黄土丘陵沟壑区植物蒸腾和植被蒸散估算尺度转换模型研究
|
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。
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.
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。
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.
引文
[1]辛晓洲,田国良,柳钦火.地表蒸散定量遥感的研究进展.遥感学报.2003.7(3):233-238.
[2]郭晓寅,程国栋.遥感技术应用于地表面蒸散的研究进展.地球科学进展.2004.19(1):107-114.
[3]刘惊涛,刘世荣.植被蒸散研究方法的进展与展望.林业科学.2006,42(6):108-114.
[4]陈发祖.蒸发测定方法.地理研究.1988,7(3):78-88.
[5]邓东周,范志平,王红等.林木蒸腾作用测定和估算方法.生态学杂志.2008,27(6):1051-1058.
[6]严昌荣,A lec Dow ney,韩兴国,等.北京山区落叶阔叶林中核桃楸在生长中期的树干液流研究.生态学报.1999,19(6):793-797.
[7]白云岗,宋郁东,周宏飞,等.应用热脉冲技术对胡杨树干液流变化规律的研究.干旱区地理.2005,28(3):373-376.
[8]Wullschleger SD,Meinzer FC,Vertessy RA,et al.A review of whole-plant water use studies in trees.Tree Physiology.1998,18:499-512.
[9]黄贤庆,刘新仁.大尺度蒸发模型研究.河海大学学报.2000.28(4):13-18.
[10]洪嘉链,王淑清.京津唐地区水面蒸发估算及其分布特征.地理研究.1987,6(1).
[11]闫俊华,周国逸,陈忠毅.鼎湖山人工松林生态系统蒸散力及计算方法的比较.生态学杂志.2001,21(1).
[12]刘德辉,梁珍海,李荣锦.蒸发研究的概况与进展.江苏林业科技.1998.25(4):54-57.
[13]刘绍民,孙中平,李小文等.蒸散量测定与估算方法的对比研究.自然资源学报.2003,18(2):161-167.
[14]张劲松,孟平,尹昌君.植物蒸散耗水量计算方法综述.世界林业研究.2001.14(2):23-28.
[15]Brutsaert W.1982.Evaporation into the atmosphere.London,D.Reidel Publishing Company.
[16]刘昌明,王会肖.土壤-作物大气界面水分过程与节水调控.北京:科学出版社.1999.
[17]郭玉川.基于遥感的区域蒸散在干旱区水资源利用中的应用.新疆农业大学硕士学位论文.2007.
[18]程根伟,余新晓,赵玉涛等.山地森林生态系统水文循环与数学模拟.北京:科学出版社.2004.
[19]邹连文,韩洪暖.可能蒸散量的三种计算方法.西北水电.1996,2:38-40.
[20]刘昌明,张士锋,傅国斌.水文循环过程理论与方法的研究进展.
[21]司建华,冯起,张小由等.植物蒸散耗水量测定方法研究进展.水科学进展.2005.16(3):450-459.
[22]杜尧东,刘作新等.参考作物蒸散计算方法及其评价.河南农业大学学报.2001,35(1):57-61.
[23]Hossein DehghaniSanij,Tahei Yamamoto,Velu Rasiah.Assessment of evapotranspiration estimation models for use in semi-arid environments.Agricultural Water Management.2004,64:91-106.
[24]张毅.几种蒸发模型的分析.新疆大学学报(自然科学版).1995.12(3):91-96.
[25]G.Rana and N.Katerji.A Measurement Based Sensitivity Analysis of the Penman-Monteith Actual Evapotranspiration Model for Crops of Different Height and in Contrasting Water Status.Theor.Appl.Climatol..1998,60:141-149.
[26]Angel Unset,Imma Farre,Antonio Martinez-Cob etal.Comparing Penman-Monteith and Priestley-Taylor approaches as reference-evaporeanspiration inputs for modeling maize water-use under Mediterranean conditions.Agricultural Water Management.2004,66:205-219.
[27]F.Domingo,L.Villagarcia,A.J.Brenner etc.Evapotranspiration model for semi-arid shrub-lands tested against data from SE Spain.Agricultural and Forest Meteorology.1999,95:67-84.
[28]莫兴国.土壤-植被-大气系统水分能量传输模拟和验证.气象学报.1998.56(3):323-332.
[29]刘昌明,窦清晨.土壤-植物-大气连续体模型中的蒸散计算.水科学进展.1992,3(4):255-263.
[30]马李一,孙鹏森,马履一.油松、刺槐单木与林分水平耗水量的尺度转换.北京林业大学学报,2001,23(4):2-5.
[31]Seguin B,Courault D,Guerif M.利用卫星数据从局部尺度到区域尺度的转换方法的应用--表面温度与蒸散量的计算.Remote Sensing of Environment.1994,49.
[32]Thunnissen H A M,Nieuwenhuis G J A.从热红外数据估计区域24小时蒸散量的简化方法.Remote Sensing Of Environment,1990,31.
[33]陈云浩,李晓兵,史培军.中国西北地区蒸散量计算的遥感研究.地理学报.2001,56(3):261-268.
[34]陈坤,陈添宇.用NOAA卫星气象资料计算复杂地形下的流域蒸散.地理学报.1993,48(1):61-69.
[35]Kenlo Nishida,Ramakrishna R.et al.An Evapotranspiration Index from Aqua/MODIS for monitoring surface moisture status.IEEE Aqua Special Issue.23 MAY 2002.
[36]Hequn Yang,Yong Liu.A satellite remote sensing based assessment of urban heat island in Lanzhou city,northwest China.来自网上.
[37]J.A.Sobrinoa,M.Go'meza et al.A simple algorithm to estimate evapotranspiration from DAIS data:Application to the DAISEX campaigns.Journal of Hydrology.2005,315:117-125.
[38]Sultan ALSULTAN,Saudi Arabia et al.An Algorithm for Land Surface Temperature Analysis of Remote Sensing Image Coverage Over AlQassim,Saudi Arabia.From Pharaohs to Geoinformatics FIG Working Week 2005 and GSDI-8 Cairo,Egypt April 16-21,2005.
[39]Yann Chemin.Evapotranspiration of crops by remote sensing using the energy balance based algorithms.来自网上.
[40]Sudheer R.Satti,Jennifer M.Jacobs.A GIS-based model to estimate the regionally distributed drought water demand.Agricultural Water Management.2004,66:1-13.
[41]Vijendra K.Boken,Gerrit Hoogenboom et al.Agricultural water use edtimation using geospatial modeling and a geographic information system.Agricultural Water Management.2004,67:185-199.
[42]Richard G.Allen,M.Tasumi,Anthony Morse,etc.A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning.Irrigation and Drainage Systems.2005,19:251-268.
[43]翁笃鸣,高歌.利用卫星资料试作青藏高原地表净辐射场的气候反演.气象科学.2001,21(2):162-168.
[44]黄妙芬.地表通量研究进展.干旱区地理.2003.26(2):159-165.
[45]Revised Landsat 5 TM Radiometric Calibration Procedures and Post-Calibration Dynamic Ranges.来自网上.
[46]黄妙芬,刘素红,朱启疆.应用遥感方法估算区域蒸散量的制约因子分析.干旱区地理.2004.27(1):100-105.
[47]王仁忠,高琼,等.松嫩草原羊草群落水分生态的研究.草业学报.1996,16(1):33-39.
[48]杨劼,高清竹,李国强,等.皇甫川流域主要人工灌木水分生态的研究.自然资源学报.2002,17(1):87-94.
[49]杨劼,宋炳煜,朴顺姬,等.皇甫川丘陵沟壑区小流域生态用水实验研究.自然资源学报.2003,18(5):513-520.
[50]杨劼,高清竹,李国强,等.皇甫川流域几种主要植物水分生态特征.生态学报.2004,24(11):2387-2394.
[51]贺康宁,田阳,张光灿.刺槐日蒸腾过程的Penman-Monteith方程模拟.生态学报.2003,23(2):251-258.
[52]范爱武,刘伟,王崇琦.环境因子对土壤水分蒸散的影响.太阳能学报.2004,25(1):1-5.
[53]刘胜,贺康宁.基于Penman-Monteith模型的林木日蒸腾模拟.西北林学院学报.2006,21(3):15-20.
[54]卢振民.农田蒸散计算中边界层阻力的确定.生态学杂志.1988,7(4):59-61.
[55]杨树栋,王天铎.气孔阻力上边界层阻力的进一步计算.植物生理学报.1988,14(1):9-15.
[56]陈镜明.现用遥感蒸散模式中的一个重要缺点及改进.科学通报.1988.(6):454-457.
[57]谢贤群.遥感瞬时作物表面温度估算农田全日蒸散总量.环境遥感.1991.6(4):253-260.
