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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability IX

作者： Gao, Zhiqiang Gao, Wei Cao Xiaoming Chen, Maosi Chinese Acad Sci Yantai Inst Coastal Zone Res Yantai 264003 Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO USA Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing Peoples R China

ISBN: (纸本)9780819492302

by using MODIS data products, combined with DEM data, land use data, meteorological data, employed SEbAL model, light use efficiency model, PAR model and the algorithm of vegetation index, the parameters of ET(Evapotranspiration), NPP(Net Primary Product), PAR (Photosynthetic Active Radiation), NDVI (Normalized Difference Vegetation Index) and EVI (Enhance Vegetation Index) in Haihe River basin were estimated. The impacts of elevation and land cover change on ET, NPP, PAR, NDVI and EVI are analyzed. We found that the impacts of elevation and land cover change on parameters are significant. The conclusions are as follows: 1) The ET in areas below 500m is the biggest, the ET in areas above 1500m is bigger and the ET in areas between 500-1500 is the smallest. 2) The impacts of location and elevation on PAR are significant, the PAR in areas with lower elevation is smaller;with the rising of elevation, the PAR has a increasing trend. The difference of PAR in different land cover is caused with location and elevation. 3) The NPP, NDVI and EVI in areas between 20-800m are bigger, and the values of these parameters in others areas is smaller. 4) The NDVI, EVI and NPP in areas covered with farmland, grassland and fores. are bigger, and the values of these parameters in areas covered with unused land, water body and built-up land are smaller.

关键词： Simulation MODIS Haihe basin China

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The differences in the transpiration of non-irrigated Haloxylon ammodendron in hinterland of Gurbantunggut desert based on diameter

The differences in the transpiration of non-irrigated <i>Hal...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability IX

作者： Cao, Xiao-ming Wang, Juan-le Chen, Mao-si Gao, Zhi-qiang Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO USA Chinese Acad Sci Yantai Inst Coastal Zone Res Yantai Peoples R China

ISBN: (纸本)9780819492302

The stem sap flow exhibited a bi-peaked or multi-peaked curve, with lower values at night than during the day. The ambiguous noon-depres.ion phenomenon usually occurs during 14:00 similar to 16: 00 from mid-May to the early September. Under the same environmental conditions, the larger the stem diameter, the larger the stem sap flow, and the more obvious the ambiguous noon-depres.ion phenomenon. The daily changes of the sap flow were highest in June and lowest in September. There were differences in the monthly mean value in different plants, which may res.lt from the differences in the crown and the number of assimilation organ. The daily accumulation showed a "S" trend between May and the end of August, and showed a straight line with the same slope in September and October. The larger the stem diameter, the larger the daily water use and the accumulative rate were. The sap flow was influenced by meterological factors, it was positively correlated with solar radiation, air temperature and wind speed, and negatively correlated with the air relative humidity, in which the solar radiation had the greatest impact on the sap flow. Under the same environmental condition, the larger the stem diameter, the better the correlation was. The correlation was the largest water use in July, and least in May and October. The larger the stem diameter, the more the water consumption was.

关键词： the stem sap flow rate Haloxylon ammodendron differences diameter transpiration

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The transpiration and the spectral res.onse of non-irrigated Haloxylon ammodendron at canopy scale

The transpiration and the spectral response of non-irrigated...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability IX

作者： Cao, Xiao-ming Wang, Juan-le Gao, Zhi-qiang Chen, Mao-si Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO USA Chinese Acad Sci Yantai Inst Coastal Zone Res Yantai Peoples R China

ISBN: (纸本)9780819492302

Transpiration, an essential component of surface evapotranspiration, is particularly important in the res.arch of surface evapotranspiration in arid areas. The paper inverted the transpiration of non-irrigated Haloxylon ammodendron and its spectral res.onses at the canopy scale in the southern edge of the Gurbantunggut desert in Xinjiang, China. The res.lts are as follows:The stem sap flow rate appeared biomadal or multi-peak course and maintained a certain flow in the night. The stem sap flow maintained at 0 similar to 0.1 L/h, with a peak appearing at 12:00 similar to 17:30, 0.316 L/h. "Noon peak" appeared from mid May to early September, at 14:00 similar to 16:00. For monthly changes, the peak value appeared in June, with the value varying (0.32 +/- 0.20) L / h, followed by July (0.30+/-0.16) L/h, then, May and August, the minimum value appeared in September (0.15+/-0.03) L/h. At the canopy scale, the optimal exponential model of the sap flow rate based on the hyperspectrum is y = 0.0015e(3.8922x), R-2 = 0.806.

关键词： the stem sap flow rate the canopy scale Haloxylon ammodendron the reflectance

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The analysis of net primary productivity in China based on GEOLUE model

The analysis of net primary productivity in China based on G...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability IX

ISBN: (纸本)9780819492302

GEOLUE model was designed with Light Use Efficiency (LUE) mechanism and was validated with observed data and models comparison (GLOPEM, CASA, and CEVSA). We found that: GEOLUE model correctly simulates monthly, quarterly and annual variation of Net Primary Product (NPP) in different vegetation communities under monsoon climate. The spatial distribution of NPP simulated by GEOLUE matched up to 96.67% with that of fores. and shrub land. The GEOLUE model perfectly simulated the seasonal characteristics and spatial pattern of biomass in different types of vegetation. The total amount NPP of China simulated by GEOLUE is 0.667GtC in spring, 1.365GtC in summer, 0.587GtC in autumn and 0.221GtC in winter. The average total NPP of China for 5 years is 2.84GtC / year.

关键词： China model of Light Use Efficiency Net Primary Product (NPP) Simulation

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Land-use and land-cover sceneries in China: an application of Dinamica EGO model

Land-use and land-cover sceneries in China: an application o...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability IX

作者： Yi, Wei Gao, Zhiqiang Li, Zhihua Chen, Maosi Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing Peoples R China Grad Univ Chinese Acad Sci Beijing Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO USA East China Normal Univ Minist Educ Key Lab Geog Informat Sci Shanghai Peoples R China

ISBN: (纸本)9780819492302

Land is an indispensable natural res.urce for human, without which we cannot survive and develop. Land-use change, influenced by both natural environment and human activity, has a close relationship with food security, res.urce utilization, biodiversity and climate change. In order to understand the process and driving mechanism of land-use change, dynamic models were developed in these years, among which Dinamica EGO is a practical one and has been widely used in the world. In this paper, we aim to use Dinamica EGO to simulate the land-use of China in 2005 with data extracted from SPOT VGT NDVI. The real land-use map was compared with the simulation res.lt so as to verify the feasibility of Dinamica EGO. Then we supposed three sceneries under which we could analyze the land-use change of China in 2020. res.lts indicated that: on the basis of no extreme natural disasters or exceptional policy fluctuation, the grassland area would reduce by 22.21 million hectares.averagely. However fores. would increase by 19.81 billion hectares.on average. Water and unused land would probably remain stable as there was little change in three sceneries. Farmland areas showed a good agreement under these sceneries whereas the greatest difference in land-use area estimations lies in built-up with an uncertainty accounting for 1.67%.

关键词： Dinamica EGO China Remote sensing Simulation

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Physical Modeling of US Cotton Yields and Climate Stres.es during 1979 to 2005

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AGRONOMY JOURNAL 2012年第3期104卷 675-683页

作者： Liang, Xin-Zhong Xu, Min Gao, Wei Reddy, K. Raja Kunkel, Kenneth Schmoldt, Daniel L. Samel, Arthur N. Univ Maryland Dep Atmospher & Ocean Sci College Pk MD 20742 USA Univ Illinois Dep Atmospher Sci Urbana IL 61801 USA Univ Maryland Earth Syst Sci Interdisciplinary Ctr College Pk MD 20740 USA Univ Illinois Inst Nat Resource Sustainabil Div Illinois State Water Survey Champaign IL 61820 USA USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO 80523 USA Colorado State Univ Dep Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA Mississippi State Univ Dep Plant & Soil Sci Mississippi State MS 39762 USA N Carolina State Univ Cooperat Inst Climate & Satellites Asheville NC 28801 USA Natl Ocean & Atmospher Adm Natl Climat Data Ctr Asheville NC 28801 USA USDA Natl Inst Food & Agr Washington DC 20024 USA Bowling Green State Univ Dep Geog Bowling Green OH 43403 USA

Climate variability and changes affect crop yields by causing climatic stres.es during various stages of the plant life cycle. A crop growth model must be able to capture the observed relationships between crop yields and climate stres.es before its credible use as a prediction tool. This study evaluated the ability of the geographically distributed cotton growth model redeveloped from GOSSYM in simulating U.S. cotton (Gossypium hirsutum L.) yields and their res.onses to climate stres.es during 1979 to 2005. Driven by realistic climate conditions, the model reproduced long-term mean cotton yields within +/- 10% of observations at the 30-km model res.lution across virtually the entire U.S. Cotton belt and correctly captured the critical dependence of their geographic distributions on regional climate characteristics. Significant correlations between simulated and observed interannual variations were found across 87% of the total harvest grids. The model also faithfully repres.nted the predictive role of July to August air temperature and August to September soil temperature anomalies on interannual cotton yield changes on unirrigated lands, with a similar but weaker predictive signal for irrigated lands as observed. The modeled cotton yields exhibited large, positive correlations with July to August leaf area index. These res.lts indicate the model's ability to depict the regional impact of climate stres.es on cotton yields and suggest the potential predictive value of satellite retrievals. They also provide a baseline reference for further model improvements and applications in the future study of climate-cotton interactions.

