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Volume 23 Issue 3

May  2006

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Article >  ADVANCES IN ATMOSPHERIC SCIENCES  > 2006 >  23(3): 391-404

Effects of Heterogeneous Vegetation on the Surface Hydrological Cycle

  • 1.

    Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044,Department of Geography and Program in Planning, University of Toronto, 100 St. George St., Room 5047, Toronto, Ontario, Canada M5S 3G3,Earth Science System Institute, Nanjing University, Nanjing 210009,Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044


doi: 10.1007/s00376-006-0391-9

  • Using the three-layer variable infiltration capacity (VIC-3L) hydrological model and the successive interpolation approach (SIA) of climate factors, the authors studied the effect of different land cover types on the surface hydrological cycle. Daily climate data from 1992 to 2001 and remotely-sensed leaf area index (LAI) are used in the model. The model is applied to the Baohe River basin, a subbasin of the Yangtze River basin, China, with an area of 2500 km2. The vegetation cover types in the Baohe River basin consist mostly of the mixed forest type (85%). Comparison of the modeled results with the observed discharge data suggests that: (1) Daily discharges over the period of 1992–2001 simulated with inputs of remotely-sensed land cover data and LAI data can generally produce observed discharge variations, and the modeled annual total discharge agrees with observations with a mean difference of 1.4%. The use of remote sensing images also makes the modeled spatial distributions of evapotranspiration physically meaningful. (2) The relative computing error (RCE) of the annual average discharge is ?24.8% when the homogeneous broadleaf deciduous forestry cover is assumed for the watershed. The error is 21.8% when a homogeneous cropland cover is assumed and ?14.32% when an REDC (Resource and Environment Database of China) land cover map is used. The error is reduced to 1.4% when a remotely-sensed land cover at 1000-m resolution is used.
  • [1] WANG Hesong, JIA Gensuo, 2013: Regional Estimates of Evapotranspiration over Northern China Using a Remote-sensing-based Triangle Interpolation Method, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1479-1490.  doi: 10.1007/s00376-013-2294-x
    [2] Yun QIAN, Teppei J. YASUNARI, Sarah J. DOHERTY, Mark G. FLANNER, William K. M. LAU, MING Jing, Hailong WANG, Mo WANG, Stephen G. WARREN, Rudong ZHANG, 2015: Light-absorbing Particles in Snow and Ice: Measurement and Modeling of Climatic and Hydrological impact, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 64-91.  doi: 10.1007/s00376-014-0010-0
    [3] Ping YANG, Kuo-Nan LIOU, Lei BI, Chao LIU, Bingqi YI, Bryan A. BAUM, 2015: On the Radiative Properties of Ice Clouds: Light Scattering, Remote Sensing, and Radiation Parameterization, ADVANCES IN ATMOSPHERIC SCIENCES, 32, 32-63.  doi: 10.1007/s00376-014-0011-z
    [4] QIU Jinhuan, CHEN Hongbin, 2004: Recent Progresses in Atmospheric Remote Sensing Research in China-- Chinese National Report on Atmospheric Remote Sensing Research in China during 1999-2003, ADVANCES IN ATMOSPHERIC SCIENCES, 21, 475-484.  doi: 10.1007/BF02915574
    [5] Zhao Gaoxiang, 1998: Analysis of the Ability of Infrared Water Vapor Channel for Moisture Remote Sensing in the Lower Atmosphere, ADVANCES IN ATMOSPHERIC SCIENCES, 15, 107-112.  doi: 10.1007/s00376-998-0022-8
    [6] ZHANG Liping, WU Lixin, YU Lisan, 2011: Oceanic Origin of A Recent La Nina-Like Trend in the Tropical Pacific, ADVANCES IN ATMOSPHERIC SCIENCES, 28, 1109-1117.  doi: 10.1007/s00376-010-0129-6
    [7] Xiaoxiong XIONG, William BARNES, 2006: An Overview of MODIS Radiometric Calibration and Characterization, ADVANCES IN ATMOSPHERIC SCIENCES, 23, 69-79.  doi: 10.1007/s00376-006-0008-3
    [8] HE Yuting, JIA Gensuo, HU Yonghong, and ZHOU Zijiang, 2013: Detecting urban warming signals in climate records, ADVANCES IN ATMOSPHERIC SCIENCES, 30, 1143-1153.  doi: 10.1007/s00376-012-2135-3
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    [11] Yunji ZHANG, Eugene E. CLOTHIAUX, David J. STENSRUD, 2022: Correlation Structures between Satellite All-Sky Infrared Brightness Temperatures and the Atmospheric State at Storm Scales, ADVANCES IN ATMOSPHERIC SCIENCES, 39, 714-732.  doi: 10.1007/s00376-021-0352-3
    [12] WANG Hesong, JIA Gensuo, 2012: Satellite-Based Monitoring of Decadal Soil Salinization and Climate Effects in a Semi-arid Region of China, ADVANCES IN ATMOSPHERIC SCIENCES, 29, 1089-1099.  doi: 10.1007/s00376-012-1150-8
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    • Manuscript History

    Manuscript received: 10 May 2006
    Manuscript revised: 10 May 2006
    通讯作者: 陈斌, bchen63@163.com
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      沈阳化工大学材料科学与工程学院 沈阳 110142

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    Effects of Heterogeneous Vegetation on the Surface Hydrological Cycle

    • 1. Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044,Department of Geography and Program in Planning, University of Toronto, 100 St. George St., Room 5047, Toronto, Ontario, Canada M5S 3G3,Earth Science System Institute, Nanjing University, Nanjing 210009,Key Laboratory of Meteorological Disaster, Nanjing University of Information Science and Technology, Nanjing 210044
    • Manuscript received: 2006-05-10
    • Manuscript revised: 2006-05-10

    Abstract: Using the three-layer variable infiltration capacity (VIC-3L) hydrological model and the successive interpolation approach (SIA) of climate factors, the authors studied the effect of different land cover types on the surface hydrological cycle. Daily climate data from 1992 to 2001 and remotely-sensed leaf area index (LAI) are used in the model. The model is applied to the Baohe River basin, a subbasin of the Yangtze River basin, China, with an area of 2500 km2. The vegetation cover types in the Baohe River basin consist mostly of the mixed forest type (85%). Comparison of the modeled results with the observed discharge data suggests that: (1) Daily discharges over the period of 1992–2001 simulated with inputs of remotely-sensed land cover data and LAI data can generally produce observed discharge variations, and the modeled annual total discharge agrees with observations with a mean difference of 1.4%. The use of remote sensing images also makes the modeled spatial distributions of evapotranspiration physically meaningful. (2) The relative computing error (RCE) of the annual average discharge is ?24.8% when the homogeneous broadleaf deciduous forestry cover is assumed for the watershed. The error is 21.8% when a homogeneous cropland cover is assumed and ?14.32% when an REDC (Resource and Environment Database of China) land cover map is used. The error is reduced to 1.4% when a remotely-sensed land cover at 1000-m resolution is used.

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