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SSRN 2025年

作者： Peng, Siyuan Yang, Yue Luo, Dengnan Zeng, Xiang Liang, Minqi Tao, Long Zhang, Guangru Li, Pan Liao, Weijie Guo, Qun Cao, Ruochen Li, Yuzhe Zhang, Weirong Hu, Zhongmin Hainan Baoting Tropical Rainforest Ecosystem Observation and Research Station School of Ecology Hainan University Haikou570228 China Department of Geography Faculty of Arts and Sciences Beijing Normal University Zhuhai519087 China Facility of Geographical Science Beijing Normal University Beijing100875 China Zhuhai Branch of State Key Laboratory of Earth Surface Processes and Resource Ecology Beijing Normal University Zhuhai519087 China School of Geography South China Normal University Shipai Campus Guangzhou510631 China School of Atmospheric Sciences Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle Sun Yat-sen University Guangdong Zhuhai510245 China Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing100101 China College of Resources and Environment University of Chinese Academy of Sciences Beijing101408 China International Institute for Earth System Sciences Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing University Jiangsu210023 China Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology Key Laboratory for Land Satellite Remote Sensing Applications of Ministry of Natural Resources School of Geography and Ocean Science Nanjing University Jiangsu210023 China Key Laboratory of Land Surface Pattern and Simulation Institute of Geographical Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China

Study region: The Tibetan Plateau in China, the Third Pole of the *** focus: Accurate descriptions of spatial variation in evapotranspiration (ET) and its components on the Tibetan Plateau (TP) are crucial for understanding the dynamics of the regional water cycle and energy balance. However, how various environmental factors affect ET and its components remains unclear. This study addresses this gap using observational data from 14 sites and employing the Shuttleworth-Wallace-Hu (SWH) model to examine the spatial relationships between ET, its components, and underlying *** hydrological insights for the region: The SWH model parameters were optimized using the Monte Carlo method, achieving a satisfactory model performance with an average R² of 0.75. The ratio of transpiration to ET was generally higher in alpine meadows (0.55) than alpine steppes (0.39). Across the TP, precipitation and the leaf area index together shaped spatial variation in ET and transpiration. Precipitation emerged as the primary driver of interannual variation in ET, while the leaf area index strongly regulated the proportion of ET accounted for by transpiration. Furthermore, above aridity index values of 0.73, grassland ecosystems transitioned from water to energy. This finding is significant as it challenges the common application of an aridity index value of 0.65 to distinguish arid from humid regions. It suggests that TP grasslands, with an AI of 0.65-0.73, remain primarily water-limited. © 2025, The Authors. All rights reserved.

关键词： Monte Carlo methods

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EFFECTS OF CLIMATE CHANGE AND PLANTATION ON CARBON BUDGET OF CONIFEROUS FORESTS IN POYANG LAKE BASIN FROM 1981 TO 2008

EFFECTS OF CLIMATE CHANGE AND PLANTATION ON CARBON BUDGET OF...

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2010年亚洲通量网会议(Asiaflux workshop2010)

作者： Shaoqiang Wang Yuan Yan Hao Nie Lei Zhou You Zhang Key Lab of Ecosystem Networking Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchCASBeijingChina

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Soil Organic Carbon Stock as Affected by Land Use/Cover Changes in the Humid Region of Northern Iran

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Journal of Mountain Science 2014年第2期11卷 507-518页

作者： Samereh FALAHATKAR Seyed Mohsen HOSSEINI Abdolrassoul SALMAN MAHINY Shamsollah AYOUBI WANG Shao-qiang Faculty of Natural Resource and Marine Science Tarbiat Modares University Department of Environmental Sciences Gorgan University of Agricultural Sciences and Natural Resources Department of Soil Sciences College of Agriculture Isfahan University of Technology Key Lab of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research

