PIAHS Proceedings of the International Association of Hydrological Sciences PIAHS Proc. IAHS 2199-899X Copernicus Publications Göttingen, Germany 10.5194/piahs-368-215-2015 Simulation of soil moisture for typical plain region using the Variable Infiltration Capacity model Wu Z. 1 Mao Y. 1 Lu G. 2 Zhang J. 1 3 National 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 National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, No.1 Xikang Road, Nanjing, Jiangsu Province, China Department of Water Resources of Jiangsu Province, Nanjing, China 06 05 2015 368 215 220 Copyright: © 2015 Z. Wu et al. 2015 This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/3.0/ This article is available from https://piahs.copernicus.org/articles/368/215/2015/piahs-368-215-2015.html The full text article is available as a PDF file from https://piahs.copernicus.org/articles/368/215/2015/piahs-368-215-2015.pdf

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.