基于TSEB平行模型的黄土丘陵沟壑区蒸散发遥感估算

复杂地形条件下和干旱半干旱植被稀疏条件下的蒸散发遥感估算一直是蒸散发区域遥感估算的难点、热点问题。针对黄土丘陵沟壑区地表起伏、覆被不均一、植被稀疏的特征,选择陕甘交界区为研究区,利用Landsat TM资料求取地表特征参数和地表能量平衡各参量,采用TSEB平行模型反演出该区域的瞬时土壤蒸发、植被蒸腾和土壤-植被总蒸散发量,经过尺度转换,得到日蒸散量;并利用附加阻抗法和FAO Penman-Monteith公式计算实际蒸散发,对TSEB平行模型法遥感估算结果进行了间接精度评价,比较验证结果表明TSEB平行模型法估算的蒸散发结果合理,精高较高。     

应用Landsat数据和SEBAL模型反演区域蒸散发及其参数估算

随着遥感技术的进步,人们发展了多种通过遥感计算区域蒸散发的方法。SEBAL模型是通过遥感反演地面蒸散的典型方法,它以陆面能量平衡为基础,物理意义明确,只利用遥感影像和少量的气象数据（风速、气温）就能反演蒸散量。Landsat数据的波谱信息丰富、空间分辨率高,数据源稳定,是通过遥感技术反演蒸散发的理想数据源。如果能合理地估算SEBAL模型中的基本参数,将会获得较高精度的反演结果,能够满足在水文、生态、林业等研究或应用中的需要,对区域水资源的管理与利用具有重要意义。从SEBAL模型的基本原理出发,分析了利用SEBAL模型采用Landsat的TM/ETM+数据反演区域蒸散发的基本过程,针对TM/ETM+数据特点对模型所需要的基本参数进行估算求解,为SEBAL模型在蒸散量反演中的广泛应用提供了一定的指导。     

TSEB模型在复杂下垫面下模拟结果比较研究

地表蒸散发对干旱半干旱地区水文过程模拟以及水文平衡有重要影响,复杂地表更是对地表蒸散发模拟提出了新的挑战。利用TSEB(Two-Source Energy Balance)模型,分别以Landsat、MODIS卫星数据为驱动数据,得到黑河下游绿洲地表蒸散发时空分布格局,并利用大孔径闪烁仪和涡动相关仪的观测数据对模拟结果分别在公里级和百米级尺度进行验证,研究结果表明：在大孔径闪烁仪观测的公里级尺度下,基于Landsat数据和MODIS数据驱动的TSEB估算感热通量与大孔径闪烁仪观测数据比较的均方根误差分别为48.47 W/m²、58.57 W/m²。基于涡动相关仪观测百米级尺度,Landsat数据驱动的TSEB估算感热通量与涡动相关仪观测数据的均方根误差为89.37 W/m²。因此,得出以中高分辨率卫星遥感数据作为驱动数据模型模拟效果更好,LAS观测公里级尺度数据能部分解决遥感地表蒸散发验证空间不匹配问题。     

大沽河流域蒸散量时空变化

鉴于基于点源的蒸散估算方法逐渐被基于遥感数据的以SEBAL(Surface Energy Balance Algorithm for Land)为主的蒸散估算模型方法所取代,但在不同地貌和气候特征的区域该模型的适用性尚待得到证实,该文利用SEBAL模型基于MODIS数据产品和野外实测气象数据对大沽河流域的日蒸散量进行了估算,并与气象站蒸散量实测值进行对比验证。结果表明,SEBAL模型反演结果与实测值之间具有良好的一致性。在此基础上将日蒸散量结果推算至月蒸散量,并分析了蒸散量的年内变化趋势和特征,发现大沽河流域年内蒸散量的变化呈单峰趋势,季节性变化特征明显:夏季秋季春季冬季。最后,结合大沽河流域土地利用现状,比较分析了不同土地利用类型蒸散量的差异,结果表明水体蒸散量最大,林地和耕地次之,城镇及建筑用地蒸散量最小。     

