【作者】 于红博；

【导师】 杨劼；

【作者基本信息】 内蒙古大学 ， 生态学， 2009， 博士

【摘要】 水循环是全球气候系统中的一个主要部分,在水循环的几个环节中,蒸散占着特别重要的地位,热量的释放和吸收是伴随着蒸散过程同时进行的。特别是在黄土丘陵沟壑干旱半干旱地区,蒸发量大,平均土壤水分含量低,水是植被生长的主要限制因子,植被在水循环过程中扮演着重要角色。而不同尺度蒸散估算的定量化、蒸散估算的尺度转换以及转换后估算值的精度问题一直是众多生态学者研究的热点问题。本研究在前人以及本项目组工作基础上,以生物学为基础,通过建立蒸散估算尺度转换模型,为实现好的蒸散模拟提供方法。本研究选择有大量数据积累的鄂尔多斯高原皇甫川流域为研究区,利用点面结合的方式对数据进行补测,在前人的工作基础上,建立了植物蒸腾和植被蒸散模型,在植物叶片——个体——群落——景观尺度上实现了尺度转换,结果如下:1植物个体尺度:针对不同的生活型,参考Penman和Priestley-Taylor模型,建立了草本和灌木的蒸腾模型~*,实现了从植物叶片到个体的尺度转换。对草本植物,运用太阳总辐射、空气温度、2m高度处风速等环境因子和叶气孔导度、单株干重等植物特性因子的数据建立了瞬时蒸腾模型,通过积分运算,得到日蒸腾模型,经过验证,平均相对误差为16.87%,在误差允许范围之内。对灌木植物,运用太阳总辐射、空气温度、空气相对湿度等环境因子和叶气孔导度、单株叶干重等植物特性因子的数据建立了瞬时蒸腾模型,通过积分运算,得到日蒸腾模型,运用实测数据进行验证,平均相对误差为14.48%,在误差允许范围之内。2群落尺度:在个体蒸腾模型基础上,建立了群落蒸散模型~*;针对不同的因子建立模型过程中,发现叶气孔导度与群落蒸散有更直接的关系,建立了与之相关的群落蒸散模型~*;基于更多因子的Penman-Monteith模型~*,用土壤含水量对其中的土壤蒸发项进行了修正,提高了精度。在植物个体尺度蒸腾模型基础上,综合考虑了群落中不同生活型植物的盖度、群落叶面积指数、个体蒸腾量和单株叶干重对群落蒸散的影响,同时根据群落蒸散量与太阳总辐射、空气温度、空气相对湿度等主要环境因子的关系,运用数据建立了群落蒸散模型,草本群落和灌木群落的模型拟和度分别为0.8845和0.9238,实现了从个体到群落的尺度转换。建立了与太阳总辐射、空气温度、空气相对湿度等气象因子和叶气孔导度、群落盖度、群落叶面积指数等生物因子相关的群落蒸散模型,草本群落和灌木群落的模型拟和度分别为0.9145和0.9449。用土壤含水量对广泛使用的Penman-Monteith蒸散公式中的土壤蒸发项进行了修正,草本群落和灌木群落的模型拟和度分别为0.9254和0.8563。敏感性分析表明,当参数值变动±20%时,模拟结果的变化范围均在±13%以内,因此该模型模拟结果比较稳定,对任一参数变化的反应比较平稳。基于个体蒸腾模型的群落蒸散模型在有叶气孔导度值,或有个体蒸腾量而没有叶气孔导度值的情况下均可使用;与叶气孔导度相关的群落蒸散模型必须在有叶气孔导度的情况下使用,精度较高;与Penman-Monteith蒸散公式相比,本研究所建两个群落蒸散模型所含参量较少,实现了模型的简单化,应用性较高。3景观尺度:基于群落蒸散模型,在考虑生物因子的前提下,提出估算景观尺度蒸散的方法。同时基于目前的研究现状,运用遥感方法对景观尺度的蒸散量进行估算,以与尺度转换方法进行对比。1)以群落蒸散模型为基础,考虑其中参量的空间变化,通过坡度坡向图、植被盖度图和植被分布图来体现景观异质性,以GIS为平台,在每个栅格上运行群落蒸散模型,即可估算景观尺度蒸散量。用该方法对2003年研究区蒸散量进行估算,经过验证,平均相对误差为14.95%,在误差允许范围之内,该方法可用于估算景观尺度蒸散量,由此实现了从群落到景观的尺度转换。2)运用遥感方法,通过1996年、2003年和2007年Landsat-5 TM影像数据,结合同期气象资料,对研究区地表特征参数和地表能量平衡各分量进行了估算,反演出该流域瞬时蒸散量,经过时间尺度转换,得到流域日蒸散量,结果表明反演的日蒸散量与实际地表状况吻合,能很好地反映研究区地表实际情况。利用广泛使用的FAO推荐的方法对1996年和2007年反演的结果进行检验,平均相对误差为12.87%;用实测数据对2003年反演的结果进行检验,平均相对误差为17.47%,均在误差允许范围之内,具有较好的实用性。特别是在估算日蒸散时,将水体单独提取出,应用Penman模型求取水体蒸发量,再整合到流域日蒸散量中,提高了精度。对以上估算研究区蒸散的3景影像进行了对比分析,从1996年到2007年11年以来,减小的植被盖度与增加的植被盖度区域面积之比为1.011,基本不变;整个流域平均植被盖度呈下降趋势,由1996年的17.33%降到2007年的11.25%;3个年份蒸散量分布范围基本一致,总体上随年代的增加蒸散量呈递减趋势,主要是由于流域平均植被盖度下降和1999年以来开始实行的“退耕还林还草”政策使农田面积有所减小;对1996年和2007年两期植被分布图进行统计分析表明,11年间,流域内裸地面积明显减少;人工灌木林的面积大幅度增加;农田面积减少;乔木林和水体的面积稍有增加,变化不明显。3)对估算景观尺度日蒸散量的两种方法进行了对比分析,考虑了生物因子的尺度转换方法可信度较高;在没有生物因子实测数据的情况下,遥感方法也不失为一种好的简便算法。以上建立的几种尺度模型中,叶气孔导度、单株叶干重、群落叶面积指数和群落盖度为建模中重要的生物因子。根据本研究建立的模型,用Visual FoxPro 6.0编程制作了估算植物蒸腾、群落蒸散的软件,并进行了打包,使其可以脱离VisualFoxPro 6.0环境运行,且操作简单,使用方便。更多还原

