不同气象插值方法在新疆草地NPP估算中的可靠性评价

发布时间：2018-02-02 23:38

本文关键词： 气象因子空间插值方法净初级生产力 CASA模型 ANUSPLIN　出处：《草业科学》2017年03期 　论文类型：期刊论文

【摘要】：气象因子对研究草地生产力、植被长势、灾害评估等都有着重要的意义,本研究采用不同空间插值方法(协同克里格法Cokriging、反距离加权法IDW和ANUSPLIN法)对新疆地区90个气象站点2000-2011年多年的7月平均降水和气温数据进行空间插值分析,使用均方根误差法(RMSE)以及平均绝对误差法(MAE)对插值的结果进行评价,讨论不同方法对该地区降水和气温插值结果的影响。利用不同插值方法,基于CASA模型进行新疆草地NPP的估算,结合实测生物量数据,对3种插值方法下的估算结果进行评估,结果表明,1)降水和气温数据都是基于ANUSPLIN法的插值结果最优(MAE_(降水)=6.45,RMSE_(降水)=8.77,MAE_(气温)=2.11,RMSE_(气温)=3.52)。2)基于不同插值方法得到的气象要素估算的新疆草地NPP精度不同,将实测数据与同时期CASA模型模拟值相关性进行分析,基于ANUSPLIN法插值的气象要素估算NPP的精度最高(R~2=0.794 7),NPP实测值与模拟值有良好的线性关系,比基于Cokriging插值的气象要素估算精度提高了13.23%,比IDW提高了20.13%。说明提高气象要素的插值精度有利于新疆草地NPP的估算研究。
[Abstract]:Meteorological factors are of great significance to the study of grassland productivity, vegetation growth and disaster assessment. Different spatial interpolation methods (cooperative Kriging method Cokriging) are used in this study. Inverse distance weighting method (IDW and ANUSPLIN) was applied to the spatial interpolation analysis of the July mean precipitation and temperature data of 90 meteorological stations in Xinjiang from 2000 to 2011. The mean square error method (RMSE) and the mean absolute error method (mae) are used to evaluate the interpolation results. The influence of different methods on precipitation and temperature interpolation results in Xinjiang grassland was discussed. Using different interpolation methods, the NPP of grassland in Xinjiang was estimated based on CASA model, and the measured biomass data were combined. The estimation results of the three interpolation methods are evaluated. The results show that the precipitation and temperature data are based on the interpolation results of ANUSPLIN method. RMSE _ S _ I (precipitation = 8.77 / MAESP) (temperature = 2.11). The NPP accuracy of Xinjiang grassland estimated by different interpolation methods is different. The correlation between the measured data and the simulated values of the CASA model in the same period is analyzed. The precision of estimating the meteorological elements of NPP based on ANUSPLIN interpolation is the highest. There is a good linear relationship between the measured values of NPP and the simulated values, and the precision of estimating meteorological elements based on Cokriging interpolation is improved by 13.23%. The interpolation accuracy of meteorological elements is better than that of IDW, which is beneficial to the estimation and study of grassland NPP in Xinjiang.
【作者单位】：新疆大学资源与环境科学学院;绿洲生态教育部重点实验室;新疆维吾尔自治区草原总站;澳大利亚国立大学芬纳资源与社会学院;
【基金】：新疆维吾尔族自治区草原总站委托项目(211-62207) 新疆维吾尔自治区高层次人才培养计划项目(104-40002) 教育部促进与美大地区科研合作与高层次人才培养项目(117-40101)
【分类号】：S812.1
【正文快照】： 草原作为陆地生态系统中分布最为广泛的生态系统之一,在气候调节以及全球碳循环中起着重要作用[1-2]。净初级生产力(net primary productivity,NPP)指植物在单位时间和单位面积内积累的有机物总量,是植物光合作用生成的有机物总量减去呼吸作用消耗之后的剩余量,也是反映陆地生

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