作者:Xie, XH (Xie, Xianhong)[ 1 ] ; Liang, SL (Liang, Shunlin)[ 1,2 ] ; Yao, YJ (Yao, Yunjun)[ 1 ] ; Jia, K (Jia, Kun)[ 1 ] ; Meng, SS (Meng, Shanshan)[ 1 ] ; Li, J (Li, Jing)[ 1 ]

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AGRICULTURAL AND FOREST METEOROLOGY

卷: 203  页: 74-87

DOI: 10.1016/j.agrformet.2015.01.003

出版年: APR 15 2015

摘要

China's Three-North region (TNR), a typical arid and semiarid area, has experienced substantial land cover (LC) changes since the early 1980s partly due to the implementation of large-scale afforestation programs and to expanding urbanization. Hydrological monitoring and simulations for the past five decades reveal that the TNR might have a trend towards environmental degradation due to decreasing soil moisture and streamflow. A few studies regarding individual basins or local scales have proposed that the drying trend is attributable to climate and LC changes; however, little is known about their relative contributions at the regional scale over the TNR. In this study, we employ the Variable Infiltration Capacity (VIC) model in conjunction with remote-sensing retrieval data sets, to detect the changes in hydrological cycle and to identify the contributions of LC and climate change during 1989-2009. The simulation results demonstrate a slight increase in ET at a rate of 3.26 mm per decade over the entire region during 1959-2009. However, ET, runoff and soil moisture exhibit significant decreases after 1989, although their trends have spatial heterogeneities. Sensitivity experiments illustrate that across the TNR, the inter-annual trends in the hydrological regimes can be primarily attributed to the decreasing precipitation which accounts for the ET and runoff declines of 27.5 mm and 16.8 mm, respectively, for the past two decades. The LC change plays a negligible role. These findings are critical to evaluate the effect of ecological projects (e.g., afforestation practices) and imply the importance of water resources management because of the decreasing water availability in this arid and semiarid region. To reduce modeling uncertainties, high-resolution historical LC data sets and model parameterization on dynamic vegetation should be improved. (C) 2015 Elsevier B.V. All rights reserved.

通讯作者地址: Xie, XH (通讯作者)

Beijing Normal Univ, State Key Lab Remote Sensing Sci, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China.

地址:

[ 1 ] Beijing Normal Univ, State Key Lab Remote Sensing Sci, Coll Global Change & Earth Syst Sci, Beijing 100875, Peoples R China

[ 2 ] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA