尹剑
, 欧照凡, 付强, 刘东, 邢贞相
东北农业大学水利与土木工程学院,黑龙江 哈尔滨 150030
Yin Jian, Ou Zhaofan, Fu Qiang, Liu Dong, Xing Zhenxiang
中图分类号: TV213
文献标识码: A
文章编号: 1000-0690(2018)03-0448-09
通讯作者:
收稿日期: 2017-02-28
修回日期: 2017-06-15
网络出版日期: 2018-03-21
版权声明: 2018 《地理科学》编辑部 本文是开放获取期刊文献，在以下情况下可以自由使用：学术研究、学术交流、科研教学等，但不允许用于商业目的.
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作者简介:
作者简介：尹剑（1984-）,男,黑龙江哈尔滨人,副教授,博士,主要从事水文水资源工程研究。E-mail: yinjiangbnu@163.com
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摘要
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。
关键词：
Abstract
Remote sensing is the effective technology for estimation evapotranspiration (ET). In recent years, many remote sensing ET methods have been developed, and great progress has been made in ET estimation research. While accurate estimation of the satellite-based global terrestrial ET at high spatial and temporal scales remains a major challenge. A review of the commonly applied ET models using remotely sensed data, including the simplified empirical regression method, empirical statistical model for global ET, Penmen-Monteith-based remote sensing model, complementary relationship model, Priestley-Taylor model, triangle or trapezoidal feature space method, residual method of surface energy balance with one-source and two-source framework, three temperature method, nonparametric approach, semiempirical Penman algorithm, and Bayesian model averaging method were presented in this article. Beside the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, these models varied greatly in inputs, main assumptions and accuracy of results, etc. Most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, relied to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. The main inputs, assumptions, theories, advantages and drawbacks of each model were discussed. Moreover, the advantages and disadvantages of remote sensing, conventional calculation formula and process model simulation were analyzed. The data assimilation approaches based on the remotely sensed data to the extrapolation of instantaneous ET to the continuous values are also presented. The data assimilation approaches were divided into surface energy balance-based method and complex process model-based method. The principles, cases and common assimilation algorithms of the two types of methods were reviewed. In the final part, the problems currently and possible solutions such as efficiency, uncertainty, validation and scale in the estimation of regional ET based on remotely sensed data and ground-based measurements were discussed.
Keywords：
蒸散发（Evapotranspiration,ET）是地表水热能量交换和陆气水循环中重要的环节,区域ET的准确估算,对气候变化、水资源管理、农作物估产等具有重要作用[1]。传统ET获取方法主要针对均匀地表下的微尺度进行测量和计算[1]。遥感技术可以实时反映下垫面空间特点,为准确估算区域尺度ET提供了途径[2]。多年来,遥感ET估算方法取得了长足的发展[3]。研究总结了常见的遥感ET方法,包括直接反演模型和数据同化,分析了各类方法的机理与适应性,为ET的研究与发展提供参考。
借助遥感技术,传统公式可以在像元空间实现尺度扩展,得出区域尺度的ET分布。
彭曼公式（Penmen-Monteith,PM）最初由Penman基于地表能量平衡（Surface Energy Balance,SEB）理论提出蒸发能力的计算公式;Monteith引入冠层阻抗的概念进一步完善了模型[4]：
式中,LE为潜热通量;Rn为净辐射;G为土壤热通量;(es - ea)为饱和水汽压差;ρ为空气密度;Cp为空气定压比热容;Δ是饱和水汽压对温度的导数;γ表示干湿表常数;rs、ra分别表示表面阻抗和空气动力学阻抗。这些参数一起决定潜热通量LE即ET瞬时速率。
为方便PM的应用,国际农粮组织定义了一种参考作物蒸散ET0[4],根据作物系数来确定实际ET,改善了农田尺度和湿润区ET的计算精度。PM模型已成为估算ET,特别是作物ET的成熟方法[1]。MODIS遥感数据的MOD16/MYD16产品是PM模型典型应用,针对土壤、湿润和干燥冠层建立PM方程生成了全球和区域尺度的ET产品。Yuan等[5]增加了气温对植被气孔导度的约束,同时完善植被覆盖率计算,设计了改进的PM模型RRS-PM,在中国区域精度高于MOD16。PM公式假设空气边界层为中性稳定层,即动量输送阻抗等于热量输送阻抗;同时把植被冠层看作均匀层,假设潜热交换只发生在叶面;当下垫面非均匀时,如植被组成复杂、稀疏植被或裸土地表时,单纯利用PM误差较大[3]。同时,模型涉及参数较多,公式（1）中的rs涉及植被生理和土壤湿度,难以通过遥感获得[5],参数化和空间插值给估算带来不确定性。
Bouchet提出,并由Morton等人发展完善的互补相关原理指出：
式中,ETwp为充分湿润环境下的潜在ET,ETP为潜在蒸散发。模型的关键在于建立潜在蒸散发ETp和ETwp的计算公式,常用的模型有互补相关陆面蒸散模型、平流-干旱模型及Granger模型等[6]。基于互补相关理论的模型简单易行,输入数据除少量气象数据外均依据遥感获得,且不用计算阻抗,在估算农田和均质下垫面ET时应用广泛[7]。由于互补相关理论简化了ET过程,忽略了土壤湿度占主导的ET,因此较适合于大气主导的湿润区域,而干旱半干旱地区应用效果不甚理想[6]。模型忽略了大尺度天气系统和平流的影响,当下垫面结构复杂时,需要借助精确的大尺度平流参数和地表参数反演模型[7]。
为减少PM模型在ET估算中的大气控制项,Priestley和Taylor利用增加经验因子来简化计算,提出了计算饱和下垫面LE 的Priestley-Taylor（PT）公式[8]：
在Priestley和Taylor的研究中,饱和条件下的PT系数α为1.26。研究发现α是随环境变化的,将α视为变量,可通过改进PT公式计算平流条件下的实际ET。一种思路是先计算ETp进而计算实际ET。如Miralles[9]基于微波遥感土壤湿度、地表温度（Land Surface Temperature, LST）、植被密度和降雨截留损失等信息,建立了ETp与ET的关系,估算了全球尺度的逐日ET。另一类方法是改进PT公式直接计算实际ET。如利用地表干燥度改进PT模型[10];结合散点图特征空间确定PT系数[11]。Fisher等[12]开发的PT-JPL模型对公式（3）引入表征相对湿度、土壤湿度和冠层系数,并基于生物气象方法对系数进行参数化约束,使PT公式分别计算截留蒸发、土壤表面蒸发、植被蒸腾和水面蒸发。PT-JPL机理较为完善,业务化相对成熟[2]。Yao等[13]简化了PT-JPL对水汽压和大气湿度的计算,构建了受NDVI和LST表观热惯量约束的MS-PT模型,考虑了冠层截留与土壤湿度之间的关系,引入相对湿度、土壤湿度以改善模型的不确定性,在中国区域的ET估算中优于PT-JPL[13]。PT法避免了阻抗计算、参数少、计算相对简便,常借助生态约束[2]、微波遥感[9]和散点图空间[11]等方法。输出以大空间尺度为主,在流域和区域尺度需进一步验证。
基于日平均潜热通量（LEd）与地气温差的近似正比关系,Seguin和Itier[14]提出经验回归公式：
式中,Rnd为日平均净辐射;T1和T2为正午的LST和气温;统计回归系数B和n分别取决于表面粗糙程度和大气稳定度。该方法近似的认为昼夜的土壤热通量相互抵消,主要优点是参数少、计算简便[3]。该模型需要在特定研究区重新校准回归系数;在复杂地形和植被稀疏时较难获得B和n,因此在下垫面异质性大时表现较差[3]。
Wang和Liang [15]基于昼夜地表温差反映土壤湿度对ET的影响,建立了基于净辐射Rn、植被指数VI、温度T、土壤湿度的经验公式：
式中,经验系数a0、a1、a2、a3基于地基通量观测确定。VI是强化植被指数或NDVI;温度T可以是LST或气温的均值或最大值;DTsR为日LST较差,可近似的反映土壤湿度和ET的关系;模型较为合理的估算了全球多年ET,并很好地反映了季节影响[15]。Yao等[16]利用日气温较差DTaR建立了幂指数经验模型,有效实现了中国区域的干旱评估。基于LST和VI等地表特征参数的经验公式是ET估算的重要研究方向之一,方法简洁易行,主要应用于均匀地表或大空间尺度。
遥感获取的LST、VI、地表反照率等参数间的二维散点图呈现一定的形状,由此来估算各像元的ET被称之为特征空间法。Price[17]发现当区域植被覆盖度和土壤湿度变化范围较大时,LST和NDVI的散点图呈梯形,其边界和极值点可结合气象资料和梯形图获得,任一点温度由对应点与极值点之间的斜率获得,再结合水分亏缺指数与垂向SEB关系,可求出ET[3]。Jiang等[18]又将其简化成三角形。根据LST和反照率的关系,Roerink等[19]开发了S-SEBI模型,可应用于大气状况稳定的无资料地区,简单实用。特征空间法也常和其他模型结合,以简化模型参数的计算[1,11]。
特征空间的边界确定带有一定的经验性和主观性,Tang等[11]构建了一种确定干湿边的自动算法,提高了方法的效率与可靠性。特征空间法存在的另一个问题是当区域没有足够的辐射值或植被覆盖度分布时,难以满足变量的满阈,影响精度。如整体植被茂密时,NDVI过大,LST-NDVI边界难以确定;当特征空间上下端离散点较多时,边界的确定也较困难。此外,特征空间法没有完整考虑下垫面的依赖性,不同的下垫面环境具有不同阻抗特性[3]。
当只考虑垂直方向能量时,基于SEB存在Rn–G =LE +H的方程关系;因此确定感热通量H是获得LE的关键。根据土壤和植被是否分开计算,将遥感ET模型分为单源和双源模型。
单源模型把土壤和植被看作一个热量来源的整体。模型采用一维通量梯度表达式计算热感通量H：
式中,T0为空气动力学温度;Ta为参考高度气温;ρ为空气密度;CP为空气定压比热容。T0较难获得,常用LST来代替。植被覆盖度大、地表粗糙度小时LST和T0差别较小;当研究区植被部分覆盖,LST远大于T0。针对此,通常有两种修正方法[3]：利用附加阻力和经验因子修正、借助经验公式调整地气温差。Bastiaanssen等[20]结合两种方法建立了SEBAL模型：先确定干、湿极值点的(T0–Ta);基于LST与(T0–Ta)的线性关系计算各像元的(T0–Ta)。SEBAL避免了动力传输粗糙长度的计算和气温的空间插值;不足之处是极值点的选择过分依赖经验,对整个区域采用同样的线性关系,在下垫面空间差异较大时不具备普适性[3]。Allen等[21]参考坡度和坡向改进SEBAL,构建了适用于不平坦地区的METRIC模型,在湿润地区应用较好[22]。与SEBAL依赖经验确定干湿边不同,Su[23]提出的SEBS模型基于计算推导得出干湿边,对每个像元都设定干湿限,削弱了空间插值误差;同时改进了部分植被覆盖条件下的经验因子计算公式。Ma等[24]优化了SEBS中空气动力学粗糙度、热传输粗糙度和G的参数化方案,提高了SEBS的估算精度。
