JOURNAL OF NATURAL RESOURCES ›› 2019, Vol. 34 ›› Issue (1): 191-204.doi: 10.31497/zrzyxb20190116

• Orginal Article • Previous Articles     Next Articles

Soil moisture in Beijing based on site observation and model simulation

Dao-qing QIN1(), Yan ZHAO1, Hong-rui WANG1(), Cai-yun DENG1, Yong ZHAO2   

  1. 1. College of Water Science, Beijing Key Laboratory of Urban Hydrological Cycle and Sponge City Technology, Beijing Normal University, Beijing 100875, China
    2. State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
  • Received:2018-06-19 Revised:2018-10-10 Online:2019-01-20 Published:2019-01-20


It is of great significance to accurately and objectively evaluate the spatial and temporal variation characteristics of soil moisture in studies on the biochemical evolution process of the earth surface. Thus, the combination of model simulation and site observation is necessary to studying water and energy recycling at a regional scale especially. In this paper, based on daily soil surface (0-10 cm) moisture data of 82 monitoring stations in Beijing and GLDAS soil moisture products, the accuracy and consistency of CLDAS was evaluated and the spatio-temporal variability of soil moisture content in Beijing was examined. The root mean square error (RMSE) was used to identify the consistency of CLDAS products and observation values. Specifically, we compared and analyzed the accumulated values of CLDAS products and observation data in 1 day (8∶00, 20∶00), 7 days (8∶00, 20∶00), 15 days (8∶00, 20∶00), 31 days (8∶00, 20∶00), 61 days (8∶00, 20∶00), and 92 days (8∶00, 20∶00). The results showed that: (1) Although the data from CLDAS products were generally slightly higher than the measured data, CLDAS products and site observation data show a good consistency that RMSE in various countries was almost around 10; (2) CLDAS products could reflect the distribution characteristics of soil moisture in Beijing when the temperature was higher than 0 ℃, while there existed a bias in GLDAS products when the temperature was lower than 0 ℃; (3) Based on drought identification based on soil moisture data, we found that the drought area in Beijing was gradually expanding and one extreme drought center was spreading from Changping (soil relative moisture content < 30%) to other districts. Meanwhile, the other area with high soil relative humidity (soil relative moisture content > 50%), centered in Shunyi District, gradually decreased at a spatial scale; (4) In terms of temporal scale, soil moisture in Beijing gradually decreased with the decrease of precipitation that soil humidity at 20∶00 was all higher than that at 8∶00 in the same day (MEobs >0). When the temperature was lower than 0 ℃, soil humidity at 20∶00 and 8∶00 became significantly different. These conclusions would help us make effective use of GLDAS products in soil moisture related studies and would help us know the spatial and temporal variability of soil moisture content in Beijing.

Key words: soil moisture, CLDAS, site observation, model simulation, Beijing