基于CASA模型的呼伦贝尔地区NPP估算研究
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摘要
呼伦贝尔市处于内蒙古自治区的东北部地区,属于西北干旱区向东北湿润区和华北旱作农业区的过渡地带,对于保障我国的生态安全和可持续发展具有重要的意义。草地植被是草地生态系统中的第一性生产者,对区域甚至全球气候和环境变化具有很大的影响作用。本论文根据CASA模型估算呼伦贝尔地区的NPP,采用遥感数据,以草地植被作为草地生态系统研究的主体,对草地状况进行监测、分析计算和评价。
     植被净初级生产力(NPP)是指绿色植物在单位时间内、单位面积上所积累的有机物的量。NPP作为地表碳循环的重要组成部分,不仅直接反映了植被群落在自然环境条件下的生产能力,表征陆地生态系统的质量状况,而且是判定生态系统碳源/汇和调节生态过程的主要因子,在全球变化及碳平衡中起着重要作用。近30年来,随着人类活动的影响,温室效应等气候和环境问题日益突出,使得陆地生态系统的碳收支的时空变化成为一项研究趋势。
     本文主要运用地理信息系统和CASA遥感模型,利用MODIS遥感数据、气象数据及相关资料,估算内蒙古呼伦贝尔地区的NPP,并将估算结果与实测数据进行对比研究,从而验证CASA模型的精度,并改进该模型。
     CASA模型从其产生开始就是基于大尺度甚至全球的空间验证,模型中的许多参数均是从区域甚至全球给定的,本论文拟应用CASA模型来模拟出呼伦贝尔草原生态系统的净初级生产力,并利用该生态系统的野外实测地上生物量数据进行模拟验证,旨在验证CASA模型的动态模拟能力,以评价CASA模型反映NPP空间变异特征的准确性及阐释程度。本研究主要得出了以下结论:
     (一) CASA模型的改进及实现
     以CASA模型的基本结构为基础,考虑到最大光能利用率的取值在不同的地表植被类型中存在的差异,结合呼伦贝尔地区存在不同植被类型的实际情况,对CASA模型进行了一些改进,通过对NPP结果与实测数据及其他模型的对比验证,发现改进后的CASA模型对小尺度植被NPP的模拟效果较好。
     (二)本文估算了呼伦贝尔草原地区的NPP,研究表明在研究区内自东北向西南NPP值逐渐减小。以大兴安岭岭东针叶林区最高,该区植被生长季长,固碳力强;西南部,呼伦湖以西的退化的荒漠草原NPP偏低,主要是由于该区土壤沙化严重,水缺乏,限制了NPP的积累。
     (三)全区内NPP值受植被指数、温度以及降水量共同的影响。同时也发现植被指数NDVI的值对NPP的值的影响很大。
     (四)不同模型估算得出的NPP值,虽然存在一定的差异,但是总体的增减趋势是一致的。
Hulun Buir is located in northeast part of Inner-Mongolia, which is transitional zone from arid areas in northwest change to the humid area in northeast and dryland farming areas in north China. It is significance meaningful to protect ecological security and sustainable development of China. Grassland vegetation is the primary producers in grassland ecosystem, and has great influence for regional as well as global climate and environmental changes. The thesis is about estimating NPP in Hulun Buir according to the CASA (Carnegie Ames Stanford Approach), on the main body status of grassland vegetation in the grassland ecosystem research to monitor, analyze and evaluate the grassland status using remote sensing data.
     Vegetation net primary producers (NPP) refer to the accumulated number of organic matter per unit area and unit time for green plants. NPP as the key component of surface carbon cycle, not only direct reflect the production capacity of vegetation type under natural environment and identify the quality status of terrestrial ecosystems, but it is important factors to determine the ecosystem carbon source/sink and adjust the ecological processes, also NPP plays an important role in global changes and carbon balance. With the impact of human being’s activities, the greenhouse effect as well as other climate and environmental problems have become increasingly prominent in past 30 years, making the temporal and spatial variation of carbon balance in terrestrial ecosystems to become a research trends.
     The thesis is about estimating NPP in Hulun Buir in Inner-Mongolia using geographical information system and CASA, and utilizing the MODIS remote sensing data, meteorological data and relative information, and then making a comparison of the estimation result and measured data to verify the accuracy of CASA and improve the model.
     CASA is verified based on the large-scale and even the world space-proven since beginning of generation, many of the model parameters are obtained from the scale of regional or even global. This thesis plans to use CASA to simulate NPP of Hulun Buir’s grassland ecosystem, and conduct the simulation verification use the actual biomass data measured by the system. All is used to validate the CASA dynamic simulation capability. According to the results, we are able to analyze the accuracy of the NPP.
     The conclusions are as follows:
     1 CASA model improvement and implementation
     Based on solar energy utilization efficiency, taking into account the greatest values in different vegetation types existing differences, combined with the same time ,takingε* different values ,this paper build an improved CASA model. By comparing the results of verification NPP found improved CASA model for regional scale vegetation of the simulation results better than before.
     2 this paper estimates the NPP of Hulun Buir regions, and the studies have shown that the NPP values gradually decrease from east to west in the region.
     3 NPP of the whole region is affected by vegetation cover, vegetation type, temperature and precipitation.
     4 although we always estimate the different values of NPP by different models, the increase or decrease trend is consistent.
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