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基于WRF模式数据和CASA模型的青海湖流域草地NPP估算研究
引用本文:郑中,祁元,潘小多,葛劲松,聂学敏.基于WRF模式数据和CASA模型的青海湖流域草地NPP估算研究[J].冰川冻土,2013,35(2):465-474.
作者姓名:郑中  祁元  潘小多  葛劲松  聂学敏
作者单位:1. 中国科学院寒区旱区环境与工程研究所,甘肃兰州 730000;中国科学院大学,北京100049
2. 中国科学院寒区旱区环境与工程研究所,甘肃兰州,730000
3. 青海省生态环境遥感监测中心,青海西宁,810000
摘    要:植被净初级生产力(NPP)是研究陆地碳循环过程的核心内容, 而高海拔区域由于气象观测数据的缺乏造成模型对其估算的不准确.在WRF模式气象数据和SPOT-VEGETATION遥感影像的基础上, 利用CASA模型对青海湖流域2000-2010年的草地NPP进行了估算, 经过实地样方数据和其他模型数据的验证后, 分析了青海湖流域近11 a来草地NPP的空间分布格局和时间变化特征.结果表明: 1)在气象观测资料缺乏的青海湖流域, WRF模式的气象数据能较好地应用到模型中, CASA模型对该区域草地NPP的模拟精度较高; 2)2000-2010年青海湖流域草地年均NPP为2.71×1012gC·a-1, 单位面积草地NPP为145.71 gC·m-2·a-1; 空间分布上呈现出由东南向西北随着海拔升高逐渐下降的格局, 在海拔3 200~3 500 m的区域草地单位面积的NPP达到最大; 3)2000-2010年青海湖流域草地NPP年际变化明显, 近11 a呈现出明显的增加趋势, 增加区域主要分布在环湖地区; 年内季节变化显著, 夏季NPP占到全年的57.36%; 4)对NPP和气象站点太阳辐射、 气温、 降水数据进行相关性分析, 发现影响青海湖流域草地NPP变化的主要驱动力是气温.

关 键 词:青海湖流域  WRF模式  CASA模型  NPP  
收稿时间:2012-10-06

Estimating the Grassland NPP in Qinghai Lake Basin Based on WRF Model Data and CASA Model
ZHENG Zhong,QI Yuan,PAN Xiao-duo,GE Jin-song,NIE Xue-min.Estimating the Grassland NPP in Qinghai Lake Basin Based on WRF Model Data and CASA Model[J].Journal of Glaciology and Geocryology,2013,35(2):465-474.
Authors:ZHENG Zhong  QI Yuan  PAN Xiao-duo  GE Jin-song  NIE Xue-min
Institution:1. Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou Gansu 730000, China;
2. University of Chinese Academy of Sciences, Beijing 100049, China;
3. Qinghai Ecological Environment Remote Monitoring Center, Xining Qinghai 810000, China
Abstract:Net primary productivity (NPP) is the core of terrestrial carbon cycle research. Estimating NPP is not accurate in high altitude regions owing to lack of meteorological data. Based on the WRF model meteorological data and SPOT-VEGETATION remote sensing images, the grassland NPP of Qinghai Lake basin was estimated using CASA model from 2000 to 2010. The simulated results were validated by observed data and other simulated data, and then the temporal and spatial variations of NPP were analyzed. The analyses show: 1) WRF meteorological data might be applied well to CASA model, perfectly simulating grassland NPP. 2) The annual grassland NPP was 2.71×10m12 gC·a-1 and the NPP per unit area was 145.71 gC·m-2·a-1 on average, and spatially, NPP showed an increasing from southeast to northwest with elevation increasing, but NPP per unit area reached a maximum at the altitude of 3 200~3 500 m. 3) The inter-annual variation of NPP was obvious and an increasing tendency could be seen from 2000 to 2010. Around Qinghai Lake there was a main NPP increasing area. The NPP changed month by month significantly; most of them (57.36%) took place in summer. 4) Correlation analysis between NPP and meteorological data, including solar radiation, air temperature and precipitation, shows that the main factor affecting NPP is air temperature.
Keywords:Qinghai Lake basin  WRF model  CASA model  net primary productivity (NPP)
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