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Simulating CO_2 flux of three different ecosystems in ChinaFLUX based on artificial neural {1.s

Science China Earth Sciences 2006年第S2期49卷 252-261页

作者： HE Honglin, YU Guirui, ZHANG Leiming, SUN Xiaomin & SU Wen key {1. of ecosystem network observation and modeling, CERN Synthesis Research Center, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 1.01.1. China 1. Key Laboratory of Ecosystem Network Observation and Modeling CERN Synthesis Research Center Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

The nonlinearity of the relationship between CO2 flux and other micrometeorological variables flux parameters limits the applicability of carbon flux models to accurately estimate the flux dynamics. However, the need for carbon dioxide (CO2) estimations covering larger areas and the limitations of the point eddy covariance technique to address this requirement necessitates the modeling of CO2 flux from other micrometeorological variables. Artificial neural {1.s (ANN) are used because of their power to fit highly nonlinear relations between input and output variables without explaining the nature of the phenomena. This paper applied a multilayer perception ANN technique with error back propagation algorithm to simulate CO2 flux on three different ecosystems (forest, grassland and cropland) in ChinaFLUX. Energy flux (net radiation, latent heat, sensible heat and soil heat flux) and temperature (air and soil) and soil moisture were used to train the ANN and predict the CO2 flux. Diurnal half-hourly fluxes data of observations from June to August in 2003 were divided into training, validating and testing. Results of the CO2 flux simulation show that the technique can successfully predict the observed values with R2 value between 0.75 and 0.866. It is also found that the soil moisture could not improve the simulative accuracy without water stress. The analysis of the contribution of input variables in ANN shows that the ANN is not a black box model, it can tell us about the controlling parameters of NEE in different ecosystems and micrometeorological environment. The results indicate the ANN is not only a reliable, efficient technique to estimate regional or global CO2 flux from point measurements and understand the spatiotemporal budget of the CO2 fluxes, but also can identify the relations between the CO2 flux and micrometeorological variables.

关键词： artificial neural network CO2 ChinaFLUX energy flux variables contribution.

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Study of a model for correcting the effects of horizontal advection on surface fluxes measurement based on remote sensing

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Science China Earth Sciences 2006年第S2期49卷 273-280页

作者： TIAN Jing, ZHANG Renhua, SUN Xiaomin, ZHU Zhilin & ZHOU Yanlian key {1. of ecosystem network observation and modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 1.01.1. China Graduate University of the Chinese Academy of Sciences, Beijing 1.0049, China 1. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China 2. Graduate University of the Chinese Academy of Sciences Beijing 100049 China

As well known, the methods of remote sensing and Bowen Ratio for retrieving surface flux are based on energy balance closure; however, in most cases, surface energy observed in experiment is lack of closure. There are two main causes for this: one is from the errors of the observation devices and the differences of their observational scale; the other lies in the effect of horizontal advection on the surface flux measurement. Therefore, it is very important to estimate the effects of horizontal advection quantitatively. Based on the local advection theory and the surface experiment, a model has been proposed for correcting the effect of horizontal advection on surface flux measurement, in which the relationship between the fetch of the measurement and pixel size for remote sensed data was considered. By means of numerical simulations, the sensitivities of the main parameters in the model and the scaling problems of horizontal advection were analyzed. At last, by using the observational data acquired in agricultural field with relatively homogeneous surface, the model was validated.

关键词： fetch horizontal advection energy balance pixel size ChinaFLUX.

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A preliminary study for spatial representiveness of flux observation at ChinaFLUX sites

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Science China Earth Sciences 2006年第S2期49卷 24-35页

作者： Ml Na, YU Guirui, WANG Panxing, WEN Xuefa & SUN Xiaomin Nanjing University of Information Science and Technology, Nanjing 21.044, China key {1. of ecosystem network observation and modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 1.01.1. China 1. Nanjing University of Information Science and Technology Nanjing 210044 China 2. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