【Title】【Author】 This study was conducted to determine the changes in the soil carbon stocks as influenced by land use in a humid zone of Deylaman district （10,876 ha）, a mountainous region of northern Iran. For this, land use maps were produced from TM and ETM＋ images for 1985, 2000 and 2010 years; and this was supplemented by field measurement of soil carbon in 2010. The results showed that the mean soil organic carbon （SOC） density was 6.7±1.8 kg C m-2, 5.2±3.4 kg C m-2 and 3.2±1.8 kg C m-2 for 0-20 cm soil layer and 4.8±1.9 kg C m-2, 3.1±2 kg C m-2 and 2.7±1.8 kg C m-2 for 20-40 cm soil layer in forest, rangeland and cultivated land, respectively. During the past 25 years, 14.4% of the forest area had been converted to rangeland; and 28.4% of rangelands had been converted to cultivated land. According to the historical land use changes in the study area, the highest loss of SOC stocks resulted from the conversion of the forest to rangeland （0.45×104 Mg C in 0-40 cm depth layer）; and the conversion of rangeland to cultivated land （0.37×104 Mg C in 0-40 cm）, which typically led to the loss of soil carbon in the area studied. The knowledge on the historical land use changes and its influence on overall SOC stocks could be helpful for making management decision for farmers and policy managers in the future, for enhancing the potential of C sequestration in northern Iran.

关键词： Soil organic carbon stocks Land cover Land use Iran

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Surface water quality forecasting based on ANN and GIS for the Chanzhi Reservoir, China

Surface water quality forecasting based on ANN and GIS for t...

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2nd International Conference on Information Science and Engineering, ICISE2010

作者： Song, Shuai Zheng, Xilai Li, Fadong Natural Resources Research Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences Beijing 100101 China Key Lab. of Marine Environment and Ecology Ministry of Education Ocean University of China Qingdao China Graduate University of Chinese Academy of Science Beijing China

ISBN: (纸本)9781424480968

Artificial neural network (ANN) based on Arc Engine (AE) of GIS is used to predict surface water quality in the Chanzhi Reservoir, Qingdao, China. The results can reflect the water quality change trends with less than 10% average relative error. Using MS SQL Server database technology combined with Geodatabase, the system achieves the fundamental geographic information and hydrological data management, and water quality prediction. It uses GIS component technology to build an efficient and stable platform which can apply to general surface water quality prediction. This software has good information extraction and query functions to help decision-makers to manage water resource better. © 2010 IEEE.

关键词： Reservoirs (water)

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Understanding the spatial representativeness of air quality monitoring network and its application to PM_(2.5)in the China's Mainland

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Geoscience Frontiers 2022年第3期13卷 130-138页

作者： Ling Su Chanchan Gao Xiaoli Ren Fengying Zhang Shanshan Cao Shiqing Zhang Tida Chen Mengqing Liu Bingchuan Ni Min Liu Shanghai Key Lab for Urban Ecological Processes and Eco-Restoration School of Ecological and Environmental SciencesEast China Normal UniversityShanghai 200241China Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Graduate University of Chinese Academy of Sciences Beijing 100049China China National Environmental Monitoring Centre Beijing 100012China Institute of Eco-Chongming Shanghai 200241China

Air pollution has seriously endangered human health and the natural ecosystem during the last *** quality monitoring stations(AQMS)have played a critical role in providing valuable data sets for recording regional air *** spatial representativeness of AQMS is a critical parameter when choosing the location of stations and assessing effects on the population to long-term exposure to air *** this paper,we proposed a methodological framework for assessing the spatial representativeness of the regional air quality monitoring network and applied it to ground-based PM_(2.5)observation in the mainland of *** multidimensional Euclidean distance between each pixel and the stations was used to determine the representativeness of the existing monitoring *** addition,the K-means clustering method was adopted to improve the spatial representativeness of the existing *** results showed that there were obvious differences among the representative area of 1820 stations in the mainland of *** monitoring stations could well represent the PM_(2.5)spatial distribution of the entire region,and the effectively represented area(*** area where the Euclidean distance between the pixels and the stations was lower than the average value)accounted for 67.32%of the total area and covered 93.12%of the *** additional stations were identified in the Northwest,North China,and Northeast regions,which could improve the spatial representativeness by 14.31%.

关键词： PM_(2.5) Euclidean distance Spatial representativeness China

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Improvement of MODIS 8-day LAI/FPAR product with temporal filters to generate high quality time-series product

Improvement of MODIS 8-day LAI/FPAR product with temporal fi...

