利用CASA模型估算黑河流域净第一性生产力

doi:10.11849/zrzyxb.2008.02.011

自然资源学报 ›› 2008, Vol. 23 ›› Issue (2): 263-273.doi: 10.11849/zrzyxb.2008.02.011

利用CASA模型估算黑河流域净第一性生产力

陈正华¹, 麻清源², 王建³, 祁元³, 李净³, 黄春林³, 马明国³, 杨国靖⁴

1. 浙江大学地球科学系,杭州 310027;
2. 中国人民大学公共管理学院城市规划与管理系,北京 100872;
3. 中国科学院寒区旱区环境与工程研究所遥感与地理信息科学研究室,兰州 730000;
4. 中国科学院寒区旱区环境与工程研究所水土资源研究室,兰州730000

收稿日期:2007-05-15 修回日期:2007-12-12 出版日期:2008-03-25 发布日期:2008-03-25
作者简介:陈正华(1980- ),女,博士生,研究方向为遥感生态应用。E-mail:chen.zhenghua@163.com
基金资助:
国家自然科学基金(30500075和40671040)共同支持。

Estimation of Heihe Basin Net Primary Productivity Using the CASA Model

CHEN Zheng-hua¹, MA Qing-yuan², WANG Jian³, QI Yuan³, LI Jing³, HUANG Chun-lin³, MA Ming-guo³, YANG Guo-jing⁴

1. Department of Earth Science, Zhejiang University, Hangzhou 310027, China;
2. Department of Urban Planning & Management, Renmin University of China, Beijing 100872, China;
3. Laboratory of Remote Sensing and GIS Science, Cold and Arid Regions Environment and Engineering Research Institute, CAS, Lanzhou 730000, China;
4. Division of Hydrology and Water-land Resources, Cold and Arid Regions Enuironment and Engineering Researoh Institute, CAS, Lanzhou 730000, China

Received:2007-05-15 Revised:2007-12-12 Online:2008-03-25 Published:2008-03-25

摘要/Abstract

摘要： 陆地生态系统是维系生物圈乃至人类存在与发展的生命支持系统。该系统净第一性生产力估算研究有助于寻找陆地植被从大气中固定碳的数量及影响其时空分布的驱动因子。基于CASA(Carnegie Ames Stanford Approach)模型,结合多光谱遥感数据和气候数据,模拟干旱半干旱典型区黑河流域1998~2002年净第一性生产力的时空分布,并分析和探讨了上、中、下游NPP的驱动因子。研究结果证明CASA模型适用于内陆河流域范围内NPP研究;通过分析黑河流域上、中、下游的NPP变化与气温、降水、太阳辐射和NDVI的相关关系,发现上游山区NPP与热量相关性显著,中游地区由于人工绿洲对水资源的截留用于作物灌溉,NPP相对稳定,下游的NPP受热量和水分因素共同复杂控制。

关键词: CASA, 植被, 碳循环, NPP, 黑河流域

Abstract: The terrestrial ecosystem is the supporting system for the biosphere as well as for human being’s survival and development. The research of net primary productivity will help in understanding the amount of carbon fixed by terrestrial vegetation and its influencing factors. The purpose of this paper was to find out the NPP spatial and temporal dynamic distribution in the Heihe Basin during 1998 to 2002, and analyze vegetation’s feedback on climatic conditions. The CASA (Carnegie Ames Stanford Approach) was selected to calculate NPP. The SPOT/VEGETATION, land use/land cover, meteorologic data and soil attribute were collected. The results validate the CASA’s applicability in inland watershed scale. The 5 years NPP variation in the Heihe Basin was monitored by the model. The upper, middle and lower reaches of the Heihe Basin contributed ~50％,~30％ and ~20％ to the total NPP of the basin respectively. From 1998 to 2000 the NPP decreased and then increased from 2000 to 2002. The NPP in the upper reaches of the basin was mainly controlled by heat because the vegetation seldom faced the problem of moisture shortage, and the NPP increased when temperature increased. The NPP in the middle reaches of the basin also had good relationship with heat. The reason was that the cropland plants could get adequate water supply when necessary because there were many reservoirs set up for irrigation system and factories. The NPP variation in the lower reaches of the basin was larger than upper and middle, and had weak relationship with meteorologic factors. The vegetation endured drought throughout the year and high temperature in summer. It seldom obtained water supply, even from the oasis along the river because of water interception by the middle reaches reservoirs. Desert plants mainly lived on groundwater to survive in case of drought.

