46和0.48 g·m-2.从空间分布上看,中部河谷和滩地的植被NPP月平均值总体上高于东南部、西部和西北部等沙丘荒漠区.月平均气温对植被NPP月平均值变化的影响最大,其次为平均实际日蒸散发量和地表月太阳辐射.植被NPP月平均值随着地下水位埋深的增加而减小,最大值出现在地下水位埋深1~2 m之间.上述研究结果显示:采用CASA模型可以较好地估算毛乌素沙地海流兔河流域植被NPP值,月平均气温和地下水位埋深对该流域植被NPP值的影响较大.

Estimation of vegetation net primary productivity in Hailiutu River catchment of Mu Us Sandland

Taking CASA ( Carnegie-Ames-Stanford Approach ) model, and combing TERRA MODIS satellite data and meteorological data, vegetation net primary productivity ( NPP ) of each month in Hailiutu River catchment of Mu Us Sandland in 2015 was estimated, and spatial and temporal distribution rule and its relationships with meteorological factors and depth to water table were analyzed. The results show that in 2015, total vegetation NPP is 2. 88×1011 g in Hailiutu River catchment of Mu Us Sandland, and the sum of vegetation NPP during the growing season ( April to October) reaches 2. 81 × 1011 g, accounting for 97. 57% of total vegetation NPP of whole year. With prolonging of time, monthly mean vegetation NPP and monthly mean normalized difference vegetation index ( NDVI) appear the trend of"increasing slowly-increasing sharply-decreasing sharply". The seasonal variation of monthly mean vegetation NPP is clear, and the sums of monthly mean vegetation NPP in spring, summer, autumn and winter are 20. 55, 69. 39, 20. 46 and 0. 48 g · m-2 , respectively. On the view of spatial distribution, monthly mean vegetation NPP in river valley and bottomland in middle area is generally higher than that in dune and desert in southeastern, western and northwestern areas. The effect of monthly mean temperature on change of monthly mean vegetation NPP is the greatest, following by mean actual daily evapotranspiration and surface monthly solar radiation. With increasing of depth to water table, monthly mean vegetation NPP decreases, and the maximum value occurs in depth to water table of 1-2 m. It is suggested that vegetation NPP in Hailiutu River catchment of Mu Us Sandland can be estimated well by using CASA model, and monthly mean temperature and depth to water table have important effects on vegetation NPP in this catchment.