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2009 Joint Urban Remote Sensing Event

作者： Huifang, Zhang Runhe, Shi Honglin, Zhong Peiqing, Qu Juan, Sun Wenpeng, Lin Su, Li Key Lab. of Geographic Information Science Ministry of Education East China Normal University Shanghai China Key Laboratory of Ecosystem Network Observation and Modeling IGSNRR CAS Beijing China Key Lab. of Urban Ecology and Environment Restoration Shanghai Normal University Shanghai China Computer College Beijing Technology and Business University Beijing China

ISBN: (纸本)9781424434619

Numerous studies have reported that the timeseries terrestrial parameters such as the Normalized Difference Vegetation Index (NDVI), Leaf Area of Index (LAI), Fraction of Absorbed Photosynthetic Active Radiation (FPAR), derived from NOAA/AVHRR, SPOT/VEGETATION, TERRA or AQUA/MODIS, have played significant roles in researching the global environment, terrestrial ecosystems and related ecological researches. However, the remotely sensed signals are interfered severely by atmospheric conditions especially clouds and such noises exists in the time-series products as well. Therefore, to obtain a high quality time-series of terrestrial parameter is a necessary step before further studies. At present several methods have been applied to reduce the noise to construct a fine time-series of NDVI, but few studies concerning the other key terrestrial parameters, such as LAI, FPAR etc. In this paper, after comparing general methods in literatures, we designed a new method based on the Savitzky-Golay filter, which was applied to improve the quality of MODIS 8-Day LAI/FPAR Product to generate timeseries of LAI and FPAR with high quality. Our validation results indicate that more smooth and realistic time-series curves of LAI/FPAR can be obtained by using this new method, which exemplify the dynamic change of forests, crop or plants and key input parameters in modeling the complex land surface processing. ©2009 IEEE.

关键词： Time series

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Response of carbon dioxide emissions to warming under no-till and conventional till systems

Response of carbon dioxide emissions to warming under no-til...

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作者： Hou, Ruixing Ouyang, Zhu Wilson, G.V. Li, Yunsheng Li, Hanxia Key Lab. of Ecosystem Network Observation and Modeling Institute of Geographic Sciences Chinese Academy of Sciences Beijing 100101 China Yucheng Comprehensive Experiment Station China Academy of Science Beijing 100101 China USDA-ARS National Sedimentation Lab. Oxford MS 38655 United States

Differences in soil organic carbon (SOC) distribution, water holding capacity, and soil temperature between no-tillage (NT) and conventional tillage (CT) systems can result in different soil CO2 emissions which could affect global warming but few studies have addressed this concern. An open warming experiment was conducted in situ by infrared heating of longterm conservation tillage management plots in North China Plain (NCP) to determine the effects of warming on soil CO2 emissions and the correlation to changes in soil temperature and moisture. This experiment was conducted from February 2010 to June 2012 and included CT and NT plots with and without warming. Warming treatment increased soil temperature by 2.1 and 1.5°C, and decreased volumetric soil-water content by 14 and 10% for CT and NT systems, respectively. Soil CO2 emissions tended to decrease with time in CT while it consistently increased in NT system over the three wheat seasons and two maize seasons under warming. Our results suggest that differences in soil temperature and soil moisture between the two tillage systems could be enlarged with time by warming, and the potential exist for warming to promote more soil CO2 emission under NT relative to CT. There is a need to consider the differences in response to global warming between these two tillage systems to properly assess the benefits of NT to C sequestration. © Soil Science Society of America.

关键词： Soil temperature

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Flood variability in the upper Yangtze River over the last millennium——Insights from a comparison of climate-hydrological model simulated and reconstruction

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Science China Earth Sciences 2023年第3期66卷 547-567页

作者： Ran HUO Hua CHEN Lu LI Chong-Yu XU Jingjing LI Si HONG Chesheng ZHAN Jun XIA State Key Laboratory of Water Resources and Hydropower Engineering Science Wuhan UniversityWuhan 430072China Hubei Provincial Key Lab of Water System Science for Sponge City Construction Wuhan UniversityWuhan 430072China NORCE Norwegian Research Centre Bjerknes Centre for Climate ResearchJahnebakken 55007 BergenNorway Department of Geosciences University of OsloP.O Box 1047 Blindern0316 OsloNorway Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China Key Laboratory of Water Cycle and Related and Surface Processes Chinese Academy of SciencesBeijing 100101China