Key words: CASA, vegetation, carbon cycling, NPP, Heihe Basin

中图分类号:

Q149

陈正华, 麻清源, 王建, 祁元, 李净, 黄春林, 马明国, 杨国靖. 利用CASA模型估算黑河流域净第一性生产力[J]. 自然资源学报, 2008, 23(2): 263-273.

CHEN Zheng-hua, MA Qing-yuan, WANG Jian, QI Yuan, LI Jing, HUANG Chun-lin, MA Ming-guo, YANG Guo-jing. Estimation of Heihe Basin Net Primary Productivity Using the CASA Model[J]. JOURNAL OF NATURAL RESOURCES, 2008, 23(2): 263-273.

参考文献

[1] 方精云.全球生态学[M].北京:高等教育出版社,2000. [2] Zhao Maosheng, Heinsch F A, Nemani R R, et al. Improvement of the MODIS terrestrial gross and net primary production global data set[J]. Remote Sensing of Environment,2005,95:164-176. [3] Tans P P, Fung I Y, Takahaski N P. Observational constraints on the global atmospheric CO₂ budget[J]. Science, 1990, 24: 1430-1438. [4] Keeling R F, Piper S C, Heimann M. Global and hemispheric CO₂ sinks deduced from changes in atmospheric O₂ concentration[J]. Nature,1996,38:218-221. [5] Tian H, Melilo J M, Kicklighter D W, et al. The sensitivity of terrestrial carbon storage to historical climate variability and atmospheric CO₂ in the United States[J]. Tellus,1999,51B:414-452. [6] Field C B, Fung I Y. The not so big U.S. carbon sink[J]. Science,1999,285:544-545. [7] 康尔泗,程国栋,董正川.中国西北干旱区冰雪水资源与出山径流[M].北京:科学出版社,2002. [8] http://heihe.westgis.ac.cn/. [9] 王根绪,程国栋.近50a来黑河流域水文及生态环境的变化[J].中国沙漠,1998,18(3):233~238. [10] Potter C S, Randerson J T, Field C B, et al. Terrestrial ecosystem production: A process model based on global satellite and surface data[J]. Global Biogeochemical Cycles,1993,7:811-841. [11] Field C B, Randerson J T, Malmstrom C M. Global net primary production: Combining ecology and remote sensing[J]. Remote Sensing of Environment,1995,51:74-88. [12] Monteith J L. Solar radiation and productivity in tropical ecosystems[J]. Journal of Applied Ecology,1972,9: 747-766. [13] Ichii K, Matsui Y, Yamaguchi Y, et al. Comparison of global net primary production trends obtained from satellite based normalized difference vegetation index and carbon cycle model[J]. Global Biogeochemical Cycles,2001,15:351-364. [14] 朴世龙,方精云,郭庆华.利用CASA模型估算我国植被净第一性生产力[J].植物生态学报,2001,25(5):603~608. [15] http://free.vgt.vito.be. [16] 孙睿,朱启疆.中国陆地植被净第一性生产力及季节变化研究[J].地理学报,2000,55(1):36~44. [17] 胡自治,孙吉雄,李洋,等.甘肃天祝主要高山草地的生物量及光能转化率[J].植物生态学报,1994,18(2):121~131. [18] 沈禹颖,阎顺国,朱兴运,等.河西走廊几种盐化草地第一性生产力的研究.Ⅰ地上生物量与地下生物量季节动态及分配[J].草业学报,1995,4(2):44~50. [19] Zhou L, Tucker C J, Kaufmann R K, et al. Variations in northern vegetation activity inferred from satellite data of vegetation index during 1981 to 1999[J]. Journal of Geophysical Research,2001,106:20069-20083. [20] 王建,李硕.气候变化对中国内陆干旱区山区融雪径流的影响[J].中国科学(D辑),2005,35(7):664-670.