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A Distributed Cotton Growth Model Developed from GOSSYM and Its Parameter Determination

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AGRONOMY JOURNAL 2012年第3期104卷 661-674页

作者： Liang, Xin-Zhong Xu, Min Gao, Wei Reddy, K. Raja Kunkel, Kenneth Schmoldt, Daniel L. Samel, Arthur N. Univ Maryland Dep Atmospher & Ocean Sci College Pk MD 20740 USA Univ Illinois Dep Atmospher Sci Urbana IL 61801 USA Univ Maryland Earth Syst Sci Interdisciplinary Ctr College Pk MD 20740 USA Univ Illinois Inst Nat Resource Sustainabil Div Illinois State Water Survey Champaign IL 61820 USA USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO 80523 USA Colorado State Univ Dep Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA Mississippi State Univ Dep Plant & Soil Sci Mississippi State MS 39762 USA N Carolina State Univ Cooperat Inst Climate & Satellites Asheville NC 28801 USA Natl Ocean & Atmospher Adm Natl Climat Data Ctr Asheville NC 28801 USA USDA Natl Inst Food & Agr Washington DC 20024 USA Bowling Green State Univ Dep Geog Bowling Green OH 43403 USA

Prediction of cotton (Gossypium hirsutum L.) production under a changing climate requires.a coupled modeling system that repres.nts climate-cotton interactions. The existing cotton growth model GOSSYM has drawbacks that prohibit its effective coupling with climate models. We developed a geographically distributed cotton growth model from the original GOSSYM and optimized it for coupling with the regional Climate-Weather res.arch Forecasting model (CWRF). This included software redesign, physics improvement, and parameter specification for consistent coupling of CWRF and GOSSYM. Through incorporation of the best available physical repres.ntations and observational estimates, the long list of inputs in the original GOSSYM was reduced to two parameters, the initial NO3 amount in the top 2 m of soil and the ratio of irrigated water amount to potential evapotranspiration. The geographic distributions of these two parameters are determined by optimization that minimizes model errors in simulating cotton yields. The res.lt shows that the redeveloped GOSSYM realistically reproduces the geographic distribution of mean cotton yields in 30-km grids, within +/- 10% of observations across most of the U.S. Cotton belt, whereas the original GOSSYM overes.imated yields by 27 to 135% at the state level and 92% overall. both models produced interannual yield variability with comparable magnitude;however, the temporal corres.ondence between modeled and observed interannual anomalies was much more realistic in the redeveloped than the original GOSSYM because significant (P = 0.05) correlations were identified in 87 and 40% of harvest grids, res.ectively. The redeveloped GOSSYM provides a starting point for additional improvements and applications of the coupled CWRF-GOSSYM system to study climate-cotton interactions.

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Integrating Satellite for Drought Impact Assessment in a Developed Coastal Region

Integrating Satellite for Drought Impact Assessment in a Dev...

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Conference on Remote Sensing and Modeling of Ecosystems for Sustainability VIII

作者： Gao, Zhiqiang Gao, Wei Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing Peoples R China Colorado State Univ USDA UV B Monitoring & Res Program Nat Resource Ecol Lab Ft Collins CO 80523 USA

ISBN: (纸本)9780819487667

This paper pres.nts a new drought assessment method by spatially and temporally integrating the regional water stres. index (RWSI) with the temperature vegetation dryness index (TVDI). With the aid of LANDSAT TM/ETM data, we were able to retrieve the land-use and land-cover (LULC), vegetation indices (VIs), and land surface temperature (LST), and derive three types of TVDI, including TVDI SAVI, TVDI ANDVI and TVDI MSAVI, for the drought impact assessment in a well-developed coastal region, northern China. The classification of four drought impact categories associated with the RWSI values enables us to refine the spatiotemporal relationship between the LST and the VIs in a greater detail. Holistic drought impact assessment between 1987 and 2000 in our study area was carried out by linking RWSI with TVDIs group wise.

