干旱区研究

干旱区研究 >

2018 , Vol. 35 >Issue 3: 597 - 605

DOI: https://doi.org/10.13866/j.azr.2018.03.12

气候环境

新疆地区遥感、融合和陆面模式模拟的蒸散产品的不确定性分析

展开
  • （1．中国科学院新疆生态与地理研究所荒漠与绿洲生态国家重点实验室，新疆 乌鲁木齐 830011；2．中国科学院大学，北京 100049）
崔俊杰（1992-），女，硕士研究生，主要从事陆面模式和遥感蒸散产品的应用. E-mail：cuijunjie15@mails.ucas.ac.cn

收稿日期: 2017-10-13

  修回日期: 2017-11-01

  网络出版日期: 2018-06-01

基金资助

国家自然科学基金委员会-新疆联合基金“本地优秀青年人才培养专项”（U1403382）；新疆维吾尔自治区重点实验室开放课题（2016D03004）资助

收起

Uncertainty of Evapotranspiration Products Based on Fusion of Multi-source Remote Sensing Data and Land Surface Modes in Xinjiang

Expand
  • （1. State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China;2. University of Chinese Academy of Sciences, Beijing 100049, China）

Received date: 2017-10-13

  Revised date: 2017-11-01

  Online published: 2018-06-01

Fold

摘要

蒸散是干旱区水资源消耗的主要方式，由于该地区地表植被覆盖稀疏且空间异质性较大，目前国际常用的众多蒸散产品的结果存在较大差异。故选取中分辨率成像光谱仪（MOD16）蒸散产品、全球陆地蒸散阿姆斯特丹模型（Global Land Evapotranspiration Amsterdam Model，GLEAM）和通用陆面模式（Common Land Model，CoLM）的蒸散产品为代表，利用三角帽（Three Cornered Hat，TCH）方法定量评价3种蒸散产品在新疆干旱区模拟结果的空间不确定性。结果表明：GLEAM和MOD16蒸散产品的空间分布规律相似，山区蒸散值均显著高于平原区；CoLM在阿勒泰山、天山蒸散值显著高于平原区。此外，全疆多年平均蒸散值分别为：GLEAM[（142.36±11.11）mm·a-1]、CoLM[（126.66±19.12）mm·a-1]、MOD16[（78.64±4.61）mm·a-1]。基于TCH方法的全疆蒸散模拟的不确定性结果大小依次为：CoLM（24.18 mm·a-1），GLEAM蒸散产品（21.58 mm·a-1），MOD16蒸散产品（17.66 mm·a-1）。在灌丛，山地半干旱区和山地半湿润区，3种蒸散产品的不确定性显著不同，其中CoLM不确定性最大（33.47 mm·a-1、30.46 mm·a-1、32.11 mm·a-1），MOD16不确定性最小（9.50 mm·a-1、14.80 mm·a-1、14.34 mm·a-1）。量化新疆地区蒸散的不确定性为更加准确估算该地的蒸散有着重要的科学意义。

关键词： 不确定性分析; 蒸散量; TCH方法; 陆面模式; 遥感模型; 新疆地区

本文引用格式

崔俊杰，白洁，郑磊，李玉珍，赵洪飞，袁秀亮，李龙辉 . 新疆地区遥感、融合和陆面模式模拟的蒸散产品的不确定性分析[J]. 干旱区研究, 2018 , 35(3) : 597 -605 . DOI: 10.13866/j.azr.2018.03.12