[58]黄永梅.黄土丘陵沟壑区小流域水分平衡的生态学研究--以纸坊沟为例.北京师范大学博士学位论文.2003.
[59]Gao Q,Zhao P,Zeng X,et al.A model of stomatal conductance to quantify the relationship between leaf transpiration,microclimate and soil water stress.Plant Cell Envir.2002,25:1373-1381.
[60]许迪.灌溉水文学尺度转换问题研究综述.水利学报.2006,37(2):141-149.
[61]吕一河,傅伯杰.生态学中的尺度及尺度转换方法.生态学报.2001,21(12):2096-2105.
[62]赵文武,傅伯杰,陈利顶.尺度推绎研究中的几点基本问题.2002,17(6):905-911.
[63]张彤,蔡永立.谈生态学研究中的尺度问题.生态科学.2004,23(2):175-178.
[64]J.Wu,K.B.Jones,H.Li,etc.Scaling and Uncertainty Analysis in Ecology:Methods and Applications.Netherlands.2006.
[65]张娜.生态学中的尺度问题--尺度上推.生态学报.2007,27(10):4252-4266.
[66]张娜.生态学中的尺度问题:内涵与分析方法.生态学报.2006.26(7):2340-2355.
[67]金争平,史培军,侯福昌,等.黄河皇甫川流域土壤侵蚀系统模型和治理模式.北京:海洋出版社.1992.
[68]金争平,苗宗义,王正文,等.水土保持与土地资源和环境--以黄土高原准格尔试验区为例.土壤侵蚀与水土保持学报.1999,5(5):1-6.
[69]苗宗义.黄土高原综合治理皇甫川流域水土流失综合治理农林牧全面发展试验研究文集.北京:中国农业科技出版社.1992.
[70]宋炳煜,杨劼.关于生态用水研究的讨论.自然资源学报.2003,18(5):617-625.
[71]高清竹,杨劫,宋炳煜,等.黄河中游砒砂岩地区长川流域生态用水分析.自然资源学报.2004,19(4):499-507.
[72]林平,李吉跃,马达.北京山区油松林蒸腾耗水特性研究.北京林业大学学报.2006,28(1):47-50.
[73]邱扬,傅伯杰,王军,等.黄土丘陵小流域土壤水分空间预测的统计模型.2001,20(6):739-751.
[74]张文彤.SPSS 11统计分析教程(高级篇).北京希望电子出版社.2002.
[75]乐通潮,张万昌.双参数月水量平衡模型在汉江流域上游的应用.资源科学.2004,26(6):97-103.
[76]吴军,张万昌.基于径流模拟的分布式水文模型参数的空间相应研究.水土保持研究.2007,14(5):1-6.
[77]郭孟霞,毕华兴,刘鑫,等.树木蒸腾耗水研究进展.中国水土保持科学.2006,4(4):114-12.
[78]刘静,王连喜,马力文等.宁夏南部山区小麦干旱监测与灾损评估模型研究.中国生态农业学报.2003.11(4):143-147.
[79]王黎明.区域蒸散与土地利用覆盖变化的关系探讨.吉林大学博士学位论文.2005.
[80]Nouvellon Y,Rambal S,Lo Seen D,etc.Modeling of daily fluxes of water and carbon from shortgrass steppes.Agric.For.Meteorol.2000,100:137-153.
[81]许红梅,贾海坤,黄永梅.黄土丘陵沟壑区小流域植被净第一性生产力模型.生态学报.2005.25(5):1064-1074.
[82]刘志红,刘文兆,李锐.基于3S技术的区域蒸散研究进展.中国水土保持科学.2006,4(3):117-122.
[83]吕厚荃,于贵瑞.几种实际蒸散计算方法在土壤水分模拟中的应用.资源科学.2001,23(6):85-90.
[84]莫兴国,林忠辉,刘苏峡.基于Penman-Monteith公式的双源模型的改进.水利学报.2000.5:6-11.
[85]莫兴国.冠层表面阻力与环境因子关系模型及其在蒸散估算中的应用.地理研究.1997,16(2):82-88.
[86]包铁军.皇甫川流域植被生态用水分析.内蒙古大学硕士学位论文.2005.
[87]许红梅.黄土丘陵沟壑区小流域植被净第一性生产过程模拟研究.北京师范大学博士学位论文.2003.
[88]张兆明,何国金,肖荣波等.利用TM6数据反演陆地表面温度新算法研究.遥感技术与应用.2005.20(6):547-550.