基于TESEBS模型估算高原地区地表蒸散发

为检验TESEBS(Topographical Enhanced Surface Energy Balance System)模型在高原地区的适用性,利用2014年高原9个站点的实测资料对TESEBS模型进行适用性检验,鉴于模型估算的感热通量偏差较大,提出利用地表温度—植被指数(LST-NDVI)特征空间法来确定蒸散发率,并将模型估算的卫星过境时刻瞬时蒸散发与实测值进行比较。结果表明:TESEBS模型估算高原不同下垫面的蒸散发与实测值之间的偏差较大;利用LST-NDVI特征空间法确定蒸散发率能很好地改善模型对蒸散发的估算精度,相关系数从0.65提高至0.83,均方根误差从144减小至80 W·m~(-2),相对误差从67%减小至39%。特征空间法引入后,TESEBS模型估算的地表蒸散发明显小于原模型的估算结果,且模型给出的研究区地表蒸散发分布特征与植被指数NDVI的分布特征相一致。     

SEBAL模型在干旱区区域蒸散发估算中的应用

蒸散发是水量平衡和能量平衡的重要环节,传统的计算方法只能以点为基础进行计算。为排除蒸散发空间变异特性的影响,在遥感技术的基础上,引入了基于地表能量平衡原理的SEBAL模型,对新疆焉耆盆地的日蒸散发情况进行了计算模拟,获取了相关地面特征参数及日蒸散量,并根据盆地内具有大面积湖泊这一实地情况对模型进行了改进。     

SEBAL模型及其在区域蒸散研究中的应用

蒸散是地表能量平衡与水量平衡的重要参数,遥感技术的发展促进了区域蒸散的研究。基于地表能量平衡方程,SEBAL模型利用遥感影像的可见光、近红外与热红外波段及少量气象数据可计算出区域的日蒸散量,是一个物理概念较为清楚的模型。采用Landsat7 ETM+数据利用SEBAL模型对河北省栾城县进行了遥感蒸散研究,计算获得相关地面特征参数与日蒸散量,模拟结果较为合理。     

基于SEBS模型的藏北那曲蒸散量研究

SEBS模型为研究高原非均匀地表区域蒸散量估算提供了一种新的方法,为高原气象台站稀少地区蒸散量变化研究提供一定的参考依据。应用SEBS模型,利用MODIS遥感数据反演所需的地表物理参数(如反照率、比辐射率、地表温度和植被覆盖度等),再结合气象站地面观测数据,包括温度、相对湿度、风速、气压等,对藏北那曲地表能量通量和蒸散量进行估算;最后分析了蒸散量与气象因子、NDVI之间的关系。结果表明:2010年藏北那曲蒸散量呈春夏季高,秋冬季低的变化趋势,蒸散量较大区域为研究区南部、东北部和区域内的水体;中部和西北部地区蒸散量较小。气温和地表温度对蒸散量的影响较明显,随着气温和地表温度的升高蒸散量不断增大,NDVI对蒸散量也有一定的影响。所以,SEBS模型在估算高原地区蒸散量方面具有一定的精度,可以满足区域日蒸散发估算的需要。     

典型黑土区作物根层土壤含水量遥感估算及影响因素研究

漫川漫岗黑土区作物根层土壤含水量受植被覆盖、地形、土壤温度、降雨等多因素的影响，是农业生产和农田管理的关键要素。以友谊农场两个不同坡度的典型耕地地块（平耕地与等高种植坡耕地）为研究对象，利用Landsat 8遥感数据结合气象数据等驱动SEBAL(Surface Energy Balance Algorithm for Land)模型估算根层土壤含水量，利用地面实测数据对估算结果展开验证。在此基础上分析根层土壤含水量空间分布的影响因素。结果表明：(1)SEBAL模型估算的根层土壤含水量6月27日决定系数R2为0.85,7月13日决定系数R2为0.68，且7月13日根层土壤含水量明显高于6月27日；平耕地6月27日决定系数R2为0.65,7月13日为0.84；等高种植坡耕地6月27日决定系数为0.64,7月13日为0.50。(2)地块不同导致作物根层土壤含水量影响因素也不同，平耕地主要影响因素为坡度、植被覆盖度和土壤温度；等高种植坡耕地为高程和土壤温度。使用SEBAL模型可以较为快速准确地估算根层土壤含水量，研究结果对于黑土区耕地的水分管理、农业灌溉及水分运移研究具有重要意义。     