Abstract

Evapotranspiration (ET) is an indispensable part of water resources consumption in arid region, and it is also one of the key indicators used for assessing water resources. As the vegetation here is extremely sparse and has relatively high spatial heterogeneity, it is a challenge to accurately estimate ET in arid region. Most of the common ET products based on fusion of multi-source remote sensing data and land surface modes showed the different ET results in arid region. The results of different ET products with eddy covariance (EC) measurements were generally compared in previous studies, but the issues of spatial scale mismatch between EC data and ET products are unresolved yet. It is difficult to obtain the true values of ET in large scale. The sources of uncertainty may be from the different model structures, calculation methods, forcing datasets, and so on. In this paper, three Cornered Hat (TCH) methods without requiring a priori knowledge of the observed ET values were used to estimate the uncertainties of ET output in Xinjiang based on the Common Land Model (CoLM), Global Land Evapotranspiration Amsterdam Model (GLEAM) and Moderate Resolution Imaging Spectroradiometer ET products (MOD16). The results showed that the spatial patterns of GLEAM and MOD16 ET products were similar, and the ET values in the mountains were significantly higher than that in the plains. The ET values of CoLM in the Altay and Tianshan mountains were significantly higher than that in the plains. In addition, the mean annual ET values in Xinjiang during the period from 2000 to 2014 differed markedly, and they were 142.36±11.11 mm·a-1, 126.66±19.12 mm•a-1 and 78.64±4.61 mm·a-1 obtained by the GLEAM, CoLM and MOD16 respectively. The CoLM and MOD16 products revealed that there was no significant decrease trend in ET during the period from 2000 to 2014 (-1.03 mm•a-1 and -0.24 mm•a-1 respectively, P> 0.05). The GLEAM product showed that there was no significant increase trend in ET (0.02 mm·a-1, P> 0.05). The uncertainty based on the TCH method of CoLM was the highest (24.18 mm•a-1) in Xinjiang, that based on the GLEAM was moderate (21.58 mm•a-1), and that based on the MOD16 was the lowest (17.66 mm•a-1). In the shrub lands, Tianshan Mountains and semi-humid region, the uncertainties of CoLM (33.47, 30.46 and 32.11 mm/a) were significantly higher than those of GLEAM (28.31, 24.73 mm•a-1 and 24.19 mm·a-1) and of MOD16 (9.50, 14.80 mm•a-1 and 14.34 mm•a-1). It was crucial to quantify the uncertainty of regional ET based on the CoLM, GLEAM and MOD16 ET products for accurately estimating water consumption and providing appropriate ET product for long-term water cycle change in Xinjiang. The method used in this paper might provide a reference for analyzing the uncertainty.

Key words： uncertainty; evapotranspiration; Cornered Hat method; land surface mode; remote sensing data