[89]梅安新,等.遥感导论.高等教育出版社.2001.
[90]马耀明,王介民,Massimo Menenti,等.HEIFE非均匀陆面上区域能量平衡研究.气候与环境研究.1997,2(3):293-301.
[91]马耀明,刘东升,苏中波等.卫星遥感藏北高原非均匀陆表地表特征参数和植被参数.大气科学.2004,28(1):23-31.
[92]孟宪红,吕世华,陈世强等.金塔绿洲地表特征参数遥感反演研究.高原气象.2005.24(4):509-515.
[93]孟宪红,吕世华,张宇等.使用LANDSAT-5 TM数据反演金塔地表温度.高原气象,2005,24(5):721-726.
[94]Gyanesh Chander,Brian Markham.Revised Landsat 5 TM Radiometric Calibration Procedures and Post-Calibration Dynamic Ranges[J].Geoscience and Remote sensing.2003,41(11):2674-2677.
[95]张长春,王晓燕,崔亚莉.黄河三角洲地表特征参数的遥感研究.水文地质工程地质.2005.(2):71-75.
[96]Enric Valor,Vicente Caselles.Mapping Land Surface Emissivity from NDVI:Application to European,African,and South American Areas.REMOTE SENS.ENVIRON.1996,57:167-184.
[97]查书平.基于RS与GIS的长江三角洲蒸散量研究.南京气象学院硕士学位论文.2004.
[98]覃志豪,ZhangMinghua,Arnon Karnieli等.用陆地卫星TM6数据演算地表温度的单窗算法.地理学报.2001.56(4):456-466.
[99]马耀明,刘东升,王介民等.卫星遥感敦煌地区地表特征参数研究.高原气象.2003,22(6):531-536.
[100]徐玉貌,刘红年,徐桂玉.大气科学概论.南京大学出版社.2000.
[101]马耀明,王介民.卫星遥感结合地面观测估算非均匀地表区域能量通量.气象学报.1999,57(2):180-189.
[102]黄妙芬,邢旭峰,朱启疆等.定量遥感地表净辐射通量所需大气下行长波辐射估算模型改进.地理研究.2005.24(5):757-766.
[103]潘志强,刘高焕.黄河三角洲蒸散的遥感研究.地球信息科学.2003.(3):91-96.
[104]郭建茂,王连喜,郑有飞,等.宁夏南部区域蒸发(散)量遥感估算方法.南京气象学院学 报.2004.27(3):302-309.
[105]郭晓寅.黑河流域蒸散分布的遥感研究[J].自然科学进展.2005,15(10):1266-1270.
[106]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究.遥感学报.2005.9(5):589-595.
[107]李玉霖,崔建垣,张铜会.参考作物蒸散量计算方法的比较研究.中国沙漠.2002.22(4):372-376.
[108]V.Magliulo,R.d'Andria,G.Rana.Use of the modified atmometer to estimate reference evapotranspiration in Mediterranean environments.Agricultural Water Management.2003,63:1-14.
[109]韩淑敏,程一松,胡春胜.太行山山前平原作物系数与降水年型关系探讨.干旱地区农业研究.2005.23(5):152-158.
[110]GAO Ge,CHEN Deliang,REN Guoyu,et al.Spatial and temporal variations and controlling factors of potential evapotranspiration in China:1956-2000.J Geographical Sciences.2006,16(1 ):3-12.
[111]刘强,何岩,崔保山.洮儿河流域土地利用变化对地表蒸散量的影响.资源科学.2007,29(4):121-126.
[112]周金龙,董新光,陈文娟等.应用彭曼-蒙特斯公式计算天山北坡平原区水面蒸发量.新疆农业大学学报.2002.25(4):35-38.
[113]李玉霖,崔建垣,张铜会.奈曼地区灌溉麦田蒸散量及作物系数的确定.应用生态学报.2003.14(6):930-934.
[114]岳天祥,刘纪远.生态地理建模中的多尺度问题.第四纪研究.2003,23(3):256-261.
[115]刘昌明 等.西北地区水资源配置生态环境建设和可持续发展战略研究(生态环境卷).科学出版社.2004.
[116]谭一波,赵仲辉.叶面积指数的主要测定方法.林业调查规划.2008,33(3):45-48.
[117]杜屿.水库湖泊水面蒸发的分析计算.海洋湖沼通报.1986,(3):25-32.