The results of eddy covariance observation system could represent the physical process at certain area of the surface. Thus point-to-area representativeness was of primary interest in flux observation. This research presents a preliminary study for flux observation at ChinaFLUX sites by the use of observation data and Flux Source Area Model (FSAM). Results show that the footprint expands and is further away from flux tower when atmosphere becomes more stable, the observation height increases, or the surfaces become smoother. This suggests that the area represented by the flux observation becomes larger. The distances from the reference point to the maximum point Smax and the minimum point x1.of source weight function (Dmax and Dmin, respectively) can be influenced by atmosphere stability which becomes longer when atmosphere is more stable. For more rough surfaces and lower observation point Dmax and Dmin become shorter. This research gives the footprint at level P=90% at ChinaFLUX sites at different atmosphere stability. The preliminary results of spatial representiveness at ChinaFLUX sites were given based on the dominant wind direction and footprint response to various factors. The study also provides some theoretical basis for data quality control and evaluating data uncertainty.

关键词： eddy covariance method footprint source weight function ChinaFLUX.

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Study on the processing method of nighttime CO_2 eddy covariance flux data in ChinaFLUX

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Science China Earth Sciences 2006年第S2期49卷 36-46页

作者： ZHU Zhilin, SUN Xiaomin, WEN Xuefa, ZHOU Yanlian, TIAN Jing & YUAN Guofu key {1. of ecosystem network observation and Model, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 1.01.1. China Graduate University of the Chinese Academy of Sciences, Beijing 1.0049, China 1. Key Laboratory of Ecosystem Network Observation and Model Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China2. Graduate University of the Chinese Academy of Sciences Beijing 100049 China

At present, using Eddy Covariance (EC) method to estimate the "true value" of carbon sequestration in terrestrial ecosystem arrests more attention. However, one issue is how to solve the uncertainty of {1.s (especially the nighttime CO2 flux data) appearing in post-processing CO2 flux data. The ratio of effective and reliable nighttime EC CO2 flux data to all nighttime data is relatively low (commonly, less than 50%) for all the long-term and continuous {1. stations in the world. Thus, the processing method of nighttime CO2 flux data and its effect analysis on estimating CO2 flux annual sums are very important. In this paper, the authors analyze and discuss the reasons for underestimating nighttime CO2 flux using EC method, and introduce the general theory and method for processing nighttime CO2 flux data. By analyzing the relationship between nighttime CO2 flux and air fraction velocity u., we present an alternate method, Average Values Test (AVT), to determine the thresholds of fraction velocity (u.c) for screening the effective nighttime CO2 flux data. Meanwhile, taking the data observed in Yucheng and Changbai Mountains stations for an example, we analyze and discuss the effects of different methods or parameters on nighttime CO2 flux estimations. Finally, based on the data of part ChinaFLUX stations and related literatures, empirical models of nighttime respiration at different sites in ChinaFLUX are summarized.

关键词： eddy covariance nighttime CO2 flux data correction ChinaFLUX.

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Surface roughness length dynamic over several different surfaces and its effects on modeling fluxes

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Science China Earth Sciences 2006年第S2期49卷 262-272页

作者： ZHOU Yanlian, SUN Xiaomin, ZHU Zhilin, ZHANG Renhua, TIAN Jing, LIU Yunfen, GUAN Dexin & YUAN Guofu key {1. of ecosystem network observation and modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 1.01.1. China Graduate University of the Chinese Academy of Sciences, Beijing 1.0049, China Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 1.001., China 1. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China2. Graduate University of the Chinese Academy of Sciences Beijing 100049 China3. Institute of Applied Ecology Chinese Academy of Sciences Shenyang 110016 China

