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Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 13, issue 7
Hydrol. Earth Syst. Sci., 13, 1375–1398, 2009
https://doi.org/10.5194/hess-13-1375-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

Special issue: Remote sensing in hydrological sciences

Hydrol. Earth Syst. Sci., 13, 1375–1398, 2009
https://doi.org/10.5194/hess-13-1375-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.

  31 Jul 2009

31 Jul 2009

Temporal variation of soil moisture over the Wuding River basin assessed with an eco-hydrological model, in-situ observations and remote sensing

S. Liu1, X. Mo1, W. Zhao2, V. Naeimi3, D. Dai2, C. Shu1, and L. Mao4 S. Liu et al.
  • 1Key Laboratory of Water Cycle & Related Land Surface Processes, Institute of Geographic Sciences & Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
  • 2The Bureau of Hydrology, Yellow River Conservancy Committee, Zhengzhou, 450004, China
  • 3Institute of Photogrammetry and Remote Sensing, Vienna University of Technology, Gusshausstrasse 27–29, 1040 Vienna, Austria
  • 4China Meteorology Administration, National Meteorological Center, Beijing, 100081, China

Abstract. The change pattern and trend of soil moisture (SM) in the Wuding River basin, Loess Plateau, China is explored based on the simulated long-term SM data from 1956 to 2004 using an eco-hydrological process-based model, Vegetation Interface Processes model, VIP. In-situ SM observations together with a remotely sensed SM dataset retrieved by the Vienna University of Technology are used to validate the model. In the VIP model, climate-eco-hydrological (CEH) variables such as precipitation, air temperature and runoff observations and also simulated evapotranspiration (ET), leaf area index (LAI), and vegetation production are used to analyze the soil moisture evolution mechanism. The results show that the model is able to capture seasonal SM variations. The seasonal pattern, multi-year variation, standard deviation and coefficient of variation (CV) of SM at the daily, monthly and annual scale are well explained by CEH variables. The annual and inter-annual variability of SM is the lowest compared with that of other CEH variables. The trend analysis shows that SM is in decreasing tendency at α=0.01 level of significance, confirming the Northern Drying phenomenon. This trend can be well explained by the decreasing tendency of precipitation (α=0.1) and increasing tendency of temperature (α=0.01). The decreasing tendency of runoff has higher significance level (α=0.001). Because of SM's decreasing tendency, soil evaporation (ES) is also decreasing (α=0.05). The tendency of net radiation (Rn), evapotranspiration (ET), transpiration (EC), canopy intercept (EI) is not obvious. Net primary productivity (NPP), of which the significance level is lower than α=0.1, and gross primary productivity (GPP) at α=0.01 are in increasing tendency.

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