[118]金争平 等.砒砂岩区水土保持与农牧业发展研究.郑州:黄河水利出版社.2003.
[2]郭晓寅,程国栋.遥感技术应用于地表面蒸散的研究进展.地球科学进展.2004.19(1):107-114.
[3]刘惊涛,刘世荣.植被蒸散研究方法的进展与展望.林业科学.2006,42(6):108-114.
[4]陈发祖.蒸发测定方法.地理研究.1988,7(3):78-88.
[5]邓东周,范志平,王红等.林木蒸腾作用测定和估算方法.生态学杂志.2008,27(6):1051-1058.
[6]严昌荣,A lec Dow ney,韩兴国,等.北京山区落叶阔叶林中核桃楸在生长中期的树干液流研究.生态学报.1999,19(6):793-797.
[7]白云岗,宋郁东,周宏飞,等.应用热脉冲技术对胡杨树干液流变化规律的研究.干旱区地理.2005,28(3):373-376.
[8]Wullschleger SD,Meinzer FC,Vertessy RA,et al.A review of whole-plant water use studies in trees.Tree Physiology.1998,18:499-512.
[9]黄贤庆,刘新仁.大尺度蒸发模型研究.河海大学学报.2000.28(4):13-18.
[10]洪嘉链,王淑清.京津唐地区水面蒸发估算及其分布特征.地理研究.1987,6(1).
[11]闫俊华,周国逸,陈忠毅.鼎湖山人工松林生态系统蒸散力及计算方法的比较.生态学杂志.2001,21(1).
[12]刘德辉,梁珍海,李荣锦.蒸发研究的概况与进展.江苏林业科技.1998.25(4):54-57.
[13]刘绍民,孙中平,李小文等.蒸散量测定与估算方法的对比研究.自然资源学报.2003,18(2):161-167.
[14]张劲松,孟平,尹昌君.植物蒸散耗水量计算方法综述.世界林业研究.2001.14(2):23-28.
[15]Brutsaert W.1982.Evaporation into the atmosphere.London,D.Reidel Publishing Company.
[16]刘昌明,王会肖.土壤-作物大气界面水分过程与节水调控.北京:科学出版社.1999.
[17]郭玉川.基于遥感的区域蒸散在干旱区水资源利用中的应用.新疆农业大学硕士学位论文.2007.
[18]程根伟,余新晓,赵玉涛等.山地森林生态系统水文循环与数学模拟.北京:科学出版社.2004.
[19]邹连文,韩洪暖.可能蒸散量的三种计算方法.西北水电.1996,2:38-40.
[20]刘昌明,张士锋,傅国斌.水文循环过程理论与方法的研究进展.
[21]司建华,冯起,张小由等.植物蒸散耗水量测定方法研究进展.水科学进展.2005.16(3):450-459.
[22]杜尧东,刘作新等.参考作物蒸散计算方法及其评价.河南农业大学学报.2001,35(1):57-61.
[23]Hossein DehghaniSanij,Tahei Yamamoto,Velu Rasiah.Assessment of evapotranspiration estimation models for use in semi-arid environments.Agricultural Water Management.2004,64:91-106.
[24]张毅.几种蒸发模型的分析.新疆大学学报(自然科学版).1995.12(3):91-96.
[25]G.Rana and N.Katerji.A Measurement Based Sensitivity Analysis of the Penman-Monteith Actual Evapotranspiration Model for Crops of Different Height and in Contrasting Water Status.Theor.Appl.Climatol..1998,60:141-149.
[26]Angel Unset,Imma Farre,Antonio Martinez-Cob etal.Comparing Penman-Monteith and Priestley-Taylor approaches as reference-evaporeanspiration inputs for modeling maize water-use under Mediterranean conditions.Agricultural Water Management.2004,66:205-219.
[27]F.Domingo,L.Villagarcia,A.J.Brenner etc.Evapotranspiration model for semi-arid shrub-lands tested against data from SE Spain.Agricultural and Forest Meteorology.1999,95:67-84.
[28]莫兴国.土壤-植被-大气系统水分能量传输模拟和验证.气象学报.1998.56(3):323-332.
[29]刘昌明,窦清晨.土壤-植物-大气连续体模型中的蒸散计算.水科学进展.1992,3(4):255-263.
[30]马李一,孙鹏森,马履一.油松、刺槐单木与林分水平耗水量的尺度转换.北京林业大学学报,2001,23(4):2-5.