【Abstract】 Hydrologic cycle is the key component of the global climate system. Evapotranspiration is one the major processes driving this cycle. Two opposing fluxes, energy release and energy absorption, take place during evapotranspiration. In arid and semiarid regions evaporation is generally high and soil moisture content is low, especially in soils developed on loess substrates. While water is often a limiting factor of vegetation growth in such areas, vegetation cover substantially regulates the hydrologic cycle here. Estimating evapotranspiration at different scales and assessing the uncertainty of such estimations are ecological research problems of high importance. This paper presents a method for estimating and scaling the evapotranspiration.Our study area is the Huangfuchuan watershed of Ordos Plateau which has been intensively studied in the past. We developed the evapotranspiration estimation and scaling model of leaf-individual-community-landscape which is described below:1) Individual level. Transpiration models* for herbs and shrubs were developed taking Penman and Priestley-Taylor models as reference and considering differences in plant life forms. These models allowed us to scale up from the leaf to the individual plant level. The instantaneous transpiration model was developed using data on environmental factors, such as incident solar radiation, air temperature, wind speed at 2m (for herbs), and relative air humidity (for shrubs), and plant characteristics, such as leaf Stomatal conductance and leaf dry weight of individual plants. Daily transpiration was calculated by the integration procedure. The verification of the model resulted in the average relative error of 16.87% for herbs and 14.48% for shrubs, which is an acceptable level of uncertainty.2) Community level models* were developed in three different ways - the model based on individual transpiration models, the model based on direct relationship between leaf Stomatal conductance and community level evapotranspiration, and the model that used the original Penman-Monteith model with additional adjustements of some factors by soil water content. These model modifications resulted in improved accuracy.The model developed from individual transpiration models used the relationships between evapotranspiration and environmental factors such as incident solar radiation, air temperature, and relative air humidity, and incorporated plant leaf area index, individual transpiration of different plant life forms and leaf dry weight. The correlation of herb community model and shrub community models were respectively 0.8845 and 0.9238.The second model used relationships with meteorological factors such as incident solar radiation, air temperature, and relative air humidity, and plant characteristics such as leaf Stomatal conductance, percent cover, and leaf area index. The correlations achieved for herb community and shrub community were 0.9145 and 0.9449 respectively.The third model used the Penman-Monteith model that was corrected by soil water content. The correlations were 0.9254 for the herb community and 0.8563 for the shrub community. Sensitivity analysis produced±13% change in evapotranspiration when model parameters were modified within±20%. Therefore, the model is regarded stable and functional.The first evapotranspiration model is useful when individual evapotranspiration is calculated but leaf Stomatal conductance is not measured. The second model is more appropriate when leaf Stomatal conductance is measured. These two models are more applicable because they use less parameters compared to the Penman-Monteith model.3) Landscape level evapotranspiration was estimated using community scale models. Additionally, we used remote sensing to estimate evapotranspiration at this scale and contrast it with model upscaling.Community model upscaling considered changes in parameters’ space and used Geographical Information Systems (GIS). GIS layers, such as topographic slope and aspect, maps of plant communities and vegetation cover were used to characterize landscape heterogeneity. We extrapolated to the entire Huangfuchuan watershed and estimated evapotranspiration in 2003 with the average relative error of 14.95%.Remote sensing approach was used to retrieve instantaneous evapotranspiration based on the estimation of land surface characteristics and fluxes from Landsat-5 TM images collected in 1996, 2003, and 2007, and using auxiliary environmental data from the same time periods. Daily evapotranspiration was estimated by scaling. Calculated daily evapotranspiration had an average relative error of 12.87% when results for 1996 and 2007 were verified using the FAO method. The average relative error for 2003 was 17.47%. This level of uncertainty is acceptable so we conclude the method is applicable. Because water was treated as bare land when using this method calculated evaporation from the water surface using the Penman model and merged this estimates into the daily evapotranspiration which resulted in improved accuracy. Finally, we compared these three images and found that vegetation cover decreased during the 11 year between 1996 and 2007. The average vegetation cover shrank from 17.33% in 1996 to 11.25% in 2007. Evapotranspiration also decrease uniformly during these time periods. No only the average vegetation cover decreased but farmland area has reduced because of the implementation of the policy promoting the return of cultivated lands to forests and grasslands. The comparison of vegetation maps from 1996 and 2007 showed that bare land area decreased, the area of newly planted shrubs greatly increased, farmland area decreased, and woodlands and water area increased insignificantly.The two methods of estimating landscape level evapotranspiration were compared. Both estimations were found plausible with the model upscaling approach being more biologically meaningful and slightly more accurate because of the use of manually interpreted vegetation maps of higher accuracy. Remote sensing approach, on the other hand, is useful in the absence of good quality biological information.Such important biological information is used to parameterize the aforementioned models and include leaf Stomatal conductance, leaf dry weight of individual plants, leaf area index and coverage. All models were coded in Visual FoxPro 6.0.更多还原