参考文献

[1] 施雅风，沈永平，胡汝骥. 西北气候由暖干向暖湿转型的信号、影响和前景初步探讨[J]. 冰川冻土, 2002, 24(3): 219-226.[Shi Yafeng, Shen Yongping, Hu Ruji. Preliminary study on signal, impact and foreground of climatic shift from warm-dry to warm-humid in northwest China[J]. Journal of Glaciology and Geocryology, 2002, 24(3): 219-226.]
[2] 周彦昭，周剑，李妍，等. 利用SEBAL和改进的SEBAL模型估算黑河中游戈壁、绿洲的蒸散发[J]. 冰川冻土, 2014, 36(6): 1 526-1 537.[Zhou Yanzhao, Zhou Jian, Li Yan, et al. Simulating the evapotranspiration with SEBAL and Modified SEBAL (M-SEBAL) models over the desert and oasis of the middle reaches of the Heihe River[J]. Journal of Glaciology and Geocryology, 2014, 36(6): 1 526-1 537.]
[3] 张强，张之贤，问晓梅，等. 陆面蒸散量观测方法比较分析及其影响因素研究[J]. 地球科学进展, 2011, 26(5): 538-547.[Zhang Qiang, Zhang Zhixian, Wen Xiaomei, et al. Comparisons of observational methods of land surface evapotranspiration and their influence factors[J]. Advances in Earth Science, 2011, 26(5): 538-547.]
[4] 赵文智，吉喜斌，刘鹄，蒸散发观测研究进展及绿洲蒸散研究展望[J]. 干旱区研究, 2011, 28(3): 463-470.[Zhao Wenzhi, Ji Xibin, Liu Hu. Progresses in evapotranspiration research and prospect in desert oasis evapotranspiration research[J]. Arid Zone Research, 2011, 28(3):463-470.]
[5] Mu Q Z, Zhao M S, Running S W. Improvements to a MODIS global terrestrial evapotranspiration algorithm[J]. Remote Sensing of Environment, 2011, 115(8): 1 781-1 800.
[6] Zhang K, Kimball J S, Nemani R R, et al. A continuous satellite-derived global record of land surface evapotranspiration from 1983 to 2006[J]. Water Resources Research, 2010, 46(9): 109-118.
[7] Martens B, Miralles D G, Lievens H, et al. GLEAM v3: satellite-based land evaporation and root-zone soil moisture[J]. Geoscientific Model Development Discussions, 2017, 10(5): 1-36.
[8] Mueller B, Hirschi M, Jimenez C, et al. Benchmark products for land evapotranspiration: LandFlux-EVAL multi-dataset synthesis[J]. Hydrology & Earth System Sciences, 2013, 17(10): 3 707-3 720.
[9] Chen Y, Xia J Z, Liang S L, et al. Comparison of satellite-based evapotranspiration models over terrestrial ecosystems in China[J]. Remote Sensing of Environment, 2014, 140(1): 279-293.
[10] Vinukollu R K, Meynadier R, Sheffield J, et al. Multi-model, multi-sensor estimates of global evapotranspiration: climatology, uncertainties and trends[J]. Hydrological Processes, 2011, 25(26): 3 993-4 010.
[11] 李向婷，白洁，李光录，等. 新疆荒漠稀疏植被覆盖度信息遥感提取方法比较[J]. 干旱区地理, 2013, 36(3): 502-511.[Li Xiangting, Bai Jie, Li Guanglu, et al. Comparison of methods based on MODIS for estimating sparse vegetation fraction across desert in Xinjiang[J]. Arid Land Geography, 2013, 36(3): 502-511.]
[12] 郝兴明，陈亚宁，李卫红，等. 胡杨根系水力提升作用的证据及其生态学意义[J]. 植物生态学报, 2009, 33(6): 1 125-1 131.[Hao Xingming, Chen Yaning, Li Weihong, et al. Evidence and ecological effects of hydraulic lift in populus euphratica[J]. Chinese Journal of Plant Ecology, 2009, 33(6): 1 125-1 131.]
[13] 徐贵青，李彦. 共生条件下三种荒漠灌木的根系分布特征及其对降水的响应[J]. 生态学报, 2009, 29(1): 130-137.[Xu Guiqing, Li Yan. Roots distribution of three desert shrubs and their response to precipitation under co-occurring conditions[J]. Acta Ecologica Sinica, 2009, 29(1): 130-137.]