[31]Seguin B,Courault D,Guerif M.利用卫星数据从局部尺度到区域尺度的转换方法的应用--表面温度与蒸散量的计算.Remote Sensing of Environment.1994,49.
[32]Thunnissen H A M,Nieuwenhuis G J A.从热红外数据估计区域24小时蒸散量的简化方法.Remote Sensing Of Environment,1990,31.
[33]陈云浩,李晓兵,史培军.中国西北地区蒸散量计算的遥感研究.地理学报.2001,56(3):261-268.
[34]陈坤,陈添宇.用NOAA卫星气象资料计算复杂地形下的流域蒸散.地理学报.1993,48(1):61-69.
[35]Kenlo Nishida,Ramakrishna R.et al.An Evapotranspiration Index from Aqua/MODIS for monitoring surface moisture status.IEEE Aqua Special Issue.23 MAY 2002.
[36]Hequn Yang,Yong Liu.A satellite remote sensing based assessment of urban heat island in Lanzhou city,northwest China.来自网上.
[37]J.A.Sobrinoa,M.Go'meza et al.A simple algorithm to estimate evapotranspiration from DAIS data:Application to the DAISEX campaigns.Journal of Hydrology.2005,315:117-125.
[38]Sultan ALSULTAN,Saudi Arabia et al.An Algorithm for Land Surface Temperature Analysis of Remote Sensing Image Coverage Over AlQassim,Saudi Arabia.From Pharaohs to Geoinformatics FIG Working Week 2005 and GSDI-8 Cairo,Egypt April 16-21,2005.
[39]Yann Chemin.Evapotranspiration of crops by remote sensing using the energy balance based algorithms.来自网上.
[40]Sudheer R.Satti,Jennifer M.Jacobs.A GIS-based model to estimate the regionally distributed drought water demand.Agricultural Water Management.2004,66:1-13.
[41]Vijendra K.Boken,Gerrit Hoogenboom et al.Agricultural water use edtimation using geospatial modeling and a geographic information system.Agricultural Water Management.2004,67:185-199.
[42]Richard G.Allen,M.Tasumi,Anthony Morse,etc.A Landsat-based energy balance and evapotranspiration model in Western US water rights regulation and planning.Irrigation and Drainage Systems.2005,19:251-268.
[43]翁笃鸣,高歌.利用卫星资料试作青藏高原地表净辐射场的气候反演.气象科学.2001,21(2):162-168.
[44]黄妙芬.地表通量研究进展.干旱区地理.2003.26(2):159-165.
[45]Revised Landsat 5 TM Radiometric Calibration Procedures and Post-Calibration Dynamic Ranges.来自网上.
[46]黄妙芬,刘素红,朱启疆.应用遥感方法估算区域蒸散量的制约因子分析.干旱区地理.2004.27(1):100-105.
[47]王仁忠,高琼,等.松嫩草原羊草群落水分生态的研究.草业学报.1996,16(1):33-39.
[48]杨劼,高清竹,李国强,等.皇甫川流域主要人工灌木水分生态的研究.自然资源学报.2002,17(1):87-94.
[49]杨劼,宋炳煜,朴顺姬,等.皇甫川丘陵沟壑区小流域生态用水实验研究.自然资源学报.2003,18(5):513-520.
[50]杨劼,高清竹,李国强,等.皇甫川流域几种主要植物水分生态特征.生态学报.2004,24(11):2387-2394.
[51]贺康宁,田阳,张光灿.刺槐日蒸腾过程的Penman-Monteith方程模拟.生态学报.2003,23(2):251-258.
[52]范爱武,刘伟,王崇琦.环境因子对土壤水分蒸散的影响.太阳能学报.2004,25(1):1-5.
[53]刘胜,贺康宁.基于Penman-Monteith模型的林木日蒸腾模拟.西北林学院学报.2006,21(3):15-20.
[54]卢振民.农田蒸散计算中边界层阻力的确定.生态学杂志.1988,7(4):59-61.
[55]杨树栋,王天铎.气孔阻力上边界层阻力的进一步计算.植物生理学报.1988,14(1):9-15.
[56]陈镜明.现用遥感蒸散模式中的一个重要缺点及改进.科学通报.1988.(6):454-457.
[57]谢贤群.遥感瞬时作物表面温度估算农田全日蒸散总量.环境遥感.1991.6(4):253-260.
[58]黄永梅.黄土丘陵沟壑区小流域水分平衡的生态学研究--以纸坊沟为例.北京师范大学博士学位论文.2003.