关键词： drought assessment remote sensing coastal management

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Integrating temperature vegetation dryness index (TVDI) and regional water stres. index (RWSI) for drought assessment with the aid of LANDSAT TM/ETM plus images

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INTERNATIONAL JOURNAL OF APPLIED EARTH ObSERVATION AND GEOINFORMATION 2011年第3期13卷 495-503页

作者： Gao, Zhiqiang Gao, Wei Chang, Ni-bin Colorado State Univ Nat Resource Ecol Lab USDA UV B Monitoring & Res Program Ft Collins CO 80521 USA Chinese Acad Sci Inst Geog Sci & Nat Resources Res Beijing Peoples R China Univ Cent Florida Dept Civil Environm & Construct Engn Orlando FL 32816 USA

This paper pres.nts a new drought assessment method by spatially and temporally integrating temperature vegetation dryness index (TVDI) with regional water stres. index (RWSI) based on a synergistic approach. With the aid of LANDSAT TM/ETM data, we were able to retrieve the land-use and land-cover (LULC), vegetation indices (VIs), and land surface temperature (LST), leading to the derivation of three types of modified TVDI including TVDI_SAVI, TVDI_ANDVI and TVDI_MSAVI, for drought assessment in a fast growing coastal area, Northern China. The categorical classification of four drought impact levels associated with the RWSI values enables us to refine the spatiotemporal relationship between the LST and the VIs. Holistic drought impact assessment between 1987 and 2000 was carried out by linking RWSI with TVDIs group wise. res.arch findings indicate that: (1) LST and VIs were negatively correlated in most cases of low, medium, and high vegetation cover except the case of high density vegetation cover in 2000 due to the effect of urban heat island (UHI) effect;(2) the shortage of water in 1987 was more salient than that that in 2000 based on all indices of TVDI and RWSI;and (3) TVDIs are more suitable for monitoring mild drought, normal and wet conditions when RWSI is smaller than 0.752;but they are not suitable for monitoring moderate and severe drought conditions. (C) 2010 Published by Elsevier b.V.

关键词： Drought assessment Remote sensing Urbanization effect Urban heat island Coastal management

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REGIONAL CLIMATE-WEATHER res.ARCH AND FORECASTING MODEL

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bULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY 2012年第9期93卷 1363-1387页

作者： Liang, Xin-Zhong Xu, Min Yuan, Xing Ling, Tiejun Choi, Hyun I. Zhang, Feng Chen, Ligang Liu, Shuyan Su, Shenjian Qiao, Fengxue He, Yuxiang Wang, Julian X. L. Kunkel, Kenneth E. Gao, Wei Joseph, Everett E. Morris, Vernon Yu, Tsann-Wang Dudhia, Jimy Michalakes, John Univ Maryland Earth Syst Sci Interdisciplinary Ctr College Pk MD 20740 USA Univ Maryland Dept Atmospher Sci College Pk MD 20740 USA Univ Maryland Dept Ocean Sci College Pk MD 20740 USA Univ Illinois Illinois State Water Survey Urbana IL USA Univ Illinois Dept Atmospher Sci Urbana IL USA Princeton Univ Dept Civil & Environm Engn Princeton NJ 08544 USA Natl Marine Environm Forecasting Ctr Key Lab Res Marine Hazards Forecasting Beijing Peoples R China Yeungnam Univ Dept Civil Engn Taegu South Korea NOAA Air Resources Lab Silver Spring MD 20910 USA N Carolina State Univ Cooperat Inst Climate & Satellites Asheville NC USA NOAA Natl Climat Data Ctr Asheville NC USA Colorado State Univ Nat Resource Ecol Lab USDA UV B Monitoring & Res Program Ft Collins CO 80523 USA Colorado State Univ Dept Ecosyst Sci & Sustainabil Ft Collins CO 80523 USA E China Normal Univ Key Lab Geog Informat Sci Shanghai 200062 Peoples R China Howard Univ Dept Phys & Astron Washington DC 20059 USA NCAR Mesoscale & Microscale Meteorol Div Boulder CO USA

The CWRF is developed as a climate extension of the Weather res.arch and Forecasting model (WRF) by incorporating numerous improvements in the repres.ntation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approac...

关键词： Clouds Prediction Aerosols Climate prediction Atmospheric forcing Climate change Ocean-atmosphere system Hydrology Weather forecasting Climate models Numerical simulations Radiation Climatology Water quality Future climates Marine

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