水文循环模拟中蒸散发估算方法综述

为选取基于水文循环估算蒸散发方法提供依据, 首先对常用水文模型中蒸散发估算方法进行回顾, 根据其物理机理的强弱性, 将水文模型中蒸散估算方法分为整体折算法和分类汇总法。当前水文模型中整体折算法占较大比重, 它们之间的差异有两点:一是潜在蒸散发估算方法不同;二是土壤干燥度折算函数不同;研究表明:由于水文模型存在不确定性及Penman-Monteith 方法具有较高资料要求, 致使模拟中使用该方法与使用其它简化经验公式相似或更差的水文循环模拟效果。所以对于不同水文模型, 如何选取与之复杂程度相兼容的潜在蒸散发估算方程和土壤干燥度折算函数来降低模型的不确定性需进一步讨论。在此基础上, 预估基于水文循环估算蒸散发方法朝着复杂机理化和简单实用化两个方向发展。     

区域尺度蒸散发遥感估算——反演与数据同化研究进展

遥感技术近年来在估算区域尺度蒸散发中应用广泛。不同方法在驱动数据、模型机理和适用范围往往存在很大差别。鉴于此,阐述了基于传统方法空间尺度扩展的遥感模型,经验统计公式,特征空间法,单源、双源垂向能量平衡余项法等几类的遥感蒸散发反演方法,简要介绍了三温模型、非参数化模型、半经验模型、集成模型等常用模型。同时,分析了遥感数据同化实现连续估算区域蒸散发的主要思路,综述了基于能量平衡和基于复杂过程模型的数据同化的原理、方法演进及常用同化算法等。最后,探讨了各类区域蒸散发遥感方法的优劣、展望了模型机理完善、不确定性研究、结果验证等与蒸散发直接反演和数据同化相关的研究方向。     

洛河流域蒸散发遥感反演及其与各参数的相关性分析

利用ETM数据和地表热量平衡模型估算洛河流域的蒸散发量,并结合地面实测资料进行检验,然后综合分析蒸散发量与土地利用/覆被、地表参数、地形参数的关系。研究发现,不同下垫面的蒸散发能力有一定的差别,其中水体和林地的日蒸散发量最大;蒸散发量与NDVI、植被覆盖度以及高程等参数呈线性相关,而与地表温度呈指数相关,与叶面积指数呈对数相关。     

以地下水位估算的荒漠河岸胡杨(Populus euphratica)林生态系统地下水蒸散发北大核心CSCD

基于2014年和2020年地下水位监测数据,估算了黑河下游额济纳绿洲七道桥胡杨(Populus euphratica)林生态系统生长季旺盛期的地下水蒸散发(ET_(g)),并与从涡度观测系统测定的蒸散发(ET)作比较,同时分析了不同模型的估算结果及其主要影响因素。结果表明:(1)基于昼夜水位波动法(White、Hays和Soylu方法)估算的ET_(g)均与生态系统ET变化趋势一致且显著相关,经过对比分析得出,Hays方法精度最高,推荐使用该方法计算ET_(g)。(2)地下水位、太阳辐射、气温和饱和水汽压差是影响ET_(g)的主要因子,风速对ET_(g)无显著影响。(3)生长季,ET_(g)占生态系统ET的比例随干旱时间的增大而增大。     

区域土壤植被系统蒸散发二源遥感估算

针对干旱半干旱复杂地形区地表起伏、覆被不均一、植被稀疏的特征,论文对N'95二源遥感模型中地表净辐射计算方案以及地表反照率、零平面位移、动量粗糙长度、热量粗糙长度、动量和热量的稳定度校正项、土壤表面的空气动力学阻抗等算法有针对性地进行了修改.利用修改后的N'95模型,选择位于黄土高原的地表起伏大,植被稀疏的陕甘宁交界区为研究区,计算了研究区的土壤蒸发、植被蒸腾和土壤一植被总蒸散发;并利用附加阻抗法计算实际蒸散发的方法对N'95二源模型法遥感估算结果进行了间接精度评价,比较验证表明N'95二源模型法估算的蒸散发结果合理,精高较高.     