[59]Gao Q,Zhao P,Zeng X,et al.A model of stomatal conductance to quantify the relationship between leaf transpiration,microclimate and soil water stress.Plant Cell Envir.2002,25:1373-1381.
[60]许迪.灌溉水文学尺度转换问题研究综述.水利学报.2006,37(2):141-149.
[61]吕一河,傅伯杰.生态学中的尺度及尺度转换方法.生态学报.2001,21(12):2096-2105.
[62]赵文武,傅伯杰,陈利顶.尺度推绎研究中的几点基本问题.2002,17(6):905-911.
[63]张彤,蔡永立.谈生态学研究中的尺度问题.生态科学.2004,23(2):175-178.
[64]J.Wu,K.B.Jones,H.Li,etc.Scaling and Uncertainty Analysis in Ecology:Methods and Applications.Netherlands.2006.
[65]张娜.生态学中的尺度问题--尺度上推.生态学报.2007,27(10):4252-4266.
[66]张娜.生态学中的尺度问题:内涵与分析方法.生态学报.2006.26(7):2340-2355.
[67]金争平,史培军,侯福昌,等.黄河皇甫川流域土壤侵蚀系统模型和治理模式.北京:海洋出版社.1992.
[68]金争平,苗宗义,王正文,等.水土保持与土地资源和环境--以黄土高原准格尔试验区为例.土壤侵蚀与水土保持学报.1999,5(5):1-6.
[69]苗宗义.黄土高原综合治理皇甫川流域水土流失综合治理农林牧全面发展试验研究文集.北京:中国农业科技出版社.1992.
[70]宋炳煜,杨劼.关于生态用水研究的讨论.自然资源学报.2003,18(5):617-625.
[71]高清竹,杨劫,宋炳煜,等.黄河中游砒砂岩地区长川流域生态用水分析.自然资源学报.2004,19(4):499-507.
[72]林平,李吉跃,马达.北京山区油松林蒸腾耗水特性研究.北京林业大学学报.2006,28(1):47-50.
[73]邱扬,傅伯杰,王军,等.黄土丘陵小流域土壤水分空间预测的统计模型.2001,20(6):739-751.
[74]张文彤.SPSS 11统计分析教程(高级篇).北京希望电子出版社.2002.
[75]乐通潮,张万昌.双参数月水量平衡模型在汉江流域上游的应用.资源科学.2004,26(6):97-103.
[76]吴军,张万昌.基于径流模拟的分布式水文模型参数的空间相应研究.水土保持研究.2007,14(5):1-6.
[77]郭孟霞,毕华兴,刘鑫,等.树木蒸腾耗水研究进展.中国水土保持科学.2006,4(4):114-12.
[78]刘静,王连喜,马力文等.宁夏南部山区小麦干旱监测与灾损评估模型研究.中国生态农业学报.2003.11(4):143-147.
[79]王黎明.区域蒸散与土地利用覆盖变化的关系探讨.吉林大学博士学位论文.2005.
[80]Nouvellon Y,Rambal S,Lo Seen D,etc.Modeling of daily fluxes of water and carbon from shortgrass steppes.Agric.For.Meteorol.2000,100:137-153.
[81]许红梅,贾海坤,黄永梅.黄土丘陵沟壑区小流域植被净第一性生产力模型.生态学报.2005.25(5):1064-1074.
[82]刘志红,刘文兆,李锐.基于3S技术的区域蒸散研究进展.中国水土保持科学.2006,4(3):117-122.
[83]吕厚荃,于贵瑞.几种实际蒸散计算方法在土壤水分模拟中的应用.资源科学.2001,23(6):85-90.
[84]莫兴国,林忠辉,刘苏峡.基于Penman-Monteith公式的双源模型的改进.水利学报.2000.5:6-11.
[85]莫兴国.冠层表面阻力与环境因子关系模型及其在蒸散估算中的应用.地理研究.1997,16(2):82-88.
[86]包铁军.皇甫川流域植被生态用水分析.内蒙古大学硕士学位论文.2005.
[87]许红梅.黄土丘陵沟壑区小流域植被净第一性生产过程模拟研究.北京师范大学博士学位论文.2003.
[88]张兆明,何国金,肖荣波等.利用TM6数据反演陆地表面温度新算法研究.遥感技术与应用.2005.20(6):547-550.
[89]梅安新,等.遥感导论.高等教育出版社.2001.
