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Proceedings of the International Association of Hydrological Sciences An open-access publication for refereed proceedings in hydrology
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Volume 368
Proc. IAHS, 368, 215–220, 2015
https://doi.org/10.5194/piahs-368-215-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.
Proc. IAHS, 368, 215–220, 2015
https://doi.org/10.5194/piahs-368-215-2015
© Author(s) 2015. This work is distributed under
the Creative Commons Attribution 3.0 License.

  06 May 2015

06 May 2015

Simulation of soil moisture for typical plain region using the Variable Infiltration Capacity model

Z. Wu1, Y. Mao1, G. Lu2, and J. Zhang1,3 Z. Wu et al.
  • 1National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, College of Hydrology and Water Resources, Hohai University, No.1 Xikang Road, Nanjing, Jiangsu Province, China
  • 2National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, No.1 Xikang Road, Nanjing, Jiangsu Province, China
  • 3Department of Water Resources of Jiangsu Province, Nanjing, China

Keywords: Soil moisture, the VIC model, Jiangsu Province, China, plain

Abstract. Droughts have a severe impact on the development of the social economy in developed plain areas. Soil moisture is a good index, it can reasonably reflect changes in drought. In this study, Jiangsu province in the Yangtze River Plain was selected as the research region, and the VIC (Variable Infiltration Capacity) large-scale hydrological model was selected to simulate the daily soil moisture with a resolution of 0.125 × 0.125 degree from 1956 to 2009. The simulated soil moisture was verified by measured soil moisture. The results indicate that the simulated soil moisture distribution is relatively consistent for the three soil layers (0–20, 20−100 and 0–100 cm), showing an increasing trend from northwest to southeast. The simulated soil moisture anomalies agreed well with in situ observations. The simulated soil moisture data thus can be used to analyze the spatio-temporal variation of the regional water content and to provide support for drought monitoring and forecasting.

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