遥感腾发模型研究及其在干旱区平原绿洲的应用
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摘要
腾发是地表水热传输过程中的重要环节,也是水资源的最终消耗方式,因此成为水文水资源、气候、农业等领域的重要研究内容。传统的腾发量计算方法基于点观测数据建立,下垫面的不均匀性使其难以扩展到比较大的空间尺度。遥感数据具有空间连续性和时间动态性的特点,为区域腾发量的计算提供了新的途径。本论文在遥感腾发模型已有研究的基础上就有关问题进行深入研究,并将其应用于干旱区平原绿洲的耗水分析。
土壤热通量是腾发量计算中的重要一项,针对现有模型中该能量分量估算的经验性,论文引入机理性较强的土壤热通量计算方法——谐波法。利用植被覆盖度改进了谐波法的计算,同时通过引入晴天地表温度日内变化典型曲线,以及谐波法与双源模型TSEB的耦合,解决了谐波法的参数获取问题。站点计算结果表明模型耦合对潜热通量的误差具有制约作用,能够提高其模拟精度。
为获取同时具有高时间分辨率和高空间分辨率的遥感数据,论文提出地表温度空间降尺度的三角形法。利用Landsat 7 ETM+数据开展该方法与多项式法、植被覆盖度法、邻域相似法等降尺度方法的对比检验,表明三角形法精度相对较高;进一步的分析表明基于地表温度—植被指数函数关系的地表温度降尺度方法只适用于低分辨率像元内植被密度变异性较大的区域。
为解决遥感反演腾发量的时间扩展问题,论文对陆面数据同化进行研究,分析了同化系统的敏感性,并开展了遥感反演的表层土壤含水率、地表温度、潜热通量和显热通量的同化试验。研究表明观测数据的系统偏差对同化结果影响较大;当观测数据的误差被控制在一定范围时,数据同化对观测变量的模拟具有改进作用,对非观测变量模拟结果的影响具有不确定性。
在上述研究基础上,论文利用多时相MODIS数据构建了不同时间尺度的腾发量估算方法,并应用于叶尔羌河平原绿洲,分析了绿洲2007年耗水的年内过程、区域分布以及不同土地利用的耗水比例,为绿洲耗水研究和水资源配置提供了科学依据。
Evapotranspiration is an important component in the mass and energy exchange between land surface and atmosphere. It is also the final type of water consumption. So it has attracted many researchers from hydrology, water resources management, climatology and agriculture fields. The traditional methods to compute evapotranspiration are based on field measurements. These results are difficult to extend to a larger spatial scale because of the heterogeneity in land surface. Remote sensing data are continuous in space and dynamic in time. So it is potential to use them to estimate regional evapotranspiration. This thesis did further researches on some aspects in evapotranspiration retrieval, and applied these results to analyze water consumption within the arid oasis.
Soil heat flux is an important component during evapotranspiration retrieval. It is estimated empirically in existing remote sensing models. This thesis introduced a more theoretical method—the harmonic method—to estimate soil heat flux. This method was modified with fractional vegetation cover. Then researches were focused on how to obtain input variables of the harmonic method. On one hand, a typical curve to describe the diurnal pattern of surface temperature was introduced to determine the harmonic term. On the other hand, the harmonic method was coupled with the Two-Source Energy Balance (TSEB) model through surface soil water content. Comparisons with field measurements indicated that errors in latent heat flux simulations are limited through model coupling.
In order to obtain remote sensing data with high spatiotemporal resolution, this thesis put forward downscaling surface temperature data with the triangle method. This method was compared with the polynomial method, the fractional vegetation cover method, and the local similarity method using Landsat 7 ETM+ data. Simulations with the triangle method are more reasonable. Further analysis showed that these downscaling methods based on vegetation index are only applicable to coarse pixels with large heterogeneity in vegetation density.
Evapotranspiration retrieved by the remote sensing model is usually instantaneous. In order to extend this value to a longer temporal scale, this thesis carried out some researches on land surface data assimilation, including analyzing sensitivity of the data assimilation system and assimilating surface soil water content, surface temperature, latent and sensible heat fluxes retrieved from remote sensing data. It was found that the systemic bias in measurements can deeply affect assimilation results. When the precision of measurements is controlled within a certain range, data assimilation can improve simulations of the measured variable. For the other variables, assimilation results may be worse than the full open loop case.