基于SiB2模型的土壤水分降尺度指标的适用性研究

土壤水分是地表过程的核心变量之一,强烈影响着陆表—植被—大气间的能量和水分交换。当前基于星载被动微波遥感的土壤水分产品的空间分辨率普遍较粗(25~40km),无法满足流域尺度水文气象、生态水文模拟及水资源管理等研究和应用的需求,而土壤水分降尺度是目前较为可行的解决方案之一。通过对不同降尺度指标的研究,分析确定每种降尺度指标的适用条件,为土壤水分的降尺度研究奠定基础。利用2013年5月1日~9月30日黑河中游人工绿洲试验区大满超级站的气象数据驱动SiB2模型,分别模拟了土壤水分、土壤表层温度、植被冠层温度以及地表蒸散发、土壤蒸发等变量,利用Penman-Monteith公式计算了地表潜在蒸散发;利用SiB2模拟结果与P-M公式计算结果估算获得常用的土壤水分降尺度指标:表观热惯量(ATI)、土壤蒸发(E)、土壤蒸发/实际蒸散发(E/ETa)、蒸发比(EF)、实际蒸发比(AEF)。通过对降尺度指标与土壤水分之间相关性分析可知,在植被的整个生长季,5种指标与土壤水分之间都具有较好的相关性。其中ATI、E、E/ETa以及EF这4种指标与土壤水分之间的相关性都随着土壤深度的增加而逐渐减弱;而AEF与植被根区土壤水分的相关性最好,更能反映根区土壤水分的动态变化。从可决系数来看,各降尺度指标与土壤水分的相关性排序如下:2cm:E/ETaEFEAEFATI;10cm:AEFEFE/ETaEATI;80cm:EFAEFE/ETaEATI。     

An intercomparison of the Surface Energy Balance Algorithm for Land (SEBAL) and the Two-Source Energy Balance (TSEB) modeling schemes

An intercomparison of output from two models estimating spatially distributed surface energy fluxes from remotely sensed imagery is conducted. A major difference between the two models is whether the soil and vegetation components of the scene are treated separately (Two-Source Energy Balance; TSEB approach) or as a lumped composite (one-source approach; Surface Energy Balance Algorithm for Land; SEBAL) in the parameterization of radiative and turbulent exchanges with the overlying air. Comparisons are performed using data from two largescale field experiments covering sub-humid grassland (Southern Great Plains '97) and semi-arid rangeland (Monsoon '90) having very different landscape properties. In general, there was reasonable agreement between flux output from both models versus a handful of flux tower observations. However, spatial intercomparisons of model output over the full modeling domains yielded relatively large discrepancies (on the order of 100 W m^− 2) in sensible heat flux (H) that are related to land cover. In particular, bare soil and sparsely vegetated areas yielded the largest discrepancies, with TSEB fluxes being in better agreement with tower observations. Modifications to SEBAL inputs that reduced discrepancies with TSEB and observations for bare soil and shrub classes tended to increase differences for other land cover classes. In particular, improvements to SEBAL inputs of surface roughness for momentum tended to exacerbate errors with respect to observed fluxes. These results suggest that some of the simplifying assumptions in SEBAL may not be strictly applicable over the wide range in conditions present within these landscapes. An analysis of TSEB and SEBAL sensitivity to uncertainties in primary inputs indicated that errors in surface temperature or surface-air temperature differences had the greatest impact on H estimates. Inputs of secondary importance were fractional vegetation cover for TSEB, while for SEBAL, the selection of pixels representing wet and dry moisture end-member conditions significantly influenced flux predictions. The models were also run using input fields derived from both local and remote data sources, to test performance under conditions of varying ancillary data availability. In this case, both models performed similarly under both constraints.     

Retrieval of Component Temperatures based on Landsat-7 ETM+ Remote Sensing Data

Land surface temperature plays an important role in drought monitoring and Simulation of surface heat flux.In arid and semi\|arid regions,the Two\|Source Energy Balance model (TSEB) is commonly used to calculate the heat flux of the earth’s surface.Taking the typical irrigated area of the middle reaches of Heihe as the research area,the four Landsat\|7 ETM+ remote sensing images are selected.The soil surface temperature and canopy temperature were retrieved by combining vegetation index with TSEB model.The decomposition algorithm of soil surface temperature and vegetation canopy temperature is mainly discussed.The results showed that soil surface temperature and vegetation canopy temperature had good temporal and spatial consistency.The inversion accuracy of soil surface temperature and vegetation canopy temperature is indirectly verified by surface net radiation and surface heat flux.The calculated values of surface net radiation and surface heat flux correlate well with the observed values,and the correlation coefficient is greater than 0.92.The linear regression analysis of surface net radiation and surface heat flux shows that the fitting accuracy is high.The soil surface temperature and canopy temperature obtained by surface temperature decomposition are feasible for monitoring drought in typical areas and simulating surface heat flux.     

