Analysis for Soil Moisture in Jiangsu Province, China, Using GLDAS Data

In this chapter, we present the analysis for the evolution characteristics of temperature, precipitation, and soil moisture. We choose a newly developed method that is based on the information flow (IF) concept to research the causality between annual mean temperature, precipitation, and soil moisture in Jiangsu province, China, from 1961 to 2011 by using the Global Land Data Assimilation System (GLDAS). The correlation and the causality of air temperature and precipitation on soil moisture were compared and discussed. The causality value of 0–10 cm layer is significantly different from zero, while the deeper, in comparison to the surface layer, is negligible. This result unambiguously shows the causality in the sense that the precipitation increase and the temperature decrease are causing the shallow soil moisture to increase. Temperature and all layers of soil moisture have a negative correlation, but precipitation inverses. Precipitation strongly has the greatest effects on soil moisture in the surface layer, though the rest layers are not obvious