[14] 许皓，李彦，邹婷，等. 梭梭(Haloxylon ammodendron)生理与个体用水策略对降水改变的响应[J]. 生态学报, 2007, 27(12): 5 019-5 028.[Xu Hao, Li Yan, Zhou Ting, et al. Ecophysiological response and morphological adjustment of Haloxylon ammodendron towards variation in summer precipitation[J]. Acta Ecologica Sinica, 2007, 27(12): 5 019-5 028.]
[15] 胡顺军，艾尼瓦尔·吾买尔，宋郁东，等. 南疆棉田实际蒸散量的计算模式[J]. 干旱区研究, 2001, 18(1): 40-42.[Hu Shunjun, Ainiwar·Mumaier, Song Yudong, et al. Calculation model of field evapotranspiration for cotton crop[J]. Arid Zone Research, 2001, 18(1): 40-42.]
[16] 周丹，沈彦俊，陈亚宁，等. 西北干旱区荒漠植被生态需水量估算[J]. 生态学杂志, 2015, 34(3): 670-680.[Zhou Dan, Shen Yanjun, Chen Yaning, et al. Estimation of ecological water requirement of desert vegetation in the arid region of northwest China[J]. Chinese Journal of Ecology, 2015, 34(3): 670-680.]
[17] 黄小涛，罗格平. 新疆草地蒸散与水分利用效率的时空特征[J]. 植物生态学报, 2017, 41(5): 506-518.[Huang Xiaotao, Luo Geping. Spatio-temporal characteristics of evapotranspiration and water use efficiency in grasslands of Xinjiang[J]. Chinese Journal of Plant Ecology, 2017, 41(5): 506-518.]
[18] 李宝富，陈亚宁，李卫红，等. 基于遥感和SEBAL模型的塔里木河干流区蒸散发估算[J]. 地理学报, 2011, 66(9): 1 230-1 238.[Li Baofu, Chen Yaning, Li Weihong, et al. Remote sensing and the SEBAL model for estimating evapotranspiration in the Tarim River[J]. Acta Geographica Sinica, 2011, 66(9): 1 230-1 238.]
[19] 谢蕾，龙爱华，邓铭江，等. 伊犁河下游三角洲生态耗水研究[J]. 冰川冻土, 2011, 33(6): 1 330-1 340.[Xie Lei, Long Aihua, Deng Mingjiang, et al. Study on ecological water consumption in Delta of the Lower Reaches of Ili River[J]. Journal of Glaciology and Geocryology, 2011, 33(6): 1 330-1 340.]
[20] Chen X, Li B L, Li Q, et al. Spatio-temporal pattern and chanses of evapotranspiration in arid Central Asia and Xinjiang of China[J]. Journal of Arid Land, 2012, 44(1): 105-112.
[21] Liu B, Ma Z G, Feng J M, et al. The relationship between pan evaporation and actual evapotranspiration in Xinjiang since 1960[J]. Acta Geographica Sinica, 2008, 63(11): 1 131-1 139.
[22] 宋晓猛，占车生，孔凡哲，等. 大尺度水循环模拟系统不确定性研究进展[J]. 地理学报, 2011, 66(3): 396-406.[Song Xiaomeng, Zhan Chesheng, Kong Fanzhe, et al. A review on uncertainty analysis of large-scale hydrological cycle modeling system[J]. Acta Geographica Sinica, 2011, 66(3): 396-406.]
[23] Hakanson L. Error propagations in step-by-step predictions: examples for environmental management using regression models for lake ecosystems[J]. Environmental Modelling & Software, 1998, 14(1): 49-58.
[24] 梁晓，戴永久. 陆面模式中土壤和植被经验参数随机误差的传播研究[J]. 大气科学, 2010, 34(2): 457-470.[Liang Xiao, Dai Yongjiu. Soil and plant parameters-related stoch as tic uncertainty propagation in the common land model[J]. Chinese Jou rn al of Atmospheric Sciences, 2010, 34(2):457-470.]
[25] 梁忠民，戴荣，李彬权. 基于贝叶斯理论的水文不确定性分析研究进展[J]. 水科学进展, 2010, 21(2): 274-281.[Liang Zhongmin, Dai Rong, Li Binquan. A review of hydrological uncertainty analysis based on bayesian theory[J]. Advances in Water Science, 2010, 21(2): 274-281.]
[26] 柏延臣，王劲峰. 遥感数据专题分类不确定性评价研究: 进展、问题与展望[J]. 地球科学进展, 2005, 20(11): 1 218-1 225.[Bo Yanchen, Wang Jinfeng. Assessment on uncertainty in remotely sensed data classification: progresses, problems and prospects[J]. Advances in Earth Science, 2005, 20(11): 1 218-1 225.]
