摘要
本文根据SEBAL模型的理论建立了利用遥感数据计算区域ET的计算模型,提出了敏感度评价指标,建立了单参数敏感性评价体系,并对模型气象参数进行敏感性评价。计算模型以Landsat7 ETM+遥感影像数据和大气温度、风速、湿度、日照时数等地表气象数据作为输入,并对一些难以获取的参数做了简化处理,以ERDAS Imagine遥感数据处理软件为工具,计算了研究区(天津市)24hET空间分布图,并与Penman-Monteith公式所计算的研究区4种典型下垫面ET比较,结果显示,SEBAL模型计算的ET空间分布比较符合下垫面实际情况,计算结果较合理。考虑到气象数据对模型的影响重大,本文利用独立敏感度评价指标对模型中几个气象参数进行了敏感性分析,发现SEABL模型对风速、气温比较敏感,而对计算过程中选取的"热点"温度不敏感。本次建立的SEBAL模型计算较准确,参数敏感度评价方法简单有效,适合独立参数的敏感性分析。
The SEBAL model is widely used in evapotranspiration calculation, and the combination of meteorological input data and remote sensing input data is crucial to the SEBAL model of a region. In this paper, computational procedure is built to calculate the regional evapotranspiration, based on the theory of the SEBAL model. Also, a single factor sensitivity evaluation system is established to generate a relatively independent sensitivity index and evaluate the sensitivity of three meteorological parameters in the model. The SEBAL model uses the remote sensing data of Landsat7 ETM ＋ and the normal meteorological data including air temperature, wind speed, relative humidity, and sunlight duration in a whole day as well as other information as the input data. Meanwhile, the original SEBAL model procedure is modified to achieve some unobtainable parameters in normal procedure. The model is built to be applied in the ERDAS Imagine platform, which is efficient software for remote sensing data processing. The 24-hour ET amount and its distribution in Tianjin are calculated with this model. It is found that the ET amount is verifiable and the ET distribution is in accordance with the land type. Considering the great influence of the meteorological data on the model, sensitivity analysis of the three meteorological parameters is conducted by using the method developed in this paper, which reveals that the model is sensitive to the wind speed and the atmospheric temperature, while it is insensitive to the temperature of the selected ＂hot point＂, which is selected during the model calculation process. In conclusion, the SEBAL model built in this research is accurate and the sensitivity analysis method is easy to use and effective for fast sensitivity analysis for independent parameters.
出处
《资源科学》
CSSCI
CSCD
北大核心
2009年第8期1303-1308,共6页
Resources Science
基金
国家重点基础研究发展计划(973)(编号:2006CB403401)
基金委创新群体研究基金(编号:50721006)
关键词
SEBAL模型
遥感
气象参数
敏感性分析
天津市
SEBAL model
Remote sensing
Meteorological parameter
Sensitivity analysis
Relatively independent sensitivity index