基于SWH模型的青藏高原高寒草甸蒸散发及其组分变化分析

基于Shuttleworth-Wallace Hu（SWH）双源蒸散模型对青藏高原那曲、纳木错、藏东南站蒸散发进行估算,在结果验证良好基础上,对青藏高原蒸散发变化特征及各站主要影响因素进行了分析。结果表明：SWH模型在青藏高原3个草甸站适用性良好;年蒸散发介于388~732 mm之间,年内分布呈先增大后减小特征;3站蒸散发组分差异较大,那曲站和纳木错站土壤蒸发对蒸散总量的贡献分别为53%和56%,藏东南站蒸散发则几乎全部由植被蒸腾贡献,占比高达95%;植被叶面积指数为3站蒸散发最主要的影响因素,饱和水汽压差对藏东南站蒸散发影响也较大。研究结果可对青藏高原蒸散发及其组分时空格局与水循环过程研究提供科学依据。     

一种基于植被指数-地表温度特征空间的蒸散指数

利用遥感获取的植被指数和地表温度信息,进行地表能量和水分平衡过程研究是目前陆表过程研究的前沿。根据地表能量和水分平衡原理,对地表温度(Ts)、植被指数(VI),地表蒸散发(ET)之间的空间关系进行了分析,并基于假设条件,构建了温度植被蒸散指数(TVETI)。为验证TVETI表征地表蒸散的能力,利用环境卫星数据和SEBAL模型,对SEBAL模型中各能量通量构建的蒸散指数与TVETI进行线性回归分析,从2012年4~9月6个不同日期的确定性系数分别为:0.838、0.935、0.912、0.921、0.926、0.825, TVETI能很好的表征地表蒸散能力。通过对SEBAL模型估算的ET和TVETI估算的ET进行交叉验证发现,两者大小一致性显著, TVETI可以实现区域尺度地表蒸散发的快速估算。     

基于水文模型的蒸散发数据同化研究进展

本文系统综述了基于水文模型的蒸散发数据同化研究,阐述了蒸散发作为非状态变量构建数据同化演算关系的难点和瓶颈,并系统分析了利用当前各种通用水文模型进行蒸散发同化的可行性.基于此,尝试提出了一种易于操作且具有水循环物理机制的蒸散发同化新方案,该方案利用具有蒸散发—土壤湿度非线性时间响应关系的分布式时变增益模型(DTVGM),并进一步完善DTVGM蒸散发机理,构建基于DTVGM水文模型的蒸散发数据同化系统.该新方案将为区域蒸散发精确模拟提供新的思路和借鉴.     

2003—2017年植被变化对全球陆面蒸散发的影响

蒸散发是陆面水循环的关键环节和过程,是研究水循环对人类活动和气候变化响应的关键要素。过去十几年,全球下垫面的植被变化剧烈,但如何影响全球陆面蒸散发仍未得到清晰的揭示。本文采用500 m分辨率MODIS数据驱动PML-V2模型,定量解析了2003—2017年植被变化对全球陆面蒸散发的影响。结果显示：在全球尺度上,植被变绿使得全球蒸散发呈现显著的增加趋势,使陆地水循环加快;区域尺度上,植被变化对蒸散发的影响则存在明显的地带性和非地带性特征,如在北美洲中北部、欧洲、中国东部、非洲南部和澳大利亚东北部等地区,蒸散发总量的增加主要是由植被蒸腾增加而引起的。分析不同植被功能类型区的贡献显示,下垫面变化对灌木和耕地影响尤为明显,并在2012年以后呈现增强趋势;这2个植被类型区的全球年总蒸散发累积增加量为0.41×10³ km³ a^-1,约为黄河流域多年平均径流量的8倍。该研究结果有助于进一步加强关于下垫面变化对陆地水循环的影响及其可能带来的局部气候变化的认识。     

SEBS模型在黑河流域中游的应用及参数敏感性分析

干旱区的蒸散发（ET）研究对干旱区的水资源管理和生态系统恢复具有重要意义。本文基于SEBS模型和参考作物蒸散量估算2009年3—9月黑河流域中游地区蒸散发。使用涡度相关蒸散数据验证表明,SEBS模型能够有效估算黑河流域中游的蒸散发。从各月的ET分布状况来看,区域平均ET有着明显的月变化;植被生长季内ET总量空间分布差异大,在23.4~752.6 mm之间,区域平均值为428.7mm。通过对SEBS模型参数敏感性分析发现,SEBS模型对地面温度最为敏感,其次是空气温度,再者是风速和反照率,对NDVI和空气湿度的敏感性最小。     