通常情况下土壤和植被的表面温度是不相等的,水热交换也不在同一界面,利用双源模型计算更加合理[3]。较常见的是Norman等[25]构建的平行模型TSEB,利用PT公式分离植被冠层温度Tc和土壤表面温度Ts,采用比尔定律分解净辐射,进而获得土壤和植被的组分通量。PT公式计算时,对平流条件下α值的估算不准,会出现土壤蒸发估算过高的问题;同时,PT公式迭代分解组分温度产生了大量的计算消耗[3]。Colaizzi等[26]用PM替代PT公式,提高了精度,但PM公式需要精确的湿度和阻抗,使其难以在下垫面异质区应用。Song等[27]提出了TSEB-A模型,基于非迭代PT公式分解组分温度,借助平流条件下的土壤湿度观测估算土壤蒸发,提高了α估算的可靠性。但TSEB-A依赖土壤湿度观测,对空间分辨率要求高时仅通过卫星遥感较难实现。另一类双源模式依赖于多角度热红外遥感可分解Tc和Ts的特点。Song等[28]以ASTER数据获得Tc和Ts构建双源模型,验证精度高于TSEB。另外一些研究[29,30]通过结合特征空间确定干湿限的方法分离Tc和Ts,避免了使用PT公式和多角度遥感数据,这类方法依赖特征空间边界的确定,批处理有一定困难。总体来说,双源模型机理性更强,避免了LST代替T0的不确定性,借助多角度遥感或合理的组分温度分解方法可以实现更准确的估算。多数双源模型需要计算阻抗、分解土壤、植被净辐射,这些环节受植被结构、土壤湿度、观测角度等影响,需进一步完善研究。
除上述几类遥感模型外,三温模型[31]、非参数化模型[32]、半经验模型[33],集成模型[34]也是常见的业务化模型。三温模型由邱国玉团队开发,以SEB方程为基础,引入参考土壤（干燥无蒸发的土壤）和参考植被（干燥无蒸腾的植被）;剔除难以准确计算的空气动力学阻抗;基于NDVI将像元划分为纯净像元（土壤或植被）和混合像元,对纯净像元计算土壤蒸发或植被蒸腾、对混合像元分开计算蒸发和蒸腾。模型计算简便,输入参数少,关键和难点在于参考面参数的获取和混合像元ET的计算。Liu等[32]提出的非参数化模型把下垫面近地层看作一个封闭的物理系统,把哈密顿量等同于系统总能量,利用LST作为广义坐标推导H的计算公式,进而得出LE。模型每个参数（Rn、LST、G、Ta）都有明确的物理意义,避免了参数化误差。研究发现非参数化模型的精度在湿润区域高于干旱区域,夏季高于冬季[35];干旱半干旱气候下植被覆盖区的反演精度略低于裸地[36]。Wang等[33]将ET划分为大气控制部分和能量控制部分,基于PM分别建立半经验公式,提出半经验算法UMD-SEMI,结合全球64个通量站验证精度较高。UMD-SEMI计算简单,在干旱和湿润条件下均有较好性能,适合研究全球尺度和长时间序列的ET,同时也是少有的将风速作为输入的遥感ET模型[34]。Yao等[34]针对MOD16、RRS-PM、PT-JPL、MS-PT、UMD-SEMI模型,基于通量观测数据来调整先验概率密度函数,利用贝叶斯均值集成模型结果,结果表明集成模型较每一个模型单独估算的结果都有所改善。
受天气和卫星周期影响,通过遥感模型直接反演的ET大多数是不连续的,且较难实现预测[37]。数据同化（Data Assimilation,DA）将可离散的遥感观测融入动态模型,实现时间尺度的扩展和精度的概率最优,获得连续ET[38]。DA主要由3部分组成：动态模型、观测和同化算法。因动态模型的不同可以归纳为基于SEB的DA和基于复杂过程模型的DA。
基于SEB的DA主要借助四维变分方法,是一种变分数据同化（Variational Data Assimilation,VDA）。基本思路是：以基于SEB的LST时间状态正演模型作为约束,同时构建一个包含变量、参数和约束的代价函数,通过代价函数的极值运算,寻求最优变量和参数。
Castelli等[39]首先提出基于伴随的强约束VDA：采用一个简单的LST模型作为约束,将同化转化为代价函数的极值问题,实现了LE的连续估算,但是该方法没有考虑正演模型中的景观空间差异,影响了同化效果[40]。Caparrini等[41]改进了LST正演模型,建立单源SEB结构的驱动-恢复方程,近似表达了有效热传输介质中的热扩散;设定了2个关键参数：中性大气条件下的感热交换系数CBN和蒸发比EF,分别反映物候和景观的影响。方法不需要借助土壤和植被参数等辅助数据,即可同化输出时间连续且精度可靠的LE和H;通过扩展同化窗口,可实现预测。Crow和Kustas[42]发现该VDA：1） 在干旱和植被稀疏区域效果较好,在湿润和高植被覆盖地区效果较差,需要叶面积指数（Leaf Area Index, LAI）或EF的取值约束等附加信息;2） 效果与下垫面条件以及LAI的准确性有关;3） 单源SEB结构对湍流过程的物理描述不完善,影响了DA。此外,驱动-恢复方程对热扩散过程过于简化,正演模型的物理机理有待完善;强约束VDA假设正演模型是完美的,因此不考虑模型误差,这与实际情况不符[43]。
针对湿润和高覆盖区域同化效果较差的问题,Sini等[44]引入基于日降雨的简单土壤湿度约束改进了正演模型。为减小植被覆盖度等下垫面条件估计不准的影响,Abdolghafoorian等[45]摒弃了CBN在一个月内为定值的假设,建立了CBN和LAI的动态函数关系,反映植被物候动态效应,在美国和中国的4个地基通量验证中研究改善了DA。
Bateni和Liang[46]构建了基于双源SEB的VDA,提高了DA与观测的相关度。Xu等[47]研究了双源VDA对气候和植被覆盖的适应性：单源、双源VDA在干旱、植被稀疏区域的表现都优于湿润、植被密集的区域;整体上双源模式精度更高、更可靠。Xu等[48]结合通量观测和稳定同位素解析,论证了双源VDA比TSEB直接反演更好的分离了土壤和植被冠层的水热通量。
一些研究完善了正演模型并考虑误差建立了弱约束VDA模式。Qin等[49]修改了正演模型中深层温度和H的参数化方案,构建了弱约束VDA,在数值实验中获得了较好的结果。Bateni等[43]引入完整的热扩散方程、考虑了SEB的误差建立弱约束VDA,提高了EF和LE的精度,并量化了DA的不确定性。Bateni等[50]论证了弱约束VDA在处理驱动数据的偶然性错误和模型结构误差方面的明显优势。Xu等[51]研究发现湿润和干燥环境下弱约束LDA都优于传统强约束方案。
相比直接反演,基于SEB的同化：1）基于离散的LST遥感观测输出了时间连续的ET;2）借助物理机理完善的正演模型,弱化了直接反演方法中的经验性和不确定性;3）通过CBN和EF使ET估算不再依赖表面粗糙度的先验估计[42];4）双源VDA可有效分离土壤和植被通量[48],而不受多角度卫星缺乏和特征空间绘图困难的局限。同时,计算消耗大,伴随模型推导难度大的问题不容忽视。计算机自动微分法可基于原始正演模型自动构建伴随码,是提高同化效率的一种方案[44]。但自动微分无法进行切线性模式的检验,当模型复杂时,难以对伴随模型进行有效评估。
DA可以不断导入有效的遥感观测,对水文、作物、陆面过程等复杂模型的参数和状态变量进行校准,实现高精度且连续性的ET模拟[3]。基于复杂过程模型的DA在模拟和预测陆面过程中发挥着越来越重要的作用,其观测可以是过程模型的驱动数据、状态变量或诊断变量[38]。
LST控制着陆面水量和能量平衡,与ET的估算精度高度相关[52]。土壤湿度作为过程模型的状态变量,对过程模型的DA作用明显[38]。因此,同化LST和土壤湿度是改善陆面通量预测的重要方案。Xu等[53]以MODIS-LST为观测同化了CLM陆面模型;Lei等[54]借助土壤湿度遥感观测同化了SWAT水文模型,均改善了ET的精度。研究发现[55]由于ET受状态变量和较多参数的影响,仅同化LST和土壤湿度可能没有完整反映模型计算ET的误差,存在DA不完全的情况。
一种改进思路是同时同化与ET相关的变量和参数：Xu等[52]构建了双通道DA,利用LST同化CoLM模型,分别实现日尺度土壤湿度和周尺度LAI的更新。该方案减少了DA中模型的不确定性,并有效改善LE的精度。另一种思路是将遥感ET作为观测,利用集合算法中的隐式观测算子方法建立遥感ET与状态变量的同化关系[56]。Pipunic等[56]将遥感LST、土壤湿度和LE同化入CSIRO生物圈陆面模型,当观测包含LE时DA效果显著。Cammalleri和Ciraolo[37]以TSEB反演的ET为观测,同化更新了SVAT模型的变量和参数,改善了缺资料乏情况下的ET估算。
变分、顺序和模型优化方法均被基于过程模型的DA采纳。由于三维变分不能传递误差,四维变分可以隐式传递误差但需要建立伴随码,而复杂过程模型难以构建伴随模型,限制了变分方法的应用。研究者尝试开发与改进算法,如利用历史样本投影的四维变分[57]可不借助伴随实现同化;孟春雷等[58]提出的一种简化的变分方法,用LST同化CoLM模型改善了ET精度。滤波、平滑和插值是较常见的顺序方法。滤波方法不用建立伴随模型,考虑了观测和模型的不确定性,并且误差可以随时间传播。集合卡尔曼滤波及其改进算法是应用最为广泛的同化方法[38]。近年来提出的基于贝叶斯条件概率的粒子滤波具有更容易解决非线性问题、实现并行运算的优点[59]。Lei等[54]也将平滑算法引入ET同化中。插值算法是一种简化同化,如Schuurmans等[60]基于ET与状态变量的线性关系更新模拟,并利用增益算子体现误差权重;虽然经验性较强,但具有计算量小和可调整系统性误差的优点。此外,SCE-UA[61]、Gauss-Marquardt-
Levenberg[62]和遗传算法[63]等最优化方法可实现过程模型的参数与背景状态的优选,实现同化。Xu等[53]比较了集合卡尔曼滤波和SCE-UA同化CoLM的效果,发现集合滤波优于SCE-UA。总体来说,基于滤波、平滑等理论的同化效果较好,但误差协方差消耗存储空间大、并行运算成本高、同化可能发散。借助确定性方法如集合平方根滤波等方法可增加小集合下的鲁棒性,减小计算和存储消耗[38];协方差修正、粒子重采样等方法可改善同化衰变。耦合多种同化算法实现优势互补也是研究的方向[64]。
当前,国际上基于数据同化建立了许多应用于气象水文业务的大型陆面数据同化系统。如北美/全球陆面数据同化系统(NLDAS/GLDAS)、欧洲陆面数据同化系统(ELDAS)、中国气象局陆面数据同化系统(CLDAS)等等。这些系统耦合了包括了水文、陆面、植被等多个模块过程模型,同时引入了多元遥感观测,整合使用了多种同化算法。因业务特征的不同输出不同时空尺度的多种陆表变量。实现包括ET在内的陆面过程的模拟与预测。
研究总结了当前常见的基于遥感估算区域ET的方法。各类反演模型均存在一定的假设和特定环境的最佳适应性。PM公式、互补相关理论、PT公式等传统方法借助遥感技术实现了空间尺度扩展,可以计算像元为单位的区域ET。PM融合了空气动力学和SEB原理,物理机理完善,难点在于大量参数的空间尺度插值与表面阻抗的求解。PT可以看作是PM模型的简化方式。PM理论认为ET和ETp存在同向的变化趋势,与互补相关理论相悖,在某一特定区域,ET与ETp的关系或只符合其中某一个理论。经验类模型需要的气象资料较少,是估算均质下垫面或空间大尺度区域ET的有效方法。单源模型具有计算简便的优点,但是需要对LST代替T0的情况进行修正,在地气温差较大的情况下效果较差;双源模型合理的描述了土壤和植被与大气的能量交换,但是多角度数据缺乏、组分温度分解困难,阻抗计算量大等问题需要进一步研究解决;单源模型更适合湿润和植被高覆盖地区;双源模型更适合植被稀疏和气候相对干旱地区。集成模型借助贝叶斯均值法提供了一种整合各类模型优势的有益尝试。
DA解决了直接反演时间不连续的问题,是ET估算研究的一个重要方向。对于数据同化中涉及到的模型算子的精度与结构合理性、同化算法的评价与完善、观测和同化变量的选择,误差协方差传递、以及同化中重要参数的确定等问题,都是需要深入研究与探讨的问题。过程模型与遥感的计算时空尺度往往有所差别,因此同化尺度的转换与匹配尚需深入研究与发展以达到合理的同化效果。此外,同化的高计算成本使其与并行计算成为一对相辅相成的技术。
ET估算方法有赖于地表水热交换的物理机理,这一机理涉及地气交换的热力学、动力学和植被生理等问题,强化模型对物理机理的解译能力,是提高精度的重要途径。研究并量化遥感ET模型的不确定性,同样有助于改善模型。模型机理和模型不确定性研究有赖于可靠的验证方法。而区域尺度ET的验证一直较为困难。目前,借助地面观测数据是最为可靠的验证方法。蒸渗仪、波文比法、涡动相关仪和大孔径闪烁仪是重要的观测方法。地面观测方法获得的是点数据,或者观测点上风向一定区域的数值,而下垫面的异质性和遥感、观测数据的尺度匹配问题,影响了验证的可靠性。Bai等[65]发现足迹分析可获得观测的有效区域,对于遥感反演和地基测量的时空匹配具有重要意义。在低分变率卫星数据验证中,还需要考虑复杂曲面亚像元尺度的空间异质性。因此,更精确的验证数据和尺度精细化方法需要研究,例如通过通量测量矩阵或机载测量获取卫星像素尺度上的地表通量。此外,如何选取验证像元、获得像元尺度“地面真值”以便解决地面观测值与遥感估算值在空间尺度上不匹配问题也是验证研究的重点,对发展ET模型和提高模拟精度至关重要。Liu等[66]基于黑河流域中游多点地基通量观测,开展了构建像元“地面真值”的研究。在比较几种尺度转换方法的基础上,提出了一种综合有效的方法：根据下垫面均匀与否选取面积加权法或辅助变量法;引入表征地表水热条件的多源数据,来获取非均匀地表下日尺度的像元“地面真值”。此外,开发一种较为完整的ET验证及评估方法,以实现点尺度和流域尺度的双重评价,是评估验证有效性和促进模型的改进的重要手段。除了利用验证方法进行模型精度评估外,误差源分析、验证的不确定性分析均应进一步展开。
The authors have declared that no competing interests exist.