[27] 吴戈男，胡中民，李胜功，等. SWH双源蒸散模型模拟效果验证及不确定性分析[J]. 地理学报, 2016, 71(11): 1 886-1 897.[Wu Genan, Hu Zhongmin, Li Shenggong, et al. Evaluation and uncertainty analysis of a two-source evapotranspiration model[J]. Acta Geographica Sinica, 2016, 71(11): 1 886-1 897.]
[28] Long D, Longuevergne L, Scanlon B R. Uncertainty in evapotranspiration from land surface modeling, remote sensing, and GRACE satellites[J]. Water Resources Research, 2014, 50(2): 1 131-1 151.
[29] 史玉光，孙照渤，杨青. 新疆区域面雨量分布特征及其变化规律[J]. 应用气象学报, 2008, 19(3): 326-332.[Shi Yuguang, Sun Zhaobo, Yang Qing. Characteristics of area precipitation in Xinjiang region with its variations[J]. Journal of Applied Meteorological Science, 2008, 19(3): 326-332.]
[30] 肖宇，马柱国，李明星. 陆面模式中土壤湿度影响蒸散参数化方案的评估[J]. 大气科学, 2017, 41(1): 132-146.[Xiao Yu, Ma Zhuguo, Li Mingxing. Evaluation of the parameterizations of soil moisture influence on evapotranspiration in land surface models[J]. Chinese Journal of Atmospheric Sciences, 2017, 41(1): 132-146.]
[31] Dai Y, Dickinson R E, Wang Y P. A two-big-leaf model for canopy temperature, photosynthesis, and stomatal conductance[J]. Journal of Climate, 2004, 17(12): 2 281-2 299.
[32] Li L H, van der Tol C, Chen X, et al. Representing the root water uptake process in the Common Land Model for better simulating the energy and water vapour fluxes in a Central Asian desert ecosystem[J]. Journal of Hydrology, 2013, 502(2): 145-155.
[33] Jing C Q, Li L H, Chen X, et al. Comparison of root water uptake functions to simulate surface energy fluxes within a deep-rooted desert shrub ecosystem[J]. Hydrological Processes, 2014, 28(21): 5 436-5 449.
[34] Miralles D G, Holmes T R H, De Jeu R A M, et al. Global land-surface evaporation estimated from satellite-based observations[J]. Hydrology and Earth System Sciences, 2011, 15(2): 453-469.
[35] 贺添，邵全琴. 基于MOD16产品的我国2001—2010年蒸散发时空格局变化分析[J]. 地球信息科学学报, 2014, 16(6): 979-988.[He Tian, Shao Quanqin. Spatial-temporal variation of terrestrial evapotranspiration in China from 2001 to 2010 using mod16 products[J]. Geo-Information Science, 2014, 16(6): 979-988.]
[36] Bai J, Chen X, Li L H, et al. Quantifying the contributions of agricultural oasis expansion, management practices and climate change to net primary production and evapotranspiration in croplands in arid northwest China[J]. Journal of Arid Environments, 2014, 100-101(1): 31-41.
[37] 牛建龙，王家强，彭杰，等. 荒漠-绿洲区潜在蒸散量变化特征及其影响因素[J]. 干旱区研究, 2016, 33(4): 766-772.[Niu Jianlong, Wang Jiaqiang, Peng Jie, et al. Change of potential evapotranspiration and its affecting factors in Desert-oasis Zone[J]. Arid Zone Research, 2016, 33(4): 766-772.]
[38] 卓嘎，尼玛央珍，唐小萍. 1980—2009年西藏西北部潜在蒸散时空分布特征及其影响因素[J]. 干旱区研究, 2016, 33(4): 698-707.[Zhuo Ga, Nima Yangzhen, Tang Xiaoping. Spatiotemporal distribution of potential evapotranspiration and its affecting factors in northwest Tibet during the period of 1980-2009[J]. Arid Zone Research, 2016, 33(4): 698-707.]
[39] 张娜，金建新，佟长福，等. 西藏参考作物蒸散量时空变化特征与影响因素[J]. 干旱区研究, 2017, 34(5): 1 027-1 034.[Zhang Na, Jin Jianxin, Tong Changfu, et al. Spatiotemporal variation of evapotranspiration of referred crops and the affecting factors in Tibet[J]. Arid Zone Research, 2017, 34(5): 1 027-1 034.]
Options
文章导航

/

〈 〉