Based on researches above, this thesis designed a process to estimate evapotranspiration at different temporal scales using multi-temporal MODIS data. It was applied to the Yerqiang Oasis. The spatiotemporal distribution of water consumption in this oasis in 2007 was analyzed. Water consumption proportions by different land use types were also calculated. These results can provide scientific basis for water consumption research and water resources allocation in the oasis.
土壤热通量是腾发量计算中的重要一项,针对现有模型中该能量分量估算的经验性,论文引入机理性较强的土壤热通量计算方法——谐波法。利用植被覆盖度改进了谐波法的计算,同时通过引入晴天地表温度日内变化典型曲线,以及谐波法与双源模型TSEB的耦合,解决了谐波法的参数获取问题。站点计算结果表明模型耦合对潜热通量的误差具有制约作用,能够提高其模拟精度。
为获取同时具有高时间分辨率和高空间分辨率的遥感数据,论文提出地表温度空间降尺度的三角形法。利用Landsat 7 ETM+数据开展该方法与多项式法、植被覆盖度法、邻域相似法等降尺度方法的对比检验,表明三角形法精度相对较高;进一步的分析表明基于地表温度—植被指数函数关系的地表温度降尺度方法只适用于低分辨率像元内植被密度变异性较大的区域。
为解决遥感反演腾发量的时间扩展问题,论文对陆面数据同化进行研究,分析了同化系统的敏感性,并开展了遥感反演的表层土壤含水率、地表温度、潜热通量和显热通量的同化试验。研究表明观测数据的系统偏差对同化结果影响较大;当观测数据的误差被控制在一定范围时,数据同化对观测变量的模拟具有改进作用,对非观测变量模拟结果的影响具有不确定性。
在上述研究基础上,论文利用多时相MODIS数据构建了不同时间尺度的腾发量估算方法,并应用于叶尔羌河平原绿洲,分析了绿洲2007年耗水的年内过程、区域分布以及不同土地利用的耗水比例,为绿洲耗水研究和水资源配置提供了科学依据。
Evapotranspiration is an important component in the mass and energy exchange between land surface and atmosphere. It is also the final type of water consumption. So it has attracted many researchers from hydrology, water resources management, climatology and agriculture fields. The traditional methods to compute evapotranspiration are based on field measurements. These results are difficult to extend to a larger spatial scale because of the heterogeneity in land surface. Remote sensing data are continuous in space and dynamic in time. So it is potential to use them to estimate regional evapotranspiration. This thesis did further researches on some aspects in evapotranspiration retrieval, and applied these results to analyze water consumption within the arid oasis.
Soil heat flux is an important component during evapotranspiration retrieval. It is estimated empirically in existing remote sensing models. This thesis introduced a more theoretical method—the harmonic method—to estimate soil heat flux. This method was modified with fractional vegetation cover. Then researches were focused on how to obtain input variables of the harmonic method. On one hand, a typical curve to describe the diurnal pattern of surface temperature was introduced to determine the harmonic term. On the other hand, the harmonic method was coupled with the Two-Source Energy Balance (TSEB) model through surface soil water content. Comparisons with field measurements indicated that errors in latent heat flux simulations are limited through model coupling.
In order to obtain remote sensing data with high spatiotemporal resolution, this thesis put forward downscaling surface temperature data with the triangle method. This method was compared with the polynomial method, the fractional vegetation cover method, and the local similarity method using Landsat 7 ETM+ data. Simulations with the triangle method are more reasonable. Further analysis showed that these downscaling methods based on vegetation index are only applicable to coarse pixels with large heterogeneity in vegetation density.
Evapotranspiration retrieved by the remote sensing model is usually instantaneous. In order to extend this value to a longer temporal scale, this thesis carried out some researches on land surface data assimilation, including analyzing sensitivity of the data assimilation system and assimilating surface soil water content, surface temperature, latent and sensible heat fluxes retrieved from remote sensing data. It was found that the systemic bias in measurements can deeply affect assimilation results. When the precision of measurements is controlled within a certain range, data assimilation can improve simulations of the measured variable. For the other variables, assimilation results may be worse than the full open loop case.
Based on researches above, this thesis designed a process to estimate evapotranspiration at different temporal scales using multi-temporal MODIS data. It was applied to the Yerqiang Oasis. The spatiotemporal distribution of water consumption in this oasis in 2007 was analyzed. Water consumption proportions by different land use types were also calculated. These results can provide scientific basis for water consumption research and water resources allocation in the oasis.
引文
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