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react-text: 203 Euler's equation is the governing equation of the irrotational flow of ideal fluids; this equation can be considered for free surface water flow in open channels. The Euler's equation, is solved by a mesh-less method. Also a fractional step method is applied which consists in splitting each time step in two steps. This numerical method is based on the Moving Particle Semi implicit method (MPS)... /react-text react-text: 204 /react-text [Show full abstract]
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Estimating surface energy fluxes using a dual-source data assimilation approach adjoined to the heat diffusion equation [J].https://doi.org/10.1029/2012JD017618 URL [本文引用: 1] 摘要
[1] Recently, a number of studies have assimilated land surface temperature (LST) within a variational data assimilation (VDA) framework to estimate turbulent heat fluxes. These VDA models have mainly considered soil and vegetation as a combined source (CS) and have not accounted for the difference between soil and canopy temperatures and turbulent exchange rates, although soil and canopy can exhibit very different behaviors. Hence, in this study the contribution of soil and canopy to the LST and turbulent heat fluxes is taken into account separately by developing a dual-source (DS) VDA model. The unknown model parameters are the neutral bulk heat transfer coefficient (that scales the sum of turbulent heat fluxes) and the evaporative fractions for soil and canopy (which represent partitioning among the turbulent fluxes over soil and vegetation). The model as developed has been tested with area-averaged measurements of turbulent heat fluxes obtained from the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) during the summers of 1987 and 1988. The results show that the predicted turbulent heat fluxes match well with observations. For FIFE 1987 (1988), the half-hourly latent heat flux estimates from the new model have a root-mean square-error (RMSE) of 57.4 Wm0908082 (66.8 Wm0908082), which represents a significant improvement over the previous study.
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Estimation of surface turbulent heat fluxes via variational assimilation of sequences of land surface temperatures from Geostationary Operational Environmental Satellites [J].https://doi.org/10.1002/2014JD021814 URL [本文引用: 1] 摘要
Abstract Recently, a number of studies have focused on estimating surface turbulent heat fluxes via assimilation of sequences of land surface temperature (LST) observations into variational data assimilation (VDA) schemes. Using the full heat diffusion equation as a constraint, the surface energy balance equation can be solved via assimilation of sequences of LST within a VDA framework. However, the VDA methods have been tested only in limited field sites that span only a few climate and land use types. Hence, in this study, combined-source (CS) and dual-source (DS) VDA schemes are tested extensively over six FluxNet sites with different vegetation covers (grassland, cropland, and forest) and climate conditions. The CS model groups the soil and canopy together as a single source and does not consider their different contributions to the total turbulent heat fluxes, while the DS model considers them to be different sources. LST data retrieved from the Geostationary Operational Environmental Satellites are assimilated into these two VDA schemes. Sensible and latent heat flux estimates from the CS and DS models are compared with the corresponding measurements from flux tower stations. The results indicate that the performance of both models at dry, lightly vegetated sites is better than that at wet, densely vegetated sites. Additionally, the DS model outperforms the CS model at all sites, implying that the DS scheme is more reliable and can characterize the underlying physics of the problem better.
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Abstract The primary objective of this study is to assess the accuracy of the two-source variational data assimilation (TVDA) system for partitioning evapotranspiration (ET) into soil evaporation (ETS) and canopy transpiration (ETC). Its secondary aim is to compare performance of the TVDA system with the commonly used two-source surface energy balance (TSEB) method. A combination of eddy-covariance-based ET observations and stable-isotope-based measurements of the ratio of evaporation and transpiration to total evapotranspiration (ETS/ET and ETC/ET) over an irrigated cropland site (the so-called Daman site) in the middle reach of the Heihe River basin (northwestern China) was used to investigate these objectives. The results indicate that theTVDAmethod predicts ETS and ETC more accurately than TSEB. Root-mean-square errors (RMSEs) of midday (1300 1500 LT) averaged soil and canopy latent heat flux (LES and LEC) estimates from TVDA are 23.1 and 133.0Wm22, respectively. Corresponding RMSE values from TSEB are 41.9 and 156.0Wm22. Compared to TSEB, the TVDA method takes advantage of all of the information in land surface temperature observations in the estimation period by leveraging a dynamic model (the heat diffusion equation) and thus can generate more accurate LES and LEC estimates.
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中国科学院机构知识库(中国科学院机构知识库网格（CAS IR GRID）)以发展机构知识能力和知识管理能力为目标，快速实现对本机构知识资产的收集、长期保存、合理传播利用，积极建设对知识内容进行捕获、转化、传播、利用和审计的能力，逐步建设包括知识内容分析、关系分析和能力审计在内的知识服务能力，开展综合知识管理。
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Mapping evaporation and estimation of surface control of evaporation using remotely sensed land surface temperature from a constellation of satellites [J].https://doi.org/10.1002/wrcr.20071 URL [本文引用: 1] 摘要
ABSTRACT 1] A variational data assimilation model is developed to estimate surface energy fluxes from remotely sensed land surface temperature (LST). Components of the surface energy balance (sensible, latent, and ground heat fluxes) have different degrees of efficiency in dissipating available energy. LST is the state variable of the surface energy balance (SEB). Land surface models that capture the exchange and storage of energy in the soil and vegetation media use LST as a prognostic variable. Sequences of LST measurements implicitly contain information on partitioning of available energy among the components of SEB. In this study, we focus on the estimation of the sum of the turbulent fluxes as well as the partitioning among them. Two dimensionless parameters are used to characterize the sum and the partitioning. Using LST observations from a constellation of satellites, these parameters are mapped over a large region. The remotely sensed LST is assimilated to the heat diffusion equation within the SEB framework. In addition, a model error term is added to the SEB equation such that the variational data assimilation scheme includes model uncertainty as well as observation error. The framework is tested over the Southern Great Plains region. The mapped results of the surface evaporation estimation are used to study the surface control on evaporation. Independent mapped soil moisture estimates from an airborne microwave campaign are used. The dependence of the evaporation control-soil moisture relationship on vegetation cover and plant functional types over large regions is examined in this first and exploratory study. Citation: Bateni, S. M., D. Entekhabi, and F. Castelli (2013), Mapping evaporation and estimation of surface control of evaporation using remotely sensed land surface temperature from a constellation of satellites, Water Resour. Res., 49, doi: 10.1002/wrcr.20071.
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Estimating turbulent heat fluxes with a weak-constraint data assimilation scheme: A case study (HiWATER-MUSOEXE) [J].https://doi.org/10.1109/LGRS.2014.2326180 URL [本文引用: 1] 摘要
A weak-constraint variational data assimilation (WC-VDA) scheme was developed to estimate turbulent heat fluxes by assimilating sequences of land surface temperature measurements. In contrast to the commonly used strong-constraint VDA system, the WC-VDA approach accounts for the effects of structural and model errors and generates better results. This is achieved by adding a model error term ( ) to the surface energy balance equation. The WC-VDA model was tested at two sites with very distinct hydrological and vegetated conditions: the Daman site (a wet site located in an oasis area and covered by seeded corn) and the Huazhaizi site (a dry site located in a desert area and covered by sparse grass). The two sites represent typical desert-oasis landscapes in the middle reaches of the Heihe River Basin, northwestern China. The results proved that the WC-VDA method performed well over very dry and wet conditions, and the estimated sensible and latent heat fluxes agree well with eddy covariance measurements.
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A dual-pass data assimilation scheme for estimating surface fluxes with FY3A-VIRR land surface temperature [J].https://doi.org/10.1007/s11430-014-4964-7 URL [本文引用: 2] 摘要
In this work, a dual-pass data assimilation scheme is developed to improve predictions of surface flux. Pass 1 of the dual-pass data assimilation scheme optimizes the model vegetation parameters at the weekly temporal scale, and Pass 2 optimizes the soil moisture at the daily temporal scale. Based on ensemble Kalman filter(EnKF), the land surface temperature(LST) data derived from the new generation of Chinese meteorology satellite(FY3A-VIRR) are assimilated into common land model(CoLM) for the first time. Six sites, Daman, Guantao, Arou, BJ, Miyun and Jiyuan, are selected for the data assimilation experiments and include different climatological conditions. The results are compared with those from a dataset generated by a multi-scale surface flux observation system that includes an automatic weather station(AWS), eddy covariance(EC) and large aperture scintillometer(LAS). The results indicate that the dual-pass data assimilation scheme is able to reduce model uncertainties and improve predictions of surface flux with the assimilation of FY3A-VIRR LST data.
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Improving the estimation of hydrological states in the SWAT model via the ensemble Kalman smoother: Synthetic experiments for the Heihe River Basin in northwest China [J].https://doi.org/10.1016/j.advwatres.2014.02.008 URL [本文引用: 2] 摘要
Data assimilation as a method to predict variables, reduce uncertainties and explicitly handle various sources of uncertainties has recently received widespread attention and has been utilized to combine in situ and remotely sensed measurements with hydrological models. However, factors that significantly influence the capability of data assimilation still need testing and verifying. In this paper, synthetic surface soil moisture data are assimilated into the Soil and Water Assessment Tool (SWAT) model to evaluate their impact on other hydrological variables via the ensemble Kalman smoother (EnKS), using data from the Heihe River Basin, northwest China. The results show that the assimilation of surface soil moisture can moderately improve estimates of deep layer soil moisture, surface runoff and lateral flow, which reduces the negative influences of erroneous forcing and inaccurate parameters. The effects of the spatially heterogeneous input data (land cover and soil type) on the performance of the data assimilation technique are noteworthy. Moreover, the approaches including inflation and localization are specifically diagnosed to further extend the capability of the EnKS.
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Data assimilation for distributed hydrological catchment modeling via ensemble Kalman filter [J].https://doi.org/10.1016/j.advwatres.2010.03.012 URL [本文引用: 1] 摘要
Catchment scale hydrological models are critical decision support tools for water resources management and environment remediation. However, the reliability of hydrological models is inevitably affected by limited measurements and imperfect models. Data assimilation techniques combine complementary information from measurements and models to enhance the model reliability and reduce predictive uncertainties. As a sequential data assimilation technique, the ensemble Kalman filter (EnKF) has been extensively studied in the earth sciences for assimilating in-situ measurements and remote sensing data. Although the EnKF has been demonstrated in land surface data assimilations, there are no systematic studies to investigate its performance in distributed modeling with high dimensional states and parameters. In this paper, we present an assessment on the EnKF with state augmentation for combined state-parameter estimation on the basis of a physical-based hydrological model, Soil and Water Assessment Tool (SWAT). Through synthetic simulation experiments, the capability of the EnKF is demonstrated by assimilating the runoff and other measurements, and its sensitivities are analyzed with respect to the error specification, the initial realization and the ensemble size. It is found that the EnKF provides an efficient approach for obtaining a set of acceptable model parameters and satisfactory runoff, soil water content and evapotranspiration estimations. The EnKF performance could be improved after augmenting with other complementary data, such as soil water content and evapotranspiration from remote sensing retrieval. Sensitivity studies demonstrate the importance of consistent error specification and the potential with small ensemble size in the data assimilation system.
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| [56] |
Assimilation of remotely sensed data for improved latent and sensible heat flux prediction:A comparative synthetic study [J].https://doi.org/10.1016/j.rse.2007.02.038 URL [本文引用: 2] 摘要
Predicted latent and sensible heat fluxes from Land Surface Models (LSMs) are important lower boundary conditions for numerical weather prediction. While assimilation of remotely sensed surface soil moisture is a proven approach for improving root zone soil moisture, and presumably latent (LE) and sensible (H) heat flux predictions from LSMs, limitations in model physics and over-parameterisation mean that physically realistic soil moisture in LSMs will not necessarily achieve optimal heat flux predictions. Moreover, the potential for improved LE and H predictions from the assimilation of LE and H observations has received little attention by the scientific community, and is tested here with synthetic twin experiments. A one-dimensional single column LSM was used in 3-month long experiments, with observations of LE, H, surface soil moisture and skin temperature (from which LE and H are typically derived) sampled from truth model run outputs generated with realistic data inputs. Typical measurement errors were prescribed and observation data sets separately assimilated into a degraded model run using an Ensemble Kalman Filter (EnKF) algorithm, over temporal scales representative of available remotely sensed data. Root Mean Squared Error (RMSE) between assimilation and truth model outputs across the experiment period were examined to evaluate LE, H, and root zone soil moisture and temperature retrieval. Compared to surface soil moisture assimilation as will be available from SMOS (every 3days), assimilation of LE and/or H using a best case MODIS scenario (twice daily) achieved overall better predictions for LE and comparable H predictions, while achieving poorer soil moisture predictions. Twice daily skin temperature assimilation achieved comparable heat flux predictions to LE and/or H assimilation. Fortnightly (Landsat) assimilations of LE, H and skin temperature performed worse than 3-day moisture assimilation. While the different spatial resolutions of these remote sensing data have been ignored, the potential for LE and H assimilation to improve model predicted LE and H is clearly demonstrated.
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| [57] |
基于历史样本投影的四维变分陆面数据同化方法及其初步应用 [J].
法面临着计算量上的挑战。本研究将一种历史样本投影的四维变分同化方法(Historical-Sample-Projection4DVar,简写为HSP-4DVar)应用于陆面数据同化,建立起CoLM陆面模型的HSP-4DVar系统。相比其他四维变分同化方法,HSP-4DVar的分析值是显式求解,不需要编写和使用伴随模式,从而大大节省了计算量,是一种易于实现的同化方案。通过同化56个月的土壤湿度观测数据表明,新的陆面同化系统不仅省时,而且能够有效吸取观测信息,使得同化后的均方根误差显著降低,各层土壤湿度模拟都有所改善,陆表1000mm层的改善最为明显。
Historical-Sample-Projection four-dimensional variational land surface data assimilation and its preliminary application .