[90]马耀明,王介民,Massimo Menenti,等.HEIFE非均匀陆面上区域能量平衡研究.气候与环境研究.1997,2(3):293-301.
[91]马耀明,刘东升,苏中波等.卫星遥感藏北高原非均匀陆表地表特征参数和植被参数.大气科学.2004,28(1):23-31.
[92]孟宪红,吕世华,陈世强等.金塔绿洲地表特征参数遥感反演研究.高原气象.2005.24(4):509-515.
[93]孟宪红,吕世华,张宇等.使用LANDSAT-5 TM数据反演金塔地表温度.高原气象,2005,24(5):721-726.
[94]Gyanesh Chander,Brian Markham.Revised Landsat 5 TM Radiometric Calibration Procedures and Post-Calibration Dynamic Ranges[J].Geoscience and Remote sensing.2003,41(11):2674-2677.
[95]张长春,王晓燕,崔亚莉.黄河三角洲地表特征参数的遥感研究.水文地质工程地质.2005.(2):71-75.
[96]Enric Valor,Vicente Caselles.Mapping Land Surface Emissivity from NDVI:Application to European,African,and South American Areas.REMOTE SENS.ENVIRON.1996,57:167-184.
[97]查书平.基于RS与GIS的长江三角洲蒸散量研究.南京气象学院硕士学位论文.2004.
[98]覃志豪,ZhangMinghua,Arnon Karnieli等.用陆地卫星TM6数据演算地表温度的单窗算法.地理学报.2001.56(4):456-466.
[99]马耀明,刘东升,王介民等.卫星遥感敦煌地区地表特征参数研究.高原气象.2003,22(6):531-536.
[100]徐玉貌,刘红年,徐桂玉.大气科学概论.南京大学出版社.2000.
[101]马耀明,王介民.卫星遥感结合地面观测估算非均匀地表区域能量通量.气象学报.1999,57(2):180-189.
[102]黄妙芬,邢旭峰,朱启疆等.定量遥感地表净辐射通量所需大气下行长波辐射估算模型改进.地理研究.2005.24(5):757-766.
[103]潘志强,刘高焕.黄河三角洲蒸散的遥感研究.地球信息科学.2003.(3):91-96.
[104]郭建茂,王连喜,郑有飞,等.宁夏南部区域蒸发(散)量遥感估算方法.南京气象学院学 报.2004.27(3):302-309.
[105]郭晓寅.黑河流域蒸散分布的遥感研究[J].自然科学进展.2005,15(10):1266-1270.
[106]徐涵秋.利用改进的归一化差异水体指数(MNDWI)提取水体信息的研究.遥感学报.2005.9(5):589-595.
[107]李玉霖,崔建垣,张铜会.参考作物蒸散量计算方法的比较研究.中国沙漠.2002.22(4):372-376.
[108]V.Magliulo,R.d'Andria,G.Rana.Use of the modified atmometer to estimate reference evapotranspiration in Mediterranean environments.Agricultural Water Management.2003,63:1-14.
[109]韩淑敏,程一松,胡春胜.太行山山前平原作物系数与降水年型关系探讨.干旱地区农业研究.2005.23(5):152-158.
[110]GAO Ge,CHEN Deliang,REN Guoyu,et al.Spatial and temporal variations and controlling factors of potential evapotranspiration in China:1956-2000.J Geographical Sciences.2006,16(1 ):3-12.
[111]刘强,何岩,崔保山.洮儿河流域土地利用变化对地表蒸散量的影响.资源科学.2007,29(4):121-126.
[112]周金龙,董新光,陈文娟等.应用彭曼-蒙特斯公式计算天山北坡平原区水面蒸发量.新疆农业大学学报.2002.25(4):35-38.
[113]李玉霖,崔建垣,张铜会.奈曼地区灌溉麦田蒸散量及作物系数的确定.应用生态学报.2003.14(6):930-934.
[114]岳天祥,刘纪远.生态地理建模中的多尺度问题.第四纪研究.2003,23(3):256-261.
[115]刘昌明 等.西北地区水资源配置生态环境建设和可持续发展战略研究(生态环境卷).科学出版社.2004.
[116]谭一波,赵仲辉.叶面积指数的主要测定方法.林业调查规划.2008,33(3):45-48.
[117]杜屿.水库湖泊水面蒸发的分析计算.海洋湖沼通报.1986,(3):25-32.
[118]金争平 等.砒砂岩区水土保持与农牧业发展研究.郑州:黄河水利出版社.2003.