Budyko方程和单作物系数法在区域蒸散发估算中的耦合及应用

实际蒸散发(ET)是水文循环的关键环节,分布式量化ET是区域水量平衡计算的重要内容。本文基于Budyko水热耦合方程推算单作物系数,在单作物系数和基于遥感方法的叶面积指数(LAI)之间进行统计回归,建立计算LAI的模式,实现Budyko方程进行区域ET估算的空间分辨率提升。洮河流域的范例研究证实了两种方法耦合在复杂地理-生态区间应用的合理性。本文为区域ET的分布式量化研究提供了一种新的思路。     

Study on daily surface evapotranspiration with SEBS in Tibet Autonomous Region简

The estimation of surface evapotranspiration （ET） with satellite dataset is one of the main subjects in the understanding of climate change, disaster monitoring and the circulation of water vapor and energy in Tibet Autonomous Region （TAR）. This research selects satellite images on January 11, April 6, July 31 and October 19 in 2010 as the representative of winter, spring, summer and autumn respectively, estimates the distribution of daily surface ET based on the surface energy balance system （SEBS） along with potential evapotranspiration （PET） and ET derived from Penman-Monteith （P-M） method. The results are obtained as follows. （1） The seasonal distribution of ET and PET basically decreases from the southeast part to the northwest part of TAR. Although ET and PET have similar spatial distributions, there are still some differences to estimate the extreme values especially the maximum value in the middle and southeastern parts of TAR. No matter what kind of methods we adopted, the maximum value of ET and PET always appears in summer, followed by autumn or spring while that in winter is the smallest. （2） In order to better understand the accuracy of SEBS model in the estimation of ET, we compared the ET from SEBS and the ET obtained from P-M method. Results show that the ET from SEBS could estimates the variation trend of actual ET, but it slightly underestimates or overestimates the value of ET as a whole, especially for those areas with thick forest. （3） The spatial distribution of Normalized Difference Vegetation Index （NDVI） exhibits a decreasing trend from the southeast part to the northwest part of TAR which displays remarkable consistency of distributions between ET and vegetation index. ET is well positively related to NDVI, minimum, mean, maximum air temperature and sunshine duration in different seasons while negatively related to precipitation, relative humidity and wind speed in summer.     

基于SEBS模型的西藏地区地表日蒸散量研究（英文）

The estimation of surface evapotranspiration(ET) with satellite dataset is one of the main subjects in the understanding of climate change,disaster monitoring and the circulation of water vapor and energy in Tibet Autonomous Region(TAR).This research selects satellite images on January 11,April 6,July 31 and October 19 in 2010 as the representative of winter,spring,summer and autumn respectively,estimates the distribution of daily surface ET based on the surface energy balance system(SEBS) along with potential evapotranspiration(PET) and ET derived from Penman-Monteith(P-M) method.The results are obtained as follows.(1) The seasonal distribution of ET and PET basically decreases from the southeast part to the northwest part of TAR.Although ET and PET have similar spatial distributions,there are still some differences to estimate the extreme values especially the maximum value in the middle and southeastern parts of TAR.No matter what kind of methods we adopted,the maximum value of ET and PET always appears in summer,followed by autumn or spring while that in winter is the smallest.(2) In order to better understand the accuracy of SEBS model in the estimation of ET,we compared the ET from SEBS and the ET obtained from P-M method.Results show that the ET from SEBS could estimates the variation trend of actual ET,but it slightly underestimates or overestimates the value of ET as a whole,especially for those areas with thick forest.(3) The spatial distribution of Normalized Difference Vegetation Index(NDVI) exhibits a decreasing trend from the southeast part to the northwest part of TAR which displays remarkable consistency of distributions between ET and vegetation index.ET is well positively related to NDVI,minimum,mean,maximum air temperature and sunshine duration in different seasons while negatively related to precipitation,relative humidity and wind speed in summer.     

中国东部南北样带森林生态系统蒸腾与蒸散比值（T/ET）时空变化

植被蒸腾与蒸散的比值（transpiration/evapotranspiration, T/ET）表征了植被蒸腾对生态系统蒸散的贡献率,是准确量化生态系统水分利用效率的关键参数,对研究植被水分运移的生理生态机理以及碳水循环关系具有重要意义。基于站点数据验证PT-JPL模型（Priestly-Taylor Jet Propulsion Laboratory Model）模拟精度,集成遥感数据和气象栅格数据模拟中国东部南北样带森林生态系统2001-2010年T/ET,并分析其时空变化及影响因子。结果表明：① PT-JPL模型适用于中国东部森林生态系统蒸散及其组分模拟,具有较高的稳定性和可靠性;② 中国东部南北样带森林生态系统T/ET空间差异显著,整体呈南部低、北部高,主要由夏季T/ET空间格局主导;样带整体T/ET均值为0.69,2001-2010年呈显著缓慢上升趋势,增幅为0.007/yr（p < 0.01）;③ T/ET季节和年际变异的主控因子不同：温度和EVI是影响T/ET季节变异的关键因子,两者均可解释T/ET季节变异的90%左右（p < 0.01）;而T/ET的年际变异则主要受EVI影响,解释率为53%（p < 0.05）。     