法面临着计算量上的挑战。本研究将一种历史样本投影的四维变分同化方法(Historical-Sample-Projection4DVar,简写为HSP-4DVar)应用于陆面数据同化,建立起CoLM陆面模型的HSP-4DVar系统。相比其他四维变分同化方法,HSP-4DVar的分析值是显式求解,不需要编写和使用伴随模式,从而大大节省了计算量,是一种易于实现的同化方案。通过同化56个月的土壤湿度观测数据表明,新的陆面同化系统不仅省时,而且能够有效吸取观测信息,使得同化后的均方根误差显著降低,各层土壤湿度模拟都有所改善,陆表1000mm层的改善最为明显。
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| [58] |
CoLM 模式地表温度变分同化研究 [J].https://doi.org/10.3878/j.issn.1006-9895.2012.11184 URL Magsci [本文引用: 1] 摘要
本文采用变分方法对通用陆面模式 (CoLM) 中的地表温度进行同化.同化伴随约束条件采用CoLM模式中的地表及植被能量平衡方程,调节因子采用裸土及植被蒸发比.采用美国通量网 (AmeriFlux) 中的Bonville站数据对同化方法进行了单点验证,验证结果表明同化后地表温度以及蒸散结果更加接近于实测值.选取中国华北地区对同化方法进行区域验证,结果显示每天仅采用白天一次观测值对地表温度进行同化的方法是有效的.通过对同化前后地表温度误差直方图比较可以发现,在有MODIS观测值的区域,同化后白天地表温度误差大大降低,同时,同化后地表蒸散空间分布图也发生了变化.单点验证以及区域验证结果都表明了变分同化方法是可靠的.变分同化方法可以改进陆面模式模拟结果,对于地表过程研究中的植被生态、水文等研究具有重要意义,同时,陆面模式可以与数值预报模式进行耦合,改进数值预报结果.
Variational assimilation of land surface temperature from Common Land Model (CoLM) .https://doi.org/10.3878/j.issn.1006-9895.2012.11184 URL Magsci [本文引用: 1] 摘要
本文采用变分方法对通用陆面模式 (CoLM) 中的地表温度进行同化.同化伴随约束条件采用CoLM模式中的地表及植被能量平衡方程,调节因子采用裸土及植被蒸发比.采用美国通量网 (AmeriFlux) 中的Bonville站数据对同化方法进行了单点验证,验证结果表明同化后地表温度以及蒸散结果更加接近于实测值.选取中国华北地区对同化方法进行区域验证,结果显示每天仅采用白天一次观测值对地表温度进行同化的方法是有效的.通过对同化前后地表温度误差直方图比较可以发现,在有MODIS观测值的区域,同化后白天地表温度误差大大降低,同时,同化后地表蒸散空间分布图也发生了变化.单点验证以及区域验证结果都表明了变分同化方法是可靠的.变分同化方法可以改进陆面模式模拟结果,对于地表过程研究中的植被生态、水文等研究具有重要意义,同时,陆面模式可以与数值预报模式进行耦合,改进数值预报结果.
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| [59] |
Estimation of regional terrestrial water cycle using multi-sensor remote sensing observations and data assimilation [J].https://doi.org/10.1016/j.rse.2007.02.039 URL [本文引用: 1] 摘要
An integrated data assimilation system is implemented over the Red-Arkansas river basin to estimate the regional scale terrestrial water cycle driven by multiple satellite remote sensing data. These satellite products include the Tropical Rainfall Measurement Mission (TRMM), TRMM Microwave Imager (TMI), and Moderate Resolution Imaging Spectroradiometer (MODIS). Also, a number of previously developed assimilation techniques, including the ensemble Kalman filter (EnKF), the particle filter (PF), the water balance constrainer, and the copula error model, and as well as physically based models, including the Variable Infiltration Capacity (VIC), the Land Surface Microwave Emission Model (LSMEM), and the Surface Energy Balance System (SEBS), are tested in the water budget estimation experiments. This remote sensing based water budget estimation study is evaluated using ground observations driven model simulations. It is found that the land surface model driven by the bias-corrected TRMM rainfall produces reasonable water cycle states and fluxes, and the estimates are moderately improved by assimilating TMI 10.67 GHz microwave brightness temperature measurements that provides information on the surface soil moisture state, while it remains challenging to improve the results by assimilating evapotranspiration estimated from satellite-based measurements.
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| [60] |
Assimilation of remotely sensed latent heat flux in a distributed hydrological model [J].https://doi.org/10.1016/S0309-1708(02)00089-1 URL [本文引用: 1] 摘要
This paper addresses the question of whether remotely sensed latent heat flux estimates over a catchment can be used to improve distributed hydrological model water balance computations by the process of data assimilation. The data used is a series of noaa-avhrr satellite images for the Drentse Aa catchment in the Netherlands for the year 1995. These 1脳1 km resolution images are converted into latent heat flux estimates using sebal ( surface energy balance algorithm for land [J Hydrol 2000;229:87]). The physically-based distributed model simgro ( simulation of groundwater flow and surface water levels [J Hydrol 1997;192:158]) is used to compute the water balance of the Drentse Aa catchment for that same year. Comparison between model-derived and remotely sensed area-averaged evapotranspiration estimates show good agreement, but spatial analysis of the model latent heat flux estimates indicate systematic underestimation in areas with higher elevation. A constant gain Kalman filter data assimilation algorithm is used to correct the internal state variables of the distributed model whenever remotely sensed latent heat flux estimates are available. It was found that the spatial distribution of model latent heat flux estimates in areas with higher elevation were improved through data assimilation.
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| [61] |
Multiobjective calibration of land surface model evapotranspiration predictions using streamflow observations and spaceborane surface radiometric temperature retrievals [J].https://doi.org/10.1029/2002JD003292 URL [本文引用: 1] 摘要
[1] Physically based models of surface water and energy balance processes typically require a large number of soil and vegetation parameters as inputs. Accurate specification of these parameters is often difficult without resorting to calibration of model predictions against independent observations. Along with streamflow observations from gauging stations, spaceborne surface radiometric temperature retrievals offer the only independent observation of land surface model output commonly available at regional spatial scales (i.e., >502 km2). This analysis examines the potential benefits of incorporating spaceborne radiometric surface temperature retrievals and streamflow observations in a multiobjective calibration framework to accurately constrain regional-scale model evapotranspiration predictions. Results for the VIC (Variable Infiltration Capacity) model over the Southern Great Plains of the United States suggest that multiobjective model calibration against radiometric skin temperatures and steamflow observations can reduce error in model monthly evapotranspiration predictions by up to 20% relative to single-objective model calibration against streamflow alone.
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| [62] |
Calibration of a distributed hydrological model based on satellite evapotranspiration [J].https://doi.org/10.1016/j.jhydrol.2007.11.017 URL [本文引用: 1] 摘要
Calibrating spatially distributed hydrological models is complex due to the lack of reliable data, uncertainty in representing the physical features of a river catchment, and the implementation of hydrological processes in a simulation model. In this paper, an innovative approach is presented which incorporates remote sensing derived evapotranspiration in the calibration of the Soil and Water Assessment Tool (SWAT) in a catchment of the Krishna basin in southern India. The Gauss arquardt evenberg algorithm is implemented to optimise different combination of land use, soil, groundwater, and meteorological model parameters. In the best performing optimisation, the r 2 between monthly sub-basin simulated and measured actual evapotranspiration (ET act ) was increased from 0.40 to 0.81. ET act was more sensitive to the groundwater and meteorological parameters than the soil and land use parameters. Traditional calibration on a limited number of discharge stations lumps all hydrological processes together and chances on the equifinality problem are larger. In this study we have shown this problem can be constrained by using spatially distributed observations with a monthly temporal resolution. At a spatial resolution below the sub-basin level further study is required to fine-tune the calibration procedure.
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| [63] |
Evapotranspiration data assimilation with genetic algorithms and SWAP model for on-demand irrigation [J].https://doi.org/10.1007/s00271-009-0193-9 URL [本文引用: 1] 摘要
Evapotranspiration (ET) is one of the indicators of water use efficiency. Periodic information of ET based on remote sensing is useful for an on-demand irrigation (ODI) management. The main objective of this paper was to develop an ET data assimilation scheme to optimize the parameters of an agro-hydrology model for ODI scheduling. The soil, water, atmosphere, and plant (SWAP) simulation model has been utilized for this purpose. We computed remote sensing-based ET for a wheat field in the Sirsa Irrigation Circle, Haryana, in India using 18 cloud-free moderate resolution imaging spectroradiometer images taken between December 2001 and April 2002. The surface energy balance algorithm for land (SEBAL) was used for this purpose. Because ET estimates from SEBAL provide information on the surface soil moisture state, they were treated as observations to estimate unknown parameters of the SWAP model via a stochastic data assimilation (genetic algorithm) approach. The SWAP parameters were optimized by minimizing the residuals between SEBAL and SWAP model-based ET values. The optimized parameters were used as input to SWAP to estimate soil water balance for ODI scheduling. The results showed that the selected parameters (i.e. sowing, harvesting, and irrigation scheduling dates) were successfully estimated with the data assimilation methodology. The SWAP model produced reasonable states of water balance by assimilating ET observations. The root mean square of error was 0.755 and 2.13202cm 3 /cm 3 for 0–15 and 15–3002cm soil depths the same layers, respectively. With optimized parameters for ODI, SWAP predicted higher yield and water use efficiency than traditional farmer’s irrigation criteria. The data assimilation methodology produced can be considered as an operational tool at the field scale to schedule irrigation or predict irrigation requirements from remote sensing-based ET.
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| [64] |
E4DVar: Coupling an ensemble kalman filter with four-dimensional variational data assimilation in a limited-area weather prediction model [J].https://doi.org/10.1175/MWR-D-11-00023.1 URL [本文引用: 1] 摘要
ABSTRACT A hybrid data assimilation approach that couples the ensemble Kalman filter (EnKF) and four-dimensional variational (4DVar) methods is implemented for the first time in a limited-area weather prediction model. In this coupled system, denoted E4DVar, the EnKF and 4DVar systems run in parallel while feeding into each other. The multivariate, flow-dependent background error covariance estimated from the EnKF ensemble is used in the 4DVar minimization and the ensemble mean in the EnKF analysis is replaced by the 4DVar analysis, while updating the analysis perturbations for the next cycle of ensemble forecasts with the EnKF. Therefore, the E4DVar can obtain flow-dependent information from both the explicit covariance matrix derived from ensemble forecasts, as well as implicitly from the 4DVar trajectory. The performance of an E4DVar system is compared with the uncoupled 4DVar and EnKF for a limited-area model by assimilating various conventional observations over the contiguous United States for June 2003. After verifying the forecasts from each analysis against standard sounding observations, it is found that the E4DVar substantially outperforms both the EnKF and 4DVar during this active summer month, which featured several episodes of severe convective weather. On average, the forecasts produced from E4DVar analyses have considerably smaller errors than both of the stand-alone EnKF and 4DVar systems for forecast lead times up to 60 h.
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| [65] |
Characterizing the Footprint of Eddy Covariance System and Large Aperture Scintillometer Measurements to Validate Satellite-Based Surface Fluxes [J].https://doi.org/10.1109/LGRS.2014.2368580 URL [本文引用: 1] 摘要
To validate satellite-based surface fluxes by ground measurements properly, several numerical simulations were carried out at a homogeneous alpine meadow site and mixed cropland site, considering various atmospheric conditions and different land cover distribution types. By comparing various pixel selection methods, the results showed that footprint was significant in insuring a consistent spatial scale between ground measurements and satellite-based surface fluxes, particularly for heterogeneous surface and high-resolution remote sensing data. Because large aperture scintillometer measurements cover larger areas than eddy covariance (EC) system measurements, the spatial heterogeneity at a subpixel scale in complicated surface should be further considered in validating coarse satellite data. Thus, more accurate validation data and scaling methods must be developed, such as measuring surface fluxes at the satellite pixel scale by a flux measurement matrix or airborne EC measurements.
