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干旱区典型流域植被净初级生产力的遥感估算研究
杨会巾
Subtype硕士
Thesis Advisor李小玉
2016
Degree Grantor中国科学院大学
Place of Conferral北京
Degree Discipline测绘工程
Keyword净初级生产力 Sebal模型 光能利用率模型 尺度效应
Abstract陆地植被净初级生产力(NPP)是生态系统碳循环的重要组成部分,并且是反映植被对自然环境资源的利用程度。随着气候的变化和大规模的水土开发,生态系统的生产力发生巨大的变化,开展流域陆地生态系统净初级生产力研究,对干旱区实现流域农业可持续发展和提高陆地生态系统可持续性具有重要的科学意义。玛纳斯河流域属于干旱区山地生态系统,植被类型复杂多样,并且绿洲景观特色鲜明。因此,借助实验观测和模型模拟方法,开展流域陆地生态系统NPP研究,分析不同时空格局下的NPP特点以及尺度效应。本文得到以下结论: (1)从整体上,生育期内碳通量动态变化均呈现单峰曲线。在整个生长季,棉花累积的NEE、Reco和GPP分别为-304.8 g C m-2, 706.18 g C m-2 和 1011.00 g C m-2。随着尺度的上升,GPP与Rn、Tair和SWC的相关性逐渐变强,其原因为生态系统的抗干扰性和稳定性。从分钟到日尺度,GPP与Rn的相关性比与Tair的相关性强;在日尺至月尺度上,反之。这主要取决于光合作用的生物化学特征。由于GPP对环境因子的响应与NPP对环境因子的响应相似,因此,NPP对环境因子有相同的响应。 (2)基于SEBAL模型和光能利用利用率模型的耦合,估算了干旱区天山北麓玛纳斯河流域2013年的植被NPP。本研究中的相关参数根据干旱区的特征进行了调整,并且其创新点在于水分胁迫系数的估算。本研究结果检验表明,SEBAL模型和光能利用率模型的耦合,对玛纳斯河流域山地-绿洲-荒漠生态系统植被NPP的模拟效果较合理,能较好地反映植被净初级生产力的实际情况,不仅提高干旱区植被NPP估算精度,还可以降低模型操作难度,是估算干旱区植被NPP的一种有效途径。 (3)玛纳斯河流域2013年植被NPP总量为7066.72 Mt C·a-1,平均值为278.06 g C·m-2·a-1,总体分布趋势是自南向北先增加-后减少-再增加-最后减少,随着地貌和土地利用类型的变化呈现明显的分布规律,且其月变化比较明显,7—8月达到最大值,占总量NPP的52.2%。植被净初级生产力随海拔和坡度的增加整体呈下降趋势,同时伴随着波动,这些波动主要由地表植被覆盖类型和环境因素所引起。随着尺度的扩展,玛纳斯河流域植被NPP呈下降趋势,产生尺度效应,其主要由地表覆盖类型引起。玛纳斯河流域未利用地NPP的最适尺度为30m,而模拟农田NPP的最适尺度为330-400m。
Other AbstractNet primary productivity of terrestrial vegetation was the major part of carbon cycling in ecosystem and reflects the utilization of vegetation to natural and environmental resource. With the changes of climate and the over exploitation of water and soil resource, productivity of ecosystem changed largely. Hence, study on NPP of terrestrial vegetation had an important scientific significance to achieve agricultural sustainable development and enhanced ecosystem sustainability in an arid region. Manas River Watershed, which had various vegetation types, was part of mountain ecosystems of arid regions and its landscape was special and distinctive. Therefore, based on experimental observations and model simulation, the study estimates NPP of terrestrial ecosystem and analyzed the temporal and spatial pattern of NPP and scale effect. Conclusions showed that: (1) On the whole, the dynamic of NEE, ecosystem respiration (Reco) or GPP showed a single-peak curve in the entire growth period of cotton. The study showed that accumulative net carbon flux (NEE), accumulative ecosystem respiration (Reco) and accumulative gross primary production were -304.8 g C m-2, 706.18 g C m-2 and 1011.00 g C m-2 over the whole cotton growing season. Moreover, with time scaling up, the correlations of GPP to net solar radiation (Rn), air temperature (Tair), and soil water content (SWC) became stronger gradually due to resistance and resilience of ecosystem and the protection of plastic film mulching. The GPP was more strongly correlated with Rn than Tair at time scales from minutes to days, while it reversed at time scales from days to weeks. This was largely determined by the biochemical characteristics of photosynthesis. Moreover, there were the responses of NPP to environmental factors, which was the same responses as GPP because relationships between GPP and factors were similar to relationships between NPP and factors. (2) Based on SEBAL and light utility efficiency model, the study estimated vegetation NPP of 2013 of Manas River Watershed located in the northern slope of Tianshan Mountain in arid regions. The parameters in the study were only adjusted for the characteristics of arid regions, and the innovation was the calculation of the water stress index(Wε). Estimated result of NPP in Manas River Watershed by coupling model was reasonable and it could actually reflect the NPP of vegetation. It not only would improve the model quality, but would reduce the difficulty of model manipulation. It was an efficient way of estimating vegetation NPP of arid regions. (3) The total annual NPP of vegetation and the mean annual NPP in Manas River Watershed in 2013 were 7066.72 Mt C·a-1 and 278.06 g C·m-2·a-1 respectively. With the variation of geomorphic type and land cover, the spatial changes of NPP were remarkable: from south to north, NPP increased firstly, and decreased secondly, and then increased, finally decreased. The temporal variations of NPP were also obvious, and the NPP in two months of July and August was account for 52.2% of total annual NPP. With the increasing of the elevation and slope, the mean annual NPP decreased as a whole with fluctuations induced by different land covers and environmental factors. With scaling up, NPP of crop increased, but NPP of forest, grassland and bare land almost remained unchanged. Average stimulated NPP of 30m resolution was 5.36% higher than of 990m resolution. Scaling up induced the change of mean estimated NPP in Mans River Watershed and scale effect, and the main reason was the change of land cover. The optimum scale of estimating NPP of unused land was 30m but the optimum scale of estimating NPP of cropland ranges from 330m to 400m.
Subject Area测绘工程
Language中文
Document Type学位论文
Identifierhttp://ir.xjlas.org/handle/365004/14698
Collection研究系统_荒漠环境研究室
Affiliation中科院新疆生态与地理研究所
Recommended Citation
GB/T 7714
杨会巾. 干旱区典型流域植被净初级生产力的遥感估算研究[D]. 北京. 中国科学院大学,2016.
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