利用CASA模型估算黑河流域净第一性生产力

Estimation of Heihe Basin Net Primary Productivity Using the CASA Model

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

Metrics

本文评价

推荐阅读 0

[1]	覃艺, 张廷斌, 易桂花, 魏澎涛, 杨达. 2000年以来内蒙古生长季旱情变化遥感监测及其影响因素分析[J]. 自然资源学报, 2021, 36(2): 459-475.
[2]	汪言在, 董一帆, 苏正安. 基于土地利用与植被恢复情景的土壤侵蚀演变特征[J]. 自然资源学报, 2020, 35(6): 1369-1380.
[3]	任正超, 朱华忠, 史华, 柳小妮. 最后间冰期至未来2070s中国潜在自然植被时空分布格局及其对气候变化的响应[J]. 自然资源学报, 2020, 35(6): 1484-1498.
[4]	刘崇刚, 孙伟, 曹玉红, 陈晨. 乡村地域生态服务功能演化测度——以南京市为例[J]. 自然资源学报, 2020, 35(5): 1098-1108.
[5]	马维伟, 孙文颖. 尕海湿地植被退化过程中有机碳及相关土壤酶活性变化特征[J]. 自然资源学报, 2020, 35(5): 1250-1260.
[6]	黄端, 闫慧敏, 池泓, 耿晓蒙, 邵奇慧. 2000—2015年江汉平原农田生态系统NPP时空变化特征[J]. 自然资源学报, 2020, 35(4): 845-856.
[7]	陈卓鑫, 王文龙, 郭明明, 王天超, 郭文召, 王文鑫, 康宏亮, 杨波, 赵满. 黄土高塬沟壑区植被恢复对不同地貌部位土壤可蚀性的影响[J]. 自然资源学报, 2020, 35(2): 387-398.
[8]	邱冬冬, 闫家国, 张树岩, 左佃龙, 刘泽正, 汪方芳, 王青, 崔保山. 滨海湿地退化区鸟类刨坑觅食行为促进植被的恢复[J]. 自然资源学报, 2020, 35(2): 449-459.
[9]	陈舒婷, 郭兵, 杨飞, 韩保民, 范业稳, 杨潇, 何田莉, 刘悦, 杨雯娜. 2000—2015年青藏高原植被NPP时空变化格局及其对气候变化的响应[J]. 自然资源学报, 2020, 35(10): 2511-2527.
[10]	肖武, 张文凯, 吕雪娇, 王新静. 西部生态脆弱区矿山不同开采强度下生态系统服务时空变化——以神府矿区为例[J]. 自然资源学报, 2020, 35(1): 68-81.
[11]	张文强, 孙从建, 李新功. 晋西南黄土高原区植被覆盖度变化及其生态效应评估[J]. 自然资源学报, 2019, 34(8): 1748-1758.
[12]	黄蓉, 张建梅, 林依雪, 卜添荟, 王鑫, 薛紫月, 李艳忠, 马燮铫, 于志国, 白鹏. 新安江上游流域径流变化特征与归因分析[J]. 自然资源学报, 2019, 34(8): 1771-1781.
[13]	白雪莲, 季树新, 王理想, 陈正新, 常学礼. 鄂尔多斯十大孔兑区植被生产力变化趋势对土地利用转移的响应[J]. 自然资源学报, 2019, 34(6): 1186-1195.
[14]	李贵芳, 周丁扬, 石敏俊. 西北干旱区作物灌溉技术效率及影响因素[J]. 自然资源学报, 2019, 34(4): 853-866.
[15]	高庆, 艾里西尔·库尔班, 肖昊. 塔里木河下游区域植被时空变化[J]. 自然资源学报, 2019, 34(3): 624-632.