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| [66] |
Upscaling evapotranspiration measurements from multi-site to the satellite pixel scale over heterogeneous land surfaces [J].https://doi.org/10.1016/j.agrformet.2016.04.008 URL [本文引用: 1] 摘要
The acquisition of “ground-truth” land surface evapotranspiration (ET) data at the satellite pixel scale over heterogeneous land surfaces is crucial to develop ET estimation models and improve the accuracy of remotely sensed ET values. However, few studies have focused on methods of acquiring ET data at the satellite pixel scale. Based on multi-site eddy covariance (EC) system measurements from the “Multi-Scale Observation Experiment on Evapotranspiration over heterogeneous land surfaces” in the middle reaches of the Heihe River Basin, five upscaling methods were compared and a combined method was developed to acquire “ground-truth” ET data at the satellite pixel scale. First, this study evaluated the performances of three simple upscaling methods (the arithmetic average, area-weighted and footprint-weighted methods). The results showed that the three simple upscaling methods perform well in the relatively homogeneous pixels. For the area-weighted method, the mean absolute percentage error (MAPE) for these pixels was 6.1%. However, the accuracy was worse in the relatively heterogeneous pixels, with a MAPE of 10.8% due to the surface heterogeneity significantly affecting the accuracy of the upscaled results. Second, the upscaling of ET results from heterogeneous land surfaces at the satellite pixel scale can be significantly improved by using two upscaling methods introducing auxiliary variables (the integrated Priestley-Taylor equation method and the area-to-area regression kriging method), that can characterize the heterogeneity of the surface water and heat conditions. Finally, a combined method (applied the area-weighted method for relative homogeneous surfaces, otherwise used the method introducing auxiliary variables) was proposed to acquire both instantaneous and daily “ground-truth” ET data at the satellite pixel scale at the time of a MODIS overpass. The uncertainties of the “ground-truth” ET data were evaluated, taking the large aperture scintillometer (LAS) measurements as the satellite pixel reference. The results show that the proposed upscaling method is reasonable and feasible, and therefore could bridge the gap between in situ ET measurements and remote-sensing estimates of ET.
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| [1] |
A review of global terrestrial evapotranspiration: Observation, modeling, climatology, and climatic variability [J].https://doi.org/10.1029/2011RG000373 URL [本文引用: 4] 摘要
[1] This review surveys the basic theories, observational methods, satellite algorithms, and land surface models for terrestrial evapotranspiration, E (or E, i.e., latent heat flux), including a long-term variability and trends perspective. The basic theories used to estimate E are the Monin-Obukhov similarity theory (MOST), the Bowen ratio method, and the Penman-Monteith equation. The latter two theoretical expressions combine MOST with surface energy balance. Estimates of E can differ substantially between these three approaches because of their use of different input data. Surface and satellite-based measurement systems can provide accurate estimates of diurnal, daily, and annual variability of E. But their estimation of longer time variability is largely not established. A reasonable estimate of E as a global mean can be obtained from a surface water budget method, but its regional distribution is still rather uncertain. Current land surface models provide widely different ratios of the transpiration by vegetation to total E. This source of uncertainty therefore limits the capability of models to provide the sensitivities of E to precipitation deficits and land cover change.
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| [2] |
Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China [J].https://doi.org/10.1016/j.rse.2013.08.045 URL [本文引用: 3] 摘要
61Eight evapotranspiration models were evaluated using 23 eddy covariance towers.61Three process-based models have higher performance according to tower validation.61Process-based models differ at regional magnitude and interannual variability.61Process-based models showed different dominated environmental variables.61More improvements and validations still need for ET models.
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| [3] |
A review of current methodologies for regional evapotranspiration estimation from remotely sensed Data [J].https://doi.org/10.3390/s90503801 URL PMID: 3297132 [本文引用: 11] 摘要
An overview of the commonly applied evapotranspiration (ET) models using remotely sensed data is given to provide insight into the estimation of ET on a regional scale from satellite data. Generally, these models vary greatly in inputs, main assumptions and accuracy of results, etc. Besides the generally used remotely sensed multi-spectral data from visible to thermal infrared bands, most remotely sensed ET models, from simplified equations models to the more complex physically based two-source energy balance models, must rely to a certain degree on ground-based auxiliary measurements in order to derive the turbulent heat fluxes on a regional scale. We discuss the main inputs, assumptions, theories, advantages and drawbacks of each model. Moreover, approaches to the extrapolation of instantaneous ET to the daily values are also briefly presented. In the final part, both associated problems and future trends regarding these remotely sensed ET models were analyzed to objectively show the limitations and promising aspects of the estimation of regional ET based on remotely sensed data and ground-based measurements.
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| [4] |
Crop evapotranspiration: Guide lines for computing crop water requirements: FAO Irrigation and Drainage Paper [M]. |
| [5] |
Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data [J].https://doi.org/10.1016/j.rse.2010.01.022 URL [本文引用: 2] 摘要
Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000–2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP at eddy flux towers showed significant underestimation of ET and GPP due to lower net radiation of MERRA dataset. Applying a procedure to correct the systematic errors of global meteorological data would improve global estimates of GPP and ET. The revised RS-PM and EC-LUE models will provide the alternative approaches making it possible to map ET and GPP over large areas because (1) the model parameters are invariant across various land cover types and (2) all driving forces of the models may be derived from remote sensing data or existing climate observation networks.
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| [6] |
Evaluation of three complementary relationship approaches for evapotranspiration over the Yellow River basin [J].https://doi.org/10.1002/hyp.6048 URL [本文引用: 2] 摘要
Abstract Regional evapotranspiration is an important component of the hydrological cycle. However, reliable estimates of regional evapotranspiration are extremely difficult to obtain. In this study, the evapotranspiration simulated by three complementary relationship approaches, namely the Advection–Aridity (AA) model, the Complementary Relationship Areal Evapotranspiration (CRAE) model and the Granger (G) model, is evaluated with the observations over the Yellow River basin during 1981–2000. The simulations on overall annual evapotranspiration are reasonably good, with mean annual errors less than 10% except in extreme dry years. The AA model gives the best estimation for the monthly evapotranspiration, and the CRAE and GM models slightly overestimate in winter. In addition, the AA model presents the same closure error of water balance over the Yellow River basin as model G, which was less than that by the CRAE model. In rather dry and rather wet cases (with higher or lower available energy), all three models perform less well. Empirical parameters of these models need to be recalibrated before they can be applied to other regions. The distribution of evapotranspiration over the Yellow River basin is also discussed. Copyright 08 2006 John Wiley & Sons, Ltd.
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| [7] |
Estimation of evapotranspiration in the Mu Us Sandland of China [J].https://doi.org/10.5194/hessd-6-5977-2009 URL [本文引用: 2] 摘要
Evapotranspiration (ET) was estimated from 1981–2005 over Wushen County located in the Mu Us Sandland, China, by applying the Advection-Aridity model, which is based on the complementary relationship hypothesis. We used National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR), Moderate Resolution Imaging Spectroradiometer (MODIS), and meteorological data. Our results show that the estimated daily ET was about 4.5% higher than measurements using an Eddy Covariance (EC) system after forcing energy balance closure over an alfalfa field from 22 July 2004 to 23 August 2004. At a regional scale, the estimated monthly ET was about 8.7% lower than measurements using the EC system after forcing energy balance closure over an alfalfa field in August 2004. These results were about 3.0% higher than ET measurements by microlysimeter over sand dunes during June 1988. From 1981 to 2005, the average annual ET and precipitation levels were 287 mm and 336 mm, respectively, in Wushen County. The average annual ET varied from 230 mm in western parts of Wushen County to 350 mm in eastern parts of the county. Both inter-annual and seasonal variations in ET were substantial in Wushen County. The annual ET was 200–400 mm from 1981–2005, and the seasonal pattern of ET showed a single peak distribution. The cumulative ET during the June–September 2004 period was 250 mm, which was 87% of the total annual ET. The annual ET, precipitation, and the maximum Normalized Difference Vegetation Index (NDVImax) showed positive correlations temporally and spatially
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| [8] |
On the assessment of surface heat flux and evaporation using large-scale parameters [J].https://doi.org/10.1175/1520-0493(1972)100<0081:OTAOSH>2.3.CO;2 URL [本文引用: 1] |
| [9] |
Global land-surface evaporation estimated from satellite-based observations [J].https://doi.org/10.5194/hess-15-453-2011 URL [本文引用: 2] 摘要
This paper outlines a new strategy to derive evaporation from satellite observations. The approach uses a variety of satellite-sensor products to estimate daily evaporation at a global scale and 0.25 degree spatial resolution. Central to this methodology is the use of the Priestley and Taylor (PT) evaporation model. The minimalistic PT equation combines a small number of inputs, the majority of which can be detected from space. This reduces the number of variables that need to be modelled. Key distinguishing features of the approach are the use of microwave-derived soil moisture, land surface temperature and vegetation density, as well as the detailed estimation of rainfall interception loss. The modelled evaporation is validated against one year of eddy covariance measurements from 43 stations. The estimated annual totals correlate well with the stations annual cumulative evaporation (lt;igt;Rlt;/igt;=0.80, lt;igt;Nlt;/igt;=43) and present a low average bias ( 5%). The validation of the daily time series at each individual station shows good model performance in all vegetation types and climate conditions with an average correlation coefficient of lt;igt;lt;span style=text-decoration: overlinegt;Rlt;/spangt;lt;/igt;=0.83, still lower than the lt;igt;lt;span style=text-decoration: overlinegt;Rlt;/spangt;lt;/igt;=0.90 found in the validation of the monthly time series. The first global map of annual evaporation developed through this methodology is also presented.
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| [10] |
A parameterization of the evaporation from nonsaturated surfaces [J].https://doi.org/10.1175/1520-0450(1979)0182.0.CO;2 URL [本文引用: 1] 摘要
The parameterization of evaporation proposed by Priestley and Taylor (1972) is modified to take account of nonsaturated surfaces. It is suggested that evaporation can be expressed as a function of net radiation, air temperature, a constant related to the nature of the surface, and a variable that is dependent on moisture availability. The constant is equal to 1.26 for water and open grassland surfaces (as in Priestley and Taylor) but is nearer unity for some other surfaces. The variable is found to be directly related to near-surface soil moisture content for both bare and grassland surfaces.
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| [11] |
An application of the Ts-VI triangle method with enhanced edges determination for evapotranspiration estimation from MODIS data in arid and semi-arid regions:implementation and validation [J].https://doi.org/10.1016/j.rse.2009.10.012 URL [本文引用: 4] 摘要
The commonly applied surface temperature–vegetation index ( T s–VI) triangle method is used to estimate regional evapotranspiration (ET) in arid and semi-arid regions. A practical algorithm based on the T s–VI triangle method is developed to determine quantitatively the dry and wet edges of this triangle space. First, the T s–VI triangle method is reviewed. Assumptions involved in this method are highlighted, and advantages, disadvantages and applicability are discussed. Then, an experimental use of the T s–VI triangle method is developed and applied to several MODIS/TERRA datasets acquired during the Heihe Field Experiment from May 20th to August 21st, 2008. The sensible heat fluxes retrieved using MODIS data from a grassland located in the middle reach of Heihe river basin, Northwest China, are in good agreement with those measured from a Large Aperture Scintillometer (LAS). The Root Mean Square Error of this comparison is 25.07 W/m 2. It is shown that determination of dry and wet edges using the proposed algorithm is accurate enough at least in most cases of our study for the estimates of regional surface ET.
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| [12] |
Global estimates of the land-atmosphere water flux based on monthly AVHRR and ISLSCP-II data, validated at 16 Fluxnet sites [J].https://doi.org/10.1016/j.rse.2007.06.025 URL [本文引用: 1] 摘要
Numerous models of evapotranspiration have been published that range in data-driven complexity, but global estimates require a model that does not depend on intensive field measurements. The Priestley–Taylor model is relatively simple, and has proven to be remarkably accurate and theoretically robust for estimates of potential evapotranspiration. Building on recent advances in ecophysiological theory that allow detection of multiple stresses on plant function using biophysical remote sensing metrics, we developed a bio-meteorological approach for translating Priestley–Taylor estimates of potential evapotranspiration into rates of actual evapotranspiration. Five model inputs are required: net radiation ( R n), normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), maximum air temperature ( T max), and water vapor pressure (ea). Our model requires no calibration, tuning or spin-ups. The model is tested and validated against eddy covariance measurements (FLUXNET) from a wide range of climates and plant functional types—grassland, crop, and deciduous broadleaf, evergreen broadleaf, and evergreen needleleaf forests. The model-to-measurement r 2 was 0.90 (RMS = 1602mm/month or 28%) for all 16 FLUXNET sites across 202years (most recent data release). Global estimates of evapotranspiration at a temporal resolution of monthly and a spatial resolution of 1° during the years 1986–1993 were determined using globally consistent datasets from the International Satellite Land-Surface Climatology Project, Initiative II (ISLSCP-II) and the Advanced Very High Resolution Spectroradiometer (AVHRR). Our model resulted in improved prediction of evapotranspiration across water-limited sites, and showed spatial and temporal differences in evapotranspiration globally, regionally and latitudinally.
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| [13] |
Validation and Application of the Modified Satellite-Based Priestley-Taylor Algorithm for Mapping?Terrestrial Evapotranspiration [J].https://doi.org/10.3390/rs6010880 URL [本文引用: 2] 摘要
Satellite-based vegetation indices (VIs) and Apparent Thermal Inertia (ATI) derived from temperature change provide valuable information for estimating evapotranspiration (LE) and detecting the onset and severity of drought. The modified satellite-based Priestley-Taylor (MS-PT) algorithm that we developed earlier, coupling both VI and ATI, is validated based on observed data from 40 flux towers distributed across the world on all continents. The validation results illustrate that the daily LE can be estimated with the Root Mean Square Error (RMSE) varying from 10.7 W/m2 to 87.6 W/m2, and with the square of correlation coefficient (R2) from 0.41 to 0.89 (p lt; 0.01). Compared with the Priestley-Taylor-based LE (PT-JPL) algorithm, the MS-PT algorithm improves the LE estimates at most flux tower sites. Importantly, the MS-PT algorithm is also satisfactory in reproducing the inter-annual variability at flux tower sites with at least five years of data. The R2 between measured and predicted annual LE anomalies is 0.42 (p = 0.02). The MS-PT algorithm is then applied to detect the variations of long-term terrestrial LE over Three-North Shelter Forest Region of China and to monitor global land surface drought. The MS-PT algorithm described here demonstrates the ability to map regional terrestrial LE and identify global soil moisture stress, without requiring precipitation information.