Understanding hydrological responses to rising levels of greenhouse gases are essential for climate and impact *** is,however,often limited by a lack of long record of observational data to provide a basis for understanding the longterm behavior of the climate *** reconstructed data and(global climate and hydrological)model simulations will help us to better understand the variability of climate and hydrology over timescales ranging from decades to *** this study,we proposed an integrated approach to study flood variability in the upper reach of the Yangtze River over the last millennium to the end of the 21st *** accomplish this,we first drove hydrological models using the precipitation and temperature from four Global Climate Models(GCM),BCC-CSM1.1,MIROC,MRI-CGCM3,and CCSM4,to simulate daily discharge for the upper reach of the Yangtze River during the period of the last millennium(850–1849),historical period(1850–2005),and a future period(2006–2099).Then,we evaluated whether the modeled precipitation,temperature,and extreme discharge had statistical properties similar to those shown in the documented dry-wet periods,temperature anomalies,and paleoflood ***,we explored the extreme discharge variability using model *** results indicate that:(1)The MIROC-ESM model,differing from the other three GCM models,revealed positive temperature changes from the warm period(Medieval Climate Anomaly;MCA)to the cold period(Little Ice Age;LIA),while the temperature variability of the other models was similar to the records.(2)The BCC-CSM1.1 model performed better than the others regarding correlations between modeled precipitation and documented dry-wet periods.(3)Over most of the subbasins in the upper Yangtze River,the magnitude of extreme discharge in the BCC-CSM1.1 model results showed that there was a decrease from the MCA to the LIA period and an increase in the historical period relative to the cold period,whil

关键词： Climate change Flood variability Paleoflood records Climate-hydrological model Upper Yangtze River

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Spatial variation in annual actual evapotranspiration of terrestrial ecosystems in China: Results from eddy covariance measurements

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Journal of Geographical Sciences 2016年第10期26卷 1391-1411页

作者：郑涵于贵瑞王秋凤朱先进何洪林王艳芬张军辉李英年赵亮赵风华石培礼王辉民闫俊华张一平 Synthesis Research Center of Chinese Ecosystem Research Network Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research CAS State Key Laboratory of Loess and Quaternary Geology Institute of Earth Environment CAS University of Chinese Academy of Sciences Institute of Applied Ecology CAS Northwest Institute of Plateau Biology CAS South China Botanical Garden CAS Key Lab of Tropical Forest Ecology Xishuangbanna Tropical Botanical Garden CAS

Understanding the spatial variation in annual actual evapotranspiration （AET） and its influencing factors is crucial for a better understanding of hydrological processes and water resources management. By synthesizing ecosystem-level observations of eddy-covariance flux sites in China （a total of 61 sites）, we constructed the most complete AET dataset in China up to now. Based on this dataset, we quantified the statistic characteristics of AET and water budgets （defined as the ratio of AET to annual mean precipitation （MAP）, AET/MAP） of terrestrial ecosystems in China. Results showed that AET differed significantly among both different vegetation types and climate types in China, with overall mean AET of 534.7＋232.8 mm yr1. AET/MAP also differed significantly among different climate types, but there were no distinct differences in AET/MAP values across vegetation types, with mean AET/MAP of 0.82＋0.28 for non-irrigated ecosystems. We further investigated how the main climatic factors and vegetation attributes control the spatial variation in AET. Our findings revealed that the spatial variation of AET in China was closely correlated with the geographical patterns of climate and vegetation, in which the effects of total annual net radiation （Ro）, MAP and mean annual air temperature （MAT） were dominant. Thus, we proposed an empirical equation to describe the spatial patterns of AET in China, which could explain about 84% of the spatial variation in AET of terrestrial ecosystems in China. Based on the constructed dataset, we also evaluated the uncertainties of five published global evapotranspiration products in simulating site-specific AET in China. Results showed that large biases in site-specific AET values existed for all five global evapotranspiration products, which indicated that it is necessary to involve more observation data of China in their parameterization or validation, while our AET dataset would provide a data source for it.

关键词： evapotranspiration water budget spatial variation eddy covariance terrestrial ecosystem China-FLUX

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The simulation of runoff process of glacier and snowmelt dominated basin in Central Asia

The simulation of runoff process of glacier and snowmelt dom...

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IGU2013 International Conference on Water Sustainability in Arid Regions(第十届国际地理大会——水资源可持续发展论坛)

作者： RongGan YiLuo Yucheng Comprehensive Experimental Station Key Lab.of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina100101 University of Chinese Academy of Science BeijingChina100049 Yucheng Comprehensive Experimental StationKey Lab.of Ecosystem Network Observation and ModelingInstitute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina100101

Glaciers and snow meltwater play an important role in runoff regimes in Syrdarya River basin,which is the longest river of Central ***-driven changes in glacier-fed catchment have direct implications on runoff process.

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