一种改进的矩匹配方法在CMODIS数据条带去除中的应用

由于传感器之间对接受的地物辐射信号的响应特性不同,导致CMODIS数据中的许多波段含有大量的条带。这些噪声严重影响了CMODIS数据的解译和信息提取。介绍了几种常用在TM、MSS、SPOT等多传感器光谱仪中条带去除方法,提出了一种改进矩匹配方法用于CMODIS数据中的条带去除,并比较了这种方法和其它几种常用方法对几何纠正前非均匀地物分布的CMODIS数据的去条带噪声结果。结果表明这种新方法要优于以上提到的几种常用方法,具有很好的去条带噪声效果,同时保持图像原有的的信息。这种方法在其它多传感器遥感图像的条带噪声去除中也有很强的适用性。     

流域尺度ET的遥感反演

利用多光谱卫星遥感可以反演水文气象模式所需的一些基本地面参数,进而得到整个流域尺度上的蒸发蒸腾量(ET)的分布图像,对流域水资源的管理提供重要依据。首先简述了当前地面观测计算ET采用的一些较新的技术和方法,然后论述了有关遥感反演ET方法的发展,并着重介绍了近年来国际上应用较好的‘陆面能量平衡方法(SEBAL)’。     

库布齐沙漠典型沙地人工林蒸散对比分析

人工造林使库布齐沙漠的生态快速逆转,深入理解沙地人工林的蒸散特征,对改善现有人工林的经营管理和开展人工林建设具有重要意义。利用Landsat 8、MODIS产品、气象观测资料等数据,通过基于能量平衡的SEBAL模型和MODIS MOD16蒸散产品获取库布齐沙漠典型林场2014年7月14日、7月30日、8月15日、9月7日的地表蒸散量,并采用波文比系统相关数据对估算的结果进行验证。得到以下结果：与波文比观测系统的蒸散相比,SEBAL模型反演的蒸散整体偏大,日蒸散分别多1.06、1.71、1.19、2.65 mm,两者的决定系数达0.827;MODIS MOD16产品的蒸散整体偏小,日蒸散分别少0.13、0.32、0.18、0.95 mm,两者的决定系数达0.823;在沙漠人工林斑块区域且植被类型较单一的情况下,MODIS MOD16的蒸散结果要好于SEBAL模型反演的蒸散,两者在空间分布上基本保持一致;林场蒸散较大的区域主要分布在中部和南部,而北部区域蒸散相对较小。研究结果可为其他沙地斑块人工林获取蒸散提供参考。     

Down-scaling of SEBAL derived evapotranspiration maps from MODIS (250 m) to Landsat (30 m) scales

problem with high spatial resolution satellite images from Landsat 7 is that imagery is not available very often (i.e. every 16 days or longer) and the coverage area is relatively small (swath width 185 km), while images of lower spatial resolution from the Moderate Resolution Imaging Spectroradiometer (MODIS) are available daily and one image covers a relatively large area (swath width 2330 km). This article considers the feasibility of applying various down-scaling methods to combine MODIS and Landsat imagery in order to obtain both high temporal and high spatial resolutions. The Surface Energy Balance Algorithm for Land (SEBAL) was used to derive daily evapotranspiration (ET) distributions from Landsat 7 and MODIS images. Two down-scaling procedures were evaluated: input down-scaling and output down-scaling. In each down-scaling scheme, disaggregated imagery was obtained by two different processes: subtraction and regression. The primary objective of this study was to investigate the effect of the different down-scaling schemes on the spatial distribution of SEBAL-derived ET. We found that all of the four proposed down-scaling methodologies can generate reasonable spatial patterns of the disaggregated ET map. The results of this study show that output down-scaling with regression between images is the most preferred scheme and input down-scaling with subtraction is the least preferred scheme.     