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| [14] |
Using midday surface temperature to estimate daily evaporation from satellite thermal IR data [J].https://doi.org/10.1080/01431168308948554 URL [本文引用: 1] 摘要
The practical experience obtained by our participation in the European project TELLUS (a part of the HCMM programme) led us to state that the thermal inertia concept and sophisticated models are useful for understanding basic processes and for performing informative simulations, but cannot be used for a real estimation of evaporation
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| [15] |
An improved method for estimating global evapotranspiration based on satellite determination of surface net radiation, vegetation index, temperature, and soil moisture [J].https://doi.org/10.1109/IGARSS.2008.4779489 URL [本文引用: 2] 摘要
We proposed a method in an earlier study to estimate latent heat of evapotranspiration (ET). However, the influence of soil moisture (SM) on ET was not well considered and is addressed in this paper by incorporating the Diurnal land surface temperature (Ts) Range (DTsR). ET, measured at twelve sites in the U. S. during 2001-2006, is used to validate the improved method. Site land cover varies from grassland, native prairie, cropland, deciduous forest, to evergreen forest. The correlation coefficient between the measured and predicted 16-day daytime-average ET is about 0.92 for all the sites, the bias is -1.9 W m-2 and the Root Mean Square Error (RMSE) is 28.6 W m-2. We calculated global monthly ET from 1986 to 1995 at a spatial resolution of 1degtimes1deg from the International Satellite Land Surface Climatology Project (ISLSCP) Initiative II global interdisciplinary monthly dataset and compared it with the fifteen land surface model simulations of the Global Soil Wetness Project-2. The results of the comparison of 118 months global daily ET show that the bias is 4.5 W m-2, the RMSE is 19.8 W m-2 and the correlation coefficient is 0.82.
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| [16] |
Evaluation of EDI derived from the exponential evapotranspiration model for monitoring China’s surface drought [J].https://doi.org/10.1007/s12665-011-0972-5 URL [本文引用: 1] 摘要
Drought has become the most severe natural disaster in many provinces of China. In this paper, evaporative drought index (EDI) has been used to monitor China’s surface dryness conditions based on the exponential evapotranspiration (ET) model and Hargreaves equation from JAXA -MODIS Insolation products, GEWEX, NCEP-2 and MODIS NDVI data. The exponential ET model based on the surface net radiation, vegetation index, mean air temperature and diurnal air temperature range (DTaR) has been developed to estimate surface ET of China and has been independently validated using ground-measured data collected from two sites (Arou and Miyun) in China, indicating that the bias varies from 615.96 to 5.0202W/m 2 . The good agreement between daily estimated and ground-measured ET using ground observation data collected from all 22 sites further supports the validity of the exponential ET model for regional ET estimation. Moreover, EDI is closely correlated to the average soil moisture at 0–1002cm soil depth of the Yongning site with coefficient of determination of R 2 02=020.52. The spatio-temporal patterns of monthly ET and EDI from April to September of 2004 over China are explored and the result indicates EDI is accordant with the precipitation by comparing the 15-day smoothed EDI with precipitation over six representative sites. The EDI based on the exponential ET model by integrating energy fluxes in response to soil moisture stress has demonstrated its validity for monitoring China’s surface drought events.
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| [17] |
Using spatial context in satellite data to infer regional scale evapotranspiration [J].https://doi.org/10.1109/36.58983 URL [本文引用: 1] 摘要
Several methods have been used to estimate regional scale evapotranspiration from satellite thermal infrared measurements. These procedures assume knowledge of surface properties such as surface roughness, albedo, vegetation characteristics, etc. In many areas of the earth these parameters are not accurately known due to the rapidity of change of vegetation, lack of adequate geographical data b...
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| [18] |
An inter comparison of regional land heat flux estimation using remote sensing data [J].https://doi.org/10.1080/01431160210154821 URL [本文引用: 1] 摘要
The aerodynamic resistance energy balance residual method is widely used for surface latent heat flux estimation. In this study, we examine the theoretical background and implementation details of this methodology with respect to remote sensing data applications. The residual method requires estimation of aerodynamic resistance to heat transfer that necessitates the measurements of several ground-based observations including land surface vegetation height and surface wind speed. Consequently, it becomes very difficult to implement this method over large areas. A simple scheme is proposed for the distributed estimation of surface latent heat flux based on an interpretation of the triangle (or trapezoid) space of remotely sensed vegetation index and radiometric surface temperature. Two case studies using realistic remote sensing data over the southern Great Plains in the United States are presented to demonstrate the performance of both methods. Results suggest that the proposed method can achieve similar or better estimation of latent heat flux over large areas. The proposed method is well suited for distributed estimation of latent heat flux while the commonly used residual method is appropriate for site-specific estimation if detailed surface information is available.
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| [19] |
S-SEBI: A simple remote sensing algorithm to estimate the surface energy balance [J].https://doi.org/10.1016/S1464-1909(99)00128-8 URL [本文引用: 1] 摘要
ABSTRACT A small field campaign was conducted during August 1997 in the Piano di Rosia area in Tuscany, Italy. The terms of both the radiation balance and the surface energy balance were measured by several techniques and for several field sites. Together with a LANDSAT-TM scene of 23 August 1997 of the same area, these data give an excellent opportunity for a profound study of interaction between the radiation and energy fluxes from point to regional scale. A new method to derive the surface energy fluxes from remote sensing measurements, called the Simplified Surface Energy Balance Index (S-SEBI), is developed, tested and validated with the available data. If the atmospheric conditions over the area can be considered constant and the area reflects sufficient variations in surface hydrological conditions the fluxes can be calculated without any further information than the remote sensing image itself. The results of this case study show that with the relative simple S-SEBI method the surface energy balance parameters can be estimated with a high precision. The measured and estimated evaporative fraction values have a maximum relative difference of 8%.
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| [20] |
SEBAL model with remotely sensed data to improve water-resources management under actual field conditions [J].https://doi.org/10.1061/(ASCE)0733-9437(2007)133:4(380) URL [本文引用: 1] 摘要
Mapping evapotranspiration at high resolution with internalized calibration (METRIC) is a satellite-based image-processing model for calculating evapotranspiration (ET) as a residual of the surface energy balance. METRIC uses as its foundation the pioneering SEBAL energy balance process developed in The Netherlands by Bastiaanssen, where the near-surface temperature gradients are an indexed function of radiometric surface temperature, thereby eliminating the need for absolutely accurate surface temperature and the need for air-temperature measurements. The surface energy balance is internally calibrated using ground-based reference ET to reduce computational biases inherent to remote sensing-based energy balance and to provide congruency with traditional methods for ET. Slope and aspect functions and temperature lapsing are used in applications in mountainous terrain. METRIC algorithms are designed for relatively routine application by trained engineers and other technical professionals who possess a familiarity with energy balance and basic radiation physics. The primary inputs for the model are short-wave and long-wave (thermal) images from a satellite (e.g., Landsat and MODIS), a digital elevation model and ground-based weather data measured within or near the area of interest. ET aps (i.e., images) via METRIC provide the means to quantify ET on a field-by-field basis in terms of both the rate and spatial distribution. METRIC has some significant advantages over many traditional applications of satellite-based energy balance in that its calibration is made using reference ET, rather than the evaporative fraction. The use of reference ET for the extrapolation of instantaneous ET from periods of24hand longer compensates for regional advection effects by not tying the evaporative fraction to net radiation, since ET can exceed daily net radiation in many arid or semi-arid locations. METRIC has some significant advantages over conventional methods of estimating ET from crop coefficient curves in that neither the crop development stages, nor the specific crop type need to be known with METRIC. In addition, energy balance can detect reduced ET caused by water shortage.
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| [21] |
Satellite-Based Energy Balance for Mapping Evapotranspiration With Internalized Calibration (METRIC) -Model [J]. |
| [22] |
Comparison of three remote sensing based models to estimate evapotranspiration in an oasis-desert region [J].https://doi.org/10.1016/j.agwat.2015.12.001 URL [本文引用: 1] 摘要
Regional evapotranspiration (ET) estimation is crucial for regional water resources management and allocation. This paper evaluated the performance of three contextual remote sensing based models for ET estimation (METRIC—Mapping Evapotranspiration at High Resolution with Internalized Calibration; the T s -VI triangle model; and SSEB-Simplified Surface Energy Balance) in an oasis-desert region during a growing season under advective environmental conditions. The performance of the three models was first assessed using surface fluxes observed at five eddy covariance (EC) flux towers installed in different land-cover types. Comparisons among model outputs were then conducted on a pixel-by-pixel basis for three main land-cover types (farmland, transition zone and desert). For METRIC and SSEB, good correlations were obtained between the modeled versus measured instantaneous latent heat flux ( λ ET), with both R 2 values above 0.90. Outliers occurred when available energy was overestimated for the T s -VI triangle model. Pixel-wise comparisons showed the greatest consistency between the T s -VI triangle model and METRIC outputs in farmland with an R 2 of 0.98 and an RMSE of 13.6902W02m 612 . Overall, METRIC outperformed both the T s -VI triangle and SSEB models; the T s -VI triangle model tended to overestimate and the SSEB to underestimate at higher values of λ ET. ET estimations by SSEB and the T s -VI triangle model are more sensitive to the estimated surface temperature and available energy than those from METRIC. Two daily ET extrapolation methods were evaluated with the EC measured daily ET . The results indicated that the constant reference ET fraction (ET r F) method could be used over well-watered areas due to the regional advection effect; the constant evaporative fraction (EF) method tended to give better outputs for other areas. Reasonable estimates of ET can be achieved by carefully selecting extreme pixels or edges, and validation is required when applying remote sensing based models, especially the contextual methods.
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| [23] |
The Surface Energy Balance System (SEBS) for estimation of turbulent heat fluxes [J].https://doi.org/10.5194/hess-6-85-2002 URL [本文引用: 1] 摘要
A Surface Energy Balance System (SEBS) is proposed for the estimation of atmospheric turbulent fluxes and evaporative fraction using satellite earth observation data, in combination with meteorological information at proper scales. SEBS consists of: a set of tools for the determination of the land surface physical parameters, such as albedo, emissivity, temperature, vegetation coverage etc., from spectral reflectance and radiance measurements; a model for the determination of the roughness length for heat transfer; and a new formulation for the determination of the evaporative fraction on the basis of energy balance at limiting cases. Four experimental data sets are used to assess the reliabilities of SEBS. Based on these case studies, SEBS has proven to be capable to estimate turbulent heat fluxes and evaporative fraction at various scales with acceptable accuracy. The uncertainties in the estimated heat fluxes are comparable to in-situ measurement uncertainties. Keywords: Surface energy balance, turbulent heat flux, evaporation, remote sensing
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| [24] |
Estimations of regional surface energy fluxes over heterogeneous oasis-Desert surfaces in the middle reaches of the Heihe River during HiWATER-MUSOEXE [J].https://doi.org/10.1109/LGRS.2014.2356652 URL [本文引用: 1] 摘要
The determination of the spatial heterogeneity of the regional evapotranspiration over a complex underlying surface in an oasis-desert region is crucial for water resource management in a river basin and aiding in irrigation decisions. The surface energy balance system (SEBS) model has been widely used to estimate surface energy fluxes. However, the parameterization of surface roughness length for momentum transfer (z0m) and heat transfer (z0h) did not perform well for a complex underlying surface. Moreover, it is difficult to estimate surface soil heat flux, i.e., G0, accurately at the regional scale. In this letter, the parameterization schemes of z0m, z0h, and G0 were optimized. Measurements from 21 sets of eddy covariance systems were used to validate the model performance. The results show that the revised SEBS model root-mean-square errors (RMSEs) of the satellite-based sensible and latent heat fluxes (H and LE) decreased from 97.2 W · m-2 to 56.9 W · m-2 and from 102.9 W · m-2 to 74.8 W · m-2, respectively, at the footprint scale. At the pixel scale, the RMSEs of the revised model estimates of the H and LE were 40.9 W · m-2 and 57.5 W · m-2, respectively. The improved agreements between the estimates and the measurements indicate that the revised SEBS model is appropriate for estimating regional energy fluxes over heterogeneous oasis-desert surfaces. Furthermore, the spatial and temporal patterns of the LE in the middle reaches of the Heihe River were investigated.
