基于CASA模型和MODIS数据的甘南草地NPP时空动态变化研究

doi:10.11686/cyxb2018320

草业学报 ›› 2019, Vol. 28 ›› Issue (6): 19-32.DOI: 10.11686/cyxb2018320

基于CASA模型和MODIS数据的甘南草地NPP时空动态变化研究

刘洁, 孟宝平, 葛静, 高金龙, 殷建鹏, 侯蒙京, 冯琦胜, 梁天刚^*

兰州大学草地农业生态系统国家重点实验室,兰州大学农业农村部草牧业创新重点实验室,兰州大学草地农业科技学院,甘肃兰州 730020

收稿日期:2018-05-15 修回日期:2018-09-25 出版日期:2019-06-20 发布日期:2019-06-20
通讯作者: *E-mail: tgliang@lzu.edu.cn
作者简介:刘洁(1995-),女,陕西渭南人,在读硕士。E-mail: liuj14@lzu.edu.cn
基金资助:
国家“十三五”重点研发计划项目(2017YFC0504801),国家自然科学基金(31672484、31702175、41801191、41805086),长江学者和创新团队发展计划(IRT 17R50),甘肃省青年科技基金(18JR3RA024)和中央高校基本科研业务费(lzujbky-2018-it17)资助

Spatio-temporal dynamic changes of grassland NPP in Gannan prefecture, as determined by the CASA model

LIU Jie, MENG Bao-ping, GE Jing, GAO Jin-long, YIN Jian-peng, HOU Meng-jing, FENG Qi-sheng, LIANG Tian-gang^*

State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou 730020, China

Received:2018-05-15 Revised:2018-09-25 Online:2019-06-20 Published:2019-06-20
Contact: * E-mail: tgliang@lzu.edu.cn

摘要/Abstract

摘要： 植被净初级生产力(net primary productivity, NPP)在全球气候变化及碳循环研究中扮演着重要的角色,精准快速的估算NPP对评估区域生态系统承载力以及合理利用自然资源具有重要的意义。利用2011-2014年甘南地面实测草地地上生物量(aboveground biomass, AGB)数据和根冠比系数计算的草地NPP数据,分别验证了MOD17A3 NPP产品和基于CASA(Carnegie-Ames-Stanford approach)模型估算的草地NPP的精度,分析了2000-2016年甘南地区草地NPP的时空动态变化。结果表明:基于CASA模型模拟的草地NPP精度整体上高于MOD17A3 NPP产品的精度,其均方根误差(root mean square error, RMSE)较MOD17A3 NPP小9.94 g C·m^-2;CASA模型分析的甘南地区草地NPP总体上呈现由西南向东北逐渐减少的趋势;对不同草地类型而言,沼泽类的平均NPP最高(469.07 g C·m^-2),温性草原类最低(324.18 g C·m^-2),而占研究区草地总面积比例较大的高寒草甸类和高寒灌丛草甸类草地的平均NPP分别为449.22和465.27 g C·m^-2;2000-2016年间,甘南地区大部分草地NPP稳定不变,其面积占研究区草地总面积的75.31%,NPP呈增加趋势的区域占草地面积的22.63%,而NPP呈减少趋势的区域占比最小,仅为2.06%。以上研究结果表明CASA模型在高寒地区草地NPP评估、草地资源合理利用与管理方面具有重要的应用价值。

关键词: 甘南地区, 草地净初级生产力, MOD17A3产品, CASA模型, 动态变化

Abstract: Net primary productivity (NPP) plays an important role in global carbon cycle and is important to understanding drivers of climate changes. Precise and rapid estimation of vegetation NPP is important for evaluating ecological carrying capacity at a regional scale and managing natural resources reasonably. In this study, field-measured grassland above ground biomass (AGB) from 2011 to 2014, MODIS remote sensing data and meteorological data in Gannan prefecture were used. In combination with the ratio of belowground biomass to AGB, we calculate the grassland NPP, and evaluate the accuracy of the MOD17A3 product and Carnegie-Ames-Stanford approach (CASA) model, and analyze the dynamic changes of grassland NPP from 2000 to 2016 using the better method. The results show that the accuracy of grassland NPP predictions from the CASA model (root mean square error (RMSE) = 9.94 g C ·m^-2·yr^-1) is higher than that of MOD17A3 product. The average annual grassland NPP determined by the CASA model shows a decreasing trend from the southwest to northeast between 2000 and 2016 in our study area. Comparing different vegetation types, the annual NPP for marsh grassland (469.07 g C ·m^-2·yr^-1) was the highest, while that of temperate steppe grassland was the lowest (324.18 g C ·m^-2·yr^-1). In addition, the annual NPP of alpine meadow and alpine shrub meadow grasslands (which have relatively large area in Gannan prefecture) was, respectively, 370 and 430 g C ·m^-2·yr^-1. Over the past 17 years, the annual grassland NPP was generally stable in most regions, (75.31% of the total grassland area). Meanwhile, an increasing NPP trend was seen in 22.63%, and a decreasing trend in just 2.06% of the Gannan prefecture area. These results suggest that the CASA model has an important role in grassland NPP estimation and will assist in the sustainable management of grassland resources in alpine areas.

Key words: Gannan prefecture, grassland net primary productivity (NPP), MOD17A3 product, CASA model, dynamic change

刘洁, 孟宝平, 葛静, 高金龙, 殷建鹏, 侯蒙京, 冯琦胜, 梁天刚. 基于CASA模型和MODIS数据的甘南草地NPP时空动态变化研究[J]. 草业学报, 2019, 28(6): 19-32.

LIU Jie, MENG Bao-ping, GE Jing, GAO Jin-long, YIN Jian-peng, HOU Meng-jing, FENG Qi-sheng, LIANG Tian-gang. Spatio-temporal dynamic changes of grassland NPP in Gannan prefecture, as determined by the CASA model[J]. Acta Prataculturae Sinica, 2019, 28(6): 19-32.

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基于CASA模型和MODIS数据的甘南草地NPP时空动态变化研究

Spatio-temporal dynamic changes of grassland NPP in Gannan prefecture, as determined by the CASA model

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