An intercomparison of three remote sensing-based energy balance models using Large Aperture Scintillometer measurements over a wheat-corn production region

This paper compares three remote sensing-based models for estimating evapotranspiration (ET), namely the Surface Energy Balance System (SEBS), the Two-Source Energy Balance (TSEB) model, and the surface temperature-vegetation index Triangle (TVT). The models used as input MODIS/TERRA products and ground measurements collected during the wheat and corn growth period in a subhumid climate at a measurement station in Yucheng, China. MODIS land surface temperature (LST) and leaf area index (LAI) products, corrected using ground-truth observations, were used in the three models. The TSEB model output of sensible (H) and latent (LE) heat fluxes were in good agreement with Large Aperture Scintillometer (LAS)-measured H and LE derived by residual (RMSD < 45 W/m²). Reasonable agreement was also obtained with the SEBS model output yielding RMSD for H of ~ 40 W/m² and LE ~ 55 W/m². However, the TVT model output resulted in poor agreement with the LAS-estimated H and LE with RMSD-values > 110 W/m². Using the uncorrected MODIS LST and LAI products resulted in a deterioration of the agreement in H and LE with LAS-estimated values for both the TSEB and SEBS models, whereas TVT performance improved marginally. These results indicate that the TSEB model yielded the closest agreement with the LAS-estimated fluxes using either the corrected or uncorrected MODIS inputs (LST and LAI). The SEBS model also computed reasonable H and LE values but was significantly more sensitive to errors in MODIS LST and LAI inputs than the TSEB model. In the TVT model, output of H and LE was unacceptable in either scenario of MODIS input which was attributable to errors in selection of the dry edge. With the TVT method, accurate determination of the dry edge end member is critical in regional ET estimation, but for humid and subhumid regions this end member may often be quite difficult to identify or encompass within a satellite scene.     

Impact and consequences of evapotranspiration changes on water resources availability in the arid Zhangye Basin,China

Evapotranspiration (ET) plays an important role in the hydrological cycle and it is essential to estimate ET accurately for the evaluation of available water resources. This is most important in arid and semi‐arid regions. In this paper, the long‐term changes in daily ET in the semi‐arid Zhangye Basin in northwest China and its impact factors were studied. The spatial distribution of ET was assessed by using the Surface Energy Balance System (SEBS). Cloud‐free National Oceanic and Atmospheric Administration Advanced (NOAA) Very High Resolution Radiometer (AVHRR) September images over the Zhangye Basin from 1990 to 2004 were used in combination with SEBS to estimate ET at a spatial resolution of 1.1 km. This daily ET was converted to a monthly ET (for September) using daily pan evaporation values from a meteorological station in the study area. Spatial aggregation of all pixels yielded the total monthly ET for the whole study area. Subsequently, the monthly ET was extrapolated to annual ET values using the pan evaporation data. The results were validated with ground‐based measurements on the water balance for the whole Zhangye Basin. The annual ET increased gradually from 23.7×10⁸ m³ in 1990 to 26.9×10⁸ m³ in 2004 for the Zhangye Basin. The main cause appeared to be change in vegetation.     

Using ASTER satellite data to calculate riparian evapotranspiration in the Middle Rio Grande,New Mexico

Riparian evapotranspiration (ET) in the Rio Grande Basin in New Mexico, USA is a major component of the hydrological system. Over a period of several years, ET has been measured in selected locations of dense saltcedar and cottonwood vegetation. Riparian vegetation varies in density, species and soil moisture availability, and to obtain accurate measurements, multiple sampling points are needed, making the process costly and impractical. An alternative solution involves using remotely sensed data to estimate ET over large areas. In this study, daily ET values were measured using eddy covariance flux towers installed in areas of saltcedar and cottonwood vegetation. At these sites, remotely sensed satellite data from the National Aeronautics and Space Administration (NASA) Terra Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used to calculate the albedo, normalized difference vegetation index (NDVI) and surface temperature. A surface energy balance model was used to calculate ET values from the ASTER data, which were available for 7 days in the year. Comparison between the daily ET values of saltcedar and cottonwood measured from the flux towers and calculated from remote sensing resulted in a mean square error (MSE) of 0.16 and 0.37 mm day^?1, respectively. The regional map of ET generated from the remote sensing data demonstrated considerable variation in ET, ranging from 0 to 9.8 mm day^?1, with a mean of 5.5 mm day^?1 and standard deviation of 1.85 mm day^?1 (n = 427481 pixels) excluding open water. This was due to variations in plant variety and density, soil type and moisture availability, and the depth to water table.