Roughness length and zero-plane displacement over three typical surfaces were calculated iteratively by least-square method, which are Yucheng Experimental Station for agriculture surfaces, Qianyanzhou Experimental Station for complex and undulant surfaces, and Changbai Mountains Experimental Station for forest surfaces. On the basis of roughness length dynamic, the effects of roughness length dynamic on fluxes were analyzed with SEBS model. The results indicate that, aerodynamic roughness length changes with vegetation conditions (such as vegetation height, LAI), wind speed, friction velocity and some other factors. In Yucheng and Changbai Mountains Experimental Station, aerodynamic roughness length over the fetch of flux tower changes with vegetation height and LAI obviously, that is, with the increase of LAI, roughness length increases to the peak value firstly, and then decreases. In Qianyanzhou Experimental Station, LAI changes slightly, so the relationship between roughness length and LAI is not obvious. The aerodynamic roughness length of Yucheng and Changbai Mountains Experimental Station changes slightly with wind direction, while aerodynamic roughness length of Qianyanzhou Experimental Station changes obviously with wind direction. The reason for that is the terrain in Yucheng and Changbai Mountains Experimental Station is relatively flat, while in Qianyanzhou Experimental Station the terrain is very undulant and heterogeneous. With the increase of wind speed, aerodynamic roughness length of Yucheng Experimental Station changes slightly, while it decreases obviously in Qianyanzhou Experimental Station and Changbai Mountains Experimental Station. Roughness length dynamic takes great effects on fluxes calculation, and the effects are analyzed by SEBS model. By comparing 1.day averaged roughness length in Yucheng Experimental Station and 5 day averaged roughness length of Qianyanzhou and Changbai Mountains Experimental Station with roughness length parameter

关键词： ChinaFLUX surface roughness length dynamic spatial heterogeneity Yucheng Experimental Station Qianyanzhou Experimental Station Changbai Mountains Experimental Station.

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Influence of ecosystem on hydrochemistry and stable isotope of surface and groundwaters in the Yellow River Delta

Influence of ecosystem on hydrochemistry and stable isotope ...

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201. HP1. IAHS-IAPSO-IASPEI Assembly

作者： Li, Fadong Liu, Qiang Zhang, Qiuying Li, Jing Zhang, Yan Song, Shuai Zhao, Guangshuai Zhu, Nong Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China Center for Agricultural Resources Research 1GDB Chinese Academy of Sciences 286 Huaizhong Road Shijiazhuang 050021 China

ISBN: (纸本)9781907161360

To determine the influence of the increased amount of transferred water on groundwater quality in the Yellow River Delta, 1. ground- and 1. surface-water samples derived from three ecosystems were collected for major ions (Na, K, Mg, Ca, NO3, SO4, Br, Cl, HCO3) and stable isotope analysis (2H/1.O). The land-use changes along the mainland towards the Bohai Sea from farmland to wetland to the coast. The hydrochemical compositions are most complicated in the farmland and wetland groundwater, indicating the mixing process with water transferred from the Yellow River, whereas the ones on the coast are dominated by NaCl. The ratios of 2H/1.O in farmland and wetland groundwater are plotted on or close to the local meteoric water line (LMWL), and ones from the coast are enriched in both 2H and 1.O (the seawater). The NO 3 positively corresponds with Cl in the farmland and wetland, with 40% of groundwater samples exceeding the allowable nitrate drinking water level (1. mg/L). Therefore, it is inferred that irrigation water from the Yellow River and anthropogenic pollution are two nitrogen sources of nitrate. Copyright © 201. IAHS Press.

关键词： ecosystems

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PATTERNS AND DRIVING FACTORS OF WUE AND NUE IN NATURAL FOREST ecosystemS ALONG NORTH-SOUTH TRANSECT OF EASTERN CHINA------BASED ON ISOTOPE AND STOICHIOMETRY ANALYSES

PATTERNS AND DRIVING FACTORS OF WUE AND NUE IN NATURAL FORES...

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201.年亚洲通量网会议(Asiaflux workshop201.)