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| [25] |
Source approach for estimating soil and vegetation energy fluxes in observations of disectional radiometric surface temperature [J].https://doi.org/10.1016/0168-1923(95)02265-Y URL [本文引用: 1] 摘要
A two-layer model of turbulent exchange that includes the view geometry associated with directional radiometric surface temperature is developed and evaluated by comparison of model predictions with field measurements. Required model inputs are directional brightness temperature and its angle of view, fractional vegetation cover or leaf area index, vegetation height and approximate leaf size, net radiation, and air temperature and wind speed. One advantage of the approach described in this paper is that directional brightness temperatures are considered so that the model should have wider applicability than single-layer models, and it opens the possibility of a simple solution if directional measurements are available from two substantially different view angles. Comparisons with several hundred measurements from two large-scale field experiments were performed. One study was conducted in a semiarid rangeland environment in Southern Arizona (Monsoon '90) while the other was conducted in a subhumid environment, namely the tall grass prairie in Eastern Kansas (FIFE). For the Monsoon '90 site, root-mean-square-differences (RMSD) between model predictions and measurements were between 35 and 60 W m 2 for soil, sensible and latent heat flux. With the FIFE site data RMSD values were between 50 and 60 W m 2 . The larger scatter with the FIFE data was mainly caused by the model having difficulty reproducing the fluxes for the observation period with dormant vegetation. Considerations of the expected variability associated with flux measurements over complex surfaces suggests that model-derived fluxes were in acceptable agreement with the observations. However refinements in formulations of soil heat flux probably would improve agreement between model predictions and measurements.
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| [26] |
Two-source energy balance model to calculate E, T, and ET: comparison of Priestley-Taylor and Penman-Monteith formulations and two time scaling methods [J].https://doi.org/10.13031/trans.57.10423 URL [本文引用: 1] 摘要
Abstract. The two-source energy balance (TSEB) model calculates the energy balance of the soil-canopy-atmosphere continuum, where transpiration is initially determined by the Priestley-Taylor equation. The TSEB was revised recently using the Penman-Monteith equation to replace the Priestley-Taylor formulation, thus better accounting for the impact of large and varying vapor pressure deficits (VPD) typical of advective, semiarid climates. This study is a comparison of the Priestley-Taylor and Penman-Monteith versions of the TSEB (termed TSEB-PT and TSEB-PM, respectively). Evaporation (E), transpiration (T), and evapotranspiration (ET) calculated by the TSEB-PT and TSEB-PM versions were compared to measurements obtained with microlysimeters, sap flow gauges, and weighing lysimeters, respectively, for fully irrigated cotton (Gossypium hirsutum L.) at Bushland, Texas. Radiometric surface temperature (TR) was used to calculate E, T, and ET in both TSEB versions in 15 min intervals and summed to intervals coinciding with times of measurements. In addition, a one-time-of-day TR measurement was used (9:45, 11:15, 12:45, 14:15, or 15:45 CST), and E, T, and ET were calculated for the appropriate measurement interval (i.e., daytime, nighttime, and 24 h) using the time scaling methods based on reference ET (TSCET) and reference temperature (TSCTEMP). Measured average values of E, T, and ET during the study period were 0.94 mm (24 h), 6.9 mm (7:00 to 22:00 CST), and 7.2 mm (24 h), respectively. The TSEB-PT consistently overestimated E and underestimated T, with RMSE/MBE of up to 2.8/1.8 mm and 4.1/-3.9 mm, respectively. In comparison, the TSEB-PM greatly reduced discrepancies between calculations and measurements, with respective RMSE/MBE for E and T of only up to 1.5/0.79 mm and 1.3/ 0.76 mm, respectively. For 24 h ET, the TSEB-PT resulted in maximum RMSE/MBE of 3.2/-1.9 mm, and the TSEB-PM had maximum RMSE/MBE of 1.7/0.95 mm. Daytime ET model agreement was very similar for both model versions (RMSE/MBE usually <1.1/< 1.0 mm). However, the TSEB-PT consistently calculated negative nighttime ET of up to -2.0 mm. Summed 15 min calculations generally had better agreement with measurements than did the TSCET or TSCTEMP methods, and results did not greatly differ for TSCET or TSCTEMP. Both time scaling methods were not very sensitive to the TR measurement time used, although morning (9:45 CST) TR measurement times did not perform as well as the other times.
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| [27] |
Applications of a thermal-based two-source energy balance model using priestley-taylor approach for surface temperature partitioning under advective conditions [J].https://doi.org/10.1016/j.jhydrol.2016.06.034 URL [本文引用: 1] 摘要
In this study ground measured soil and vegetation component temperatures and composite temperature from a high spatial resolution thermal camera and a network of thermal-IR sensors collected in an irrigated maize field and in an irrigated cotton field are used to assess and refine the component temperature partitioning approach in the Two-Source Energy Balance (TSEB) model. A refinement to TSEB using a non-iterative approach based on the application of the Priestley-Taylor formulation for surface temperature partitioning and estimating soil evaporation from soil moisture observations under advective conditions (TSEB-A) was developed. This modified TSEB formulation improved the agreement between observed and modeled soil and vegetation temperatures. In addition, the TSEB-A model output of evapotranspiration (ET) and the components evaporation (E), transpiration (T) when compared to ground observations using the stable isotopic method and eddy covariance (EC) technique from the HiWATER experiment and with microlysimeters and a large monolithic weighing lysimeter from the BEAREX08 experiment showed good agreement. Difference between the modeled and measuredETmeasurements were less than 10% and 20% on a daytime basis for HiWATER and BEAREX08 data sets, respectively. The TSEB-A model was found to accurately reproduce the temporal dynamics ofE,TandETover a full growing season under the advective conditions existing for these irrigated crops located in arid/semi-arid climates. With satellite data this TSEB-A modeling framework could potentially be used as a tool for improving water use efficiency and conservation practices in water limited regions. However, TSEB-A requires soil moisture information which is not currently available routinely from satellite at the field scale.
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| [28] |
Application of remote sensing-based two-source energy balance model for mapping field surface fluxes with composite and component surface temperatures [J].https://doi.org/10.1016/j.agrformet.2016.01.005 URL [本文引用: 1] 摘要
Operational application of a remote sensing-based two source energy balance model (TSEB) to estimate evaportranspiration ( ET ) and the components evaporation ( E ), transpiration ( T ) at a range of space and time scales is very useful for managing water resources in arid and semiarid watersheds. The TSEB model uses composite land surface temperature as input and applies a simplified Priestley aylor formulation to partition this temperature into soil and vegetation component temperatures and then computes subsequent component energy fluxes. The remote sensing-based TSEB model using component temperatures of the soil and canopy has not been adequately evaluated due to a dearth of reliable observations. In this study, soil and vegetation component temperatures partitioned from visible and near infrared and thermal remote sensing data supplied by advanced scanning thermal emission and reflection radiometer (ASTER) are applied as model inputs (TSEB CT ) to assess and refine the subsequent component energy fluxes estimation in TSEB scheme under heterogeneous land surface conditions in an advective environment. The model outputs including sensible heat flux ( H ), latent heat flux ( LE ), component LE from soil and canopy from the TSEB CT and original model (TSEB PT ) are compared with ground measurements from eddy covariance (EC) and larger aperture scintillometers (LAS) technique, and stable isotopic method. Both model versions yield errors of about 10% with LE observations. However, the TSEB CT model output of H and LE are in closer agreement with the observations and is found to be generally more robust in component flux estimation compared to the TSEB PT using the ASTER data in this heterogeneous advective environment. Thus given accurate soil and canopy temperatures, TSEB CT may provide more reliable estimates of plant water use and values of water use efficiency at large scales for water resource management in arid and semiarid landscapes.
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| [29] |
Two improvements of an operational Two-Layer Model for terrestrial surface heat flux retrieval [J].https://doi.org/10.3390/s8106165 URL PMID: 3707444 [本文引用: 1] 摘要
In order to make the prediction of land surface heat fluxes more robust, two improvements were made to an operational two-layer model proposed previously by Zhang. These improvements are: 1) a surface energy balance method is used to determine the theoretical boundary lines (namely 0104000000true wet/cool edge0104000064 and 0104000000true dry/warm edge0104000064 in the trapezoid) in the scatter plot for the surface temperature versus the fractional vegetation cover in mixed pixels; 2) a new assumption that the slope of the Tm 01040000“ f curves is mainly controlled by soil water content is introduced. The variables required by the improved method include near surface vapor pressure, air temperature, surface resistance, aerodynamic resistance, fractional vegetation cover, surface temperature and net radiation. The model predictions from the improved model were assessed in this study by in situ measurements, which show that the total latent heat flux from the soil and vegetation are in close agreement with the in situ measurement with an RMSE (Root Mean Square Error) ranging from 30 w/m2~50 w/m2,which is consistent with the site scale measurement of latent heat flux. Because soil evaporation and vegetation transpiration are not measured separately from the field site, in situ measured CO2 flux is used to examine the modeled 01050003Eveg. Similar trends of seasonal variations of vegetation were found for the canopy transpiration retrievals and in situ CO2 flux measurements. The above differences are mainly caused by 1) the scale disparity between the field measurement and the MODIS observation; 2) the non-closure problem of the surface energy balance from the surface fluxes observations themselves. The improved method was successfully used to predict the component surface heat fluxes from the soil and vegetation and it provides a promising approach to study the canopy transpiration and the soil evaporation quantitatively during the rapid growing season of winter wheat in northern China.
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| [30] |
A Two-source Trapezoid Model for Evapotranspiration (TTME) from satellite imagery [J].https://doi.org/10.1016/j.rse.2012.02.015 URL [本文引用: 1] 摘要
78 A Two-source Trapezoid Model for ET (TTME) from satellite imagery is developed. 78 Theoretical boundaries of evaporative fraction (EF) in the fc-Trad space are derived. 78 Trad of a pixel is decomposed based on soil surface moisture availability isopleths. 78 TTME reproduces latent heat flux and EF of MAPD within ~10%.
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| [31] |
The three-temperature model to estimate evapotranspiration and its partitioning at multiple scales: A review [J].https://doi.org/10.13031/trans.59.11087 URL [本文引用: 1] 摘要
Abstract Remotely estimating evapotranspiration (ET) and partitioning of its two components, soil evaporation (E) and vegetation transpiration (T), have been challenges for ET studies and their applications. In this study, we reviewed the three-temperature model (3T model) and its applications for thermal remote sensing under multi-scale conditions. There are two submodels in the 3T model: the soil evaporation submodel and the vegetation transpiration submodel. E and T can be separately estimated with these two submodels, and then ET can be obtained by putting E and T together. One of the most significant advantages of the 3T model is that only a minimum number of parameters are required. The necessary parameters for E estimation are net radiation, soil heat flux, surface temperature (drying soil and dry soil), and air temperature, while the parameters for T estimation are net radiation, surface temperature (canopy and dry canopy), and air temperature. Verifications and applications were carried out using ground-based and space-based thermal remote sensing from chamber scale to catchment scale. Verifications were carried out by comparing the estimated results with estimated ET from the Penman-Monteith method and measured ET from weighing lysimeter, Bowen ratio, eddy covariance, and water budget methods. Results showed that the "3T model + thermal remote sensing" approach is a reliable and practical method for remotely estimating ET, especially in arid and semi-arid regions. Therefore, it can be applicable for irrigation water management, water and energy budget monitoring, thermal environment monitoring and evaluation, and other applications. 2016 American Society of Agricultural and Biological Engineers.
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| [32] |
A novel method for extracting green fractional vegetation cover from digital images [J].https://doi.org/10.1111/j.1654-1103.2011.01373.x URL [本文引用: 2] 摘要
QuestionAlthough digital photography is an efficient and objective means of extracting green fractional vegetation cover (FVC), it lacks automation and classification accuracy. How can green FVC be extracted from digital images in an accurate and automated method?MethodsSeveral colour spaces were compared on the basis of a separability index, and CIE L*a*b* was shown to be optimal for the tested colour spaces. Thus, all image processing was performed in CIE L*a*b* colour space. Gaussian models were used to fit the green vegetation and background distributions of the a* component. Three strategies (T0, T1 and T2 thresholding method) were tested to select the optimal thresholds for segmenting the image into green vegetation and non-green vegetation. The a* components of the images were then segmented and the green FVC extracted.ResultsThe FVC extracted using T0, T1, and T2 thresholding methods were evaluated with simulated images, and cross-validated with FVC extracted with supervised classification methods. The results show that FVC extracted with T0, T1 and T2 thresholding methods are similar to those estimated with supervised classification methods. The mean errors associated with the FVC values provided in our approach and supervised classification are less than 0.035. In a test with simulated data, our method performed better than the supervised classification method.ConclusionsMethods presented in this paper were demonstrated to be feasible and applicable for automatically and accurately extracting FVC of several green vegetation types with varying background and shadow conditions. However, our algorithm design assumes a Gaussian distribution for both vegetated and non-vegetated portions of a digital image; moreover, the impact of view angle on the FVC extraction from digital images must also be considered.
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| [33] |
Evidence for decadal variation in global terrestrial evapotranspiration between 1982 and 2002: 2. Results [J].https://doi.org/10.1029/2010JD013847 URL [本文引用: 2] |
| [34] |
Bayesian multimodel estimation of global terrestrial latent heat flux from eddy covariance, meteorological, and satellite observations [J].https://doi.org/10.1002/2013JD020864 URL [本文引用: 3] 摘要
for crop and grass sites, and by more than 6 W/m for forest, shrub, and savanna sites. The average coefficients of determination () increased by approximately 0.05 for most sites. To test the BMA method for regional mapping, we applied it for MODIS data and GMAO-MERRA meteorology to map annual global terrestrial LE averaged over 2001–2004 for spatial resolution of 0.05°. The BMA method provides a basis for generating a long-term global terrestrial LE product for characterizing global energy, hydrological, and carbon cycles.