遥感蒸散模型的时间重建方法研究

本文提出的遥感蒸散模型的时间重建方法考虑了逐日蒸散可能的变化情况, 在阻抗- 彭曼单层模型的基础 上, 将图像去云处理与时间重建结合在一起, 先使用SEBS 能量平衡余项模型获得晴好日的地表阻抗信息, 选择了 叶面积指数LAI 作为反映植被表面阻抗的参量, 通过时间序列谐波分析(HANTS)获得逐日逐像元的LAI 信息, 将晴 好日的阻抗信息扩展至待定日, 并使用因子函数表达了极端温湿条件对植被叶面阻抗的限制作用。使用中科院禹 城站2003 年作物季的大型蒸渗仪数据对模型所得逐日蒸散结果进行了验证。在作物生长季, 模型结果相对于实测 结果表现出了良好的相关性(R2≈0.7), 远优于作为对比的蒸发比不变法。受单层模型假设局限, 方法在裸地及稀疏 植被上的结果还存在着较大的误差。     

A review on evapotranspiration data assimilation based on hydrological models

Accurate estimation of evapotranspiration (ET), especially at the regional scale, is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper, a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET, being a non-state variable, to construct data assimilation relationships are elaborated upon, with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this, a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model (DTVGM), and the ET-soil humidity nonlinear time response relationship of this model. Moreover, the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states, and may be referenced for accurate estimation of regional evapotranspiration.     

陇西黄土高原陆面蒸散的遥感研究

该文以陆面能量平衡过程为基础,基于定量遥感的理论,提出了适合半干旱区(陇西黄土高原)的陆面蒸散估算遥感模型(SEBS)。结合该区域的NOAA/AVHRR数据、气象观测数据、土地利用数据和地形高程(DEM)数据,依据定量遥感的理论和技术,计算反照率、陆面温度、植被指数和地表比辐射率四个重要地表特征参数。应用SEBS模型,估算了该区域的陆面蒸散量。结果表明：该研究具有较好的理论和实践意义,为陆面过程、植被生产、生态环境保护与生态重建等研究提供科学依据。     

基于水文模型的蒸散发数据同化研究进展（英文）

Accurate estimation of evapotranspiration(ET),especially at the regional scale,is an extensively investigated topic in the field of water science. The ability to obtain a continuous time series of highly precise ET values is necessary for improving our knowledge of fundamental hydrological processes and for addressing various problems regarding the use of water. This objective can be achieved by means of ET data assimilation based on hydrological modeling. In this paper,a comprehensive review of ET data assimilation based on hydrological modeling is provided. The difficulties and bottlenecks of using ET,being a non-state variable,to construct data assimilation relationships are elaborated upon,with a discussion and analysis of the feasibility of assimilating ET into various hydrological models. Based on this,a new easy-to-operate ET assimilation scheme that includes a water circulation physical mechanism is proposed. The scheme was developed with an improved data assimilation system that uses a distributed time-variant gain model(DTVGM),and the ET-soil humidity nonlinear time response relationship of this model. Moreover,the ET mechanism in the DTVGM was improved to perfect the ET data assimilation system. The new scheme may provide the best spatial and temporal characteristics for hydrological states,and may be referenced for accurate estimation of regional evapotranspiration.     

基于遥感的黄河三角洲蒸散的动态分析

Evapotranspiration (ET) is an important parameter for water resource management. Compared to the traditional ET computation and measurement methods, the ET computation method based on remote sensing has the advantages of quickness, precision, raster mapping and regional scale. SEBAL, an ET computation model using remote sensing method is based on the surface energy balance equation which is a function of net radiance flux, soil heat flux, sensible heat flux and latent heat flux. The former three fluxes can be computed through the parameters retrieved from remote sensing image, then the latent heat flux can be obtained to provide energy for ET. Finally we can obtain the daily ET. In this study SEBAL was applied to compute ET in the Yellow River Delta of China where water resource faces a rigorous situation. Three Landsat TM images and meteorology data of 1999 were used for ET computation, and spatial and temporal change patterns of ET in the Yellow River Delta were analysed.