作者： Wenping Sheng Shujie Ren Guirui YU Huajun Fang Key Laboratory of Ecosystem Network Observation and Modeling Synthesis Research Center of Chinese Ecosystem Research NetworkInstitute of Geographic Sciences and Natural Resources ResearchCASBeijing 1O0101China

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Quantitative estimation of the shrub canopy LAI from atmosphere-corrected HJ-1.CCD data in Mu Us Sandland

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Science China Earth Sciences 2010年第S1期53卷 26-33页

作者： CHEN Wei1.2,CAO ChunXiang1.HE QiSheng1.2,GUO HuaDong3,ZHANG Hao1.2,LI RenQiang4,ZHENG Sheng1.2,XU Min1.2,GAO MengXu1.2,ZHAO Jian1.2,LI Sha1.NI XiLiang1.2,JIA HuiCong1.JI Wei1.TIAN Rong1.2,LIU Cheng1.2,ZHAO YuXing5 & LI JingLu6 1.State key {1. of Remote Sensing Science,Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University,Beijing 1.01.1.China 2 Graduate University of Chinese Academy of Sciences,Beijing 1.0049,China 3 Center for Earth observation and Digital Earth,Chinese Academy of Sciences,Beijing 1.01.0,China 4 China key {1. of Ecological network observation and modeling,Institute of Geographical Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 1.01.1.China 5 Ordos Forestry Sand Control Science Institute,Dongsheng 01.000,China 6 Inner Mongolia Biomass Thermoelectricity Limited Company,Wushen 01.300,China 1. State Key Laboratory of Remote Sensing Science Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University Beijing 100101 China 2. Graduate University of Chinese Academy of Sciences Beijing 100049 China 3. Center for Earth Observation and Digital Earth Chinese Academy of Sciences Beijing 100190 China 4. China Key Laboratory of Ecological Network Observation and Modeling Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China 5. Ordos Forestry Sand Control Science Institute Dongsheng 017000 China 6. Inner Mongolia Biomass Thermoelectricity Limited Company Wushen 017300 China

The leaf area index(LAI) is an important ecological parameter that characterizes the interface between vegetation canopy and the *** addition,it is used by most process-oriented ecosystem *** paper investigates the potential of HJ-1.CCD data combined with linear spectral unmixing and an inverted geometric-optical model for the retrieval of the shrub LAI in Wushen Banner of Inner Mongolia in the Mu Us ***(Moderate Resolution Atmospheric Radiance and Transmittance Model) was used for atmospheric *** was extracted using the threshold of the normalized difference vegetation index,with which water bodies and farmland were separated,in combination with a vegetation map of the People's Republic of China(1.1.00000).Using the geometric-optical model,we derive the per-pixel reflectance as a simple linear combination of two components,namely sunlit background and *** fraction of sunlit background is related to the shrub *** the support of HJ-1.CCD data,we employ linear spectral unmixing to obtain the fraction of sunlit background in an atmospherically corrected HJ *** addition,we use the measured shrub canopy structural parameters for shrub communities to invert the geometric-optical model and retrieve the pixel-based shrub *** total,1. sample plots collected in Wushen Banner of Inner Mongolia are used for *** results of the shrub LAI show good agreement with R2 of 0.81. and a root-mean-squared error of 0.1.3.

关键词： shrub leaf area index inversion HJ-1 data geometric-optical model MODTRAN Mu Us Sandland

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FOREST TYPE CONTROLS THE LANDSCAPE VARIATION OF SOIL RESPIRATION IN A HILLY REGION IN SUBTROPICAL CHINA

FOREST TYPE CONTROLS THE LANDSCAPE VARIATION OF SOIL RESPIRA...

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201.年亚洲通量网会议(Asiaflux workshop201.)

作者： Y.-D.Wang H.-M.Wang Z.-Q.Ma W.-J.Zhang Z.-L.Wang 1Qianyanzhou Ecological Station Key Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Tianjin Key Laboratory of Water Environment and Resources Tianjin Normal UniversityTianjin 300387China Qianyanzhou Ecological StationKey Laboratory of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Tianjin Key Laboratory of Water Environment and ResourcesTianjin Normal UniversityTianjin 300387China

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APPLICATION OF MODEL-DATA SYNTHESIS ON SIMULATING CARBON AND WATER FLUXES AT FORESTED ecosystemS IN CHINAFLUX

APPLICATION OF MODEL-DATA SYNTHESIS ON SIMULATING CARBON AND...

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201.年亚洲通量网会议(Asiaflux workshop201.)

作者： Min Liu Honglin He Xiaomin Sun Li Zhang Guirui Yu Graduate University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 1O0101China

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