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| [35] |
非参数化蒸散发估算方法在黑河流域的适用性分析 [J].https://doi.org/10.7522/j.issn.1000-0534.2014.00124 URL Magsci [本文引用: 1] 摘要
<p>陆面蒸散发是水循环过程中的重要组成部分,直接关系到地表的能量和水量平衡。基于哈密顿原理的非参数化蒸散发估算方法能够避免复杂的参数化过程,降低计算过程的不确定性。首先,利用非参数化方法估算了黑河流域不同下垫面的蒸散发,并利用地面观测数据进行了验证,分析了非参数化方法在不同下垫面和不同季节的适用性。对不同下垫面的验证结果表明,在湿润下垫面该方法会低估实际蒸散发,在干旱下垫面会高估实际蒸散发;对不同季节的验证结果表明,夏季蒸散发估算精度明显优于冬季。其次,进一步对非参数化方法进行了敏感性分析:在湿润下垫面,地表净辐射通量对估算结果影响较大;在干旱下垫面,地表净辐射通量和地表温度对非参数化估算方法结果影响较大。最后,利用非参数化方法结合遥感数据和大气驱动数据估算了黑河流域中上游的区域蒸散发,并利用地面观测数据结合足迹模型进行了验证,分析了非参数化方法估算区域蒸散发的适用性,估算结果能够反映该区域地表通量的分布特征,但是与地面观测数据相比存在一定的误差,不同下垫面的均方根误差在50~100 W·m<sup>-2</sup>之间。</p>
Applicability analysis of nonparametric evapotranspiration approach over Heihe River Basin .https://doi.org/10.7522/j.issn.1000-0534.2014.00124 URL Magsci [本文引用: 1] 摘要
<p>陆面蒸散发是水循环过程中的重要组成部分,直接关系到地表的能量和水量平衡。基于哈密顿原理的非参数化蒸散发估算方法能够避免复杂的参数化过程,降低计算过程的不确定性。首先,利用非参数化方法估算了黑河流域不同下垫面的蒸散发,并利用地面观测数据进行了验证,分析了非参数化方法在不同下垫面和不同季节的适用性。对不同下垫面的验证结果表明,在湿润下垫面该方法会低估实际蒸散发,在干旱下垫面会高估实际蒸散发;对不同季节的验证结果表明,夏季蒸散发估算精度明显优于冬季。其次,进一步对非参数化方法进行了敏感性分析:在湿润下垫面,地表净辐射通量对估算结果影响较大;在干旱下垫面,地表净辐射通量和地表温度对非参数化估算方法结果影响较大。最后,利用非参数化方法结合遥感数据和大气驱动数据估算了黑河流域中上游的区域蒸散发,并利用地面观测数据结合足迹模型进行了验证,分析了非参数化方法估算区域蒸散发的适用性,估算结果能够反映该区域地表通量的分布特征,但是与地面观测数据相比存在一定的误差,不同下垫面的均方根误差在50~100 W·m<sup>-2</sup>之间。</p>
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| [36] |
Estimation of evapotranspiration using a nonparametric approach under all sky: Accuracy evaluation and error analysis [J].https://doi.org/10.1109/JSTARS.2017.2707586 URL [本文引用: 1] 摘要
Accurate estimation of regional evapotranspiration (ET) or latent heat flux (latent energy, LE) remains a challenge. On the basis of a nonparametric approach, this study proposed an all-sky algorithm based on moderate-resolution imaging spectroradiometer (MODIS) products and datasets of China Meteorological Administration Land Data Assimilation System (CLDAS). Eddy covariance observations from three nonvegetated sites (desert, Gobi, and village) and three vegetated sites (orchard, vegetable, and wetland) over an arid/semiarid region were used as references to validate the new algorithm. Results showed that the spatial and temporal patterns of LE coincided with desert–oasis ecosystems. Comparison of the retrieved and reference values yielded the following results: R2 = 0.19–0.63, bias = 61129–56 W/m2, relative error (RE) = 5%–29%, and root-mean-square error (RMSE) = 95–150 W/m2. Remote-sensing-retrieved LE (RSLE) exhibited relatively good accuracy and poor agreement with ground observations at the nonvegetated sites (RE: 5%–23%, R2: 0.19–0.40), whereas contradicting scenario occurred at the vegetated sites (RE: 24%–29%, R2: 0.46–0.63). In the arid nonvegetated region, the ET error might have been caused by net radiation, soil heat flux, land surface temperature, and air temperature. In the vegetated region, the errors of MODIS and CLDAS products were not the dominant error sources of RSLE. The validation supported the applicability of the proposed algorithm in the arid/semiarid region.
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| [37] |
State and parameter update in a coupled energy/hydrologic balance model using ensemble Kalman filtering [J].https://doi.org/10.1016/j.jhydrol.2011.11.049 URL [本文引用: 2] 摘要
The capability to accurately monitor and describe daily evapotranspiration (ET) in a cost effective manner is generally attributed to hydrological models. However, continuous solution of energy and water balance provides precise estimations only when a detailed knowledge of sub-surface characteristics is available. On the other hand, residual surface energy balance models, based on remote observation of land surface temperature, are characterised by sufficient accuracy, but their applicability is limited by the lack of high frequency and high resolution thermal data. A compromise between these two methodologies is represented by the use of data assimilation scheme to include sparse remote estimates of surface fluxes into continuous modelling. This paper aims to test the combined use of coupled energy/water budget model and data assimilation schemes to assess daily evapotranspiration at field scale in a typical Mediterranean environment characterised by sparse olive trees. The continuous model was applied at hourly scale using remote multispectral images in the short-wave and standard meteorological information. The model was validated by means of contextual micro-meteorological information adopting the best available parameterisation (including root zone depth). The validation suggests an accuracy of about 35 W m 612 for the hourly turbulent fluxes and of about 0.3–0.4 mm d 611 for the daily ET. Successively, two data assimilation schemes based on the ensemble version of the Kalman filter were tested under the hypothesis of absence of information about the root zone depth. The application of a dual state-parameter filter (2EnKF) allows to obtain results very close to the ‘optimal’ ones independently from the value adopted as initial of root zone depth. Moreover, these results were obtained both by assimilating synthetic ‘perfect’ observations and ‘real’ remotely-derived estimations of latent heat flux. The methodology, which combines a coupled energy/water budget model and a dual state-parameter assimilation scheme, seems to be suitable to provide precise estimations of daily ET also when information on root zone depth are absent or not enough accurate.
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| [38] |
Nistor I et al. Review of the Kalman type hydrological data assimilation [J].https://doi.org/10.1080/02626667.2015.1127376 URL [本文引用: 5] 摘要
There is great potential in Data Assimilation (DA) for the purposes of uncertainty identification, reduction and real-time correction of hydrological models. This paper reviews the latest developments in Kalman filters (KFs), particularly the Extended KF (EKF) and the Ensemble KF (EnKF) in hydrological DA. The hydrological DA targets, methodologies and their applicability are examined. The recent applications of the EKF and EnKF in hydrological DA are summarized and assessed critically. Furthermore, this review highlights the existing challenges in the implementation of the EKF and EnKF, especially error determination and joint parameter estimation. A detailed review of these issues would benefit not only the Kalman-type DA but also provide an important reference to other hydrological DA types.Editor D. Koutsoyiannis; Associate editor F. Pappenberger
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| [39] |
Estimation of surface heat flux and an index of soil moisture using adjoint-state surface energy balance [J].https://doi.org/10.1029/1999WR900140 URL [本文引用: 1] 摘要
Estimates of surface heat flux and an index of the surface control over evaporation are made based on radiometric observations of ground temperature. A variational data assimilation approach is used to include surface energy balance in the estimation procedure as a physical constraint (the adjoint technique). This technique formulates the estimation problem as a minimization of ground temperature forecast misfits against observations. The surface energy balance equation is incorporated as a physical constraint. Applications to the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) are presented. The procedure estimates of the surface control over latent heat flux match those values based on independent latent heat flux measurements. The estimates of surface heat flux, when compared with measurements, have a root-mean-square error of 20 W m. The need to discriminate between soil wetness and aerodynamic contributions to the surface control over evaporation is recognized.
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| [40] |
Sampling strategies and assimilation of ground temperature for the estimation of surface energy balance components [J].https://doi.org/10.1109/36.898678 URL [本文引用: 1] 摘要
The performance of a land data assimilation system for surface ground temperature sensing is demonstrated for the U.S. Southern Great Plains 1997 Hydrologic Field Experiment. Adjoint state formulation is used in a variational scheme to minimize the error of surface ground temperature predictions subject to constraints imposed by the system model. It is shown that continuous sampling of observations result in accurate estimation of the components of the surface energy balance and an index of soil moisture. Experiments on the effects of sparse temporal sampling (near the mean of minimum and maximum in the diurnal cycle) on the estimation show that observations at the peak of the diurnal cycle is the most suitable for the land data assimilation system. It is suggested that surface ground temperature within a ~3 h window centered on this time in the diurnal cycle contains information on the cumulative heating and available energy partitioning at the land surface
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| [41] |
Estimation of surface turbulent fluxes through assimilation of radiometric surface temperature sequences [J].https://doi.org/10.1175/1525-7541(2004)005<0145:EOSTFT>2.0.CO;2 URL [本文引用: 1] |
| [42] |
Utility of assimilating surface radiometric temperature observations for evaporative fraction and heat transfer coefficient retrieval [J].https://doi.org/10.1007/s10546-004-2121-0 URL [本文引用: 2] 摘要
Recent advances in land data assimilation have yielded variational smoother techniques designed to solve the surface energy balance based on remote observations of surface radiometric temperature. These approaches have a number of potential advantages over existing diagnostic models, including the ability to make energy flux predictions between observation times and reduced requirements for ancillary parameter estimation. Here, the performance of a recently developed variational smoother approach is examined in detail over a range of vegetative and hydrological conditions in the southern U.S.A. during the middle part of the growing season. Smoother results are compared with flux tower observations and energy balance predictions obtained from the two-source energy balance model (TSM). The variational approach demonstrates promise for flux retrievals at dry and lightly vegetated sites. However, results suggest that the simultaneous retrieval of both evaporative fraction and turbulent transfer coefficients by the variational approach will be difficult for wet and/or heavily vegetated land surfaces. Additional land surface information (e.g. leaf area index ( L AI ) or the rough specification of evaporative fraction bounds) will be required to ensure robust predictions under such conditions. The single-source nature of the variational approach also hampers the physical interpretation of turbulent transfer coefficient retrievals. Intercomparisons between energy flux predictions from the variational approach and the purely diagnostic TSM demonstrate that the relative accuracy of each approach is contingent on surface conditions and the accuracy with which L AI values required by the TSM can be estimated.
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| [43] |
Variational assimilation of land surface temperature and the estimation of surface energy balance components [J].https://doi.org/10.1016/j.jhydrol.2012.12.039 URL [本文引用: 2] 摘要
Recently, numerous studies have focused on the estimation of surface energy flux components, based on the assimilation of land surface temperature (LST) within a variational data assimilation (VDA) framework. Unlike the previous investigations based on the force-restore equation, in this study, the full heat diffusion equation is employed in the VDA scheme as an adjoint (constraint). In addition, a model error term is added to the surface energy balance (SEB) equation and the VDA scheme to include the model uncertainty. Both VDA schemes (with and without the model uncertainty) are tested over the First International Satellite Land Surface Climatology Project Field Experiment (FIFE) site. The comprehensive comparisons between the present model (with heat diffusion equation) and previous model (with the force-restore equation) demonstrate that the present model will decrease the phase error associated with the ground heat flux diurnal cycle, and improve the evaporative fraction and heat fluxes estimation. The numerical examples also conclude that the errors caused by model structures and noisy data in the SEB equation can be detected and quantified in the present model (with model uncertainty).
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| [44] |
Estimation of large-scale evaporation fields based on assimilation of remotely sensed land temperature [J].https://doi.org/10.1029/2006WR005574 URL [本文引用: 2] 摘要
Many Earth system science and environmental applications require knowledge of mapped evaporation. Satellite remote sensing can indirectly provide these measurements with a spatial coverage that is logistically and economically impossible to obtain through ground-based observation networks. Here a model for surface energy fluxes estimation based on the assimilation of land surface temperature from satellite is presented. The data assimilation scheme provides a useful framework that allows us to combine measurements and models to produce an optimal and dynamically consistent estimate of the evolving state of the system. The assimilation scheme can take advantage of the synergy of multisensor-multiplatform observations in order to obtain estimations of surface fluxes, flux partitioning, and surface characteristics. The model is based on the surface energy balance and bulk transfer formulation. A simplified soil wetness model, which is a filter of antecedent precipitation, is introduced in order to develop a more robust estimation scheme. This approach is implemented and tested over the Southern Great Plain field experiment domain. Comparisons with observed surface energy fluxes and soil moisture maps have shown that this assimilation system can estimate, when compared with the ground truth observations, the surface energy balance and its partitioning among turbulent heat fluxes. The introduction of the simplified soil wetness model forced by precipitation data improved evaporative fraction estimation. Further research is still required to analyze the reliability of retrieved fluxes in periods where radiation is the limiting factor for latent heat flux.
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